B_tm3_topic2_Waveforms_exercise.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "575160a3-c96d-4787-b2cf-4ecc78761735",
   "metadata": {},
   "source": [
    "<img src=\"media/eoafrica.png\" width=\"200px\"></img>\n",
    "\n",
    "Author: R. Rietbroek, April 2022\n",
    "\n",
    "# Jupyter Notebook Exercise: A look at the waveforms of Lake Turkana (Kenya)\n",
    "\n",
    "In this Jupyter exercise, you're going to have a look at the waveforms of the Sentinel 3-A mission which are collected over Lake Turkana in Kenya.\n",
    "\n",
    "Once you have this notebook running on a jupyterlab instance, you can follow the steps below by executing the code-cells one by one.\n",
    "\n",
    "[This exercise](https://github.com/EOAfrica/tm3-lakes-rivers/raw/main/B_tm3_topic2_Waveforms_exercise.ipynb) is part of the jupyter notebook collections available at https://github.com/EOAfrica/tm3-lakes-rivers\n",
    "\n",
    "You can use the jupyter notebook exercise separately, but it's advisable to clone the collection of notebooks. \n",
    "To start using it on a Jupyter lab instance, login to the Jupyterlab instance [e.g. the innovation lab from EOAfrica](https://test.jhub.innovation-lab.eoafrica-rd.org). After that you can clone the notebooks to your user directory using the follwoing steps:\n",
    "\n",
    "1. Click on the gitlab icon from the Jupyter lab instance\n",
    "\n",
    "<img src=\"media/jupyClonegitlab1.png\" width=\"200px\"></img>\n",
    "\n",
    "2. Chose: `Clone a repository`\n",
    "\n",
    "3. Paste the following address in the textbox: https://github.com/EOAfrica/tm3-lakes-rivers.git and press `clone`\n",
    "\n",
    "4. On the left hand-side you can now navigate to the folder tm3-lakes-rivers and click on `B_tm3_topic2_Waveforms_exercise.ipynb` to start the exercise.\n",
    "\n",
    "<img src=\"media/jupyClonegitlab2.png\" width=\"200px\"></img>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd1bb53d-6e19-4d04-9af5-7514ae064c96",
   "metadata": {},
   "source": [
    "# 21 April 2022: temporary solution for when the kernel is restarting when executing the plotting cells\n",
    "This appears to be related to [this issue](https://github.com/SciTools/cartopy/issues/2006) and can be solved by *installing a previous version of shapely*\n",
    "To do that:\n",
    "1. Open a new terminal in the jupyterhub `File -> New -> Terminal`\n",
    "2. Install version 1.8.0 of shapely by typing `pip install shapely==1.8.0` and pressing enter on the command prompt\n",
    "3. Restart your notebook kernel"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e729f91-acb3-406c-9e93-2890d2c8bad3",
   "metadata": {},
   "source": [
    "## Step 1 load appropriate python modules\n",
    "There are several modules which provide functionality needed for this exercise. If you're running this notebook on an other instance than the innovation lab of EOAfrica, yiou may need to to install some of the packages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6de6c6da-0355-4805-8938-2ec4f64198b1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.8/dist-packages/geopandas/_compat.py:111: UserWarning: The Shapely GEOS version (3.9.1-CAPI-1.14.2) is incompatible with the GEOS version PyGEOS was compiled with (3.10.1-CAPI-1.16.0). Conversions between both will be slow.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "import fiona\n",
    "from shapely.geometry import shape, Polygon,box,Point\n",
    "import requests\n",
    "import zipfile\n",
    "import io\n",
    "import os\n",
    "import cartopy.crs as ccrs\n",
    "import matplotlib.pyplot as mpl\n",
    "import numpy as np\n",
    "from cartopy.io.img_tiles import OSM\n",
    "import geopandas as gpd\n",
    "import xarray as xr\n",
    "import warnings\n",
    "from datetime import datetime,timedelta\n",
    "import glob\n",
    "import re\n",
    "import yaml\n",
    "import json\n",
    "from tqdm import tqdm\n",
    "from netCDF4 import Dataset\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "#enable reading KML support with fiona\n",
    "fiona.drvsupport.supported_drivers['KML'] = 'rw'\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c3c7204-13a9-4042-9236-d9e4fd76910c",
   "metadata": {},
   "source": [
    "## Step 2: Read in the Polygon which describes Lake Turkana\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "20bcd70c-89e1-4014-bf36-11415d585791",
   "metadata": {},
   "outputs": [],
   "source": [
    "def readShapes(filename):\n",
    "    \"\"\"A quick helper function which returns a list of shapely geometries from a gis file\"\"\"\n",
    "    return [shape(geom[1][\"geometry\"]) for geom in fiona.open(filename).items()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5fba3e91-2b50-4073-8f23-ce83ab935412",
   "metadata": {},
   "outputs": [],
   "source": [
    "# read Lake Turkana polygon in shapely object\n",
    "lakePoly = readShapes(\"data/LakeTurkana_NaturalEarth.gpkg\")\n",
    "\n",
    "#buffered boundingbox for displaying purposes (i.e. makes the plot wider than just the Lake)\n",
    "bbox=box(*(lakePoly[0].buffer(1).bounds))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "082169cf-0619-4d11-94cf-a9e934eabcea",
   "metadata": {},
   "source": [
    "## Step 3: Download the reference orbits for Sentinel-3 (A & B)\n",
    "This will be used for an initial visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "99d6e281-0cd9-4fec-9596-b655236288dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to download Sentinel 3 reference orbits\n",
    "def downloadS3RefOrbit():\n",
    "    \"\"\"A function which download the kml files which contain the reference orbits for Sentinel-3\"\"\"\n",
    "    url=\"https://sentinel.esa.int/documents/247904/685098/Sentinel-3-Absolute-Ground-Tracks.zip\"\n",
    "    \n",
    "    if os.path.exists(\"data/S3A_abs_orbit_ground_track_10sec_v1_4.kml\"):\n",
    "        print(\"Sentinel 3 reference orbits already downloaded, skipping\")\n",
    "        return\n",
    "                  \n",
    "    print(\"Downloading Sentinel 3 reference orbit\")\n",
    "    #reads the data in a buffer variable\n",
    "    zipbuffer=requests.get(url)\n",
    "    # We pass the buffer directly to a zipfile processor so we can unpack it without writing the zipfile itself to the disk\n",
    "    z = zipfile.ZipFile(io.BytesIO(zipbuffer.content))\n",
    "    #extract the content of the zipfile in the data folder\n",
    "    z.extractall(\"data\")\n",
    "    \n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "328d99d0-7759-425a-9bf9-b3473c12581c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sentinel 3 reference orbits already downloaded, skipping\n"
     ]
    }
   ],
   "source": [
    "# perform the actual download\n",
    "downloadS3RefOrbit()\n",
    "\n",
    "#Read the reference orbits and accompanying data in a Geopandas dataframe (essentially a table containing the different orbits and meta information)\n",
    "s3aref= gpd.read_file(\"data/S3A_rel_orbit_ground_track_10sec_v1_4.kml\", driver='KML')\n",
    "# The relative orbitcolumn is given as a strin, so let's extract the orbit number as an integer number and put it into thedataframe as a new column\n",
    "s3aref[\"relorbit\"]=[int(sp.split()[2]) for sp in s3aref[\"Name\"].values]\n",
    "\n",
    "# Educated guess: this is a list with selected orbits which pass over Lake Turkana. \n",
    "s3arelorbits=[299,49,377,242,320,356]\n",
    "\n",
    "#only keep the orbits associated with those orbits (overwrites the geopandas dataframe with a lighter subset)\n",
    "s3aref=s3aref[s3aref['relorbit'].isin(s3arelorbits)]\n",
    "#select a pass of interest\n",
    "s3aorb=377"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5dac2b9-5412-4b72-8591-fe6fd6ac60fb",
   "metadata": {},
   "source": [
    "## Step 4: Create a plot to see where the orbits pass over the Lake"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3a63de5d-ecd1-40c8-9198-fd334f0569a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# %matplotlib widget\n",
    "# Create a regional plot around Lake Turkana\n",
    "pltextent=np.array([ i for i in lakePoly[0].buffer(1).bounds])[[0,2,1,3]]\n",
    "\n",
    "mpl.figure(figsize=(12,12))\n",
    "crs=ccrs.PlateCarree()\n",
    "ax = mpl.subplot(projection=crs)\n",
    "\n",
    "ax.set_extent(pltextent,crs=crs)\n",
    "\n",
    "# add Openstreet map background\n",
    "imagery = OSM()\n",
    "\n",
    "ax.add_image(imagery,8)\n",
    "\n",
    "# # add the Lake polygon\n",
    "ax.add_geometries(lakePoly,crs=crs,alpha=0.5,edgecolor='blue')\n",
    "# add the Sentinel 3 reference tracks\n",
    "s3aref.plot(ax=ax,edgecolor='red')\n",
    "\n",
    "# # plot the pass of interest\n",
    "s3aref[s3aref['relorbit']==s3aorb].plot(ax=ax,edgecolor='green')\n",
    "\n",
    "mpl.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9659143-9a6c-414a-a7ce-4edeb7b5c39f",
   "metadata": {},
   "source": [
    "As you can see, the Sentinel-3 mission has two orbits which pass over Lake Turkana. We will have a closer look at orbit number 377 (indicated in green)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6014e6ec-958d-4224-b64f-75912c7f170e",
   "metadata": {},
   "source": [
    "## Step 5 : Gather radar altimetry data\n",
    "\n",
    "We'll have a look at the Non-time-critical Level-1 product of the Sentinel SRAL instrument.\n",
    "\n",
    "If you're working on the EOAfrica Innovation Lab, the data does need to be downloaded. However, an inventory of the available files will be made, so this can take a while."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1de59ebd-9eab-4835-bc54-86c5fccb2bae",
   "metadata": {},
   "outputs": [],
   "source": [
    "def getEOAfricaSRALInventory(sat,orbit,product,latency,trange):\n",
    "    # search for appropriate files\n",
    "    eoafdir=os.path.join(\"/home/eoafrica/eodata/Sentinel-3/SRAL\",product)\n",
    "    if not os.path.exists(eoafdir):\n",
    "        raise NotADirectoryError(\"Directory not found,  not in the EOAfrica lab\")\n",
    "    \n",
    "    inventfile=f\"data/EOAfrica_Inventory_{sat}_{product}_{orbit}.yml\"\n",
    "    \n",
    "    if os.path.exists(inventfile):\n",
    "        #re use the inventory\n",
    "        print(f\"Reading cached inventory {inventfile}\")\n",
    "        with open(inventfile, 'r') as file:\n",
    "            return yaml.safe_load(file)\n",
    "            \n",
    "    # get a list of possible days in the time range\n",
    "    #generate a list per day\n",
    "    dur=trange[1]-trange[0]\n",
    "    alldays=[trange[0]+timedelta(days=dy) for dy in range(dur.days)]  \n",
    "    regex=re.compile(f\"{sat}_{product}.*{orbit}_+LR1_R_{latency}.*\\.nc\")\n",
    "    invent={\"files\":[]}\n",
    "    for dt in tqdm(alldays,desc=\"Scanning directories\"):\n",
    "        subdir=os.path.join(eoafdir,dt.strftime(\"%Y/%m/%d\"))\n",
    "        if os.path.exists(subdir):\n",
    "            for root, dirs, files in os.walk(subdir, topdown=False):\n",
    "                \n",
    "                for f in files:\n",
    "                    ffull=os.path.join(root,f)\n",
    "                    if regex.search(ffull):\n",
    "                        invent[\"files\"].append(ffull)\n",
    "            \n",
    "    \n",
    "    # Also write to inventory\n",
    "    with open(inventfile, 'w') as file:\n",
    "        print(f\"Caching inventory {inventfile}\")\n",
    "        yaml.dump(invent,file)\n",
    "    \n",
    "    return invent\n",
    "    \n",
    "\n",
    "def getGenericSRALInventory(sat,orbit,product,latency,trange):\n",
    "    \"\"\"Downloads the products from the copernicus servers\"\"\"\n",
    "    # opensearchroot=\"https://scihub.copernicus.eu/dhus/search\"\n",
    "    # qry={\"beginPosition\":[2018-01-01T00:00:00.000Z TO 2018-05-31T23:59:59.999Z] AND endPosition:[2018-01-01T00:00:00.000Z TO 2018-05-31T23:59:59.999Z] ) AND ( (platformname:Sentinel-3 AND filename:S3A_* AND producttype:SR_1_SRA_A_ AND timeliness:\"Non Time Critical\" AND productlevel:L1 AND relativeorbitnumber:377)) \n",
    "    raise NotImplementedError(\"This function is not yet implemented\")\n",
    "    \n",
    "    \n",
    "def getS3Inventory(orbit,product,sat,trange=None,latency=\"NT\"):\n",
    "    \n",
    "    try:\n",
    "        return getEOAfricaSRALInventory(sat,orbit,product,latency,trange)\n",
    "    except NotADirectoryError:\n",
    "        #Fall back to download the actual data\n",
    "        return getGenericSRALInventory(sat,orbit,product,latency,trange)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4bced07e-f77e-478e-92b6-09a68e92c5b1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading cached inventory data/EOAfrica_Inventory_S3A_SR_1_SRA_377.yml\n"
     ]
    }
   ],
   "source": [
    "# Get a list of Sentinel-3 netcdf files\n",
    "s3ainvent=getS3Inventory(orbit=s3aorb,trange=[datetime(2018,1,1),datetime(2018,2,28)],product=\"SR_1_SRA\",sat=\"S3A\",latency=\"NT\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e267808c-1e00-4187-af10-deb1d9dff059",
   "metadata": {},
   "source": [
    "## Step 6: Visualize some waveforms "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "73ea4164-61ec-410b-8509-137feb3c32b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "filein=s3ainvent[\"files\"][0] #note select a single file (this one is the descending part of the orbit)\n",
    "#open the file with xarray\n",
    "ds=xr.open_dataset(filein,use_cftime=True,engine=\"netcdf4\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2533d768-37d4-4244-8ac3-f6db4bfd4b08",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                              (echo_sample_ind: 128,\n",
       "                                          max_multi_stack_ind: 256,\n",
       "                                          time_l1b_echo_lrm: 0,\n",
       "                                          time_l1b_echo_sar_ku: 58956,\n",
       "                                          time_l1b_echo_plrm: 57591)\n",
       "Coordinates:\n",
       "  * echo_sample_ind                      (echo_sample_ind) int8 0 1 ... 126 127\n",
       "  * max_multi_stack_ind                  (max_multi_stack_ind) int16 0 1 ... 255\n",
       "  * time_l1b_echo_lrm                    (time_l1b_echo_lrm) object \n",
       "    lat_l1b_echo_lrm                     (time_l1b_echo_lrm) float64 \n",
       "    lon_l1b_echo_lrm                     (time_l1b_echo_lrm) float64 \n",
       "  * time_l1b_echo_sar_ku                 (time_l1b_echo_sar_ku) object 2018-0...\n",
       "    lat_l1b_echo_sar_ku                  (time_l1b_echo_sar_ku) float64 81.42...\n",
       "    lon_l1b_echo_sar_ku                  (time_l1b_echo_sar_ku) float64 131.3...\n",
       "  * time_l1b_echo_plrm                   (time_l1b_echo_plrm) object 2018-01-...\n",
       "    lat_l1b_echo_plrm                    (time_l1b_echo_plrm) float64 81.42 ....\n",
       "    lon_l1b_echo_plrm                    (time_l1b_echo_plrm) float64 131.4 ....\n",
       "Data variables: (12/174)\n",
       "    UTC_day_l1b_echo_lrm                 (time_l1b_echo_lrm) object \n",
       "    UTC_sec_l1b_echo_lrm                 (time_l1b_echo_lrm) float64 \n",
       "    GPS_time_l1b_echo_lrm                (time_l1b_echo_lrm) object \n",
       "    isp_coarse_time_l1b_echo_lrm         (time_l1b_echo_lrm) float64 \n",
       "    isp_fine_time_l1b_echo_lrm           (time_l1b_echo_lrm) float64 \n",
       "    sral_fine_time_l1b_echo_lrm          (time_l1b_echo_lrm) float64 \n",
       "    ...                                   ...\n",
       "    agc_cor_ku_l1b_echo_plrm             (time_l1b_echo_plrm) float64 0.17 .....\n",
       "    agc_cor_c_l1b_echo_plrm              (time_l1b_echo_plrm) float64 0.05 .....\n",
       "    sig0_cal_ku_l1b_echo_plrm            (time_l1b_echo_plrm) float64 0.78 .....\n",
       "    sig0_cal_c_l1b_echo_plrm             (time_l1b_echo_plrm) float64 -0.48 ....\n",
       "    i2q2_meas_ku_l1b_echo_plrm           (time_l1b_echo_plrm, echo_sample_ind) float64 ...\n",
       "    i2q2_meas_c_l1b_echo_plrm            (time_l1b_echo_plrm, echo_sample_ind) float64 ...\n",
       "Attributes: (12/29)\n",
       "    Conventions:                      CF-1.6\n",
       "    title:                            IPF SRAL Level 1 Measurement\n",
       "    mission_name:                     Sentinel 3A\n",
       "    altimeter_sensor_name:            SRAL\n",
       "    gnss_sensor_name:                 GNSS\n",
       "    doris_sensor_name:                DORIS\n",
       "    ...                               ...\n",
       "    source:                           IPF-SR-1 06.13\n",
       "    history:                           \n",
       "    contact:                          s3ome@acri-st.fr\n",
       "    creation_time:                    2018-03-02T03:13:32Z\n",
       "    first_meas_time:                  2018-01-16T07:13:52.506803Z\n",
       "    last_meas_time:                   2018-01-16T08:04:21.473974Z</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a78d981d-9e59-4bdc-91b1-11ac174d0e7e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a78d981d-9e59-4bdc-91b1-11ac174d0e7e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>echo_sample_ind</span>: 128</li><li><span class='xr-has-index'>max_multi_stack_ind</span>: 256</li><li><span class='xr-has-index'>time_l1b_echo_lrm</span>: 0</li><li><span class='xr-has-index'>time_l1b_echo_sar_ku</span>: 58956</li><li><span class='xr-has-index'>time_l1b_echo_plrm</span>: 57591</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0b5729ce-f5aa-4e5d-8b87-f92d3f11ad5e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0b5729ce-f5aa-4e5d-8b87-f92d3f11ad5e' class='xr-section-summary' >Coordinates: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>echo_sample_ind</span></div><div class='xr-var-dims'>(echo_sample_ind)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 123 124 125 126 127</div><input id='attrs-3b12f4e4-ebe4-40b5-b786-09e30609863f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b12f4e4-ebe4-40b5-b786-09e30609863f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35d5438d-721f-474a-9e5b-6ac15a5cead0' class='xr-var-data-in' type='checkbox'><label for='data-35d5438d-721f-474a-9e5b-6ac15a5cead0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>number of samples in I2+Q2, I and Q echoes</dd><dt><span>units :</span></dt><dd>count</dd><dt><span>comment :</span></dt><dd>Set to be compliant with the CF-1.6 convention</dd></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,  13,\n",
       "        14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,  26,  27,\n",
       "        28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,  40,  41,\n",
       "        42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,  55,\n",
       "        56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,\n",
       "        70,  71,  72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,\n",
       "        84,  85,  86,  87,  88,  89,  90,  91,  92,  93,  94,  95,  96,  97,\n",
       "        98,  99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,\n",
       "       112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125,\n",
       "       126, 127], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>max_multi_stack_ind</span></div><div class='xr-var-dims'>(max_multi_stack_ind)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 251 252 253 254 255</div><input id='attrs-4ab9e0ca-b602-41e5-9a6b-39904c632b77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ab9e0ca-b602-41e5-9a6b-39904c632b77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a527953d-370d-4cae-bf4b-6fe21bce5239' class='xr-var-data-in' type='checkbox'><label for='data-a527953d-370d-4cae-bf4b-6fe21bce5239' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>maximum number of multilook beams per stack</dd><dt><span>units :</span></dt><dd>count</dd><dt><span>comment :</span></dt><dd>Set to be compliant with the CF-1.6 convention</dd></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 253, 254, 255], dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'></div><input id='attrs-1f4944b8-af82-4279-97a1-ac66a7692d5a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f4944b8-af82-4279-97a1-ac66a7692d5a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06a35dcd-8e00-48a3-8494-2e970f73a562' class='xr-var-data-in' type='checkbox'><label for='data-06a35dcd-8e00-48a3-8494-2e970f73a562' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>UTC : l1b_echo_lrm mode</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d7c02c47-7251-4a5a-9898-c7a57f06812a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7c02c47-7251-4a5a-9898-c7a57f06812a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e0a51ff-efd0-41b6-a27d-50752969870e' class='xr-var-data-in' type='checkbox'><label for='data-3e0a51ff-efd0-41b6-a27d-50752969870e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude : l1b_echo_lrm mode</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6391f8ad-34e2-43b9-9f6b-cc6ddf0094fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6391f8ad-34e2-43b9-9f6b-cc6ddf0094fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d77d94d-89e8-4d90-b52e-cd48675a88cd' class='xr-var-data-in' type='checkbox'><label for='data-5d77d94d-89e8-4d90-b52e-cd48675a88cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude : l1b_echo_lrm mode</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>2018-01-16 07:13:52.543664 ... 2...</div><input id='attrs-4dcb4d12-70e6-485d-a5d9-e1d41a16b274' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4dcb4d12-70e6-485d-a5d9-e1d41a16b274' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07ba57c6-c359-41de-a0a6-007f9bfff253' class='xr-var-data-in' type='checkbox'><label for='data-07ba57c6-c359-41de-a0a6-007f9bfff253' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>UTC : l1b_echo_sar_ku mode</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeGregorian(2018, 1, 16, 7, 13, 52, 543664, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 7, 13, 52, 593505, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 7, 13, 52, 643358, has_year_zero=False),\n",
       "       ...,\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 8, 4, 21, 371619, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 8, 4, 21, 422796, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 8, 4, 21, 473974, has_year_zero=False)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f1d4093f-2ad7-40f4-af26-d064bd20fce7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1d4093f-2ad7-40f4-af26-d064bd20fce7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0cfdd3b7-a559-4499-9de6-515845c1c498' class='xr-var-data-in' type='checkbox'><label for='data-0cfdd3b7-a559-4499-9de6-515845c1c498' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude : l1b_echo_sar_ku mode</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 81.416987,  81.416976,  81.416964, ..., -81.415993, -81.415997,\n",
       "       -81.416001])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-30df2903-6029-4278-bca3-0651bca67d12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30df2903-6029-4278-bca3-0651bca67d12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e14e9bf-d0f4-4cfe-b7c3-c7d46e2d29a7' class='xr-var-data-in' type='checkbox'><label for='data-4e14e9bf-d0f4-4cfe-b7c3-c7d46e2d29a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude : l1b_echo_sar_ku mode</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([131.335393, 131.315418, 131.295439, ..., 299.021434, 299.001017,\n",
       "       298.9806  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>2018-01-16 07:13:52.506803 ... 2...</div><input id='attrs-38a2e8cb-c409-4111-a2f0-da490a566f2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-38a2e8cb-c409-4111-a2f0-da490a566f2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10f8fa81-7c58-415d-982a-898e8219d289' class='xr-var-data-in' type='checkbox'><label for='data-10f8fa81-7c58-415d-982a-898e8219d289' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>UTC : l1b_echo_plrm mode</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeGregorian(2018, 1, 16, 7, 13, 52, 506803, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 7, 13, 52, 557738, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 7, 13, 52, 608674, has_year_zero=False),\n",
       "       ...,\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 8, 4, 21, 358262, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 8, 4, 21, 409197, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 8, 4, 21, 460133, has_year_zero=False)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7c240191-f740-48db-9086-8155cbf20110' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c240191-f740-48db-9086-8155cbf20110' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5702b508-a8c2-4714-98a3-a40a7c368db7' class='xr-var-data-in' type='checkbox'><label for='data-5702b508-a8c2-4714-98a3-a40a7c368db7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude : l1b_echo_plrm mode</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 81.416995,  81.416984,  81.416973, ..., -81.415991, -81.415996,\n",
       "       -81.416   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5a40103e-1ecf-4138-8824-e68fd093a9cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a40103e-1ecf-4138-8824-e68fd093a9cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64fe2204-7089-4244-bab6-946e612845a0' class='xr-var-data-in' type='checkbox'><label for='data-64fe2204-7089-4244-bab6-946e612845a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude : l1b_echo_plrm mode</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([131.350166, 131.329753, 131.309339, ..., 299.026762, 299.006442,\n",
       "       298.986122])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dddad2c7-9fa9-48ac-a420-c52e19422170' class='xr-section-summary-in' type='checkbox'  ><label for='section-dddad2c7-9fa9-48ac-a420-c52e19422170' class='xr-section-summary' >Data variables: <span>(174)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>UTC_day_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dab817ee-2167-41dc-96ae-49d6823eafc6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dab817ee-2167-41dc-96ae-49d6823eafc6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d76a2f0d-cdbf-47cd-bd64-d9574b38c839' class='xr-var-data-in' type='checkbox'><label for='data-d76a2f0d-cdbf-47cd-bd64-d9574b38c839' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>day UTC : l1b_echo_lrm mode</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UTC_sec_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bfba595a-c402-460a-9709-333968ed45a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfba595a-c402-460a-9709-333968ed45a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55beeb64-2f09-4855-9a8a-89100ea44eed' class='xr-var-data-in' type='checkbox'><label for='data-55beeb64-2f09-4855-9a8a-89100ea44eed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>seconds in the day UTC : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GPS_time_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9267e24d-6f7d-479a-af40-926fce80eb60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9267e24d-6f7d-479a-af40-926fce80eb60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ff87ed8-e5b5-4f22-b70a-936c306b34fe' class='xr-var-data-in' type='checkbox'><label for='data-5ff87ed8-e5b5-4f22-b70a-936c306b34fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>GPS time : l1b_echo_lrm mode</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>isp_coarse_time_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-07abf778-4de3-4cf9-ba5e-45ef1fbaaf08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07abf778-4de3-4cf9-ba5e-45ef1fbaaf08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05c895da-0f62-4f40-9314-17a6591b9bc4' class='xr-var-data-in' type='checkbox'><label for='data-05c895da-0f62-4f40-9314-17a6591b9bc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ISP coarse time : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>second</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>isp_fine_time_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-eb4f25b1-7a4f-4d9e-81f0-4e3c5870c6cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb4f25b1-7a4f-4d9e-81f0-4e3c5870c6cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89b8a1e0-936f-4a8c-9ee4-443e46fef9db' class='xr-var-data-in' type='checkbox'><label for='data-89b8a1e0-936f-4a8c-9ee4-443e46fef9db' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ISP fine time : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>2^-24 second</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sral_fine_time_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b94dcaa3-8943-4867-ba79-31233de15cec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b94dcaa3-8943-4867-ba79-31233de15cec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92055ccf-ccdf-4208-a14d-2b8b2df0f3a5' class='xr-var-data-in' type='checkbox'><label for='data-92055ccf-ccdf-4208-a14d-2b8b2df0f3a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ISP SRAL fine datation : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>137.5*10^-9 second</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>alt_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5f62a9cd-4f33-44a3-907b-db14dbdf4a37' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5f62a9cd-4f33-44a3-907b-db14dbdf4a37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0dc47f2-48d5-4fcc-8937-b9da7ae83383' class='xr-var-data-in' type='checkbox'><label for='data-a0dc47f2-48d5-4fcc-8937-b9da7ae83383' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>altitude of satellite : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orb_alt_rate_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8a20e456-1697-4ed4-b9e3-3a2b0b00b1d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a20e456-1697-4ed4-b9e3-3a2b0b00b1d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-242bdf9b-adf8-4e4d-93ba-2fa4512624c3' class='xr-var-data-in' type='checkbox'><label for='data-242bdf9b-adf8-4e4d-93ba-2fa4512624c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>orbital altitude rate : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_time_status_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e4d0301a-85ae-4005-ac85-03dcf80322b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e4d0301a-85ae-4005-ac85-03dcf80322b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-561ca9a5-beaf-4910-b824-c66c485751c4' class='xr-var-data-in' type='checkbox'><label for='data-561ca9a5-beaf-4910-b824-c66c485751c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time status flag : l1b_echo_lrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>comment :</span></dt><dd>flag indicating if the time is synchronized or not with GPS time</dd><dt><span>flag_meanings :</span></dt><dd>synchronization no_synchronization</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_time_corr_val_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5619699e-5371-4c95-9470-14692345bec1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5619699e-5371-4c95-9470-14692345bec1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09282c58-a5c3-46a4-8bc0-bb214fd80bf1' class='xr-var-data-in' type='checkbox'><label for='data-09282c58-a5c3-46a4-8bc0-bb214fd80bf1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time correlation validity flag : l1b_echo_lrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1 2]</dd><dt><span>comment :</span></dt><dd>flag indicating if the time correlation information is valid provided by OBSW, valid provided by Ground Segment or invalid</dd><dt><span>flag_meanings :</span></dt><dd>valid_obsw valid_ground_segment invalid</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_man_pres_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-05d26dd5-78d5-4e51-99f4-1ec59d229442' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05d26dd5-78d5-4e51-99f4-1ec59d229442' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a85d933-babf-4b9f-9365-6b8c071d4b11' class='xr-var-data-in' type='checkbox'><label for='data-8a85d933-babf-4b9f-9365-6b8c071d4b11' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>manoeuvre presence flag: l1b_echo_lrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>no_manoeuvre ongoing_manoeuvre</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_man_thrust_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8788a7f1-89fd-4206-9620-bdadf9b26bcb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8788a7f1-89fd-4206-9620-bdadf9b26bcb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-702dafd2-cffe-4c13-b670-59882c1222ae' class='xr-var-data-in' type='checkbox'><label for='data-702dafd2-cffe-4c13-b670-59882c1222ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>manoeuvre thrust flag: l1b_echo_lrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>no_thrust ongoing_thrust</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_man_plane_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-64331e47-ff3e-4f4e-b18d-0ab50d84a46a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64331e47-ff3e-4f4e-b18d-0ab50d84a46a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e49c971b-ab9b-40fd-af27-a3b6ee012a2a' class='xr-var-data-in' type='checkbox'><label for='data-e49c971b-ab9b-40fd-af27-a3b6ee012a2a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>manoeuvre plane flag: l1b_echo_lrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>in_plane out_of_plane</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_gnss_status_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2810d58a-b2cd-4ffe-8485-1668229e5c9c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2810d58a-b2cd-4ffe-8485-1668229e5c9c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b04d2454-7c91-4c39-aac3-53cb2e53d6bb' class='xr-var-data-in' type='checkbox'><label for='data-b04d2454-7c91-4c39-aac3-53cb2e53d6bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>validity flag for the navigation message from the gnss receiver: l1b_echo_lrm mode</dd><dt><span>comment :</span></dt><dd>indicating if the navigation message from the GNSS receiver is valid or not valid/available</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>valid invalid_unavailable</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x_pos_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-875fcd05-f45c-4f77-9d16-fee901ae3e7d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-875fcd05-f45c-4f77-9d16-fee901ae3e7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3232c4ce-1c42-42b2-9480-9c652f24ee7e' class='xr-var-data-in' type='checkbox'><label for='data-3232c4ce-1c42-42b2-9480-9c652f24ee7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite altitude - x component : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y_pos_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-edecfd08-912b-400a-9a4b-b94c99238e52' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-edecfd08-912b-400a-9a4b-b94c99238e52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42d7006c-a1d6-43a4-b5fb-61f261de5fab' class='xr-var-data-in' type='checkbox'><label for='data-42d7006c-a1d6-43a4-b5fb-61f261de5fab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite altitude - y component : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z_pos_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-36a47026-6078-47d5-a78b-9703cce19784' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36a47026-6078-47d5-a78b-9703cce19784' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4269311-ae72-4652-8b15-d39b9a7ef0da' class='xr-var-data-in' type='checkbox'><label for='data-d4269311-ae72-4652-8b15-d39b9a7ef0da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite altitude - z component : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x_vel_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2a3d37f5-4d3f-401f-976f-acd1ada6fa1b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a3d37f5-4d3f-401f-976f-acd1ada6fa1b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83992021-761a-4fe8-af24-5d54fc29dc32' class='xr-var-data-in' type='checkbox'><label for='data-83992021-761a-4fe8-af24-5d54fc29dc32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite velocity - x component : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y_vel_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b5807467-5470-4acd-add0-de168757d84f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5807467-5470-4acd-add0-de168757d84f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad949cc0-04a2-45a9-a016-a6eaa0a97bc2' class='xr-var-data-in' type='checkbox'><label for='data-ad949cc0-04a2-45a9-a016-a6eaa0a97bc2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite velocity - y component : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z_vel_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-22d358c7-5fcd-4414-b661-4db76a6a7842' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22d358c7-5fcd-4414-b661-4db76a6a7842' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-548c1ccd-78b7-4016-afa5-38eefcb8a03a' class='xr-var-data-in' type='checkbox'><label for='data-548c1ccd-78b7-4016-afa5-38eefcb8a03a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite velocity - z component : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nav_bul_status_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-df74f26a-a0a0-4227-9331-a0731c3d0c2e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df74f26a-a0a0-4227-9331-a0731c3d0c2e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d07480ab-1748-4bb3-8776-b854a0c1f060' class='xr-var-data-in' type='checkbox'><label for='data-d07480ab-1748-4bb3-8776-b854a0c1f060' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>navigation bulletin status : l1b_echo_lrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>ok ko</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nav_bul_source_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1ba38ffe-4ae1-4806-bd0c-71c55819da74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ba38ffe-4ae1-4806-bd0c-71c55819da74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-992bdd7c-a353-479b-b792-d221fb0150bc' class='xr-var-data-in' type='checkbox'><label for='data-992bdd7c-a353-479b-b792-d221fb0150bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>navigation bulletin source identifier : l1b_echo_lrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>gps doris</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nav_bul_coarse_time_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f07c7d56-8218-4029-bce0-a40d67454c40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f07c7d56-8218-4029-bce0-a40d67454c40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67c5e031-91b6-4450-bf16-8837411b06ea' class='xr-var-data-in' type='checkbox'><label for='data-67c5e031-91b6-4450-bf16-8837411b06ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>navigation bulletin coarse time : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>second</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nav_bul_fine_time_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-21e626d0-6709-4a0e-93a6-ee73e1e47f26' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21e626d0-6709-4a0e-93a6-ee73e1e47f26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c83e061-3157-42a3-a80e-21bc980b52b5' class='xr-var-data-in' type='checkbox'><label for='data-0c83e061-3157-42a3-a80e-21bc980b52b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>navigation bulletin fine time : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>2^-24 second</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>seq_count_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-26ea42c0-337f-4770-9113-d4ce0db5505f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26ea42c0-337f-4770-9113-d4ce0db5505f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c101d9aa-eff5-4f02-8fe3-7fd0525761e3' class='xr-var-data-in' type='checkbox'><label for='data-c101d9aa-eff5-4f02-8fe3-7fd0525761e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>sequence count : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>count</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>isp_time_status_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-96abef4f-8c9b-47d4-b8dd-20821bd2759c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96abef4f-8c9b-47d4-b8dd-20821bd2759c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09232f1c-5161-426e-9b84-59491cbaa4ca' class='xr-var-data-in' type='checkbox'><label for='data-09232f1c-5161-426e-9b84-59491cbaa4ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ISP time status : l1b_echo_lrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>SRAL_OBT_extrapolated SRAL_OBT_updated_with_SMU_OBT</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>oper_instr_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-10f073c2-6338-4ff6-a4fd-d3e1a8e39fb1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10f073c2-6338-4ff6-a4fd-d3e1a8e39fb1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17d2e41c-4dca-46d8-a901-55974ece798d' class='xr-var-data-in' type='checkbox'><label for='data-17d2e41c-4dca-46d8-a901-55974ece798d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>operating instrument : l1b_echo_lrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>A B</dd><dt><span>comment :</span></dt><dd>Instrument A stands for SRAL Nominal and instrument B stands for SRAL Redundant</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mode_id_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b8be6968-e2e4-4faf-8721-b72a6543db5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b8be6968-e2e4-4faf-8721-b72a6543db5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73f9ebca-d87b-4ffb-8a61-0f396f4e031c' class='xr-var-data-in' type='checkbox'><label for='data-73f9ebca-d87b-4ffb-8a61-0f396f4e031c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>LRM mode identifier : l1b_echo_lrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>closed_loop open_loop</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cl_gain_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-84ff7fe6-1059-46f6-9ee7-f54c3e2be66d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-84ff7fe6-1059-46f6-9ee7-f54c3e2be66d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdb90e62-b6e6-43ce-969b-c41c7976f53e' class='xr-var-data-in' type='checkbox'><label for='data-fdb90e62-b6e6-43ce-969b-c41c7976f53e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>tracking configuration - closed loop gain : l1b_echo_lrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd> Nominal_value Nominal_value_with_back-off </dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acq_stat_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-74526431-f5b0-4c39-a41d-5124d8b09124' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74526431-f5b0-4c39-a41d-5124d8b09124' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06580662-2c74-4927-b35c-29fc1851c9ee' class='xr-var-data-in' type='checkbox'><label for='data-06580662-2c74-4927-b35c-29fc1851c9ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>tracking configuration - acquisition status : l1b_echo_lrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>no_acquisition acquisition</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dem_eeprom_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3d0111a4-9b05-4099-bb61-f74ce5d8d1e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d0111a4-9b05-4099-bb61-f74ce5d8d1e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e299e35a-04f4-41bf-bff1-4055629da8df' class='xr-var-data-in' type='checkbox'><label for='data-e299e35a-04f4-41bf-bff1-4055629da8df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>tracking configuration - DEM EEPROM read access : l1b_echo_lrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>enabled disabled </dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>weighting_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-54f4efa8-a7d3-485c-aeb1-b18241647d83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-54f4efa8-a7d3-485c-aeb1-b18241647d83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29289469-7f83-456f-a519-6dff4ce3d45d' class='xr-var-data-in' type='checkbox'><label for='data-29289469-7f83-456f-a519-6dff4ce3d45d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>altimeter configuration - weighting function : l1b_echo_lrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>enabled disabled </dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>loss_track_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6e2d7018-3e05-4cf9-a5e6-b1907684853c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e2d7018-3e05-4cf9-a5e6-b1907684853c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-839690a9-0093-4fd6-808c-e6e9eddc2ce1' class='xr-var-data-in' type='checkbox'><label for='data-839690a9-0093-4fd6-808c-e6e9eddc2ce1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>loss of track criterion : l1b_echo_lrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>normal loss_of_track</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h0_nav_dem_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fd90904a-de3f-492b-8137-b4ca01953b4d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd90904a-de3f-492b-8137-b4ca01953b4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbcb1e20-da47-42bb-b9e5-dd3f7a41a54d' class='xr-var-data-in' type='checkbox'><label for='data-dbcb1e20-da47-42bb-b9e5-dd3f7a41a54d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>altitude command H0 computed with nav / DEM : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>3.125/64*10^-9 s</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h0_applied_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5c5edeb4-d540-493c-b61d-cec93e956f68' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c5edeb4-d540-493c-b61d-cec93e956f68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-175eea51-4072-4749-8bf5-9608858f6325' class='xr-var-data-in' type='checkbox'><label for='data-175eea51-4072-4749-8bf5-9608858f6325' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>applied altitude command H0 : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>3.125/64*10^-9 s</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cor2_nav_dem_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-46abf1b1-a220-4c8e-8d9b-5da6b5116491' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46abf1b1-a220-4c8e-8d9b-5da6b5116491' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-afc03fc0-28c2-4074-b740-cb9973a53567' class='xr-var-data-in' type='checkbox'><label for='data-afc03fc0-28c2-4074-b740-cb9973a53567' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>altitude command COR2 computed with nav / DEM : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>3.125/1024 10-9 s</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cor2_applied_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-12fd2adf-bbf7-4b97-9fc2-403a66329856' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12fd2adf-bbf7-4b97-9fc2-403a66329856' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ccd13449-e38e-4769-b1df-2eaafaaec17e' class='xr-var-data-in' type='checkbox'><label for='data-ccd13449-e38e-4769-b1df-2eaafaaec17e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>applied altitude command COR2 : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>3.125/1024*10^-9 s</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dh0_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b8d32f07-09c8-4eba-9af6-97be0eb27ece' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b8d32f07-09c8-4eba-9af6-97be0eb27ece' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be210449-6288-4327-a1b5-7dca52d02913' class='xr-var-data-in' type='checkbox'><label for='data-be210449-6288-4327-a1b5-7dca52d02913' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd> distance error computed on the echo of the cycle (N-2) in open loop mode (current cyc</dd><dt><span>units :</span></dt><dd>3.125/64*10^-9 s</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>agccode_ku_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ca8b7e0a-d6f7-4af9-b95b-b663785885fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca8b7e0a-d6f7-4af9-b95b-b663785885fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a24f84a-ccb4-46d8-ad08-382b80f49de4' class='xr-var-data-in' type='checkbox'><label for='data-9a24f84a-ccb4-46d8-ad08-382b80f49de4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>AGCCODE for ku band : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>agccode_c_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-36eb4eab-8add-4558-83d5-d9dbf75741c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36eb4eab-8add-4558-83d5-d9dbf75741c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9533e10a-5a56-4884-bf52-2796a5418860' class='xr-var-data-in' type='checkbox'><label for='data-9533e10a-5a56-4884-bf52-2796a5418860' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>AGCCODE for c band : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>surf_type_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a8e17549-4149-407f-9686-bc1272f43cb8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a8e17549-4149-407f-9686-bc1272f43cb8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-478e74c6-dfdd-4f24-834b-c7e25a938d60' class='xr-var-data-in' type='checkbox'><label for='data-478e74c6-dfdd-4f24-834b-c7e25a938d60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>altimeter surface type : l1b_echo_lrm mode </dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3]</dd><dt><span>flag_meanings :</span></dt><dd>open_ocean_or_semi-enclosed_seas enclosed_seas_or_lakes continental_ice land</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>range_ku_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-aec8a2e9-a6e2-4988-9cde-fc32256b4fae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aec8a2e9-a6e2-4988-9cde-fc32256b4fae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e7f3a3b-6ee7-4003-b27a-549487d82731' class='xr-var-data-in' type='checkbox'><label for='data-4e7f3a3b-6ee7-4003-b27a-549487d82731' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>corrected range for ku band : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>range_c_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f1e47bfd-930b-46e5-a032-f3542fdfe336' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1e47bfd-930b-46e5-a032-f3542fdfe336' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-560332f9-0ddd-4afa-8e96-8d340789e15b' class='xr-var-data-in' type='checkbox'><label for='data-560332f9-0ddd-4afa-8e96-8d340789e15b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>corrected range for c band : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uso_cor_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7c24bfef-26cc-471f-a3b3-c9e6b27fa586' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c24bfef-26cc-471f-a3b3-c9e6b27fa586' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-359564fd-00ad-4db2-b53a-4f3ce3f6b9fc' class='xr-var-data-in' type='checkbox'><label for='data-359564fd-00ad-4db2-b53a-4f3ce3f6b9fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>USO frequency drift correction : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>int_path_cor_ku_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-597110f2-f7a5-4b6d-bd01-11720bee67f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-597110f2-f7a5-4b6d-bd01-11720bee67f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b74daf58-b17a-4d15-898b-a9deeee39c38' class='xr-var-data-in' type='checkbox'><label for='data-b74daf58-b17a-4d15-898b-a9deeee39c38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>internal path correction for ku band : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>int_path_cor_c_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ad36d26e-5a3a-4b90-99e4-22f41c183135' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad36d26e-5a3a-4b90-99e4-22f41c183135' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47595b39-ed79-4e1f-bad1-5e84678324c3' class='xr-var-data-in' type='checkbox'><label for='data-47595b39-ed79-4e1f-bad1-5e84678324c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>internal path correction for c band : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dop_cor_ku_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c3e5e508-0c74-40ad-8c9c-5b97f73d5f26' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3e5e508-0c74-40ad-8c9c-5b97f73d5f26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a92f8c7a-3377-489f-aae7-74fc800c813c' class='xr-var-data-in' type='checkbox'><label for='data-a92f8c7a-3377-489f-aae7-74fc800c813c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>doppler correction for ku band : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dop_cor_c_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-33e64bac-3e0d-4dfb-848d-32b869707f86' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33e64bac-3e0d-4dfb-848d-32b869707f86' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e9307c9-bcf8-4bde-8f05-0326321c97a9' class='xr-var-data-in' type='checkbox'><label for='data-0e9307c9-bcf8-4bde-8f05-0326321c97a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>doppler correction for c band : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>range_rate_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-57bcf989-c9e6-4ce9-bce2-abaa94d9412a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-57bcf989-c9e6-4ce9-bce2-abaa94d9412a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cba80e67-df42-4a31-abfb-a07ca78705fc' class='xr-var-data-in' type='checkbox'><label for='data-cba80e67-df42-4a31-abfb-a07ca78705fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>range rate : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>agc_ku_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-572c53c5-3762-4679-956f-b6aa0fc18b69' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-572c53c5-3762-4679-956f-b6aa0fc18b69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a12787dc-354b-4542-883e-79d133cb5031' class='xr-var-data-in' type='checkbox'><label for='data-a12787dc-354b-4542-883e-79d133cb5031' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>corrected AGC for ku band: l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>comment :</span></dt><dd> AGC corrected for instrumental errors </dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>agc_c_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-aa31b4e5-c4b7-46a2-964e-95e0a7b3277c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa31b4e5-c4b7-46a2-964e-95e0a7b3277c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae9d8fbb-df2d-40da-a9e5-004936935571' class='xr-var-data-in' type='checkbox'><label for='data-ae9d8fbb-df2d-40da-a9e5-004936935571' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>corrected AGC for c band: l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>comment :</span></dt><dd> AGC corrected for instrumental errors </dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>scale_factor_ku_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b2b69ad5-c2a2-421f-a011-cfd250d1d743' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2b69ad5-c2a2-421f-a011-cfd250d1d743' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af33beb0-6ccd-4b6b-b870-f335b1bd6269' class='xr-var-data-in' type='checkbox'><label for='data-af33beb0-6ccd-4b6b-b870-f335b1bd6269' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>scaling factor for sigma0 evaluation for ku band: l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>comment :</span></dt><dd>scaling factor corrected for AGC instrumental errors and internal calibration</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>scale_factor_c_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-17190f00-0003-4c2e-838a-4a34f8bd30ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17190f00-0003-4c2e-838a-4a34f8bd30ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de29723e-f30f-46fe-9ce1-9ff7f30ac8f1' class='xr-var-data-in' type='checkbox'><label for='data-de29723e-f30f-46fe-9ce1-9ff7f30ac8f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>scaling factor for sigma0 evaluation for c band: l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>comment :</span></dt><dd>scaling factor corrected for AGC instrumental errors and internal calibration</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>agc_cor_ku_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7236b6c8-397c-41f0-a3d5-0111eec933db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7236b6c8-397c-41f0-a3d5-0111eec933db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59a68446-7f8f-4e8a-b63b-00b6f96aab13' class='xr-var-data-in' type='checkbox'><label for='data-59a68446-7f8f-4e8a-b63b-00b6f96aab13' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>correction for instrumental errors on AGC for ku band: l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>agc_cor_c_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-788da7e8-f3a1-4f54-b5a4-c1e17dacdbd5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-788da7e8-f3a1-4f54-b5a4-c1e17dacdbd5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ccbce15-933f-4119-9a5f-df1d6b3e2f77' class='xr-var-data-in' type='checkbox'><label for='data-5ccbce15-933f-4119-9a5f-df1d6b3e2f77' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>correction for instrumental errors on AGC for c band: l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sig0_cal_ku_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6bccd099-5a9d-4188-9d8a-e07f89559a03' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6bccd099-5a9d-4188-9d8a-e07f89559a03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f28f507-80a0-48b3-a1f9-2312a6e345a3' class='xr-var-data-in' type='checkbox'><label for='data-9f28f507-80a0-48b3-a1f9-2312a6e345a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>internal calibration correction on Sigma0 for ku band: l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sig0_cal_c_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a8f9cfe1-348f-468d-9743-afe1c14820ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a8f9cfe1-348f-468d-9743-afe1c14820ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c5fadb7-8a08-459b-8c34-434af8473290' class='xr-var-data-in' type='checkbox'><label for='data-0c5fadb7-8a08-459b-8c34-434af8473290' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>internal calibration correction on Sigma0 for c band: l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>i2q2_meas_ku_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm, echo_sample_ind)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-549c6840-2fb3-4a37-b5b9-cac6044f43c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-549c6840-2fb3-4a37-b5b9-cac6044f43c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-244f94e8-2a22-49da-b25b-129300dc6c00' class='xr-var-data-in' type='checkbox'><label for='data-244f94e8-2a22-49da-b25b-129300dc6c00' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>I2+Q2 measurement for ku band : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>count</dd><dt><span>comment :</span></dt><dd>the echo is corrected for the GPRW effect</dd></dl></div><div class='xr-var-data'><pre>array([], shape=(0, 128), dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>i2q2_meas_c_l1b_echo_lrm</span></div><div class='xr-var-dims'>(time_l1b_echo_lrm, echo_sample_ind)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4b1c71f5-eca3-44e8-86af-621492c359d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b1c71f5-eca3-44e8-86af-621492c359d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40232d91-0282-44e1-850e-689f1548d9e6' class='xr-var-data-in' type='checkbox'><label for='data-40232d91-0282-44e1-850e-689f1548d9e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>I2+Q2 measurement for c band : l1b_echo_lrm mode</dd><dt><span>units :</span></dt><dd>count</dd><dt><span>comment :</span></dt><dd>the echo is corrected for the GPRW effect</dd></dl></div><div class='xr-var-data'><pre>array([], shape=(0, 128), dtype=float64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UTC_day_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3719821b-b0d7-42db-a935-a4cae242c7a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3719821b-b0d7-42db-a935-a4cae242c7a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b67b77f-c59f-4e65-ab7a-5dfe69b0408b' class='xr-var-data-in' type='checkbox'><label for='data-5b67b77f-c59f-4e65-ab7a-5dfe69b0408b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>day UTC : l1b_echo_sar_ku mode</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeGregorian(2018, 1, 16, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 0, 0, 0, 0, has_year_zero=False),\n",
       "       ...,\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 0, 0, 0, 0, has_year_zero=False)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UTC_sec_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b7a2d2c4-1c53-49e8-9798-cf81636372db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b7a2d2c4-1c53-49e8-9798-cf81636372db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c886c74-db5b-4e0b-9b51-ad8836744ad3' class='xr-var-data-in' type='checkbox'><label for='data-8c886c74-db5b-4e0b-9b51-ad8836744ad3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>seconds in the day UTC : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([26032.543664, 26032.593505, 26032.643358, ..., 29061.371619,\n",
       "       29061.422796, 29061.473974])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GPS_time_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c4d4f7bd-0344-48ab-8e44-ee1356143a80' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c4d4f7bd-0344-48ab-8e44-ee1356143a80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-80c5c7fa-6874-44b5-aa8a-2c810c2c02aa' class='xr-var-data-in' type='checkbox'><label for='data-80c5c7fa-6874-44b5-aa8a-2c810c2c02aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>GPS time : l1b_echo_sar_ku mode</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeGregorian(2018, 1, 16, 7, 14, 10, 543664, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 7, 14, 10, 593505, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 7, 14, 10, 643358, has_year_zero=False),\n",
       "       ...,\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 8, 4, 39, 371619, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 8, 4, 39, 422796, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 8, 4, 39, 473974, has_year_zero=False)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>isp_coarse_time_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0910318c-2b36-405f-a796-f86c96bc79c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0910318c-2b36-405f-a796-f86c96bc79c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4e3563b-7c27-41e1-8ab8-496caa0d3fd9' class='xr-var-data-in' type='checkbox'><label for='data-d4e3563b-7c27-41e1-8ab8-496caa0d3fd9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ISP coarse time : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>second</dd></dl></div><div class='xr-var-data'><pre>array([1.200122e+09, 1.200122e+09, 1.200122e+09, ..., 1.200125e+09,\n",
       "       1.200125e+09, 1.200125e+09])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>isp_fine_time_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dbdf7ccf-6655-4794-8c95-2611405c9740' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dbdf7ccf-6655-4794-8c95-2611405c9740' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b354b66c-2718-455d-abd2-59984cb0423d' class='xr-var-data-in' type='checkbox'><label for='data-b354b66c-2718-455d-abd2-59984cb0423d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ISP fine time : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>2^-24 second</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sral_fine_time_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c7d03ec0-97da-4881-b22f-c4f7d7b433b6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7d03ec0-97da-4881-b22f-c4f7d7b433b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c8d40b4-87e1-4c3f-8342-b4b13e0c9d10' class='xr-var-data-in' type='checkbox'><label for='data-2c8d40b4-87e1-4c3f-8342-b4b13e0c9d10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ISP SRAL fine datation : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>137.5*10^-9 second</dd></dl></div><div class='xr-var-data'><pre>array([3881850., 4252290., 4622730., ..., 2430720., 2801160., 3171600.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>alt_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-98d88768-6b8c-40eb-9769-ca78c3e79384' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98d88768-6b8c-40eb-9769-ca78c3e79384' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02c6a26f-6076-4dc6-94cf-a1927284c9a1' class='xr-var-data-in' type='checkbox'><label for='data-02c6a26f-6076-4dc6-94cf-a1927284c9a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>altitude of satellite : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([815353.0071, 815353.0051, 815353.003 , ..., 831622.552 , 831622.5517,\n",
       "       831622.5513])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orb_alt_rate_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a0232ed9-b0db-487d-aa98-e1d74f608278' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0232ed9-b0db-487d-aa98-e1d74f608278' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69630900-376a-43f4-bd31-1a0ff2709855' class='xr-var-data-in' type='checkbox'><label for='data-69630900-376a-43f4-bd31-1a0ff2709855' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>orbital altitude rate : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([-0.04, -0.04, -0.04, ...,  0.  , -0.01, -0.01], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_time_status_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-263f9a78-121b-4580-8e95-cabfa7f0b257' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-263f9a78-121b-4580-8e95-cabfa7f0b257' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c376b76-e152-4148-bfba-2606e46e4835' class='xr-var-data-in' type='checkbox'><label for='data-8c376b76-e152-4148-bfba-2606e46e4835' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time status flag : l1b_echo_sar_ku mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>comment :</span></dt><dd>flag indicating if the time is synchronized or not with GPS time</dd><dt><span>flag_meanings :</span></dt><dd>synchronization no_synchronization</dd></dl></div><div class='xr-var-data'><pre>array([1., 1., 1., ..., 1., 1., 1.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_time_corr_val_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d6979e91-7186-431f-9c01-6ca9d1eb27ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d6979e91-7186-431f-9c01-6ca9d1eb27ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2968d8a-44dc-43bd-a892-994bb93294b4' class='xr-var-data-in' type='checkbox'><label for='data-b2968d8a-44dc-43bd-a892-994bb93294b4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time correlation validity flag : l1b_echo_sar_ku mode</dd><dt><span>flag_values :</span></dt><dd>[0 1 2]</dd><dt><span>comment :</span></dt><dd>flag indicating if the time correlation information is valid provided by OBSW, valid provided by Ground Segment or invalid</dd><dt><span>flag_meanings :</span></dt><dd>valid_obsw valid_ground_segment invalid</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_man_pres_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d4cc336c-c144-4057-a393-d25f08ea1fd3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d4cc336c-c144-4057-a393-d25f08ea1fd3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1cf97129-ed6b-4478-8006-e6e3031f4c4e' class='xr-var-data-in' type='checkbox'><label for='data-1cf97129-ed6b-4478-8006-e6e3031f4c4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>manoeuvre presence flag: l1b_echo_sar_ku mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>no_manoeuvre ongoing_manoeuvre</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_man_thrust_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-62d55122-a0b7-48f1-8ee6-e910c726a3a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62d55122-a0b7-48f1-8ee6-e910c726a3a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b939c511-fd47-496b-8d69-b9de776b0160' class='xr-var-data-in' type='checkbox'><label for='data-b939c511-fd47-496b-8d69-b9de776b0160' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>manoeuvre thrust flag: l1b_echo_sar_ku mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>no_thrust ongoing_thrust</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_man_plane_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-165c496c-698d-45a2-9a9b-67e75c4fad4d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-165c496c-698d-45a2-9a9b-67e75c4fad4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ddd0e99d-12ce-4492-aeae-1ee907a1a003' class='xr-var-data-in' type='checkbox'><label for='data-ddd0e99d-12ce-4492-aeae-1ee907a1a003' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>manoeuvre plane flag: l1b_echo_sar_ku mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>in_plane out_of_plane</dd></dl></div><div class='xr-var-data'><pre>array([1., 1., 1., ..., 1., 1., 1.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_gnss_status_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-23b8968d-8532-4b0c-acc3-4245b6d583f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23b8968d-8532-4b0c-acc3-4245b6d583f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c013d67f-9e04-4512-a63b-a9f903fa76b7' class='xr-var-data-in' type='checkbox'><label for='data-c013d67f-9e04-4512-a63b-a9f903fa76b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>validity flag for the navigation message from the gnss receiver: l1b_echo_sar_ku mode</dd><dt><span>comment :</span></dt><dd>indicating if the navigation message from the GNSS receiver is valid or not valid/available</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>valid invalid_unavailable</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x_pos_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d2c47cf1-4c1a-4852-9712-04584feb9d4d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2c47cf1-4c1a-4852-9712-04584feb9d4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dcc3593d-8116-4b64-b5d9-689481ff4be2' class='xr-var-data-in' type='checkbox'><label for='data-dcc3593d-8116-4b64-b5d9-689481ff4be2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite altitude - x component : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([-711125.151028, -710844.160921, -710563.101478, ...,  523586.258848,\n",
       "        523249.644598,  522913.02202 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y_pos_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-08f629f1-078d-47ba-bd0c-4891d5ba0bd1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-08f629f1-078d-47ba-bd0c-4891d5ba0bd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c9a46ea-a7c0-4ad4-b099-de9c16443c18' class='xr-var-data-in' type='checkbox'><label for='data-4c9a46ea-a7c0-4ad4-b099-de9c16443c18' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite altitude - y component : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 808449.043173,  808697.932669,  808946.87611 , ..., -943741.840097,\n",
       "       -943927.832311, -944113.822416])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z_pos_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-504b7b44-66e4-491b-9dfa-0be9ac9affeb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-504b7b44-66e4-491b-9dfa-0be9ac9affeb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f548ba64-110f-422c-af5d-06695ad3d0bd' class='xr-var-data-in' type='checkbox'><label for='data-f548ba64-110f-422c-af5d-06695ad3d0bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite altitude - z component : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 7091310.849534,  7091310.642062,  7091310.415553, ..., -7107379.457812,\n",
       "       -7107379.547596, -7107379.617457])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x_vel_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-31124478-afcc-4f35-81dd-4480f3557a36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31124478-afcc-4f35-81dd-4480f3557a36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e793f7e-63f7-411f-95f6-ecd95c334d2e' class='xr-var-data-in' type='checkbox'><label for='data-5e793f7e-63f7-411f-95f6-ecd95c334d2e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite velocity - x component : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([ 5637.714334,  5637.788534,  5637.862736, ..., -6577.369537,\n",
       "       -6577.425113, -6577.48067 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y_vel_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-17363f46-b1e6-4b6d-9aab-2a18ba9fd68d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17363f46-b1e6-4b6d-9aab-2a18ba9fd68d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a86d5081-9261-404d-98ee-39eb6473f8e2' class='xr-var-data-in' type='checkbox'><label for='data-a86d5081-9261-404d-98ee-39eb6473f8e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite velocity - y component : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([ 4993.730713,  4993.646628,  4993.562511, ..., -3634.313109,\n",
       "       -3634.212707, -3634.112292])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z_vel_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-00299f1f-930a-43c2-a262-9c18de77fa3b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-00299f1f-930a-43c2-a262-9c18de77fa3b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2fe16aa-72fc-4b03-a1e6-d40866945216' class='xr-var-data-in' type='checkbox'><label for='data-b2fe16aa-72fc-4b03-a1e6-d40866945216' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite velocity - z component : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([-3.972243, -4.353108, -4.734062, ..., -1.949015, -1.559704, -1.170387])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nav_bul_status_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-84ef2d67-f72e-44d4-b026-a77f30ccb2c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-84ef2d67-f72e-44d4-b026-a77f30ccb2c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c4bdaa66-6085-4a68-94b7-f5d4cfc66300' class='xr-var-data-in' type='checkbox'><label for='data-c4bdaa66-6085-4a68-94b7-f5d4cfc66300' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>navigation bulletin status : l1b_echo_sar_ku mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd><dt><span>flag_meanings :</span></dt><dd>ok ko</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nav_bul_source_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4ffba376-4a4c-4bcc-9f4d-0c5ab6fa81ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ffba376-4a4c-4bcc-9f4d-0c5ab6fa81ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4a62b60-df66-4e11-a615-dc384e7c0fa5' class='xr-var-data-in' type='checkbox'><label for='data-b4a62b60-df66-4e11-a615-dc384e7c0fa5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>navigation bulletin source identifier : l1b_echo_sar_ku mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd><dt><span>flag_meanings :</span></dt><dd>gps doris</dd></dl></div><div class='xr-var-data'><pre>array([1., 1., 1., ..., 1., 1., 1.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nav_bul_coarse_time_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1c7f5d02-e7b2-4bc4-bfc6-7407f0cc0330' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c7f5d02-e7b2-4bc4-bfc6-7407f0cc0330' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9ff9864-6970-4273-a070-01c54f348cfe' class='xr-var-data-in' type='checkbox'><label for='data-e9ff9864-6970-4273-a070-01c54f348cfe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>navigation bulletin coarse time : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>second</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd></dl></div><div class='xr-var-data'><pre>array([1.200122e+09, 1.200122e+09, 1.200122e+09, ..., 1.200125e+09,\n",
       "       1.200125e+09, 1.200125e+09])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nav_bul_fine_time_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-41013178-f716-4be6-b1dc-a8e89dd637c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-41013178-f716-4be6-b1dc-a8e89dd637c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff79349a-5818-4404-91e0-be109a740ef8' class='xr-var-data-in' type='checkbox'><label for='data-ff79349a-5818-4404-91e0-be109a740ef8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>navigation bulletin fine time : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>2^-24 second</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>seq_count_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0d6627ff-2be0-47a1-abf5-c7aff803189a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d6627ff-2be0-47a1-abf5-c7aff803189a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-add45fcd-b4c0-4860-ba5b-561672db61c9' class='xr-var-data-in' type='checkbox'><label for='data-add45fcd-b4c0-4860-ba5b-561672db61c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>sequence count : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>count</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd></dl></div><div class='xr-var-data'><pre>array([11988., 11992., 11996., ..., 12963., 12967., 12971.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>isp_time_status_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-93391bba-0288-4334-a886-0e3e3f02013b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93391bba-0288-4334-a886-0e3e3f02013b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ebd1a83f-91a6-4254-8762-8363030ae776' class='xr-var-data-in' type='checkbox'><label for='data-ebd1a83f-91a6-4254-8762-8363030ae776' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ISP time status : l1b_echo_sar_ku mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd><dt><span>flag_meanings :</span></dt><dd>SRAL_OBT_extrapolated SRAL_OBT_updated_with_SMU_OBT</dd></dl></div><div class='xr-var-data'><pre>array([1., 1., 1., ..., 1., 1., 1.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>oper_instr_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-227c24a2-4e6c-4759-ad19-72b0f2eacc13' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-227c24a2-4e6c-4759-ad19-72b0f2eacc13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14aee746-e29f-4096-9fe2-6643d3c8c022' class='xr-var-data-in' type='checkbox'><label for='data-14aee746-e29f-4096-9fe2-6643d3c8c022' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>operating instrument : l1b_echo_sar_ku mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>comment :</span></dt><dd>Instrument A stands for SRAL Nominal and instrument B stands for SRAL Redundant</dd><dt><span>flag_meanings :</span></dt><dd>A B</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SAR_mode_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dccdbd80-cefa-477d-b794-c93a855851b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dccdbd80-cefa-477d-b794-c93a855851b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee0c159c-47a5-4a7c-9b66-ceeb0a606de7' class='xr-var-data-in' type='checkbox'><label for='data-ee0c159c-47a5-4a7c-9b66-ceeb0a606de7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd> SAR mode identifier : l1b_echo_sar_ku mode</dd><dt><span>flag_values :</span></dt><dd>[0 1 2]</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd><dt><span>flag_meanings :</span></dt><dd>closed_loop open_loop open_loop_fixed_gain</dd></dl></div><div class='xr-var-data'><pre>array([1., 1., 1., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cl_gain_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f5e158ef-54f7-4a9d-8025-d989c286fd33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f5e158ef-54f7-4a9d-8025-d989c286fd33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fefba22-6abb-4e6b-9b6c-c9331721cbb4' class='xr-var-data-in' type='checkbox'><label for='data-2fefba22-6abb-4e6b-9b6c-c9331721cbb4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>tracking configuration - closed loop gain : l1b_echo_sar_ku mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd><dt><span>flag_meanings :</span></dt><dd> Nominal_value Nominal_value_with_back-off </dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acq_stat_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d584dab6-051d-49ec-9ed8-d2d89cbcf96d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d584dab6-051d-49ec-9ed8-d2d89cbcf96d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40a379cb-9a40-46cb-aba4-c8eacf9f26c2' class='xr-var-data-in' type='checkbox'><label for='data-40a379cb-9a40-46cb-aba4-c8eacf9f26c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>tracking configuration - acquisition status : l1b_echo_sar_ku mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd><dt><span>flag_meanings :</span></dt><dd>no_acquisition acquisition</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dem_eeprom_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5660f35a-85bb-4525-bf92-12bad61d7550' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5660f35a-85bb-4525-bf92-12bad61d7550' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57256654-fbb0-4e71-82db-77f597dc49c2' class='xr-var-data-in' type='checkbox'><label for='data-57256654-fbb0-4e71-82db-77f597dc49c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>tracking configuration - DEM EEPROM read access : l1b_echo_sar_ku mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd><dt><span>flag_meanings :</span></dt><dd>enabled disabled </dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>weighting_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fc350895-acda-4f7b-a307-948ab17eea4a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fc350895-acda-4f7b-a307-948ab17eea4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b93906fc-c44e-4401-9aec-234c5d071e62' class='xr-var-data-in' type='checkbox'><label for='data-b93906fc-c44e-4401-9aec-234c5d071e62' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>altimeter configuration - weighting function : l1b_echo_sar_ku mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd><dt><span>flag_meanings :</span></dt><dd>enabled disabled </dd></dl></div><div class='xr-var-data'><pre>array([1., 1., 1., ..., 1., 1., 1.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>loss_track_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2d7eebcf-e088-49d6-8157-9fdcfb7d06de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d7eebcf-e088-49d6-8157-9fdcfb7d06de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7a89c8c-7f26-4533-bee6-9523b5e07f26' class='xr-var-data-in' type='checkbox'><label for='data-f7a89c8c-7f26-4533-bee6-9523b5e07f26' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>loss of track criterion : l1b_echo_sar_ku mode</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>normal loss_of_track</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h0_nav_dem_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fd73d091-96f2-4d61-9634-1b85f71b14d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd73d091-96f2-4d61-9634-1b85f71b14d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5513cea-451b-407c-afca-803034dfa1a8' class='xr-var-data-in' type='checkbox'><label for='data-a5513cea-451b-407c-afca-803034dfa1a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>altitude command H0 computed with nav / DEM : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>3.125/64*10^-9 s</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd></dl></div><div class='xr-var-data'><pre>array([1.114018e+08, 1.114018e+08, 1.114018e+08, ..., 1.136119e+08,\n",
       "       1.136119e+08, 1.136120e+08])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h0_applied_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-32c79023-3d71-4a62-a3b1-b4c8bb4b689e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32c79023-3d71-4a62-a3b1-b4c8bb4b689e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-130a85e1-8b10-4e11-8681-0e7845c3420d' class='xr-var-data-in' type='checkbox'><label for='data-130a85e1-8b10-4e11-8681-0e7845c3420d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>applied altitude command H0 : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>3.125/64*10^-9 s</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd></dl></div><div class='xr-var-data'><pre>array([1.114018e+08, 1.114018e+08, 1.114018e+08, ..., 1.136122e+08,\n",
       "       1.136122e+08, 1.136122e+08])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cor2_nav_dem_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c87aa8de-8bbb-4100-adc0-45ecde0008c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c87aa8de-8bbb-4100-adc0-45ecde0008c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95d7c139-dc6c-4937-8bc9-1f33f06275e1' class='xr-var-data-in' type='checkbox'><label for='data-95d7c139-dc6c-4937-8bc9-1f33f06275e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>altitude command COR2 computed with nav / DEM : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>3.125/1024 10-9 s</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd></dl></div><div class='xr-var-data'><pre>array([ 26.,  26.,  26., ..., 703., 703., 703.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cor2_applied_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-da983be1-6998-44ba-ada7-2837a624bb63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da983be1-6998-44ba-ada7-2837a624bb63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ab91562-9817-4cbd-8368-d0f8ed5e5dce' class='xr-var-data-in' type='checkbox'><label for='data-7ab91562-9817-4cbd-8368-d0f8ed5e5dce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>applied altitude command COR2 : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>3.125/1024*10^-9 s</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd></dl></div><div class='xr-var-data'><pre>array([26., 26., 26., ..., 18., 29., 34.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dh0_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6fdfd391-22fe-4bff-8c05-35c849406626' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6fdfd391-22fe-4bff-8c05-35c849406626' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44a16270-f1ef-457c-878d-3078cb8289d6' class='xr-var-data-in' type='checkbox'><label for='data-44a16270-f1ef-457c-878d-3078cb8289d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd> distance error computed on the echo of the cycle (N-2) in open loop mode (current cyc</dd><dt><span>units :</span></dt><dd>3.125/64*10^-9 s</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd></dl></div><div class='xr-var-data'><pre>array([-402., -399., -575., ...,    0.,    0.,    0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>agccode_ku_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-641c982d-6a90-42d7-963d-36d12cda04a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-641c982d-6a90-42d7-963d-36d12cda04a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-feaf01a8-5853-4257-ad21-47e5069b4a14' class='xr-var-data-in' type='checkbox'><label for='data-feaf01a8-5853-4257-ad21-47e5069b4a14' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>AGCCODE for ku band : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd></dl></div><div class='xr-var-data'><pre>array([27., 27., 27., ..., 23., 23., 23.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>surf_type_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f5ae4936-5eb1-44fa-88ef-01161c61f497' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f5ae4936-5eb1-44fa-88ef-01161c61f497' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-623869b3-bc56-4fda-b18e-4f3d3dd662ba' class='xr-var-data-in' type='checkbox'><label for='data-623869b3-bc56-4fda-b18e-4f3d3dd662ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>altimeter surface type : l1b_echo_sar_ku mode </dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3]</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement</dd><dt><span>flag_meanings :</span></dt><dd>open_ocean_or_semi-enclosed_seas enclosed_seas_or_lakes continental_ice land</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>range_ku_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e5eea845-92cd-41ad-be4c-bbcbd1ee970d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5eea845-92cd-41ad-be4c-bbcbd1ee970d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c9f6e30-3718-4ff8-8ac5-6787ad54f31d' class='xr-var-data-in' type='checkbox'><label for='data-9c9f6e30-3718-4ff8-8ac5-6787ad54f31d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>corrected range for ku band : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>comment :</span></dt><dd>reference range corrected for USO frequency drift and internal path correction</dd></dl></div><div class='xr-var-data'><pre>array([815351.9348, 815351.9348, 815351.9348, ..., 831531.3588, 831531.3588,\n",
       "       831531.3588])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uso_cor_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b0fcf88c-def1-4fdf-934a-7e8e985179d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0fcf88c-def1-4fdf-934a-7e8e985179d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ccfcbb2d-8616-4e36-a1c5-5cdd749cedc1' class='xr-var-data-in' type='checkbox'><label for='data-ccfcbb2d-8616-4e36-a1c5-5cdd749cedc1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>USO frequency drift correction : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement </dd></dl></div><div class='xr-var-data'><pre>array([-0.0098, -0.0098, -0.0098, ..., -0.01  , -0.01  , -0.01  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>int_path_cor_ku_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b5b37995-2c2e-4374-b771-d3d59fd57089' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5b37995-2c2e-4374-b771-d3d59fd57089' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c86733f-620f-4673-8872-b1cdb9558df4' class='xr-var-data-in' type='checkbox'><label for='data-4c86733f-620f-4673-8872-b1cdb9558df4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>internal path correction for ku band : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement </dd></dl></div><div class='xr-var-data'><pre>array([-4.8456, -4.8456, -4.8456, ..., -4.8456, -4.8456, -4.8456])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>range_rate_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fdf3fa37-5c60-4c91-a59f-118603187814' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fdf3fa37-5c60-4c91-a59f-118603187814' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c23a763-9000-4fca-98a2-2df12c502fa8' class='xr-var-data-in' type='checkbox'><label for='data-6c23a763-9000-4fca-98a2-2df12c502fa8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>range rate : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>m/s</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement </dd></dl></div><div class='xr-var-data'><pre>array([0.234, 0.234, 0.234, ..., 0.162, 0.26 , 0.305])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>agc_ku_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-79db8f82-85d4-4003-b61d-dab7e39cccf8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79db8f82-85d4-4003-b61d-dab7e39cccf8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf227a71-e326-44a9-bece-d8e612e682b8' class='xr-var-data-in' type='checkbox'><label for='data-bf227a71-e326-44a9-bece-d8e612e682b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>corrected AGC for ku band: l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>comment :</span></dt><dd> AGC corrected for instrumental errors - value the closest in time to the reference measurement </dd></dl></div><div class='xr-var-data'><pre>array([27.17, 27.17, 27.17, ..., 23.12, 23.12, 23.12])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>scale_factor_ku_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c0d6a7c0-afa8-4edc-8a8a-f6d96e55cbe5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c0d6a7c0-afa8-4edc-8a8a-f6d96e55cbe5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b2a255d-bc15-45e7-906a-67b215d04f75' class='xr-var-data-in' type='checkbox'><label for='data-8b2a255d-bc15-45e7-906a-67b215d04f75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>scaling factor for sigma0 evaluation for ku band: l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>comment :</span></dt><dd>scaling factor corrected for AGC instrumental errors and internal calibration</dd></dl></div><div class='xr-var-data'><pre>array([18.91, 18.91, 18.91, ..., 15.07, 15.07, 15.07])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>agc_cor_ku_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8894c99e-0bfc-4e64-b49b-55eeffcee433' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8894c99e-0bfc-4e64-b49b-55eeffcee433' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cadd34c2-b4c0-46b9-a9a6-bf6f4415555e' class='xr-var-data-in' type='checkbox'><label for='data-cadd34c2-b4c0-46b9-a9a6-bf6f4415555e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>correction for instrumental errors on AGC for ku band: l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>comment :</span></dt><dd>value the closest in time to the reference measurement </dd></dl></div><div class='xr-var-data'><pre>array([0.17, 0.17, 0.17, ..., 0.12, 0.12, 0.12])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sig0_cal_ku_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-aaefe334-907f-49e3-9848-babe708dac56' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aaefe334-907f-49e3-9848-babe708dac56' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62523f24-5b78-4d90-9988-4620328638d9' class='xr-var-data-in' type='checkbox'><label for='data-62523f24-5b78-4d90-9988-4620328638d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>internal calibration correction on Sigma0 for ku band: l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([0.78, 0.78, 0.78, ..., 0.78, 0.78, 0.78])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nb_stack_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e9e25a8c-8f49-44eb-97cc-233f32470743' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e9e25a8c-8f49-44eb-97cc-233f32470743' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34a0fcac-4dc9-4a2c-96cd-8b051d770212' class='xr-var-data-in' type='checkbox'><label for='data-34a0fcac-4dc9-4a2c-96cd-8b051d770212' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>number of waveforms summed in stack : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>count</dd></dl></div><div class='xr-var-data'><pre>array([180., 180., 180., ..., 180., 180., 180.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max_stack_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-27bd1116-d125-445a-8d39-6d44f8843946' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-27bd1116-d125-445a-8d39-6d44f8843946' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89f94a72-f781-4ead-a53d-cad92609450f' class='xr-var-data-in' type='checkbox'><label for='data-89f94a72-f781-4ead-a53d-cad92609450f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>maximum power of stack : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>FFT power unit</dd></dl></div><div class='xr-var-data'><pre>array([275394., 612551., 286209., ...,  38431.,  37381.,  35550.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stdev_stack_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fe23407d-06f5-4716-af35-03211eecb9d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fe23407d-06f5-4716-af35-03211eecb9d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43fd3e7b-dc08-464f-bb4a-ddecc51c9e5d' class='xr-var-data-in' type='checkbox'><label for='data-43fd3e7b-dc08-464f-bb4a-ddecc51c9e5d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>standard deviation of stack : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>rad</dd></dl></div><div class='xr-var-data'><pre>array([0.003457, 0.003361, 0.003423, ..., 0.004232, 0.004207, 0.004232])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>skew_stack_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-889c2684-8b18-4ad9-892a-7a62458b5461' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-889c2684-8b18-4ad9-892a-7a62458b5461' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23764ba5-64df-417d-b76f-17fa8b9d4e0b' class='xr-var-data-in' type='checkbox'><label for='data-23764ba5-64df-417d-b76f-17fa8b9d4e0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>skewness of stack : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>count</dd></dl></div><div class='xr-var-data'><pre>array([ 0.014442,  0.01923 , -0.036999, ...,  0.007011, -0.010485, -0.002641])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>kurt_stack_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d1f21cd2-3047-42dd-b2dc-13974c1adf1f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1f21cd2-3047-42dd-b2dc-13974c1adf1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d317ffb-601d-440e-a180-018f05d2fe8f' class='xr-var-data-in' type='checkbox'><label for='data-9d317ffb-601d-440e-a180-018f05d2fe8f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>kurtosis of stack : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>count</dd></dl></div><div class='xr-var-data'><pre>array([-0.147059,  0.024279, -0.069423, ..., -0.838515, -0.818213, -0.831127])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_ang_stack_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku, max_multi_stack_ind)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a7e54b0a-2c0c-418b-b225-116c5c28b7d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7e54b0a-2c0c-418b-b225-116c5c28b7d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90c0d8c5-0faf-4964-b234-746e51ea185c' class='xr-var-data-in' type='checkbox'><label for='data-90c0d8c5-0faf-4964-b234-746e51ea185c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>look angles in stack: l1b_echo_sar_ku mode</dd><dt><span>comment :</span></dt><dd>Look angles in stack: l1b_echo_sar_ku mode. These are looking angles and not beam angles. The useful values of the table are the first n_useful values where n_useful is the number of waveforms summed in stack (nb_stack_l1b_echo_sar_ku)</dd><dt><span>units :</span></dt><dd>rad</dd></dl></div><div class='xr-var-data'><pre>[15092736 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_form_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ec3ffa4d-8c4b-4239-95c7-6602c182b0b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ec3ffa4d-8c4b-4239-95c7-6602c182b0b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9a29b53-7c58-400b-935e-f527cdc84227' class='xr-var-data-in' type='checkbox'><label for='data-f9a29b53-7c58-400b-935e-f527cdc84227' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>flag on beam formation quality in stack : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>percent</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>i2q2_meas_ku_l1b_echo_sar_ku</span></div><div class='xr-var-dims'>(time_l1b_echo_sar_ku, echo_sample_ind)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1d1d5dc4-e948-454b-bcae-59fbb6c1d98a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d1d5dc4-e948-454b-bcae-59fbb6c1d98a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9072c8f-fa52-4d59-907e-3825ec75ad3f' class='xr-var-data-in' type='checkbox'><label for='data-e9072c8f-fa52-4d59-907e-3825ec75ad3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>multilooked I2+Q2 measurement for ku band : l1b_echo_sar_ku mode</dd><dt><span>units :</span></dt><dd>count</dd><dt><span>comment :</span></dt><dd>the echo is corrected for Doppler range effect, phase/power burst calibration and GPRW effect; the echo is scaled using the corrected AGC (agc_ku_l1b_echo_sar_ku)</dd></dl></div><div class='xr-var-data'><pre>[7546368 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UTC_day_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c727293f-f978-47b6-9093-96fc22bd2b0f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c727293f-f978-47b6-9093-96fc22bd2b0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51b5be00-bb6c-4158-b369-de1b213592b8' class='xr-var-data-in' type='checkbox'><label for='data-51b5be00-bb6c-4158-b369-de1b213592b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>day UTC : l1b_echo_plrm mode</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeGregorian(2018, 1, 16, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 0, 0, 0, 0, has_year_zero=False),\n",
       "       ...,\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 0, 0, 0, 0, has_year_zero=False)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UTC_sec_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a259ce02-9b7b-4cd3-b96d-d4e4dc12c53f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a259ce02-9b7b-4cd3-b96d-d4e4dc12c53f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72c8c2fb-5235-439b-9487-7d40e4752e72' class='xr-var-data-in' type='checkbox'><label for='data-72c8c2fb-5235-439b-9487-7d40e4752e72' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>seconds in the day UTC : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([26032.506803, 26032.557738, 26032.608674, ..., 29061.358262,\n",
       "       29061.409197, 29061.460133])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GPS_time_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-31b710e7-b6be-4da6-8c6a-6b15abc8705e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31b710e7-b6be-4da6-8c6a-6b15abc8705e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e175e7bf-9b07-48b9-81be-7e4bb0dda14f' class='xr-var-data-in' type='checkbox'><label for='data-e175e7bf-9b07-48b9-81be-7e4bb0dda14f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>GPS time : l1b_echo_plrm mode</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeGregorian(2018, 1, 16, 7, 14, 10, 506803, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 7, 14, 10, 557738, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 7, 14, 10, 608674, has_year_zero=False),\n",
       "       ...,\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 8, 4, 39, 358262, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 8, 4, 39, 409197, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2018, 1, 16, 8, 4, 39, 460133, has_year_zero=False)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>isp_coarse_time_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cc8ad186-6d8a-4ed3-8108-ef7f554acb20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc8ad186-6d8a-4ed3-8108-ef7f554acb20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a56d8f30-bf37-4591-8cdb-55cdc052e8f1' class='xr-var-data-in' type='checkbox'><label for='data-a56d8f30-bf37-4591-8cdb-55cdc052e8f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ISP coarse time : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>second</dd></dl></div><div class='xr-var-data'><pre>array([1.200122e+09, 1.200122e+09, 1.200122e+09, ..., 1.200125e+09,\n",
       "       1.200125e+09, 1.200125e+09])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>isp_fine_time_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d719fb7d-e06d-44e4-aa18-51f9210a6b42' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d719fb7d-e06d-44e4-aa18-51f9210a6b42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb037be6-2d17-4530-bf92-18629faf4cdd' class='xr-var-data-in' type='checkbox'><label for='data-eb037be6-2d17-4530-bf92-18629faf4cdd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ISP fine time : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>2^-24 second</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sral_fine_time_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5b632df1-8739-4018-9a07-d3e6df1719b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b632df1-8739-4018-9a07-d3e6df1719b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-effddcde-8518-4523-83c9-a538b8cef271' class='xr-var-data-in' type='checkbox'><label for='data-effddcde-8518-4523-83c9-a538b8cef271' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ISP SRAL fine datation : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>137.5*10^-9 second</dd></dl></div><div class='xr-var-data'><pre>array([3511410., 3881850., 4252290., ..., 2430720., 2801160., 3171600.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>alt_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-351bfb09-baa8-4508-a91e-aca8a53b66e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-351bfb09-baa8-4508-a91e-aca8a53b66e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a42a31ad-39a4-4236-a834-bd282ba3ef4f' class='xr-var-data-in' type='checkbox'><label for='data-a42a31ad-39a4-4236-a834-bd282ba3ef4f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>altitude of satellite : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([815353.0085, 815353.0065, 815353.0045, ..., 831622.552 , 831622.5518,\n",
       "       831622.5514])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orb_alt_rate_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-36b4f29a-3bc0-4881-8f2b-1ac3d9c9c62f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36b4f29a-3bc0-4881-8f2b-1ac3d9c9c62f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c3651c8-10b4-4e33-87aa-79f1a57fe8a2' class='xr-var-data-in' type='checkbox'><label for='data-5c3651c8-10b4-4e33-87aa-79f1a57fe8a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>orbital altitude rate : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([-0.04, -0.04, -0.04, ...,  0.  , -0.01, -0.01], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_time_status_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-389d268d-639d-4264-9613-2d9eb5c599ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-389d268d-639d-4264-9613-2d9eb5c599ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a5b18ba-8b42-45bb-8f53-b3d5e42b7ff0' class='xr-var-data-in' type='checkbox'><label for='data-9a5b18ba-8b42-45bb-8f53-b3d5e42b7ff0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time status flag : l1b_echo_plrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>comment :</span></dt><dd>flag indicating if the time is synchronized or not with GPS time</dd><dt><span>flag_meanings :</span></dt><dd>synchronization no_synchronization</dd></dl></div><div class='xr-var-data'><pre>array([1., 1., 1., ..., 1., 1., 1.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_time_corr_val_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-554f8285-567b-40f8-8f3c-d12d1811743f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-554f8285-567b-40f8-8f3c-d12d1811743f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-426d5c71-6f96-4a3a-9aaa-37fb629b761d' class='xr-var-data-in' type='checkbox'><label for='data-426d5c71-6f96-4a3a-9aaa-37fb629b761d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time correlation validity flag : l1b_echo_plrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1 2]</dd><dt><span>comment :</span></dt><dd>flag indicating if the time correlation information is valid provided by OBSW, valid provided by Ground Segment or invalid</dd><dt><span>flag_meanings :</span></dt><dd>valid_obsw valid_ground_segment invalid</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_man_pres_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-781e7c6e-fd79-4c21-911d-ffa9b0f4387e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-781e7c6e-fd79-4c21-911d-ffa9b0f4387e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d66a6523-34a1-441d-9ff3-badc69705086' class='xr-var-data-in' type='checkbox'><label for='data-d66a6523-34a1-441d-9ff3-badc69705086' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>manoeuvre presence flag: l1b_echo_plrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>no_manoeuvre ongoing_manoeuvre</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_man_thrust_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7c3444fd-3356-46d1-b416-614629970f58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c3444fd-3356-46d1-b416-614629970f58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a752cfa-b6b2-4a1d-99a3-78905d77f51a' class='xr-var-data-in' type='checkbox'><label for='data-3a752cfa-b6b2-4a1d-99a3-78905d77f51a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>manoeuvre thrust flag: l1b_echo_plrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>no_thrust ongoing_thrust</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_man_plane_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-404b8f43-1bf9-4b7f-812f-99ae54a716f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-404b8f43-1bf9-4b7f-812f-99ae54a716f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d732f808-fede-47e2-8230-f7df4220a058' class='xr-var-data-in' type='checkbox'><label for='data-d732f808-fede-47e2-8230-f7df4220a058' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>manoeuvre plane flag: l1b_echo_plrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>in_plane out_of_plane</dd></dl></div><div class='xr-var-data'><pre>array([1., 1., 1., ..., 1., 1., 1.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag_gnss_status_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1b9592cd-3b82-4f1c-9798-256b67a9353c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b9592cd-3b82-4f1c-9798-256b67a9353c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d32c4150-24ff-4cf0-9a91-4994cf96db6a' class='xr-var-data-in' type='checkbox'><label for='data-d32c4150-24ff-4cf0-9a91-4994cf96db6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>validity flag for the navigation message from the gnss receiver: l1b_echo_plrm mode</dd><dt><span>comment :</span></dt><dd>indicating if the navigation message from the GNSS receiver is valid or not valid/available</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>valid invalid_unavailable</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x_pos_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-22ebe287-0293-4d70-8072-0052a85b5fe5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22ebe287-0293-4d70-8072-0052a85b5fe5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca320fd6-4f88-4144-9016-afba3254a200' class='xr-var-data-in' type='checkbox'><label for='data-ca320fd6-4f88-4144-9016-afba3254a200' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite altitude - x component : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([-711332.96362 , -711045.80755 , -710758.642301, ...,  523674.112123,\n",
       "        523339.093188,  523004.064717])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y_pos_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-86a092e5-bce4-4c7c-b5cc-6bcd8480ccb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86a092e5-bce4-4c7c-b5cc-6bcd8480ccb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f07f5af3-00fd-4a4e-955d-ca491c8bf66d' class='xr-var-data-in' type='checkbox'><label for='data-f07f5af3-00fd-4a4e-955d-ca491c8bf66d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite altitude - y component : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 808264.966512,  808519.323124,  808773.680068, ..., -943693.296708,\n",
       "       -943878.409207, -944063.520329])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z_pos_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9f18abdb-1c78-40d5-977f-dbf91d621909' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f18abdb-1c78-40d5-977f-dbf91d621909' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e35d439-ef81-40e5-9562-27a212ec2bac' class='xr-var-data-in' type='checkbox'><label for='data-2e35d439-ef81-40e5-9562-27a212ec2bac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite altitude - z component : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 7091310.990764,  7091310.792873,  7091310.575152, ..., -7107379.431101,\n",
       "       -7107379.525682, -7107379.600529])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x_vel_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-60a5a8d0-303f-4d2d-8382-9f4831454f1a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60a5a8d0-303f-4d2d-8382-9f4831454f1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0825507b-9ba5-4dfd-a955-2af51c1f82a8' class='xr-var-data-in' type='checkbox'><label for='data-0825507b-9ba5-4dfd-a955-2af51c1f82a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite velocity - x component : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([ 5637.659447,  5637.735288,  5637.811113, ..., -6577.355029,\n",
       "       -6577.410346, -6577.465646])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y_vel_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-07df5ea9-65b4-4f69-9e79-877585b845a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07df5ea9-65b4-4f69-9e79-877585b845a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee380aee-1b4e-43de-b1e5-ca02ff2555b3' class='xr-var-data-in' type='checkbox'><label for='data-ee380aee-1b4e-43de-b1e5-ca02ff2555b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite velocity - y component : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([ 4993.792891,  4993.706971,  4993.621035, ..., -3634.339312,\n",
       "       -3634.239388, -3634.139451])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z_vel_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-915d692a-6560-4781-8c65-8ffca3f470c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-915d692a-6560-4781-8c65-8ffca3f470c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-024a1041-cea7-4dcc-95b9-24d54d74fa30' class='xr-var-data-in' type='checkbox'><label for='data-024a1041-cea7-4dcc-95b9-24d54d74fa30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>satellite velocity - z component : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([-3.690562, -4.079788, -4.469022, ..., -2.050622, -1.663156, -1.275681])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nav_bul_status_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b1421441-f154-47f1-a352-b8a9c270fbb0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1421441-f154-47f1-a352-b8a9c270fbb0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40311742-4330-4d7c-9783-554a2035d126' class='xr-var-data-in' type='checkbox'><label for='data-40311742-4330-4d7c-9783-554a2035d126' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>navigation bulletin status : l1b_echo_plrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>ok ko</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nav_bul_source_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-84dc00ec-a32f-40d1-be49-777c176a1aa5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-84dc00ec-a32f-40d1-be49-777c176a1aa5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14480a24-d449-4f0f-b7d6-8e0dce8e11ec' class='xr-var-data-in' type='checkbox'><label for='data-14480a24-d449-4f0f-b7d6-8e0dce8e11ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>navigation bulletin source identifier : l1b_echo_plrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>gps doris</dd></dl></div><div class='xr-var-data'><pre>array([1., 1., 1., ..., 1., 1., 1.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nav_bul_coarse_time_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e88017e6-29ae-4350-90ad-82dba8756b48' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e88017e6-29ae-4350-90ad-82dba8756b48' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-687fbb61-2df3-449a-adb9-e939e215bf6b' class='xr-var-data-in' type='checkbox'><label for='data-687fbb61-2df3-449a-adb9-e939e215bf6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>navigation bulletin coarse time : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>second</dd></dl></div><div class='xr-var-data'><pre>array([1.200122e+09, 1.200122e+09, 1.200122e+09, ..., 1.200125e+09,\n",
       "       1.200125e+09, 1.200125e+09])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nav_bul_fine_time_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-78c7ad2a-5ed4-441b-a6e5-7b6ca626dd93' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78c7ad2a-5ed4-441b-a6e5-7b6ca626dd93' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02e6b7a5-7a59-40b6-bf52-09a384d187be' class='xr-var-data-in' type='checkbox'><label for='data-02e6b7a5-7a59-40b6-bf52-09a384d187be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>navigation bulletin fine time : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>2^-24 second</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>seq_count_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0dd3adaa-b715-4fae-93ba-f88c69e5ae87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0dd3adaa-b715-4fae-93ba-f88c69e5ae87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7981a7d-e937-4bf5-8feb-45315991934b' class='xr-var-data-in' type='checkbox'><label for='data-f7981a7d-e937-4bf5-8feb-45315991934b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>sequence count : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>count</dd></dl></div><div class='xr-var-data'><pre>array([11987., 11991., 11995., ..., 12963., 12967., 12971.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>isp_time_status_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0ac3abf0-b61c-4da0-9293-bf894e670d01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ac3abf0-b61c-4da0-9293-bf894e670d01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c39e6752-47aa-43bc-95d3-01a7bfc8b111' class='xr-var-data-in' type='checkbox'><label for='data-c39e6752-47aa-43bc-95d3-01a7bfc8b111' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ISP time status : l1b_echo_plrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>SRAL_OBT_extrapolated SRAL_OBT_updated_with_SMU_OBT</dd></dl></div><div class='xr-var-data'><pre>array([1., 1., 1., ..., 1., 1., 1.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>oper_instr_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-610cf75c-5215-4a06-97d2-c00dd782a5ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-610cf75c-5215-4a06-97d2-c00dd782a5ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3bb87bf4-5fc8-4acc-b166-922f17155132' class='xr-var-data-in' type='checkbox'><label for='data-3bb87bf4-5fc8-4acc-b166-922f17155132' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>operating instrument : l1b_echo_plrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>A B</dd><dt><span>comment :</span></dt><dd>Instrument A stands for SRAL Nominal and instrument B stands for SRAL Redundant</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SAR_mode_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-40338805-6b75-4012-9af2-2cbb1cde9a2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-40338805-6b75-4012-9af2-2cbb1cde9a2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e8bf7ba-ca03-4ea8-a99b-353496d4f4cc' class='xr-var-data-in' type='checkbox'><label for='data-6e8bf7ba-ca03-4ea8-a99b-353496d4f4cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd> SAR mode identifier : l1b_echo_plrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1 2]</dd><dt><span>flag_meanings :</span></dt><dd>closed_loop open_loop open_loop_fixed_gain</dd></dl></div><div class='xr-var-data'><pre>array([1., 1., 1., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cl_gain_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-36457347-788d-4b93-922b-9678d22c5080' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36457347-788d-4b93-922b-9678d22c5080' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ce48e84-8fd7-4b77-b6b3-024cba9fa57e' class='xr-var-data-in' type='checkbox'><label for='data-6ce48e84-8fd7-4b77-b6b3-024cba9fa57e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>tracking configuration - closed loop gain : l1b_echo_plrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd> Nominal_value Nominal_value_with_back-off</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acq_stat_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-da761337-4962-4a7a-857f-076e29d1b771' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da761337-4962-4a7a-857f-076e29d1b771' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ed28b3c-4805-4850-a7b0-1030465d0cc0' class='xr-var-data-in' type='checkbox'><label for='data-5ed28b3c-4805-4850-a7b0-1030465d0cc0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>tracking configuration - acquisition status : l1b_echo_plrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>no_acquisition acquisition</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dem_eeprom_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e2b7bd7d-63b3-4999-a7c3-ab967cb9ddcc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2b7bd7d-63b3-4999-a7c3-ab967cb9ddcc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d2e5fc5-2e4b-4bff-b9f1-d7ce3d7586c5' class='xr-var-data-in' type='checkbox'><label for='data-7d2e5fc5-2e4b-4bff-b9f1-d7ce3d7586c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>tracking configuration - DEM EEPROM read access : l1b_echo_plrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>enabled disabled </dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>weighting_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9c4a175e-c812-4e7d-9ee9-2a75fc1b95c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c4a175e-c812-4e7d-9ee9-2a75fc1b95c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-015ac583-1056-4d6b-971d-683d1a6d00e3' class='xr-var-data-in' type='checkbox'><label for='data-015ac583-1056-4d6b-971d-683d1a6d00e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>altimeter configuration - weighting function : l1b_echo_plrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>enabled disabled </dd></dl></div><div class='xr-var-data'><pre>array([1., 1., 1., ..., 1., 1., 1.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>loss_track_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1b92244e-4a9c-40c5-8ed7-a6ec0fc9ab3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b92244e-4a9c-40c5-8ed7-a6ec0fc9ab3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aff97e74-1fa0-4b3d-8a64-681f53ff4d80' class='xr-var-data-in' type='checkbox'><label for='data-aff97e74-1fa0-4b3d-8a64-681f53ff4d80' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>loss of track criterion : l1b_echo_plrm mode</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>normal loss_of_track</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h0_nav_dem_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-14c5c9a5-54c2-4765-a99f-71b80613db56' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14c5c9a5-54c2-4765-a99f-71b80613db56' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77ab76c8-e968-4381-85b4-b20bd5cf636b' class='xr-var-data-in' type='checkbox'><label for='data-77ab76c8-e968-4381-85b4-b20bd5cf636b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>altitude command H0 computed with nav / DEM : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>3.125/64*10^-9 s</dd></dl></div><div class='xr-var-data'><pre>array([1.114018e+08, 1.114018e+08, 1.114018e+08, ..., 1.136119e+08,\n",
       "       1.136119e+08, 1.136120e+08])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>h0_applied_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6aecd949-ef50-4eb2-8162-30713f46fe20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6aecd949-ef50-4eb2-8162-30713f46fe20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1ec5ccd-56d2-4ffa-b608-b88f9291799b' class='xr-var-data-in' type='checkbox'><label for='data-c1ec5ccd-56d2-4ffa-b608-b88f9291799b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>applied altitude command H0 : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>3.125/64*10^-9 s</dd></dl></div><div class='xr-var-data'><pre>array([1.114018e+08, 1.114018e+08, 1.114018e+08, ..., 1.136122e+08,\n",
       "       1.136122e+08, 1.136122e+08])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cor2_nav_dem_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-89ee26e8-b256-4360-976b-92443b2efd19' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89ee26e8-b256-4360-976b-92443b2efd19' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-697b0957-aeaf-43c3-bf57-01030f73dc14' class='xr-var-data-in' type='checkbox'><label for='data-697b0957-aeaf-43c3-bf57-01030f73dc14' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>altitude command COR2 computed with nav / DEM : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>3.125/1024 10-9 s</dd></dl></div><div class='xr-var-data'><pre>array([ 26.,  26.,  26., ..., 703., 703., 703.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cor2_applied_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e24ac110-bc41-42c0-8ee9-5d60672988bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e24ac110-bc41-42c0-8ee9-5d60672988bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35bbec35-8cd5-460f-9388-53f81990b85c' class='xr-var-data-in' type='checkbox'><label for='data-35bbec35-8cd5-460f-9388-53f81990b85c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>applied altitude command COR2 : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>3.125/1024*10^-9 s</dd></dl></div><div class='xr-var-data'><pre>array([26., 26., 26., ..., 18., 29., 34.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dh0_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cf491b58-8d09-4464-8dba-ec19b6667a8e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cf491b58-8d09-4464-8dba-ec19b6667a8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd45a6fa-c7ef-45ae-bdba-80fe5e4e4b38' class='xr-var-data-in' type='checkbox'><label for='data-cd45a6fa-c7ef-45ae-bdba-80fe5e4e4b38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd> distance error computed on the echo of the cycle (N-2) in open loop mode (current cyc</dd><dt><span>units :</span></dt><dd>3.125/64*10^-9 s</dd></dl></div><div class='xr-var-data'><pre>array([-398., -402., -399., ...,    0.,    0.,    0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>agccode_ku_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-521ed4db-0590-408e-ad77-5e4e9feee2f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-521ed4db-0590-408e-ad77-5e4e9feee2f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-459baacf-71ab-4171-b4a0-1a64ea22ecba' class='xr-var-data-in' type='checkbox'><label for='data-459baacf-71ab-4171-b4a0-1a64ea22ecba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>AGCCODE for ku band : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([27., 27., 27., ..., 23., 23., 23.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>agccode_c_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6fd7962b-30e0-4d0c-aaa4-3fc080298bb3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6fd7962b-30e0-4d0c-aaa4-3fc080298bb3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b7996b4-369f-45dd-aa9f-83a8c8ea2903' class='xr-var-data-in' type='checkbox'><label for='data-7b7996b4-369f-45dd-aa9f-83a8c8ea2903' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>AGCCODE for c band : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([23., 23., 23., ..., 20., 20., 20.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>surf_type_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-04a273dc-8889-4790-b33f-706169511675' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-04a273dc-8889-4790-b33f-706169511675' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac21c836-69e5-4591-a7df-e170166c8024' class='xr-var-data-in' type='checkbox'><label for='data-ac21c836-69e5-4591-a7df-e170166c8024' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>altimeter surface type : l1b_echo_plrm mode </dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3]</dd><dt><span>flag_meanings :</span></dt><dd>open_ocean_or_semi-enclosed_seas enclosed_seas_or_lakes continental_ice land</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>range_ku_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7e7bf841-9b54-484b-9d8c-ab5d5b44ade1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e7bf841-9b54-484b-9d8c-ab5d5b44ade1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b758437b-4302-40aa-aea2-8dad972c0ac6' class='xr-var-data-in' type='checkbox'><label for='data-b758437b-4302-40aa-aea2-8dad972c0ac6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>corrected range for ku band : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>comment :</span></dt><dd>tracker range corrected for USO frequency drift, internal path and Doppler corrections</dd></dl></div><div class='xr-var-data'><pre>array([815352.4402, 815352.4476, 815352.4402, ..., 831530.4882, 831530.6567,\n",
       "       831530.7081])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>range_c_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6bd294e6-f4b1-4b6d-ba6c-2735285af2ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6bd294e6-f4b1-4b6d-ba6c-2735285af2ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-099d6c3b-7bf0-468f-a5f1-0e78704a3f47' class='xr-var-data-in' type='checkbox'><label for='data-099d6c3b-7bf0-468f-a5f1-0e78704a3f47' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>corrected range for c band : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>comment :</span></dt><dd>tracker range corrected for USO frequency drift, internal path and Doppler corrections</dd></dl></div><div class='xr-var-data'><pre>array([815351.8273, 815351.8346, 815351.8273, ..., 831529.8752, 831530.0437,\n",
       "       831530.095 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uso_cor_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-534db033-7ecf-4096-9e6e-c74d4385ad24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-534db033-7ecf-4096-9e6e-c74d4385ad24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c1deac2-a4a7-4463-b95f-8cac86ee7411' class='xr-var-data-in' type='checkbox'><label for='data-6c1deac2-a4a7-4463-b95f-8cac86ee7411' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>USO frequency drift correction : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([-0.0098, -0.0098, -0.0098, ..., -0.01  , -0.01  , -0.01  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>int_path_cor_ku_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6f904816-6567-4e1c-9480-298be6dc68d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f904816-6567-4e1c-9480-298be6dc68d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27d64193-e682-4dee-adeb-5da0596b896f' class='xr-var-data-in' type='checkbox'><label for='data-27d64193-e682-4dee-adeb-5da0596b896f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>internal path correction for ku band : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([-4.8456, -4.8456, -4.8456, ..., -4.8456, -4.8456, -4.8456])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>int_path_cor_c_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-478cef0e-ed3b-4415-bce8-33cf003a322f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-478cef0e-ed3b-4415-bce8-33cf003a322f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-abccfa09-ffd7-4349-a7ca-f18cc802831b' class='xr-var-data-in' type='checkbox'><label for='data-abccfa09-ffd7-4349-a7ca-f18cc802831b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>internal path correction for c band : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([-5.524, -5.524, -5.524, ..., -5.524, -5.524, -5.524])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dop_cor_ku_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e396d97b-2aeb-4dad-a303-68a10d46d35b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e396d97b-2aeb-4dad-a303-68a10d46d35b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7813e3a8-da58-4769-9e18-bcfb984d3dd6' class='xr-var-data-in' type='checkbox'><label for='data-7813e3a8-da58-4769-9e18-bcfb984d3dd6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>doppler correction for ku band : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([-0.0001, -0.0001, -0.0001, ...,  0.    ,  0.    ,  0.    ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dop_cor_c_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-de779362-f52c-4399-9f1c-cbec3ede5bd5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-de779362-f52c-4399-9f1c-cbec3ede5bd5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af98533c-742d-4756-b8c0-eb5f588490f3' class='xr-var-data-in' type='checkbox'><label for='data-af98533c-742d-4756-b8c0-eb5f588490f3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>doppler correction for c band : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>range_rate_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c895a1e9-4649-4d47-81e1-de859e5deddb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c895a1e9-4649-4d47-81e1-de859e5deddb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a107b0b1-dc36-40af-b09f-628cebc160e2' class='xr-var-data-in' type='checkbox'><label for='data-a107b0b1-dc36-40af-b09f-628cebc160e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>range rate : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([0.234, 0.234, 0.234, ..., 0.162, 0.26 , 0.305])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>agc_ku_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-330f2b78-2520-4270-9890-d72cdc708b42' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-330f2b78-2520-4270-9890-d72cdc708b42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6fffce7e-ddaf-433f-851d-fa8417ed4319' class='xr-var-data-in' type='checkbox'><label for='data-6fffce7e-ddaf-433f-851d-fa8417ed4319' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>corrected AGC for ku band: l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>comment :</span></dt><dd>AGC corrected for instrumental errors</dd></dl></div><div class='xr-var-data'><pre>array([27.17, 27.17, 27.17, ..., 23.12, 23.12, 23.12])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>agc_c_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5ebd062c-bb70-4703-bc47-f14d99f6426e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ebd062c-bb70-4703-bc47-f14d99f6426e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4fe017e-1663-4833-b2e8-30b2b272e508' class='xr-var-data-in' type='checkbox'><label for='data-a4fe017e-1663-4833-b2e8-30b2b272e508' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>corrected AGC for c band: l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>comment :</span></dt><dd>AGC corrected for instrumental errors</dd></dl></div><div class='xr-var-data'><pre>array([23.05, 23.05, 23.05, ..., 20.27, 20.27, 20.27])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>scale_factor_ku_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8de322c1-dc0e-4a81-bb95-614df1f55792' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8de322c1-dc0e-4a81-bb95-614df1f55792' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e58886d-c389-4e59-93d2-bd2a0234e464' class='xr-var-data-in' type='checkbox'><label for='data-0e58886d-c389-4e59-93d2-bd2a0234e464' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>scaling factor for sigma0 evaluation for ku band: l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>comment :</span></dt><dd>scaling factor corrected for AGC instrumental errors and internal calibration</dd></dl></div><div class='xr-var-data'><pre>array([ -6.71,  -6.71,  -6.71, ..., -10.49, -10.49, -10.49])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>scale_factor_c_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3c249e23-232f-44bf-a680-88bfbfdf2403' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c249e23-232f-44bf-a680-88bfbfdf2403' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e810b5ab-2684-4b0c-8b03-adeebff7de11' class='xr-var-data-in' type='checkbox'><label for='data-e810b5ab-2684-4b0c-8b03-adeebff7de11' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>scaling factor for sigma0 evaluation for c band: l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>comment :</span></dt><dd>scaling factor corrected for AGC instrumental errors and internal calibration</dd></dl></div><div class='xr-var-data'><pre>array([ -7.54,  -7.54,  -7.54, ..., -10.05, -10.05, -10.05])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>agc_cor_ku_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c65af841-4acf-4700-8290-71eff71462f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c65af841-4acf-4700-8290-71eff71462f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-972909a9-a155-4610-9136-a48cc91ce88b' class='xr-var-data-in' type='checkbox'><label for='data-972909a9-a155-4610-9136-a48cc91ce88b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>correction for instrumental errors on AGC for ku band: l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([0.17, 0.17, 0.17, ..., 0.12, 0.12, 0.12])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>agc_cor_c_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ce1c5a73-f8ca-4497-8a76-04ee18b0fbc7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce1c5a73-f8ca-4497-8a76-04ee18b0fbc7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ecc2925-0fa2-41bf-95f8-e64312ff855a' class='xr-var-data-in' type='checkbox'><label for='data-8ecc2925-0fa2-41bf-95f8-e64312ff855a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>correction for instrumental errors on AGC for c band: l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([0.05, 0.05, 0.05, ..., 0.27, 0.27, 0.27])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sig0_cal_ku_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9e430fb1-af02-447c-af23-86e14f81621e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9e430fb1-af02-447c-af23-86e14f81621e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d967d5e-50eb-4d18-82ae-af4c19b6279d' class='xr-var-data-in' type='checkbox'><label for='data-3d967d5e-50eb-4d18-82ae-af4c19b6279d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>internal calibration correction on Sigma0 for ku band: l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([0.78, 0.78, 0.78, ..., 0.78, 0.78, 0.78])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sig0_cal_c_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-32a46d4e-2fea-4cdb-86e4-5abfe14ab475' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32a46d4e-2fea-4cdb-86e4-5abfe14ab475' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c452abf-44d0-41f0-82d3-33b564292c8e' class='xr-var-data-in' type='checkbox'><label for='data-1c452abf-44d0-41f0-82d3-33b564292c8e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>internal calibration correction on Sigma0 for c band: l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([-0.48, -0.48, -0.48, ..., -0.48, -0.48, -0.48])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>i2q2_meas_ku_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm, echo_sample_ind)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-541a978b-eb77-45fd-9ef6-6032213107aa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-541a978b-eb77-45fd-9ef6-6032213107aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-141d8a4b-2c43-4d10-af1f-874dfac5eeb4' class='xr-var-data-in' type='checkbox'><label for='data-141d8a4b-2c43-4d10-af1f-874dfac5eeb4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>I2+Q2 measurement for ku band : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>count</dd><dt><span>comment :</span></dt><dd>the echo is the so-called ku-band averaged echo, corrected for the GPRW effect</dd></dl></div><div class='xr-var-data'><pre>[7371648 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>i2q2_meas_c_l1b_echo_plrm</span></div><div class='xr-var-dims'>(time_l1b_echo_plrm, echo_sample_ind)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dc40f1b2-12c6-4fc8-8c2f-0609d7461548' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc40f1b2-12c6-4fc8-8c2f-0609d7461548' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e885e2e-ad72-4353-813e-6bbed1bdcc16' class='xr-var-data-in' type='checkbox'><label for='data-5e885e2e-ad72-4353-813e-6bbed1bdcc16' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>I2+Q2 measurement for c band : l1b_echo_plrm mode</dd><dt><span>units :</span></dt><dd>count</dd><dt><span>comment :</span></dt><dd>the echo is the so-called c-band averaged echo, corrected for the GPRW effect</dd></dl></div><div class='xr-var-data'><pre>[7371648 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a8d98ecb-6f8f-4719-83a5-19fdd5ba75f7' class='xr-section-summary-in' type='checkbox'  ><label for='section-a8d98ecb-6f8f-4719-83a5-19fdd5ba75f7' class='xr-section-summary' >Attributes: <span>(29)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>title :</span></dt><dd>IPF SRAL Level 1 Measurement</dd><dt><span>mission_name :</span></dt><dd>Sentinel 3A</dd><dt><span>altimeter_sensor_name :</span></dt><dd>SRAL</dd><dt><span>gnss_sensor_name :</span></dt><dd>GNSS</dd><dt><span>doris_sensor_name :</span></dt><dd>DORIS</dd><dt><span>references :</span></dt><dd>S3IPF PDS 003 - i2r10 - Product Data Format Specification - SRAL-MWR</dd><dt><span>acq_station_name :</span></dt><dd>N/A</dd><dt><span>xref_altimeter_level0 :</span></dt><dd>S3A_SR_0_SRA____20180116T071324_20180116T072324_20180116T090547_0599_026_377______SVL_O_NR_002.SEN3 S3A_SR_0_SRA____20180116T072325_20180116T073324_20180116T090547_0599_026_377______SVL_O_NR_002.SEN3 S3A_SR_0_SRA____20180116T073324_20180116T074324_20180116T090539_0599_026_377______SVL_O_NR_002.SEN3 S3A_SR_0_SRA____20180116T074324_20180116T075324_20180116T090611_0599_026_377______SVL_O_NR_002.SEN3 S3A_SR_0_SRA____20180116T075324_20180116T080324_20180116T090611_0599_026_377______SVL_O_NR_002.SEN3 S3A_SR_0_SRA____20180116T080324_20180116T081324_20180116T090618_0599_026_377______SVL_O_NR_002.SEN3</dd><dt><span>xref_navatt_level0 :</span></dt><dd>S3A_TM_0_NAT____20180116T071325_20180116T085435_20180116T090428_6070_026_377______SVL_O_AL_002.SEN3 S3A_TM_0_NAT____20180116T071325_20180116T085418_20180116T085614_6053_026_377______SVL_O_AL_002.SEN3</dd><dt><span>xref_altimeter_orbit :</span></dt><dd>S3A_SR___POESAX_20180115T215523_20180117T002323_20180129T214757___________________CNE_O_NT_001.SEN3</dd><dt><span>xref_doris_uso :</span></dt><dd>S3A_SR_1_USO_AX_20160223T195017_20180220T013250_20180220T084743___________________CNE_O_AL_001.SEN3</dd><dt><span>xref_altimeter_ltm_lrm_cal1 :</span></dt><dd>S3A_SR_1_CA1LAX_20000101T000000_20180215T203206_20180227T034802___________________LR1_R_AL____.SEN3</dd><dt><span>xref_altimeter_ltm_sar_cal1 :</span></dt><dd>S3A_SR_1_CA1SAX_20000101T000000_20180215T203213_20180227T034802___________________LR1_R_AL____.SEN3</dd><dt><span>xref_altimeter_ltm_ku_cal2 :</span></dt><dd>S3A_SR_1_CA2KAX_20000101T000000_20180215T203219_20180227T034802___________________LR1_R_AL____.SEN3</dd><dt><span>xref_altimeter_ltm_c_cal2 :</span></dt><dd>S3A_SR_1_CA2CAX_20000101T000000_20180215T203219_20180227T034802___________________LR1_R_AL____.SEN3</dd><dt><span>xref_altimeter_characterisation :</span></dt><dd>S3A_SR___CHDNAX_20000101T000000_20991231T235959_20160603T120000___________________MPC_O_AL_002.SEN3</dd><dt><span>xref_time_correlation :</span></dt><dd>S3A_AX___FRO_AX_20180116T000000_20180126T000000_20180119T064150___________________EUM_O_AL_001.SEN3</dd><dt><span>semi_major_ellipsoid_axis :</span></dt><dd>6378137.0</dd><dt><span>ellipsoid_flattening :</span></dt><dd>0.00335281066474748</dd><dt><span>netcdf_version :</span></dt><dd>4.2 of Jul  5 2012 17:07:43 $</dd><dt><span>product_name :</span></dt><dd>S3A_SR_1_SRA____20180116T071353_20180116T080421_20180302T031249_3028_026_377______LR1_R_NT_003.SEN3</dd><dt><span>institution :</span></dt><dd>LR1</dd><dt><span>source :</span></dt><dd>IPF-SR-1 06.13</dd><dt><span>history :</span></dt><dd> </dd><dt><span>contact :</span></dt><dd>s3ome@acri-st.fr</dd><dt><span>creation_time :</span></dt><dd>2018-03-02T03:13:32Z</dd><dt><span>first_meas_time :</span></dt><dd>2018-01-16T07:13:52.506803Z</dd><dt><span>last_meas_time :</span></dt><dd>2018-01-16T08:04:21.473974Z</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                              (echo_sample_ind: 128,\n",
       "                                          max_multi_stack_ind: 256,\n",
       "                                          time_l1b_echo_lrm: 0,\n",
       "                                          time_l1b_echo_sar_ku: 58956,\n",
       "                                          time_l1b_echo_plrm: 57591)\n",
       "Coordinates:\n",
       "  * echo_sample_ind                      (echo_sample_ind) int8 0 1 ... 126 127\n",
       "  * max_multi_stack_ind                  (max_multi_stack_ind) int16 0 1 ... 255\n",
       "  * time_l1b_echo_lrm                    (time_l1b_echo_lrm) object \n",
       "    lat_l1b_echo_lrm                     (time_l1b_echo_lrm) float64 ...\n",
       "    lon_l1b_echo_lrm                     (time_l1b_echo_lrm) float64 ...\n",
       "  * time_l1b_echo_sar_ku                 (time_l1b_echo_sar_ku) object 2018-0...\n",
       "    lat_l1b_echo_sar_ku                  (time_l1b_echo_sar_ku) float64 ...\n",
       "    lon_l1b_echo_sar_ku                  (time_l1b_echo_sar_ku) float64 ...\n",
       "  * time_l1b_echo_plrm                   (time_l1b_echo_plrm) object 2018-01-...\n",
       "    lat_l1b_echo_plrm                    (time_l1b_echo_plrm) float64 ...\n",
       "    lon_l1b_echo_plrm                    (time_l1b_echo_plrm) float64 ...\n",
       "Data variables: (12/174)\n",
       "    UTC_day_l1b_echo_lrm                 (time_l1b_echo_lrm) object ...\n",
       "    UTC_sec_l1b_echo_lrm                 (time_l1b_echo_lrm) float64 ...\n",
       "    GPS_time_l1b_echo_lrm                (time_l1b_echo_lrm) object ...\n",
       "    isp_coarse_time_l1b_echo_lrm         (time_l1b_echo_lrm) float64 ...\n",
       "    isp_fine_time_l1b_echo_lrm           (time_l1b_echo_lrm) float64 ...\n",
       "    sral_fine_time_l1b_echo_lrm          (time_l1b_echo_lrm) float64 ...\n",
       "    ...                                   ...\n",
       "    agc_cor_ku_l1b_echo_plrm             (time_l1b_echo_plrm) float64 ...\n",
       "    agc_cor_c_l1b_echo_plrm              (time_l1b_echo_plrm) float64 ...\n",
       "    sig0_cal_ku_l1b_echo_plrm            (time_l1b_echo_plrm) float64 ...\n",
       "    sig0_cal_c_l1b_echo_plrm             (time_l1b_echo_plrm) float64 ...\n",
       "    i2q2_meas_ku_l1b_echo_plrm           (time_l1b_echo_plrm, echo_sample_ind) float64 ...\n",
       "    i2q2_meas_c_l1b_echo_plrm            (time_l1b_echo_plrm, echo_sample_ind) float64 ...\n",
       "Attributes: (12/29)\n",
       "    Conventions:                      CF-1.6\n",
       "    title:                            IPF SRAL Level 1 Measurement\n",
       "    mission_name:                     Sentinel 3A\n",
       "    altimeter_sensor_name:            SRAL\n",
       "    gnss_sensor_name:                 GNSS\n",
       "    doris_sensor_name:                DORIS\n",
       "    ...                               ...\n",
       "    source:                           IPF-SR-1 06.13\n",
       "    history:                           \n",
       "    contact:                          s3ome@acri-st.fr\n",
       "    creation_time:                    2018-03-02T03:13:32Z\n",
       "    first_meas_time:                  2018-01-16T07:13:52.506803Z\n",
       "    last_meas_time:                   2018-01-16T08:04:21.473974Z"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# You can explore xarray  data by 'displaying' it in jupyter notebook\n",
    "display(ds)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dbbea612-8e08-4939-a192-1419eb4c4aa2",
   "metadata": {},
   "source": [
    "## Step 7: Select waveforms within Lake Turkana\n",
    "\n",
    "Sentinel-3A has been operating in SAR mode over land. An synthetic 'Pseudo Low Resolution Mode' (PLRM) is however present which contains the averaged (over the along-track SAR bins) waveforms. We'll have a look at these PLRM waveforms as they will look similar to what conventional altimetry would provide."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "688937cc-19ba-4131-9d3d-8704fc89c005",
   "metadata": {},
   "outputs": [],
   "source": [
    "#extract the longitude,latitude footprints as a list of points\n",
    "lonvar='lon_l1b_echo_plrm'\n",
    "latvar='lat_l1b_echo_plrm'\n",
    "wavevar='i2q2_meas_ku_l1b_echo_plrm'\n",
    "track2 = gpd.GeoSeries(map(Point, zip(ds[lonvar].values, ds[latvar].values)))\n",
    "\n",
    "#select only data from within Lake Turkana\n",
    "# The index of this series will refer to the data points within the netcdf file\n",
    "track2=track2[track2.within(lakePoly[0])]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ed392a7-1d5d-41f0-9e22-aef1cae89e13",
   "metadata": {},
   "source": [
    "We expect that the waveforms will look different in the vicinity of the shoreline due to the contamination by other (land) scatterers. So we willlook at 3 sections of the track:\n",
    "\n",
    "1. The northern part of the track close to the shore\n",
    "2. A central part of the track over the lake surface\n",
    "3. The southern part of the track close to the shore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e5d6f1b5-b103-4c8c-b293-1191c3ee80c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#create 3 segments to plot\n",
    "nvals=20\n",
    "northIdx=track2.index.values[0:nvals]\n",
    "int(np.median(track2.index))\n",
    "cp=int(len(track2)/2)\n",
    "centerIdx=track2.index.values[cp-int(nvals/2):cp+int(nvals/2)]\n",
    "southIdx=track2.index.values[-nvals:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ade9613b-2c8f-44fe-9fe3-1ee8ea42861a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "# Create a regional plot around Lake Turkana\n",
    "pltextent=np.array([ i for i in lakePoly[0].buffer(1).bounds])[[0,2,1,3]]\n",
    "\n",
    "fig = mpl.figure(figsize=(12, 12))\n",
    "ax = fig.add_subplot(1, 1, 1, projection=ccrs.PlateCarree())\n",
    "\n",
    "ax.set_extent(pltextent,crs=ccrs.PlateCarree())\n",
    "\n",
    "# add the Lake polygon\n",
    "ax.add_geometries(lakePoly,crs=ccrs.PlateCarree(),facecolor='lightblue')\n",
    "\n",
    "# # add the selected track parts\n",
    "track2[northIdx].plot(ax=ax,facecolor='green')\n",
    "track2[centerIdx].plot(ax=ax,facecolor='red')\n",
    "track2[southIdx].plot(ax=ax,facecolor='orange')\n",
    "ax.set_title(\"North, South and Center altimetry section to be considered\")\n",
    "\n",
    "mpl.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2a93cb98-000c-4fed-9b3a-e5ae1dac210a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "13d5fb1553e449f29b34ce40d0babf83",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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width=1200.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot wave forms for the 3 different sections\n",
    "%matplotlib widget\n",
    "def addtoplot(ds,idx,ax,hilight):\n",
    "    \"\"\"Quick helper function which plots waveforms in gray while highlighting one\"\"\"\n",
    "    for i,ith in enumerate(idx):\n",
    "        dstmp=ds[wavevar][ith,:]\n",
    "        if i == hilight:\n",
    "            color='red'\n",
    "            zorder=10\n",
    "        else:\n",
    "            zorder=1\n",
    "            color='gray'\n",
    "        dstmp.plot(x='echo_sample_ind',color=color,ax=ax,zorder=zorder)\n",
    "\n",
    "    \n",
    "\n",
    "\n",
    "fig = mpl.figure(figsize=(12, 12))\n",
    "\n",
    "ax = fig.add_subplot(3, 1, 1)\n",
    "\n",
    "\n",
    "addtoplot(ds,northIdx,ax,3)\n",
    "ax.set_title('North: close to shore')  \n",
    "    \n",
    "ax = fig.add_subplot(3, 1, 2)\n",
    "addtoplot(ds,centerIdx,ax,10)\n",
    "ax.set_title('Lake center')  \n",
    "\n",
    "    \n",
    "ax = fig.add_subplot(3, 1, 3)\n",
    "addtoplot(ds,southIdx,ax,10)\n",
    "ax.set_title('South:close to shore')  \n",
    "\n",
    "mpl.tight_layout()\n",
    "\n",
    "mpl.show()\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "733f7ca5-f522-46b1-aa13-15d42c40087a",
   "metadata": {},
   "source": [
    "## Exercise Questions\n",
    "After completing the exercise, it's time to reflect on what you've learned by discussing the following questions.\n",
    "\n",
    "1. The waveform close to the shores are pointy and some show more power compared to the ones from the central lake. Why do you think that is the case?\n",
    "2. For the Lake center, we see that the waveform of the leading edge is quite steep. If this were an ocean waveform how would this effect the steepness of the leading edge?\n",
    "3. Try changing the north and sections to move towards the lake center, and highlight different waveforms in the plot. How far do you need to be away from the shoreline before the waveforms look similar to those of the central lake?"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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