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Documentation: https://radar-api.readthedocs.io
RADAR-API provides an easy-to-use python interface to find, download and read weather radar data from several meteorological services.
RADAR-API currently provides data access to the following
radar networks: NEXRAD, IDEAM and FMI.
The list of available radars can be retrieved using:
import radar_api
radar_api.available_networks()
radar_api.available_radars()
radar_api.available_radars(network="NEXRAD")Before starting using RADAR-API, we highly suggest to save into a configuration file the directory on your local disk where to save the radar data of interest.
To facilitate the creation of the RADAR-API configuration file, you can adapt and execute the following script:
import radar_api
base_dir = (
"<path/to/directory/RADAR" # path to the directory where to download the data
)
radar_api.define_configs(base_dir=base_dir)
# You can check that the config file has been correctly created with:
configs = radar_api.read_configs()
print(configs)You can start to download radar data editing the following code example:
import radar_api
start_time = "2021-09-07 17:00:00"
end_time = "2021-09-07 17:30:00"
radar = "KMKX"
network = "NEXRAD"
filepaths = radar_api.download_files(
network=network,
radar=radar,
start_time=start_time,
end_time=end_time,
)RADAR-API allows to read directly radar data from the cloud without the need to previously download and save the files on your disk.
RADAR-API make use of pyart and xradar readers to open the files into either an xarray object or pyart radar object.
import radar_api
import pyart
# Search for files on cloud bucket
filepaths = radar_api.find_files(
network=network,
radar=radar,
start_time=start_time,
end_time=end_time,
protocol="s3",
)
print(filepaths)
# Define the file to open
filepath = filepaths[0]
# Open all sweeps of a radar volume into a xradar datatree
dt = radar_api.open_datatree(filepath, network=network)
# Extract the radar sweep of interest
ds = dt["sweep_0"].to_dataset()
# Open directly a single radar sweep into a xradar dataset
ds = radar_api.open_dataset(filepath, network=network, sweep="sweep_0")
# Open all sweeps of a radar volume into a pyart radar object
radar_obj = radar_api.open_pyart(filepath, network=network)
# Display the data with pyart
display = pyart.graph.RadarDisplay(radar_obj)
display.plot("reflectivity", cmap="pyart_ChaseSpectral", vmin=-20, vmax=70)
display.set_limits((-150, 150), (-150, 150))To discover RADAR-API utilities and functionalities, please read the software documentation available at https://radar-api.readthedocs.io/en/latest/.
All RADAR-API tutorials are available as Jupyter Notebooks in the tutorial directory.
RADAR-API can be installed via conda on Linux, Mac, and Windows. Install the package by typing the following command in the terminal:
conda install radar-apiIn case conda-forge is not set up for your system yet, see the easy to follow instructions on conda-forge.
RADAR-API can be installed also via pip on Linux, Mac, and Windows. On Windows you can install WinPython to get Python and pip running. Then, install the RADAR-API package by typing the following command in the terminal:
pip install radar-apiTo install the latest development version via pip, see the documentation.
If you aim to contribute your data or discuss the future development of RADAR-API, we suggest to join the Open Radar Science Discourse Group.
Feel free to also open a GitHub Issue or a GitHub Discussion specific to your questions or ideas.
If you are using RADAR-API in your publication please cite our Zenodo repository:
Ghiggi Gionata. ghiggi/radar_api. Zenodo.
If you want to cite a specific software version, have a look at the Zenodo site.
The content of this repository is released under the terms of the MIT license.