Code update

1_data_processing.py

@@ -388,7 +388,7 @@ def interp_pandas(s, kind="quadratic"):
 df_swc["reference_short"] = ["Ohmura et al. (1992)"]*3
 df_swc[
     "reference"
-] = ["Ohmura, A. and 10 others. 1992; Energy and Mass balance during the melt season at the equilibrium line altitude, Paakitsoq, Greenland ice sheet. Zürich, Swiss Federal Institute of Technology. (ETH Greenland Expedition. Progress Report 2.)"]*3
+] = ["Ohmura, A., Steffen, K., Blatter, H., Greuell, W., Rotach, M., Stober, M., Konzelmann, T., Forrer, J., Abe-Ouchi, A., Steiger, D. and Niederbaumer, G.: Energy and mass balance during the melt season at the equilibrium line altitude. Paakitsoq, Greenland ice sheet: Progress report, 2, 1992."]*3
 
 df_swc["method"] = ["NA"]*3
 df_swc["durationOpen"] = ["NA"]*3

4_RCM_comparison.py

@@ -125,7 +125,7 @@
 # ds_ann = ds_ann.rio.reproject(target_crs)
 
 
-# %% Extracting model values at observation sites
+# Extracting model values at observation sites
 # finding observation coordinate in RACMO's CRS
 df.date = pd.to_datetime(df.date)
 df["x"], df["y"] = transform(
@@ -417,8 +417,8 @@ def get_distance(point1, point2):
         latitude=site_list.loc[site, "lat"],
         method="nearest").to_dataframe().resample("Y").mean()
     df_ANN_interp = np.interp(df_select.date, df_ANN.index, df_ANN.T10m)
-    MD = np.sqrt(np.mean((df_ANN_interp - df_select.temperatureObserved) ** 2))
-    RMSD = np.mean((df_ANN_interp - df_select.temperatureObserved))
+    RMSD = np.sqrt(np.mean((df_ANN_interp - df_select.temperatureObserved) ** 2))
+    MD = np.mean((df_ANN_interp - df_select.temperatureObserved))
     N = df_select.temperatureObserved.notnull().sum()
     print("%s, %i, %0.1f, %0.1f" % (site, N, RMSD, MD))
 
@@ -954,10 +954,10 @@ def plot_selected_ds(tmp_in, ax, label, mask=0, trend_line=False):
 def table_selected_ds(tmp_in,label, mask=0):
     # tmp.plot(ax=ax, color='black', label='_no_legend_',alpha=0.3)
     tmp_in = tmp_in.resample("Y").mean()
-    # y1 = [1980, 2010]
-    # y2 = [1990, 2020]
-    y1 = [1950, 2017]
-    y2 = [1960, 2022]
+    y1 = [1980, 2010]
+    y2 = [1990, 2020]
+    # y1 = [1950, 2017]
+    # y2 = [1960, 2022]
 
     for i in range(len(y1)):
         tmp = tmp_in.loc[str(y1[i]):str(y2[i])]