Add HF average over grid and data

add download ERA5 script

Compute/heat_fluxes_ts.py

+"""Compute heat fluxes timeseries over grid boxes."""
+
+import lib
+import lib.box
+import lib.data.heat_fluxes
+import lib.data.HF_TS
+
+
+def main():
+    args = lib.get_args(['region', 'grid_file', 'days', 'fixes', 'year'])
+    grid_file = lib.box.IndexBox.GetGridFile(args)
+    boxes = lib.box.IndexBox.ReadGridText(grid_file)
+
+    args['fixes']['Y'] = args['year']
+    ds = lib.data.heat_fluxes.get_data(args)
+
+    for box in lib.progressbar(boxes):
+        args['fixes']['idx'] = box.idx
+        ofile = lib.data.HF_TS.get_filename(args['fixes'])
+        lib.check_output_dir(ofile, file=True)
+
+        dst = box.extract(ds)
+        dst = dst.hf.mean(['lat', 'lon'])
+        dst.to_netcdf(ofile)
+
+
+if __name__ == '__main__':
+    main()

Download/era5_land_mask.py

+"""Download land mask for ERA5 GLOBAL_025 grid.
+
+First to download the land/sea fraction the code below can be used in the
+Copernicus Climate Data Store toolbox at
+<https://cds.climate.copernicus.eu/toolbox-editor>.
+
+Place the file in
+`${SUBMESO_COLOR_DATA_DIR}/{region}/zones/ERA5_land_area_fraction.nc`.
+
+Then /Compute/make_land.py can be run.
+"""
+
+import cdstoolbox as ct
+
+@ct.application(title='Download data')
+@ct.output.download()
+def download_application():
+    data = ct.catalogue.retrieve(
+        'reanalysis-era5-single-levels',
+        {
+            'product_type': 'reanalysis',
+            'variable': 'land_sea_mask',
+            'year': '2000',
+            'month': '01',
+            'day': '01',
+            'time': '00:00',
+            'area': [
+                60, -85, 0, 0,  # Same as /Download/integrate_daily_sf.sh
+            ],
+        }
+    )
+    return data

lib/data/HF_TS.py

+"""Time series of heat fluxes in grided boxes."""
+
+from os import path
+
+import lib
+import lib.data
+
+ARGS_DIR = {'region', 'days'}
+pregex = '%(idx:fmt=04d)/HF_TS_%(Y).nc'
+
+
+def get_root(args=None, **kwargs):
+    args = lib.data.process_args(ARGS_DIR, args, **kwargs)
+    root = path.join(lib.root_data, args['region'], 'HF_TS',
+                     lib.data.get_time_folder(args))
+    return root
+
+
+def add_idx_dim(ds, filename, finder):
+    idx = finder.get_matches(filename)['idx'].match_str
+    ds = ds.expand_dims({'idx': [idx]})
+    return ds
+
+
+lib.data.create_data(__name__, pregex, get_root, ARGS_DIR,
+                     open_mf_kw=dict(preprocess_finder=add_idx_dim))