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infer mask from cell_area in 1x1deg #81

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9 changes: 5 additions & 4 deletions om4labs/diags/seaice/seaice.py
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Original file line number Diff line number Diff line change
Expand Up @@ -107,10 +107,11 @@ def read(dictArgs):
ds["GEOLON"] = xr.DataArray(X, dims=["lat", "lon"])
ds["GEOLAT"] = xr.DataArray(Y, dims=["lat", "lon"])
_AREA = standard_grid_cell_area(_lat, _lon)
_MASK = np.array(dstatic["mask"].fillna(0.0).to_masked_array())
_AREA = _AREA * _MASK
ds["CELL_AREA"] = xr.DataArray(_AREA, dims=["lat", "lon"])
ds["AREA"] = xr.DataArray(_AREA, dims=["lat", "lon"])
# backward fill to zero NaNs on the antarctic continent (unmapped points)
_CELL_AREA = dstatic["CELL_AREA"].bfill(dim='lat')
# replace non-land values by result of analytical computation
ds["CELL_AREA"] = xr.where(_CELL_AREA == 0, 0, _AREA)
ds["AREA"] = ds["CELL_AREA"].copy()
ds = ds.rename({"lon": "x", "lat": "y"})
else:
ds["CELL_AREA"] = dstatic["CELL_AREA"]
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