Comments (3)
Addendum:
albedo
is only choosen as an example. temperature
and influx_toa
are affected similarly. influx_diffuse
and influx_direct
have a different problem: All values are simply (see below)nan
.
from atlite.
Update:
I recreated the cutout again to exclude problems during creation or from transfer / faulty input files.
Problems regarding coordinates persist.
The problem with influx_diffuse
and influx_direct
is a bit different from what I described earlier:
The values for both variables for January until including November are zero or nan
. Only December has usable data in these variables.
from atlite.
The problem lays not directly in the sarah.py script but in the era5 script. The albedo
and other influx variables are retrieved from era5
even though when the module is set to sarah
(which is kind of weird, but I think the intention is to have a complete dataset...)
ERA5 datasets have reversed y axis. In the normal case this is fixed in the standard prepare_cutout
function when the merging the empty cutout (coordinates only) with the feature datasets. In the sarah.py script the axis is not double-checked and overwritten here.
An easy fix is to make a double check and correction in the era5.py script, by adding
ds = maybe_swap_spatial_dims(ds)
into the _rename_and_clean_coords
function. This ensures the correct alignment of the datasets.
maybe_swap_spatial_dims
is defined in gis.py
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