Is there a way to load and convert grib file from reduced gaussian grid (reduced_gg) to regular gaussian grid (regular_gg) using cfgrib?
Assuming the file fgrib contains temperature on 60 levels and on a reduced gaussian grid N128, the command: ds=cfgrib.open_dataset(fgrib)
provide me the xarray dataset with the temperature and its coords:
<xarray.Dataset>
Dimensions: (hybrid: 60, values: 88838)
Coordinates:
time datetime64[ns] ...
step timedelta64[ns] ...
* hybrid (hybrid) float64 1.0 2.0 3.0 4.0 5.0 ... 57.0 58.0 59.0 60.0
latitude (values) float64 ...
longitude (values) float64 ...
valid_time datetime64[ns] ...
Dimensions without coordinates: values
Data variables:
t (hybrid, values) float32 ...
Attributes:
GRIB_edition: 2
GRIB_centre: ecmf
GRIB_centreDescription: European Centre for Medium-Range Weather Forecasts
GRIB_subCentre: 0
Conventions: CF-1.7
institution: European Centre for Medium-Range Weather Forecasts
history: 2023-04-03T13:10 GRIB to CDM+CF via cfgrib-0.9.9...
We can see that t dimensions are (hybrid,values) which are 60 and 88838. (Coords hybrib corresponds to the hybrid model levels.) The latitude and longitude coords are of dimensions (values). Is there any cfgrib method allowing to regrid on a regular gaussian grib where, in the N128 case, whould provide the t with the dimensions (60,256 latitude,512 longitude)?
