Open bbakernoaa opened 11 months ago
this addresses #152
@bbakernoaa I made an extraction (forecast hour 6 of the run you shared, 5 levels closest to surface, selected variables, etc.), now available at https://csl.noaa.gov/groups/csl4/modeldata/melodies-monet/data/example_model_data/rrfssd_example/rrfs-sd_dynf006.nc (104M) for testing.
We can set it up like I did here, which also uses data stored in that location.
@bbakernoaa I made an extraction (forecast hour 6 of the run you shared, 5 levels closest to surface, selected variables, etc.), now available at https://csl.noaa.gov/groups/csl4/modeldata/melodies-monet/data/example_model_data/rrfssd_example/rrfs-sd_dynf006.nc (104M) for testing.
We can set it up like I did here, which also uses data stored in that location.
maybe we can add some netcdf tricks to compress that even further using integers instead of floats and the add_offset and scale_factor netcdf attributes
maybe we can add some netcdf tricks to compress that even further using integers instead of floats and the add_offset and scale_factor netcdf attributes
Perhaps, but I think it is better to keep format closer to the original. And I used NCO lossy compression, which already decreases the size a lot due to quantization, I don't know if additionally doing the int packing transform would make it any more compressible.
create a separate reader for RRFS-SD. This is based on
_rrfs_cmaq_mm
but removes many of the functions as rrfs-sd is obviously much simpler.