This is the first step to do bias correction for the GFSv16 products. In this task:
1) a utility will be created to generate a time serious of the GFSV16 2m temperature, this will be used as input to the ML model
2) collect the ERA5 2m temperature during the same period, the data will be used as truth to tune the ML model.
This is the first step to do bias correction for the GFSv16 products. In this task:
1) a utility will be created to generate a time serious of the GFSV16 2m temperature, this will be used as input to the ML model 2) collect the ERA5 2m temperature during the same period, the data will be used as truth to tune the ML model.