I have the task of producing a cloudiness forecasts from GFS model. I found a way to get GFS data and manipulate it with metpy, but there are multiple data about clouds, for example: Pressure_convective_cloud_bottom Total_cloud_cover_convective_cloud Pressure_high_cloud_bottom_6_Hour_Average etc
How can I produce a meaningful forecast from them? Any tips to point me in the right direction?
Thank you
GFS output includes a value for the total cloud cover over the depth of the entire atmosphere. When accessing this data from a THREDDS server, it's called
Total_cloud_cover_entire_atmosphere.