I currently develop a ml model to forecast temperature (spatial resolution 10 m x 10m) by leveraging these models (in this case Climax by Microsoft https://github.com/microsoft/climax ). Feel free to ask!
Do you use WRF as an input? I think graphcast uses some kind of NWP input (qhich in my mind i've equated to WRF). Thank you for offering to answer questions!
We use a commercial meteorology service (aka Openweathermap with resolution 500m x 500m ) as one input so they might use WRF data (and indirectly my model as well).
OWM was chosen, because they provide an easy api for providing general weather data.
Last I checked the AI models still used the same initial conditions used in models like the GFS and ECMWF which is a combination of a previous forecast adjusted with observations.
So GFS->graphcast = more accurate coarse-grained prediction (0,25 degree iirc), -> WRF for fine grained interpolation of forecast?