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Elaborated from #18 . The neural network that we train has certain characteristics which must be known for integrating into a climate model. These characteristics are explained in Arthur's 2021 paper, though with a statistical focus. Providing an overview of model input and output shape with a coding focus (e.g. variable/coord names used, how the forcing scaling works, an example of using the predicted probability distribution) would make it easier to adapt GZ21.
The text was updated successfully, but these errors were encountered:
Elaborated from #18 . The neural network that we train has certain characteristics which must be known for integrating into a climate model. These characteristics are explained in Arthur's 2021 paper, though with a statistical focus. Providing an overview of model input and output shape with a coding focus (e.g. variable/coord names used, how the forcing scaling works, an example of using the predicted probability distribution) would make it easier to adapt GZ21.
The text was updated successfully, but these errors were encountered: