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In the context of 1000 year long dataset it seemed that global zg500 mattered less, therefore decision was taken to ignore this more advanced treatment. In 8000 year long dataset (possibly also due to weaker soil atmosphere interactions) global zg500 is more prominent, also possibly for shorter heat waves this could also be the case. In Besombes at al 2021 we see this setup for their generative model. VAE trained on Plasim shows that it is harder to generate continuous outputs with standard padding (convolution), although deeper network seems to perform better in this regard.
Take into account the connectivity
Take into account that grid points are not equally spaced
The text was updated successfully, but these errors were encountered:
In the context of 1000 year long dataset it seemed that global zg500 mattered less, therefore decision was taken to ignore this more advanced treatment. In 8000 year long dataset (possibly also due to weaker soil atmosphere interactions) global zg500 is more prominent, also possibly for shorter heat waves this could also be the case. In Besombes at al 2021 we see this setup for their generative model. VAE trained on Plasim shows that it is harder to generate continuous outputs with standard padding (convolution), although deeper network seems to perform better in this regard.
The text was updated successfully, but these errors were encountered: