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Learning to forecast diagnostic parameters using pre-trained weather embedding
In the second stage, the autoencoder is frozen and "downstream" models are trained to predict diagnostic variables using only the latent representations of prognostic variables as input.
Verification against in-situ observations for Data-Driven Weather Prediction
With an eye towards climate justice and the uneven availability of weather data: is the simulation equally good for all regions of the world, and would DDWPs exacerbate biases present in the training data?
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