DE_393 Development and Implementation of Climate Emulator for Destination Earth

Description du marché

The aim of this project is to develop a machine learning-based DestinE Climate Twin emulator in the form of well-documented and runnable code package for both training and inference and with pre-trained neural network models. The contract also includes documentation that details the capabilities and limitations of the emulator with respect to expected properties of the climate system (mean state, variability, etc).

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