Introducing ClimaX: The first foundation model for weather and climate - Microsoft Research

We are announcing ClimaX, a flexible and generalizable deep learning model for weather and climate science. ClimaX is trained using several heterogeneous datasets spanning many weather variables at multiple spatio-temporal resolutions. We show that such a foundational model can be fine-tuned to address a wide variety of climate and weather tasks, including those that involve atmospheric variables and spatio-temporal granularities unseen during pretraining. ClimaX will be made available for academic and research use shortly. The key insight behind our effort is the realization that all the prediction and modeling tasks in weather and climate science are based on physical phenomena and their interactions with the local and global geography. Consequently, a foundational model that models a multitude of weather and climate variables at many different scales eventually will encode these physical laws and the relevant geographical interactions. Current state-of-the-art numerical weather and

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