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Jan 25, 2023 · We are announcing ClimaX, a flexible and generalizable deep learning model for weather and climate science. Figure 1: ClimaX is the first foundation model designed to perform a wide variety of weather and climate modeling tasks. For weather, these tasks include standard forecasting tasks of relevant weather variables like temperature, humidity ...
What is ClimaX? ️ ClimaX is the first foundation model for weather and climate science. ️ Simple, flexible, and easy to use. ️ Ample examples for the workflow to apply to various downstream tasks ranging from weather forecasting to climate downscaling. ️ Supports efficient scalable distributed training, powered by PyTorch Lightning .
Jan 30, 2023 · In the new paper ClimaX: A Foundation Model for Weather and Climate, a team from Microsoft Autonomous Systems and Robotics Research, Microsoft Research AI4Science and the University of California at Los Angeles presents ClimaX, a foundation model for weather and climate that can be efficiently adapted for general-purpose tasks related to the Earth’s atmosphere.
Jan 24, 2023 · ClimaX: A foundation model for weather and climate. Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K. Gupta, Aditya Grover. Most state-of-the-art approaches for weather and climate modeling are based on physics-informed numerical models of the atmosphere. These approaches aim to model the non-linear dynamics and complex interactions ...
We develop and demonstrate ClimaX, a flexible and generalizable deep learning model for weather and climate science that can be trained using heterogeneous datasets spanning different variables, spatio-temporal coverage, and physical groundings. Published at ICML 2023 (Spotlight).
Jan 24, 2023 · ClimaX is developed and demonstrated, a flexible and generalizable deep learning model for weather and climate science that can be trained using heterogeneous datasets spanning different variables, spatio-temporal coverage, and physical groundings and results in superior performance on benchmarks for weather forecasting and climate projections, even when pretrained at lower resolutions and ...
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ClimaX is pre-trained with a self-supervised learning objective on climate datasets derived from CMIP6. The pretrained ClimaX can then be fine-tuned to address a breadth of climate and weather tasks, including those that involve atmospheric variables and spatiotemporal scales unseen during pretraining. Compared to existing data-driven baselines ...
