NVIDIA Earth2Studio: Custom Weather Forecasting
Sana Hassan from IIT Madras introduces a custom batched ensemble weather forecasting workflow using NVIDIA Earth2Studio on Google Colab with Zarr datasets.
Stock photo for illustration only, not from the actual event
- Direct control over initial-condition perturbation and member batching
- Executed entirely within a single Google Colab environment
- Evaluated forecast accuracy using RMSE, fair CRPS, and spread-skill
- Preserved ensemble structure in Zarr datasets accessible via Xarray
A flexible and extensible workflow for custom weather forecasting has been demonstrated, moving far beyond standard predefined ensemble functions. Researchers can directly manage initial-condition perturbation, member batching, model iteration, and diagnostic chaining within a unified Google Colab environment.
This approach highlights how physically scaled perturbations and unperturbed control members assist in interpreting ensemble spread, alongside alignment, persistence, verification, and visualization
Stock photo for illustration only, not from the actual event
Leveraging advanced machine learning frameworks like NVIDIA Earth2Studio on accessible cloud environments significantly lowers the barrier for meteorological research. By utilizing robust statistical evaluation metrics, developers can rigorously test and calibrate complex atmospheric models before operational deployment.
To evaluate forecast calibration across lead times, the workflow incorporates standard metrics such as RMSE, fair CRPS, and spread-skill diagnostics. The resulting Zarr dataset preserves the complete ensemble structure, allowing seamless integration and further analysis through Xarray.
Because the workflow adheres strictly to Earth2Studio component interfaces, it remains highly scalable. Users can easily swap prognostic models, change atmospheric data sources, integrate new diagnostics, scale up ensemble sizes, or adopt asynchronous storage without rebuilding the entire pipeline from scratch.
Source: MarkTechPost
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