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  • NVIDIA
    Earth-2 FourCastNet 3
    Model
    NVIDIA
    Earth-2 FourCastNet 3

    FourCastNet 3 is a probabilistic global weather modeling that uses geometric machine learning.

  • This model is backed by NVIDIA's Plus Plus (++) Promise
    NVIDIA's ++ Promise covers the quality of the datasets used to train this model.
    FieldResponse
    Intended Task/Domain:Weather Forecasting and Simulation
    Model Type:Spherical Neural Operator
    Intended Users:Weather Forecasters, Researchers, Related Industrial users.
    Output:Tensor representing 72 atmospheric variables
    Describe how the model works:Input variables are fed through a spherical convolutional architecture to produce the weather state in the next 6 hours.
    Name the adversely impacted groups this has been tested to deliver comparable outcomes regardless of:Not Applicable (N/A)
    Technical Limitations & Mitigation:The model may perform poorly for systems that are not similar to those in the training data, namely for rare weather phenomena or weather behavior outside of the 1980-2016 training dataset. There is no mechanism to enforce physical consistency for predictions.
    Verified to have met prescribed NVIDIA quality standards:Yes
    Performance Metrics:Accuracy (ACC), Error (RMSE), and Probabilistic Calibration (CRPS)
    Potential Known Risks:This model may incorrectly predict future weather states and phenomenon
    Licensing:Apache 2.0 license.

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