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Seasonal to Subseasonal Forecast Model

Seasonal to Subseasonal Forecast Model

  • Seasonal to Subseasonal Forecast Model

    • Technology Overview

    Seasonal to subseasonal forecasting (S2S) predicts weather and climate on time scales between conventional weather forecasts (usually a few days) and seasonal forecasts (usually a few months). The typical range is from two weeks to two months. This forecast supports agricultural planning, resource management, disaster preparedness, and responses to extreme weather events.

    Advantages

  • High-precision Prediction

  • High-precision Prediction

    Utilizes machine learning and deep learning models to significantly improve forecast accuracy, capable of completing a comprehensive 42-day forecast within 7 seconds.

  • Multivariate Integration

  • Multivariate Integration

    Includes upper-atmosphere variables, surface variables, and air-sea interaction processes, providing comprehensive forecast information.

  • Innovative Technology

  • Innovative Technology

    Employs advanced techniques such as flow-dependent intelligent perturbation generation modules and Circular Transformer (CirT), enhancing the ability to predict complex meteorological phenomena like the Madden-Julian Oscillation (MJO).