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Status: Unchecked ×Keyword: typhoon intensity prediction ×Clear all

4 claims from 2 papers

1. Earth and Planetary Sciences › Meteorological Phenomena and Simulations

   Evaluation of five global AI models for predicting weather in Eastern Asia and Western Pacific

   Liu, Hsu, Peng et al. · npj Climate and Atmospheric Science · 2024

   The study compared five global AI weather models over Eastern Asia from June to November 2023, looking at general forecast accuracy, typhoon tracks and intensity, and typhoon rainfall.

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   1. UncheckedAveraging the forecasts of five AI weather models gave performance that rivalled the best single model, FengWu, in this Eastern Asia evaluation.“A multi-model ensemble, constructed by averaging predictions from the five models, demonstrates superior performance, rivaling that of FengWu.”
   2. UncheckedAmong five AI weather models tested on 11 typhoons in 2023, FengWu had the most accurate tracks but also the largest intensity errors.“For the 11 typhoons in 2023, FengWu demonstrates the most accurate track prediction; however, it also has the largest intensity errors.”

2. Earth and Planetary Sciences › Meteorological Phenomena and Simulations

   Machine‐Learning (ML)‐Physics Fusion Model Accelerates the Paradigm Shift in Typhoon Forecasting With a CNOP‐Based Assimilation Framework

   Niu, Wang, Mu et al. · Geophysical Research Letters · 2025

   The authors couple the FuXi machine-learning model with the physics-based Shanghai Typhoon Model, then use a sensitivity method to guide satellite data assimilation for two 2024 super typhoons.

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   1. UncheckedDense satellite data assimilated in sensitive regions can further improve typhoon forecasts, even though the hybrid model is constrained by FuXi's large-scale fields.“Despite being constrained by FuXi's large‐scale forecast fields, the dense assimilation of satellite observations within these sensitive regions can further enhance typhoon forecasts.”
   2. UncheckedA hybrid of the FuXi machine-learning model and the physics-based SHTM, linked by spectral nudging, improved forecasts of two 2024 super typhoons.“By employing spectral nudging, the hybrid FuXi‐SHTM model leverages FuXi's robust large‐scale forecasting capabilities alongside SHTM's mesoscale strengths, significantly enhancing track, intensity, and precipitation predictions for super typhoons Yagi (2024) and Krathon (2024).”