TL;DR
Diagram showing an AI cyclone forecasting workflow that uses global atmospheric model data to generate repeated forecasts and predict a tropical cyclone’s track and intensity over time, with projected positions from 6 to 96 hours and color-coded wind speeds.
One of the major challenges in forecasting is the rapid intensification (RI) of tropical cyclones, wherein cyclone intensity can increase rapidly under dynamic and changing atmospheric and oceanic conditions. This paper explores how a hybrid artificial intelligence (AI)-physics model can be used to enhance tropical cyc...
An extensive benchmark of tropical cyclone forecasting is conducted, comparing GenCast, FourCastNet 3, and FGN with ECMWF's operational physics-based ensemble, IFS-ENS, finding that leading AI models substantially outperform IFS-ENS in cyclone tracking.
A potentially super El Ni\~no is forecasted in 2026, raising the need to anticipate land carbon-cycle risks before its impacts unfold. We develop a prospective early-warning framework that uses dynamic global vegetation models driven by an ensemble of ECMWF seasonal climate forecasts and machine-learning burned area pr...
Atmospheric rivers (ARs) produce many of the world's most extreme precipitation events and hydrometeorological hazards. Although artificial intelligence weather prediction (AIWP) models have demonstrated skill comparable to or exceeding numerical weather prediction (NWP) systems for large-scale atmospheric variables, t...
Tropical cyclones (TCs) pose significant risk to infrastructure and human safety, and the frequency and intensity of large TCs are expected to increase in the future. Quantifying such risk to coastal and inland regions is challenging, largely due to the rare nature of TCs which limits historical data availability. We i...
AI-based ensemble weather prediction is emerging as a new paradigm for probabilistic forecasting, yet its ability to represent the key physical processes that govern high-impact extreme rainfall remains unclear. Here, we compare an AI-based ensemble system (AIFS-CRPS) with a conventional physics-based ensemble (IFS-E...
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