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From the 1 of 5 linked papers with an AI index.

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5 papers

physics.ao-ph2026

AIFS-TC: A simple correction competitive with the operational frontier for tropical cyclone intensity forecasting

Anna Allen, Wessel P. Bruinsma, Michael Maier-Gerber +3

AI weather models are in the process of revolutionising weather forecasting. While these models have been shown to achieve superior performance to physics-based NWP in forecasting…

physics.ao-ph2026

HourGlass: A probabilistic data-driven temporal downscaler for global and regional weather forecasting

Magnus Sikora Ingstad, Mariana C. A. Clare, Olav Ersland +16

HourGlass is a probabilistic, data‑driven method that downscales 6‑hourly weather forecasts to hourly resolution, preserving small‑scale spatial detail and temporal consistency.

physics.ao-ph2026

Evaluation of medium range machine learning models for sub-seasonal prediction

Catherine de Burgh-Day, Chen Li, Debra Hudson +4

The performance of two machine learning (ML) atmosphere models - GraphCast and FourCastNetV2 - is evaluated in the context of sub-seasonal prediction, including their ability to re…

physics.ao-ph2026

Representing the Surface Ocean in ECMWF's data-driven forecasting system AIFS

Sara Hahner, Lorenzo Zampieri, Jean-Raymond Bidlot +22

Machine-learning (ML) models, such as the AIFS at the ECMWF, have revolutionised weather forecasting in recent years. We present an extension of the AIFS that jointly models the at…

physics.ao-ph2025

An update to ECMWF's machine-learned weather forecast model AIFS

Gabriel Moldovan, Ewan Pinnington, Ana Prieto Nemesio +18

We present an update to ECMWF's machine-learned weather forecasting model AIFS Single with several key improvements. The model now incorporates physical consistency constraints thr…