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From the 2 of 17 linked papers with an AI index.

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20242026
most citedAIMIP Phase 1: systematic evaluations of AI weather and climate models

1 citations · 2 across the 6 of their papers we have counts for

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physics.ao-ph20261 cited

AIMIP Phase 1: systematic evaluations of AI weather and climate models

Brian Henn, Christopher S. Bretherton, Nikolay Koldunov +18

The paper introduces AIMIP Phase 1, an intercomparison framework for AI‑based weather and climate models that evaluates their ability to simulate historical atmospheric conditions…

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

Evaluating Skill and Stability of ArchesWeather and ArchesWeatherGen under Multi-Decadal Climate Simulations

Renu Singh, Robert Brunstein, Antonia Jost +5

We evaluate the climate simulation capabilities of ArchesWeather and ArchesWeatherGen, two machine learning models originally trained for weather forecasting and evaluated up to a…

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-ph2024

Robustness of AI-based weather forecasts in a changing climate

Thomas Rackow, Nikolay Koldunov, Christian Lessig +9

Data-driven machine learning models for weather forecasting have made transformational progress in the last 1-2 years, with state-of-the-art ones now outperforming the best physics…

physics.ao-ph2024

Machine Learning for the Physics of Climate

Annalisa Bracco, Julien Brajard, Henk A. Dijkstra +3

An exponential growth in computing power, which has brought more sophisticated and higher resolution simulations of the climate system, and an exponential increase in observations…