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From the 1 of 4 linked papers with an AI index.

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

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

collaborators

4 papers

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

Probabilistic Seasonal Streamflow Forecasting Across California's Sierra Nevada Watersheds with Agentic AI

Ignacio Lopez-Gomez, Michael P. Brenner, Tapio Schneider

Accurate seasonal runoff forecasts are critical for managing California's reservoirs and water supply for millions of its residents. Winter snow accumulation provides a strong sour…

cs.LG2026

Regional climate risk assessment from climate models using probabilistic machine learning

Zhong Yi Wan, Ignacio Lopez-Gomez, Robert Carver +4

Effective climate risk assessment is hindered by the resolution gap between coarse global climate models and the fine-scale information needed for regional decisions. We introduce…

cs.LG2024

A probabilistic framework for learning non-intrusive corrections to long-time climate simulations from short-time training data

Benedikt Barthel Sorensen, Leonardo Zepeda-Núñez, Ignacio Lopez-Gomez +4

Chaotic systems, such as turbulent flows, are ubiquitous in science and engineering. However, their study remains a challenge due to the large range scales, and the strong interact…