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AI for Climate refers to the application of artificial intelligence techniques to address climate-related challenges. This includes using AI for climate modeling, prediction, and mitigation strategies.
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 A Diffusion-Based Framework for High-Resolution Precipitation Forecasting over CONUS Marina Vicens-Miquel Amy McGovern Aaron J. Hill Efi Foufoula-Georgiou Clement Guilloteau Samuel S. P. Shen | |||
 China Regional 3km Downscaling Based on Residual Corrective Diffusion Model Honglu Sun Hao Jing Zhixiang Dai Sa Xiao Wei Xue Jian Sun Qifeng Lu | |||
 FuXi-Nowcast: Meet the longstanding challenge of convective initiation in nowcasting Lei Chen Zijian Zhu Xiaoran Zhuang Tianyuan Qi Yuxuan Feng Xiaohui Zhong Hao Li | |||
 Observation-driven correction of numerical weather prediction for marine winds Matteo Peduto Qidong Yang Jonathan Giezendanner Devis Tuia Sherrie Wang | |||
 Retrofitting Earth System Models with Cadence-Limited Neural Operator Updates Aniruddha Bora Shixuan Zhang Khemraj Shukla Bryce Harrop George Em. Karniadakis L. Ruby Leung | |||
 On Global Applicability and Location Transferability of Generative Deep Learning Models for Precipitation Downscaling Paula Harder Christian Lessig Matthew Chantry Francis Pelletier David Rolnick | |||
 High-Resolution Probabilistic Data-Driven Weather Modeling with a Stretched-Grid Even Marius Nordhagen Håvard Homleid Haugen Aram Farhad Shafiq Salihi Magnus Sikora Ingstad Thomas Nils Nipen ...Mariana Clare Simon Lang Matthew Chantry Peter Dueben Jørn Kristiansen | |||
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