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Abstract: Can AI Data-Driven Models Capture the Temporal Clustering of Unique Atmospheric Rivers and the Influence of Climate Modes? (AGU25)

Can AI Data-Driven Models Capture the Temporal Clustering of Unique Atmospheric Rivers and the Influence of Climate Modes?

Zhiqi Yang1, Michael J Deflorio2, Agniv Sengupta3, Bin Guan4, Zhenhai Zhang5, Kristen Guirguis1, Alexander Gershunov6 and Luca Delle Monache3, (1)University of California San Diego, Scripps Institution of Oceanography, Center for Western Weather and Water Extremes (CW3E), La Jolla, United States, (2)Scripps Institution of Oceanography, UC San Diego, Center for Western Weather and Water Extremes (CW3E), La Jolla, United States, (3)Center for Western Weather and Water Extremes (CW3E), Scripps Institution of Oceanography, UC San Diego, La Jolla, United States, (4)University of California, Los Angeles, Joint Institute for Regional Earth System Science and Engineering, Los Angeles, United States, (5)Scripps Institution of Oceanography, UCSD, Center for Western Weather and Water Extremes (CW3E), La Jolla, United States, (6)Scripps Institution of Oceanography, University of California San Diego, Center for Western Weather and Water Extremes (CW3E), La Jolla, United States
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