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Artificial Intelligence for the Earth Systems (AMS Journal)
Hybrid Foreasting (ECMWF Newsletter)
Building on recent advances in artificial intelligence within the climate science community, our group aims to contribute to societally relevant challenges, including but not limited to improving subseasonal-to-seasonal prediction, evaluating projected climate changes, and supporting preparation and mitigation policies for extreme weather events.
💡Using AI/ML techniques, we plan to explore the following research topics:
Improving the prediction skill of summertime midlatitude heatwaves through better representation of land-atmosphere coupling.
Detecting sources of predictability for atmospheric blocking on the subseasonal timescale
Assessing AI-generated climate model simulations in their representation of midlatitude atmospheric dynamics
Figure. Schematic illustration of the seasonal forecast of East Asian precipitation using optimized analog forecast approach with spatially-weighted mask learned by the neural network. Inspired by Rader and Barnes (2022, GRL).
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