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physics.ao-ph2025
An intercomparison of generative machine learning methods for downscaling precipitation at fine spatial scales
Neelesh Rampal, Bryn Ward-Leikis, Yun Sing Koh +7
Machine learning (ML) offers a computationally efficient approach for generating large ensembles of high-resolution climate projections, but deterministic ML methods often smooth f…
physics.ao-ph2025
Generative AI-Downscaling of Large Ensembles Project Unprecedented Future Droughts
Hamish Lewis, Neelesh Rampal, Peter B. Gibson +4
Understanding how droughts may change in the future is essential for anticipating and mitigating their adverse impacts. However, robust climate projections require large amounts of…
physics.ao-ph2025
Downscaling with AI reveals the large role of internal variability in fine-scale projections of climate extremes
Neelesh Rampal, Peter B. Gibson, Steven C. Sherwood +3
The computational cost of dynamical downscaling limits ensemble sizes in regional downscaling efforts. We present a newly developed generative-AI approach to greatly expand the sco…