3 papers
cs.LG2026
Domain-Adaptive Climate Downscaling Under Temporal Distribution Shift
Shuochen Wang, Nishant Yadav, Auroop R. Ganguly
Deep-learning-based climate downscaling aims to learn relationships from historical low-resolution (LR) and high-resolution (HR) climate data to generate HR climate projections. Ho…
physics.ao-ph2026
climt-paraformer: Stable Emulation of Convective Parameterization using a Temporal Memory-aware Transformer
Shuochen Wang, Nishant Yadav, Joy Merwin Monteiro +1
Accurate representation of moist convective sub-grid-scale processes remains a major challenge in global climate models, as traditional parameterization schemes are both computatio…
cs.LG2024
Paraformer: Parameterization of Sub-grid Scale Processes Using Transformers
Shuochen Wang, Nishant Yadav, Auroop R. Ganguly
One of the major sources of uncertainty in the current generation of Global Climate Models (GCMs) is the representation of sub-grid scale physical processes. Over the years, a seri…