collaborators

5 papers

cs.LG2026

A Differentiable Framework for Global Circulation Model Precipitation Bias Correction

Kamlesh Sawadekar, Seth McGinnis, Peijun Li +2

Systematic biases in General Circulation Model (GCM) outputs limit their direct applicability in regional planning, making bias correction a technically demanding but necessary ste…

cs.LG2026

StefaLand: An Efficient Geoscience Foundation Model That Improves Dynamic Land-Surface Predictions

Nicholas Kraabel, Jiangtao Liu, Yuchen Bian +2

Managing natural resources and mitigating risks from floods, droughts, wildfires, and landslides require models that can accurately predict climate-driven land-surface responses. T…

physics.geo-ph2025

DRUM: Diffusion-based runoff model for probabilistic flood forecasting

Zhigang Ou, Congyi Nai, Baoxiang Pan +7

Extreme floods pose escalating risks in a changing climate, yet forecasting remains challenging due to peak flow underestimation and high uncertainty. We introduce DRUM, a diffusio…

physics.geo-ph2025

Distinct hydrologic response patterns and trends worldwide revealed by physics-embedded learning

Haoyu Ji, Yalan Song, Tadd Bindas +9

To track rapid changes within our water sector, Global Water Models (GWMs) need to realistically represent hydrologic systems' response patterns - such as baseflow fraction - but a…

physics.flu-dyn2025

Update hydrological states or meteorological forcings? Comparing data assimilation methods for differentiable hydrologic models

Amirmoez Jamaat, Yalan Song, Farshid Rahmani +3

Data assimilation (DA) enables hydrologic models to update their internal states using near-real-time observations for more accurate forecasts. With deep neural networks like long…