11 citations · 28 across the 11 of their papers we have counts for
4 papers · 1 filter
A Deep Learning Earth System Model for Efficient Simulation of the Observed Climate
Nathaniel Cresswell-Clay, Bowen Liu, Dale Durran +4
A key challenge for computationally intensive state-of-the-art Earth System models is to distinguish global warming signals from interannual variability. Here we introduce DLESyM,…
Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling
Jaideep Pathak, Yair Cohen, Piyush Garg +8
Storm-scale convection-allowing models (CAMs) are an important tool for predicting the evolution of thunderstorms and mesoscale convective systems that result in damaging extreme w…
Coupled Ocean-Atmosphere Dynamics in a Machine Learning Earth System Model
Chenggong Wang, Michael S. Pritchard, Noah Brenowitz +5
Seasonal climate forecasts are socioeconomically important for managing the impacts of extreme weather events and for planning in sectors like agriculture and energy. Climate predi…
DiffObs: Generative Diffusion for Global Forecasting of Satellite Observations
Jason Stock, Jaideep Pathak, Yair Cohen +5
This work presents an autoregressive generative diffusion model (DiffObs) to predict the global evolution of daily precipitation, trained on a satellite observational product, and…