5 papers
Long-window 4DVar for reanalysis using a differentiable weather model
Gregory J. Hakim, Jeffrey S. Whitaker, Bo Huang +1
Atmospheric reanalyses combine observations with model forecasts using complex data assimilation systems. We test whether a differentiable weather model permits a simpler and more…
HealDA: Highlighting the importance of initial errors in end-to-end AI weather forecasts
Aayush Gupta, Akshay Subramaniam, Michael S. Pritchard +6
AI weather models now rival leading numerical weather prediction (NWP) systems in medium-range skill. However, almost all still rely on NWP data assimilation (DA) to provide initia…
Skillful Global Ocean Emulation and the Role of Correlation-Aware Loss
Niraj Agarwal, Timothy A. Smith, Sergey Frolov +1
Machine learning emulators have shown extraordinary skill in forecasting atmospheric states, and their application to global ocean dynamics offers similar promise. Here, we adapt t…
Deep-Learned Observation Operators for Artificial Intelligence Weather Forecasting Models
Kelsey Lieberman, Laura Slivinski, Matt Bender +6
Satellite observation operators play an essential role in atmospheric data assimilation by translating model state variables into observation space. Previous work has shown that de…
Assimilating Observed Surface Pressure into ML Weather Prediction Models
Laura C. Slivinski, Jeffrey S. Whitaker, Sergey Frolov +2
There has been a recent surge in development of accurate machine learning (ML) weather prediction models, but evaluation of these models has mainly been focused on medium-range for…