2 citations · 3 across the 2 of their papers we have counts for
4 papers
AIMIP Phase 1: systematic evaluations of AI weather and climate models
Brian Henn, Christopher S. Bretherton, Nikolay Koldunov +18
We present the AI weather and climate model intercomparison project (AIMIP), phase 1. Drawing from the rich tradition of intercomparisons in climate model development, we specify a…
Accelerating scientific discovery with the common task framework
J. Nathan Kutz, Peter Battaglia, Michael Brenner +12
Machine learning (ML) and artificial intelligence (AI) algorithms are transforming and empowering the characterization and control of dynamic systems in the engineering, physical,…
Neural general circulation models optimized to predict satellite-based precipitation observations
Janni Yuval, Ian Langmore, Dmitrii Kochkov +1
Climate models struggle to accurately simulate precipitation, particularly extremes and the diurnal cycle. Here, we present a hybrid model that is trained directly on satellite-bas…
4D-Var using Hessian approximation and backpropagation applied to automatically-differentiable numerical and machine learning models
Kylen Solvik, Stephen G. Penny, Stephan Hoyer
Constraining a numerical weather prediction (NWP) model with observations via 4D variational (4D-Var) data assimilation is often difficult to implement in practice due to the need…