5 papers
Spatial Generalization Tests for Machine Learning-based Weather Models to Assess Physical Consistency
Maren Höver, Milan Klöwer, Christian Schroeder de Witt +1
Machine learning-based weather prediction is revolutionizing weather forecasting by learning from weather data in present-day climate. However, generalization to other climates rem…
ACE2-NEMO: Coupling an ML atmospheric emulator to a full-depth dynamical ocean model
Bobby Antonio, Kristian Strommen, Pablo Ortega +1
Understanding how fast atmospheric variability shapes slow climate variability and sensitivity remains a central challenge in Earth-system science. Recent advances in machine-learn…
Role of the ocean for fast atmospheric evolution revealed by machine learning
Bobby Antonio, Kristian Strommen, Hannah M. Christensen
There have recently been many efforts to create machine learnt atmospheric emulators designed to replace physical models. So far these have mainly focused on medium-range weather f…
Error in ERA5 2m Temperature identified using GraphCast
Hannah M. Christensen, Jack Barker, Bobby Antonio +3
Reanalyses such as ERA5 have long been foundational for weather and climate science. They have also found a new use case, as training and verification data for machine-learnt weath…
Seasonal forecasting using the GenCast probabilistic machine learning model
Bobby Antonio, Kristian Strommen, Hannah M. Christensen
Machine-learnt weather prediction (MLWP) models are now well established as being competitive with conventional numerical weather prediction (NWP) models in the medium range. Howev…