eyringmlclimategroup Goto Github PK
Name: EyringMLClimateGroup
Type: Organization
Name: EyringMLClimateGroup
Type: Organization
Code repository to reproduce: G.Behrens, T. Beucler, F. Iglesias-Suarez, S. Yu, P. Gentine, M. Pritchard, M. Schwabe and V. Eyring, 2024. Simulating Atmospheric Processes in Earth System Models and Quantifying Uncertainties with Deep Learning Multi-Member and Stochastic Parameterizations
Code to reproduce figures of Debeire, K., Runge, J., Gerhardus, A., Eyring, V. (2024). Bootstrap aggregation and confidence measures to improve time series causal discovery
A NN based cloud cover parameterization for the ICON-A model
A hierarchical modeling framework to discover new machine learning-based equations for cloud cover, including symbolic regression
Creation and analysis of the CCClim dataset
Notebooks for the code used to perform regime-oriented causal model evaluation of CMIP6 LEs
Code to reproduce figures from Karmouche, S., Galytska, E., Meehl, G. A., Runge, J., Weigel, K., and Eyring, V. (2024) Changing effects of external forcing on Atlantic-Pacific interactions
This repository provides a Python implementation of the Gaussian Mixture Model (GMM) algorithm for detecting extreme events in CMIP6 data.
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