VE
Member Since 2018
Veronika Eyring
Prof Dr, Deutsches Zent Luft-Raumfahrt
AGU Research
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Interpretable Multiscale Machine Learning‐Based Parameterizations of Convection for ICON
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
22 august 2024
Helge Heuer, Veronika Eyring, Pierre Gentine, Marc...
Machine learning (ML)‐based parameterizations have been developed for Earth System Models (ESMs) with the goal to better represent subgrid...
Data‐Driven Equation Discovery of a Cloud Cover Parameterization
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
29 february 2024
Arthur Grundner, Tom Beucler, Pierre Gentine, Vero...
A promising method for improving the representation of clouds in climate models, and hence climate projections, is to develop machine learning̴...
Causally‐Informed Deep Learning to Improve Climate Models and Projections
JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES
19 february 2024
Fernando Iglesias-Suarez, Pierre Gentine, Breixo S...
Climate models are essential to understand and project climate change, yet long‐standing biases and uncertainties in their projections remain...
Machine Learning-Based Parameterizations of Convection for ICON
MACHINE LEARNING SUBGRID-SCALE PARAMETERIZATIONS FOR EARTH SYSTEM MODELING II POSTER
nonlinear geophysics | 14 december 2023
Helge Heuer, Mierk Schwabe, Pierre Gentine, Marco ...
In order to improve climate projections, machine learning (ML)-based parameterizations have been developed in the past for Earth System Models (ESMs) ...
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Improvement of the radiation parameterization of ICON by including subgrid-scale cloud properties using machine learning
MACHINE LEARNING SUBGRID-SCALE PARAMETERIZATIONS FOR EARTH SYSTEM MODELING I ORAL
nonlinear geophysics | 13 december 2023
Katharina Hafner, Fernando Iglesias-Suarez, Sara S...
Earth system models (ESMs) are fundamental for understanding and projecting future climate change. For feasibility reasons, ESMs typically run for dec...
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Pushing the Frontiers in Climate Modeling and Analysis with Machine Learning
THE FUTURE OF CLIMATE SCIENCE
union sessions | 12 december 2023
William D. Collins, Veronika Eyring, Pierre Gentin...
Climate and Earth system models are important tools to understand andproject climate change. Due to their complexity, they are limited intheir horizon...
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Transferring climate change knowledge
CLIMATE SENSITIVITY AND FEEDBACKS: ADVANCES AND NEW PARADIGMS I POSTER
atmospheric sciences | 11 december 2023
Francesco Immorlano, Veronika Eyring, Thomas le Mo...
Climate scientists clearly showed that the increase in atmospheric carbon dioxide concentration reached unprecedented levels over the past decades. It...
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Machine learning based PPEs of ICON-A for Processes understanding and Automated parameter tuning
PERTURBED PARAMETER ENSEMBLES (PPES) FOR UNDERSTANDING PROCESSES AND QUANTIFYING UNCERTAINTY IN EARTH SYSTEM MODELS I ORAL
global environmental change | 11 december 2023
Pauline H. Bonnet, Fernando Iglesias-Suarez, Loren...
Global climate models use parameterizations to represent the effect of subgrid-scale processes on the resolved state. Parameterizations in the atmosph...
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