Tom Beucler

Publications | Phd and Masters theses

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28 publications

En préparation
 
Machine Learning for Clouds and Climate (Invited Chapter for the AGU Geophysical Monograph Series "Clouds and Climate")
Beucler Tom, Ebert-Uphoff Imme, Rasp Stephan, Pritchard Michael, Gentine Pierre Clouds and Their Climatic Impact: Radiation, Circulation, and Precipitation, edited by: Sullivan, SC and Hoose, C., Wiley–American Geophysical Union: 327-346.. Peer-reviewed.
[DOI][serval:BIB_B7C845AC0449]
2024
Climate-invariant machine learning.
Beucler T., Gentine P., Yuval J., Gupta A., Peng L., Lin J., Yu S., Rasp S., Ahmed F., O'Gorman P.A. et al., 2024/02/09. Science advances, 10 (6) pp. eadj7250. Peer-reviewed.
[URN][DOI][Pmid][serval:BIB_E422A7BB1B25]
2023
Comparing storm resolving models and climates via unsupervised machine learning.
Mooers G., Pritchard M., Beucler T., Srivastava P., Mangipudi H., Peng L., Gentine P., Mandt S., 2023/12/15. Scientific reports, 13 (1) p. 22365. Peer-reviewed.
[URN][DOI][Pmid][serval:BIB_781CFB944FB8]
 
Data-Driven Cloud Cover Parameterizations
Arthur Grundner, Tom Beucler, Pierre Gentine, Marco A. Giorgetta, Fernando Iglesias-Suarez, Veronika Eyring, 2023/05/15..
[DOI][serval:BIB_EEEDA84951CC]
 
Extended-range predictability of stratospheric extreme events using explainable neural networks
Zheng Wu, Tom Beucler, Daniela Domeisen, 2023/05/15..
[DOI][serval:BIB_B016D4C134C6]
 
The key role of causal discovery to improve data-driven parameterizations in climate models
Fernando Iglesias-Suarez, Veronika Eyring, Pierre Gentine, Tom Beucler, Michael Pritchard, Jakob Runge, Breixo Solino-Fernandez, 2023/05/15..
[DOI][serval:BIB_C3E55BE5D278]
 
Causally-informed deep learning to improve climate models and projections
Fernando Iglesias-Suarez, Pierre Gentine, Breixo Solino-Fernandez, Tom Beucler, Michael Pritchard, Jakob Runge, Veronika Eyring, 2023..
[DOI][serval:BIB_64A698C1160F]
 
ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators
Sungduk Yu, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius J. M. Busecke et al., 2023..
[DOI][serval:BIB_A51EF14CFD95]
Selecting robust features for machine-learning applications using multidata causal discovery
Ganesh S. Saranya, Beucler Tom, Tam Frederick Iat-Hin, Gomez Milton S., Runge Jakob, Gerhardus Andreas, 2023. Environmental Data Science, 2.
[URN][DOI][serval:BIB_D0DCB42C4015]
 
Systematic Sampling and Validation of Machine Learning-Parameterizations in Climate Models
Jerry Lin, Sungduk Yu, Tom Beucler, Pierre Gentine, David Walling, Mike Pritchard, 2023..
[DOI][serval:BIB_B5276A20F608]
2022
Deep Learning Based Cloud Cover Parameterization for ICON
Grundner A., Beucler T., Gentine P., Iglesias-Suarez F., Giorgetta M.A., Eyring V., 2022/12. Journal of advances in modeling earth systems, 14 (12) pp. e2021MS002959. Peer-reviewed.
[URN][DOI][WoS][Pmid][serval:BIB_768D96868930]
Non-Linear Dimensionality Reduction With a Variational Encoder Decoder to Understand Convective Processes in Climate Models.
Behrens G., Beucler T., Gentine P., Iglesias-Suarez F., Pritchard M., Eyring V., 2022/08. Journal of advances in modeling earth systems, 14 (8) pp. e2022MS003130. Peer-reviewed.
[URN][DOI][WoS][Pmid][serval:BIB_A387096635C6]
 
A Data-Driven Approach to Isolate the Role of Radiative Heating in Tropical Cyclone Intensification
Tam Frederick Iat-Hin, Beucler Tom, Ruppert James, 2022/03/28. dans EGU General Assembly 2022, Vienna, Austria, Copernicus GmbH.
[DOI][serval:BIB_4B1FC77A3734]
 
An Improved Genesis and Evolution Parameter for Subseasonal Prediction of the North Indian Ocean Tropical Cyclones
Sudheesh Saranya Ganesh, Sahai Atul Kumar, Sukumarapillai Abhilash, Joseph Susmitha, Beucler Tom, 2022/03/27. dans EGU General Assembly 2022, Vienna, Austria, Copernicus GmbH.
[DOI][serval:BIB_BF9285061796]
 
Climate-Invariant, Causally Consistent Neural Networks as Robust Emulators of Subgrid Processes across Climates
Beucler Tom, Iglesias-Suarez Fernando, Eyring Veronika, Pritchard Michael, Runge Jakob, Gentine Pierre, 2022/03/26. dans EGU General Assembly 2022, Vienna, Austria, Copernicus GmbH.
[DOI][serval:BIB_EE901951DBA9]
 
Identifying precursors for extreme stratospheric polar vortex events using an explainable neural network
Wu Zheng, Beucler Tom, de Fondeville Raphaël, Székely Eniko, Obozinski Guillaume, Ball William, Domeisen Daniela, 2022/03/26. dans EGU General Assembly 2022, Vienna, Austria, Copernicus GmbH.
[DOI][serval:BIB_0394979A9B24]
Modeling stratospheric polar vortex variation and identifying vortex extremes using explainable machine learning
Wu Zheng, Beucler Tom, Székely Enikő, Ball William T., Domeisen Daniela I.V., 2022. Environmental Data Science, 1 pp. e17. Peer-reviewed.
[URN][DOI][serval:BIB_0CE5C474601D]
2021
 
Assessing the Potential of Deep Learning for Emulating Cloud Superparameterization in Climate Models With Real‐Geography Boundary Conditions
Mooers Griffin, Pritchard Michael, Beucler Tom, Ott Jordan, Yacalis Galen, Baldi Pierre, Gentine Pierre, 2021/05. Journal of Advances in Modeling Earth Systems, 13 (5). Peer-reviewed.
[DOI][WoS][serval:BIB_A7F04116FCF5]
 
Enforcing Analytic Constraints in Neural Networks Emulating Physical Systems.
Beucler Tom, Pritchard Michael, Rasp Stephan, Ott Jordan, Baldi Pierre, Gentine Pierre, 2021/03/05. Physical review letters, 126 (9) p. 098302. Peer-reviewed.
[DOI][WoS][Pmid][serval:BIB_A4DC5F3D8416]
2020
 
Interpreting and Stabilizing Machine-Learning Parametrizations of Convection
Brenowitz Noah D., Beucler Tom, Pritchard Michael, Bretherton Christopher S., 2020/12. Journal of the Atmospheric Sciences, 77 (12) pp. 4357-4375. Peer-reviewed.
[DOI][WoS][serval:BIB_D99C79F5B319]
Quantifying Convective Aggregation Using the Tropical Moist Margin's Length
Beucler Tom, Leutwyler David, Windmiller Julia M., 2020/10. Journal of Advances in Modeling Earth Systems, 12 (10). Peer-reviewed.
[DOI][WoS][serval:BIB_B7E5E07CCE15]
 
Convective Dynamics and the Response of Precipitation Extremes to Warming in Radiative–Convective Equilibrium
Abbott Tristan H., Cronin Timothy W., Beucler Tom, 2020/05. Journal of the Atmospheric Sciences, 77 (5) pp. 1637-1660. Peer-reviewed.
[DOI][WoS][serval:BIB_E437806CFF27]
2019
 
Comparing Convective Self‐Aggregation in Idealized Models to Observed Moist Static Energy Variability Near the Equator
Beucler Tom, Abbott Tristan H., Cronin Timothy W., Pritchard Michael S., 2019/09. Geophysical Research Letters, 46 (17-18) pp. 10589-10598. Peer-reviewed.
[DOI][WoS][serval:BIB_B5F35C660440]
 
Achieving Conservation of Energy in Neural Network Emulators for Climate Modeling
Beucler Tom, 2019/06/15. dans ICML 2019 Workshop. Climate Change: How Can AI Help?.
[DOI][serval:BIB_B08FB90B497B]
 
A budget for the size of convective self‐aggregation
Beucler Tom, Cronin Timothy, 2019/04. Quarterly Journal of the Royal Meteorological Society, 145 (720) pp. 947-966. Peer-reviewed.
[DOI][WoS][serval:BIB_B7F171ECAF12]
2018
 
A Linear Response Framework for Radiative-Convective Instability
Beucler Tom, Cronin Timothy, Emanuel Kerry, 2018/08. Journal of Advances in Modeling Earth Systems, 10 (8) pp. 1924-1951. Peer-reviewed.
[DOI][WoS][serval:BIB_28252BFC8799]
2016
Moisture‐radiative cooling instability
Beucler Tom, Cronin Timothy W., 2016/12. Journal of Advances in Modeling Earth Systems, 8 (4) pp. 1620-1640. Peer-reviewed.
[DOI][WoS][serval:BIB_EC2DA3A2108A]
 
A correlated stochastic model for the large‐scale advection, condensation and diffusion of water vapour
Beucler Tom, 2016/04. Quarterly Journal of the Royal Meteorological Society, 142 (697) pp. 1721-1731. Peer-reviewed.
[DOI][WoS][serval:BIB_CC3F4B34630C]
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