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Deep learning to represent sub-grid processes in climate models

12 June 2018

Papers citing "Deep learning to represent sub-grid processes in climate models"

50 / 152 papers shown

Title
Emulating Aerosol Microphysics with Machine Learning P. Harder D. Watson‐Parris Dominik Strassel N. Gauger P. Stier J. Keuper 107 6 0 22 Sep 2021
Combining data assimilation and machine learning to estimate parameters of a convective-scale modelQuarterly Journal of the Royal Meteorological Society (QJRMS), 2021 Stefanie Legler T. Janjić 121 20 0 07 Sep 2021
Combining machine learning and data assimilation to forecast dynamical systems from noisy partial observationsChaos (Chaos), 2021 Georg Gottwald Sebastian Reich AI4CE 174 40 0 08 Aug 2021
Quantum Artificial Intelligence for the Science of Climate Change Manmeet Singh C. Dhara Adarsh Kumar S. Gill Steve Uhlig AI4CE 167 17 0 28 Jul 2021
A comparison of combined data assimilation and machine learning methods for offline and online model error correctionJournal of Computer Science (JCS), 2021 A. Farchi Marc Bocquet P. Laloyaux Massimo Bonavita Quentin Malartic OffRL 189 45 0 23 Jul 2021
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equationsAdvances in Computational Mathematics (Adv. Comput. Math.), 2021 Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 133 284 0 16 Jul 2021
Batch Inverse-Variance Weighting: Deep Heteroscedastic Regression Vincent Mai Waleed D. Khamies Liam Paull NoLa BDL 106 3 0 09 Jul 2021
Deep learning for improved global precipitation in numerical weather prediction systems Manmeet Singh B. Kumar Suryachandra A. Rao S. Gill R. Chattopadhyay R. Nanjundiah D. Niyogi AI4Cl 104 16 0 20 Jun 2021
PCE-PINNs: Physics-Informed Neural Networks for Uncertainty Propagation in Ocean Modeling Björn Lütjens Catherine H. Crawford Mark S. Veillette Dava Newman 144 11 0 05 May 2021
Bridging observation, theory and numerical simulation of the ocean using Machine LearningEnvironmental Research Letters (ERL), 2021 Maike Sonnewald Redouane Lguensat Daniel C. Jones P. Dueben J. Brajard Venkatramani Balaji AI4Cl AI4CE 196 115 0 26 Apr 2021
Mosaic Flows: A Transferable Deep Learning Framework for Solving PDEs on Unseen DomainsComputer Methods in Applied Mechanics and Engineering (CMAME), 2021 Hengjie Wang R. Planas Aparna Chandramowlishwaran Ramin Bostanabad AI4CE 244 68 0 22 Apr 2021
Controlled abstention neural networks for identifying skillful predictions for regression problemsJournal of Advances in Modeling Earth Systems (JAMES), 2021 E. Barnes R. Barnes 158 28 0 16 Apr 2021
Using Machine Learning at Scale in HPC Simulations with SmartSim: An Application to Ocean Climate Modeling Sam Partee M. Ellis Alessandro Rigazzi S. Bachman Gustavo M. Marques Andrew Shao Benjamin Robbins AI4Cl AI4CE 93 21 0 13 Apr 2021
Machine Learning Emulation of 3D Cloud Radiative EffectsJournal of Advances in Modeling Earth Systems (JAMES), 2021 David Meyer R. Hogan P. Dueben Shannon L. Mason 144 31 0 22 Mar 2021
Data-driven geophysical forecasting: Simple, low-cost, and accurate baselines with kernel methodsProceedings of the Royal Society A (Proc. R. Soc. A), 2021 B. Hamzi R. Maulik H. Owhadi AI4TS 177 30 0 13 Feb 2021
Urban Change Detection by Fully Convolutional Siamese Concatenate Network with Attention Farnoosh Heidary M. Yazdi M. Dehghani P. Setoodeh 85 3 0 31 Jan 2021
Will Artificial Intelligence supersede Earth System and Climate Models?Nature Machine Intelligence (Nat. Mach. Intell.), 2021 C. Irrgang Niklas Boers Maike Sonnewald E. Barnes C. Kadow J. Staneva J. Saynisch‐Wagner AI4Cl AI4CE 180 214 0 22 Jan 2021
Copula-based synthetic data augmentation for machine-learning emulatorsGeoscientific Model Development (GMD), 2020 David Meyer T. Nagler R. Hogan 108 27 0 16 Dec 2020
Forecasting: theory and practiceInternational Journal of Forecasting (IJF), 2020 F. Petropoulos D. Apiletti Vassilios Assimakopoulos M. Z. Babai Devon K. Barrow ... J. Arenas Xiaoqian Wang R. L. Winkler Alisa Yusupova F. Ziel AI4TS 291 437 0 04 Dec 2020
Machine-Learned Preconditioners for Linear Solvers in Geophysical Fluid Flows Jan Ackmann P. Düben T. Palmer P. Smolarkiewicz AI4Cl AI4CE 124 23 0 06 Oct 2020
Combining data assimilation and machine learning to infer unresolved scale parametrisation J. Brajard A. Carrassi Marc Bocquet Laurent Bertino 237 130 0 09 Sep 2020
TRU-NET: A Deep Learning Approach to High Resolution Prediction of Rainfall Rilwan A. Adewoyin P. Dueben P. Watson Yulan He Ritabrata Dutta AI4CE 96 75 0 20 Aug 2020
Climbing down Charney's ladder: Machine Learning and the post-Dennard era of computational climate science Venkatramani Balaji AI4CE 196 54 0 24 May 2020
Deep Learning for Post-Processing Ensemble Weather Forecasts Peter Grönquist Chengyuan Yao Tal Ben-Nun Nikoli Dryden P. Dueben Shigang Li Torsten Hoefler 155 177 0 18 May 2020
Sherpa: Robust Hyperparameter Optimization for Machine Learning L. Hertel Julian Collado Peter Sadowski J. Ott Pierre Baldi 151 112 0 08 May 2020
A Fortran-Keras Deep Learning Bridge for Scientific ComputingScientific Programming (SP), 2020 J. Ott M. Pritchard Natalie Best Erik J. Linstead M. Curcic Pierre Baldi AI4CE 147 104 0 14 Apr 2020
Resampling with neural networks for stochastic parameterization in multiscale systems D. Crommelin W. Edeling AI4CE 96 14 0 03 Apr 2020
Improving data-driven global weather prediction using deep convolutional neural networks on a cubed sphereJournal of Advances in Modeling Earth Systems (JAMES), 2020 Jonathan A. Weyn Dale Durran R. Caruana AI4Cl 94 302 0 15 Mar 2020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental SystemsACM Computing Surveys (ACM CSUR), 2020 J. Willard X. Jia Shaoming Xu M. Steinbach Vipin Kumar AI4CE 376 488 0 10 Mar 2020
Data-driven super-parameterization using deep learning: Experimentation with multi-scale Lorenz 96 systems and transfer-learningJournal of Advances in Modeling Earth Systems (JAMES), 2020 Ashesh Chattopadhyay Adam Subel Pedram Hassanzadeh BDL AI4CE 127 60 0 25 Feb 2020
Towards Physically-consistent, Data-driven Models of ConvectionIEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2020 Tom Beucler Michael S. Pritchard Pierre Gentine S. Rasp AI4CE 148 33 0 20 Feb 2020
WeatherBench: A benchmark dataset for data-driven weather forecastingJournal of Advances in Modeling Earth Systems (JAMES), 2020 S. Rasp P. Dueben S. Scher Jonathan A. Weyn Soukayna Mouatadid Nils Thuerey AI4Cl AI4TS 426 547 0 02 Feb 2020
Using Machine Learning for Model Physics: an Overview V. Krasnopolsky Aleksei A. Belochitski PINN AI4CE 151 10 0 02 Feb 2020
Where Are We? Using Scopus to Map the Literature at the Intersection Between Artificial Intelligence and Research on CrimeJournal of Computational Social Science (JCSS), 2019 G. Campedelli 112 27 0 23 Dec 2019
Physically Interpretable Neural Networks for the Geosciences: Applications to Earth System VariabilityJournal of Advances in Modeling Earth Systems (JAMES), 2019 B. Toms E. Barnes I. Ebert‐Uphoff AI4CE 184 234 0 04 Dec 2019
AI Ethics for Systemic Issues: A Structural Approach A. Loeff I. Bassi S. Kapila Jevgenij Gamper 67 8 0 08 Nov 2019
Learning Everywhere: A Taxonomy for the Integration of Machine Learning and SimulationseScience (eScience), 2019 Geoffrey C. Fox S. Jha AI4CE 144 13 0 29 Sep 2019
Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz '96 ModelJournal of Advances in Modeling Earth Systems (JAMES), 2019 D. Gagne H. Christensen A. Subramanian A. Monahan AI4CE BDL 211 151 0 10 Sep 2019
Understanding ML driven HPC: Applications and InfrastructureeScience (eScience), 2019 Geoffrey C. Fox S. Jha 74 14 0 05 Sep 2019
Analog forecasting of extreme-causing weather patterns using deep learningJournal of Advances in Modeling Earth Systems (JAMES), 2019 Ashesh Chattopadhyay Ebrahim Nabizadeh Pedram Hassanzadeh 173 160 0 26 Jul 2019
Data-driven prediction of a multi-scale Lorenz 96 chaotic system using deep learning methods: Reservoir computing, ANN, and RNN-LSTM Ashesh Chattopadhyay Pedram Hassanzadeh D. Subramanian AI4CE 217 41 0 20 Jun 2019
Achieving Conservation of Energy in Neural Network Emulators for Climate Modeling Tom Beucler S. Rasp Michael S. Pritchard Pierre Gentine 97 87 0 15 Jun 2019
Tackling Climate Change with Machine LearningACM Computing Surveys (ACM CSUR), 2019 David Rolnick P. Donti L. Kaack K. Kochanski Alexandre Lacoste ... Demis Hassabis John C. Platt F. Creutzig J. Chayes Yoshua Bengio AI4Cl AI4CE 278 923 0 10 Jun 2019
Combining crowd-sourcing and deep learning to explore the meso-scale organization of shallow convectionBulletin of The American Meteorological Society - (BAMS) (BAMS), 2019 S. Rasp H. Schulz S. Bony B. Stevens 188 59 0 05 Jun 2019
Stratospheric Aerosol Injection as a Deep Reinforcement Learning Problem Christian Schroeder de Witt Thomas Hornigold AI4CE 74 8 0 17 May 2019
Enforcing Statistical Constraints in Generative Adversarial Networks for Modeling Chaotic Dynamical SystemsJournal of Computational Physics (JCP), 2019 Jin-Long Wu K. Kashinath A. Albert D. Chirila P. Prabhat Heng Xiao AI4CE 147 142 0 13 May 2019
Visualizing the Consequences of Climate Change Using Cycle-Consistent Adversarial Networks Victor Schmidt A. Luccioni S. Mukkavilli Narmada M. Balasooriya Kris Sankaran J. Chayes Yoshua Bengio GAN 89 40 0 02 May 2019
Applying machine learning to improve simulations of a chaotic dynamical system using empirical error correction P. Watson AI4Cl AI4CE 87 69 0 24 Apr 2019
Representing ill-known parts of a numerical model using a machine learning approach J. Brajard A. Charantonis J. Sirven 41 3 0 18 Mar 2019
Learning Everywhere: Pervasive Machine Learning for Effective High-Performance ComputationIEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPS), 2019 Geoffrey C. Fox J. Glazier J. Kadupitiya V. Jadhao Minje Kim ... Madhav V. Marathe Abhijin Adiga Jiangzhuo Chen O. Beckstein S. Jha 108 57 0 27 Feb 2019