| Deep learning to represent subgrid processes in climate models S Rasp, MS Pritchard, P Gentine Proceedings of the national academy of sciences 115 (39), 9684-9689, 2018 | 878 | 2018 |
| WeatherBench: a benchmark data set for data‐driven weather forecasting S Rasp, PD Dueben, S Scher, JA Weyn, S Mouatadid, N Thuerey Journal of Advances in Modeling Earth Systems 12 (11), e2020MS002203, 2020 | 503 | 2020 |
| Could machine learning break the convection parameterization deadlock? P Gentine, M Pritchard, S Rasp, G Reinaudi, G Yacalis Geophysical Research Letters 45 (11), 5742-5751, 2018 | 482 | 2018 |
| Neural networks for postprocessing ensemble weather forecasts S Rasp, S Lerch Monthly Weather Review 146 (11), 3885-3900, 2018 | 457 | 2018 |
| Enforcing analytic constraints in neural networks emulating physical systems T Beucler, M Pritchard, S Rasp, J Ott, P Baldi, P Gentine Physical Review Letters 126 (9), 098302, 2021 | 319 | 2021 |
| Data‐driven medium‐range weather prediction with a resnet pretrained on climate simulations: A new model for weatherbench S Rasp, N Thuerey Journal of Advances in Modeling Earth Systems 13 (2), e2020MS002405, 2021 | 231 | 2021 |
| Coupled online learning as a way to tackle instabilities and biases in neural network parameterizations: General algorithms and Lorenz 96 case study (v1. 0) S Rasp Geoscientific Model Development 13 (5), 2185-2196, 2020 | 116 | 2020 |
| Neural general circulation models for weather and climate D Kochkov, J Yuval, I Langmore, P Norgaard, J Smith, G Mooers, ... Nature 632 (8027), 1060-1066, 2024 | 94 | 2024 |
| WeatherBench 2: A benchmark for the next generation of data‐driven global weather models S Rasp, S Hoyer, A Merose, I Langmore, P Battaglia, T Russell, ... Journal of Advances in Modeling Earth Systems 16 (6), e2023MS004019, 2024 | 93 | 2024 |
| Achieving conservation of energy in neural network emulators for climate modeling T Beucler, S Rasp, M Pritchard, P Gentine arXiv preprint arXiv:1906.06622, 2019 | 87 | 2019 |
| Potential and limitations of machine learning for modeling warm‐rain cloud microphysical processes A Seifert, S Rasp Journal of Advances in Modeling Earth Systems, e2020MS002301, 2020 | 84 | 2020 |
| Combining crowdsourcing and deep learning to explore the mesoscale organization of shallow convection S Rasp, H Schulz, S Bony, B Stevens Bulletin of the American Meteorological Society 101 (11), E1980-E1995, 2020 | 80 | 2020 |
| Increasing the accuracy and resolution of precipitation forecasts using deep generative models I Price, S Rasp International conference on artificial intelligence and statistics, 10555-10571, 2022 | 66 | 2022 |
| Climate-invariant machine learning T Beucler, P Gentine, J Yuval, A Gupta, L Peng, J Lin, S Yu, S Rasp, ... Science Advances 10 (6), eadj7250, 2024 | 61 | 2024 |
| Relative contribution of soil moisture, boundary‐layer and microphysical perturbations on convective predictability in different weather regimes C Keil, F Baur, K Bachmann, S Rasp, L Schneider, C Barthlott Quarterly Journal of the Royal Meteorological Society 145 (724), 3102-3115, 2019 | 58 | 2019 |
| Neural general circulation models D Kochkov, J Yuval, I Langmore, P Norgaard, JA Smith, G Mooers, ... CoRR, 2023 | 50 | 2023 |
| Stochastic parameterization of processes leading to convective initiation in kilometer-scale models M Hirt, S Rasp, U Blahak, GC Craig Monthly Weather Review 147 (11), 3917-3934, 2019 | 47 | 2019 |
| Towards physically-consistent, data-driven models of convection T Beucler, M Pritchard, P Gentine, S Rasp Igarss 2020-2020 ieee international geoscience and remote sensing symposium …, 2020 | 46 | 2020 |
| Machine learning for clouds and climate T Beucler, I Ebert‐Uphoff, S Rasp, M Pritchard, P Gentine Clouds and their climatic impacts: Radiation, circulation, and precipitation …, 2023 | 44 | 2023 |
| Variability and clustering of midlatitude summertime convection: Testing the Craig and Cohen theory in a convection-permitting ensemble with stochastic boundary layer perturbations S Rasp, T Selz, GC Craig Journal of the Atmospheric Sciences 75 (2), 691-706, 2018 | 44 | 2018 |
Michael S. PritchardAssociate Professor of Earth System Science, University of California IrvineEmail verificata su uci.edu
