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Machine learning-based weather forecasting models have quickly emerged as a promising methodology for accurate medium-range global weather forecasting.
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Strictly proper scoring rules, prediction, and estimation
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A new equitable score suitable for verifying precipitation in numerical weather prediction
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Progress and challenges in forecast verification
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Fair scores for ensemble forecasts
C. A. T. Ferro · 2013
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Increasing the horizontal resolution in numerical weather prediction and climate simulations: illusion or panacea?
N. P. Wedi · 2013
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Deep unsupervised learning using nonequilibrium thermodynamics
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Interaction networks for learning about objects, relations and physics
Peter W. Battaglia, Razvan Pascanu, Matthew Lai, Danilo Rezende, and Koray Kavukcuoglu · 2016
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Training deep nets with sublinear memory cost
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Challenges and design choices for global weather and climate models based on machine learning
Peter D. Dueben and Peter Bauer · 2018
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Paulius Micikevicius, Sharan Narang, Jonah Alben, Gregory Diamos, Erich Elsen, David Garcia, Boris Ginsburg, Michael Houston, Oleksii Kuchaiev, Ganesh Venkatesh, and Hao Wu · 2018
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Generating long sequences with sparse transformers
Rewon Child, Scott Gray, Alec Radford, and Ilya Sutskever · 2019
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Fast graph representation learning with PyTorch Geometric
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
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PyTorch: An imperative style, high-performance deep learning library
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Longformer: The long-document transformer
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The ERA5 global reanalysis
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Shuaiwen Leon Song, Samyam Rajbhandari, and Yuxiong He · 2023
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Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed · 2023
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Learning skillful medium-range global weather forecasting
Remi Lam, Alvaro Sanchez-Gonzalez, Matthew Willson, Peter Wirnsberger, Meire Fortunato, Ferran Alet, Suman Ravuri, Timo Ewalds, Zach Eaton-Rosen, Weihua Hu, Alexander Merose, Stephan Hoyer, George Holland, Oriol Vinyals, Jacklynn Stott, Alexander Pritzel, Shakir Mohamed, and Peter Battaglia · 2023
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IFS upgrade brings many improvements and unifies medium-range resolutions
Simon Lang, Mark Rodwell, and Dinand Schepers · 2023
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More accuracy with less precision
S.T.K. Lang, A. Dawson, M. Diamantakis, P. Dueben, S. Hatfield, M. Leutbecher, et al · 2021
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Masked label prediction: Unified message passing model for semi-supervised classification
Yunsheng Shi, Zhengjie Huang, Shikun Feng, Hui Zhong, Wenjin Wang, and Yu Sun · 2021
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Elucidating the design space of diffusion-based generative models
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
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Forecasting global weather with graph neural networks
R. Keisler · 2022
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T. Kurth, S. Subramanian, P. Harrington, J. Pathak, M. Mardani, D. Hall, A. Miele, K. Kashinath, and A. Anandkumar · 2022
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J. Pathak, S. Subramanian, P. Harrington, S. Raja, A. Chattopadhyay, M. Mardani, T. Kurth, D. Hall, Z. Li, K. Azizzadenesheli, and P. Hassanzadeh · 2022
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Accurate medium-range global weather forecasting with 3D neural networks
K. Bi, L. Xie, H. Zhang, et al · 2023
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Tung Nguyen, Rohan Shah, Hritik Bansal, Troy Arcomano, Sandeep Madireddy, Romit Maulik, Veerabhadra Kotamarthi, Ian Foster, and Aditya Grover · 2023
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GenCast: Diffusion-based ensemble forecasting for medium-range weather
Ilan Price, Alvaro Sanchez-Gonzalez, Ferran Alet, Timo Ewalds, Andrew El-Kadi, Jacklynn Stott, Shakir Mohamed, Peter Battaglia, Remi Lam, and Matthew Willson · 2023
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The rise of data-driven weather forecasting: A first statistical assessment of machine learning-based weather forecasts in an operational-like context
Zied Ben Bouallègue, Mariana C A Clare, Linus Magnusson, Estibaliz Gascón, Michael Maier-Gerber, Martin Janoušek, Mark Rodwell, Florian Pinault, Jesper S Dramsch, Simon T K Lang, Baudouin Raoult, Florence Rabier, Matthieu Chevallier, Irina Sandu, Peter Dueben, Matthew Chantry, and Florian Pappenberger · 2024
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A new ml model in the ecmwf web charts, 2024
Zied Ben Bouallègue, Rilwan Adewoyin, Mihai Alexe, Matthew Chantry, Mariana Clare, Jesper Dramsch, Sara Hahner, Simon Lang, Christian Lessig, Linus Magnusson, Michael Maier-Gerber, Gert Mertes, Gabriel Moldovan, Ana Prieto Nemesio, Cathal O’Brien, Florian Pinault, Baudouin Raoult, Mario Santa Cruz, Helen Theissen, and Steffen Tietsche · 2024
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It’s rain(ing) data
M. Chantry, Rilwan Adewoyin, Mihai Alexe, Zied Ben Bouallègue, Mariana Clare, Jesper Dramsch, Sara Hahner, Simon Lang, Christian Lessig, Linus Magnusson, Michael Maier-Gerber, Gert Mertes, Gabriel Moldovan, Ana Prieto Nemesio, Cathal O’Brien, Florian Pinault, Baudouin Raoult, Mario Santa Cruz, Helen Theissen, and Steffen Tietsche · 2024
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Do ai models produce better weather forecasts than physics-based models? a quantitative evaluation case study of storm ciarán
A.J. Charlton-Perez, H.F. Dacre, S. Driscoll, et al · 2024
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Neural general circulation models for weather and climate
Dmitrii Kochkov, Janni Yuval, Ian Langmore, Peter Norgaard, Jamie Smith, Griffin Mooers, Milan Klöwer, James Lottes, Stephan Rasp, Peter Düben, Sam Hatfield, Peter Battaglia, Alvaro Sanchez-Gonzalez, Matthew Willson, Michael P. Brenner, and Stephan Hoyer · 2024
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AIFS: A new ECMWF forecasting system
S. Lang, M. Alexe, M. Chantry, J. Dramsch, F. Pinault, B. Raoult, Z. Ben Bouallegue, M. Clare, C. Lessig, L. Magnusson, and A. Prieto Nemesio · 2024
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Red sky at night… Producing weather forecasts directly from observations
Tony McNally, Christian Lessig, Peter Lean, Matthew Chantry, Mihai Alexe, and Simon Lang · 2024
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Data-driven regional modelling
T. Nipen, M. Chantry, and et al · 2024
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Probabilistic forecasting with generative networks via scoring rule minimization
Lorenzo Pacchiardi, Rilwan Adewoyin, Peter Dueben, and Ritabrata Dutta · 2024
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