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Over the last three decades, ensemble forecasts have become an integral part of forecasting the weather.
Stochastic latent transformer: Efficient modeling of stochastically forced zonal jets
Ira J. S. Shokar, Rich R. Kerswell, and Peter H. Haynes · 1942
Earlier work this paper cites.
Detection of a 40–50 day oscillation in the zonal wind in the tropical Pacific
Roland A Madden and Paul R Julian · 1971
Earlier work this paper cites.
Distortion representation of forecast errors
Ross N. Hoffman, Zheng Liu, Jean-Francois Louis, and Christopher Grassoti · 1995
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Decomposition of the continuous ranked probability score for ensemble prediction systems
Hans Hersbach · 2000
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An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction
Matthew C Wheeler and Harry H Hendon · 2004
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Roots of ensemble forecasting
John M. Lewis · 2005
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PyTorch distributed: Experiences on accelerating data parallel training, 2020
Shen Li, Yanli Zhao, Rohan Varma, Omkar Salpekar, Pieter Noordhuis, Teng Li, Adam Paszke, Jeff Smith, Brian Vaughan, Pritam Damania, and Soumith Chintala · 2006
Earlier work this paper cites.
Ensemble forecasting
Martin Leutbecher and Tim N Palmer · 2008
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Potential use of an ensemble of analyses in the ECMWF ensemble prediction system
Roberto Buizza, Martin Leutbecher, and Lars Isaksen · 2008
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On the effect of ensemble size on the discrete and continuous ranked probability scores
Christopher A. T. Ferro, David S. Richardson, and Andreas P. Weigel · 2008
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The new vareps-monthly forecasting system: A first step towards seamless prediction
Frédéric Vitart, Roberto Buizza, Magdalena Alonso Balmaseda, Gianpaolo Balsamo, Jean-Raymond Bidlot, Axel Bonet, Manuel Fuentes, Alfred Hofstadler, Franco Molteni, and Tim N. Palmer · 2008
Earlier work this paper cites.
Ensemble of data assimilations at ECMWF
L. Isaksen, M. Bonavita, R. Buizza, M. Fisher, J. Haseler, M. Leutbecher, and L. Raynaud · 2010
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A framework for assessing operational model MJO forecasts: a project of the CLIVAR Madden-Julian Oscillation working group
Jon Gottschalck, M Wheeler, K Weickmann, F Vitart, N Savage, H Lin, H Hendon, D Waliser, K Sperber, C Prestrelo, et al · 2010
Earlier work this paper cites.
Progress and challenges in forecast verification
E. Ebert, L. Wilson, A. Weigel, M. Mittermaier, P. Nurmi, P. Gill, M. Göber, S. Joslyn, B. Brown, T. Fowler, and A. Watkins · 2013
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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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Why should ensemble spread match the RMSE of the ensemble mean?
V. Fortin, M. Abaza, F. Anctil, and R. Turcotte · 2014
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
Earlier work this paper cites.
Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E. Hinton · 2016
Earlier work this paper cites.
Training deep nets with sublinear memory cost
T. Chen, B. Xu, C. Zhang, and C. Guestrin · 2016
Cited alongside, same era.
Stochastic representations of model uncertainties at ECMWF: state of the art and future vision
Martin Leutbecher, Sarah-Jane Lock, Pirkka Ollinaho, Simon T. K. Lang, Gianpaolo Balsamo, Peter Bechtold, Massimo Bonavita, Hannah M. Christensen, Michail Diamantakis, Emanuel Dutra, Stephen English, Michael Fisher, Richard M. Forbes, Jacqueline Goddard, Thomas Haiden, Robin J. Hogan, Stephan Juricke, Heather Lawrence, Dave MacLeod, Linus Magnusson, Sylvie Malardel, Sebastien Massart, Irina Sandu, Piotr K. Smolarkiewicz, Aneesh Subramanian, Frédéric Vitart, Nils Wedi, and Antje Weisheimer · 2017
Cited alongside, same era.
Stochastic parameterization: Toward a new view of weather and climate models
Judith Berner, Ulrich Achatz, Lauriane Batte, Lisa Bengtsson, Alvaro de la Cámara, Hannah M Christensen, Matteo Colangeli, Danielle RB Coleman, Daan Crommelin, Stamen I Dolaptchiev, et al · 2017
Cited alongside, same era.
The new ecmwf interpolation package mir, 2017
P. Maciel, T. Quintino, U. Modigliani, P. Dando, B. Raoult, W. Deconinck, F. Rathgeber, and C. Simarro · 2017
Cited alongside, same era.
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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Accurate medium-range global weather forecasting with 3d neural networks
Kaifeng Bi, Lingxi Xie, Hengheng Zhang, Xin Chen, Xiaotao Gu, and Qi Tian · 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
Later among the works it cites.
FuXi: a cascade machine learning forecasting system for 15-day global weather forecast
Lei Chen, Xiaohui Zhong, Feng Zhang, Yuan Cheng, Yinghui Xu, Yuan Qi, and Hao Li · 2023
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Potential applications of subseasonal-to-seasonal (s2s) predictions
Christopher J. White, Henrik Carlsen, Andrew W. Robertson, Richard J.T. Klein, Jeffrey K. Lazo, Arun Kumar, Frederic Vitart, Erin Coughlan de Perez, Andrea J. Ray, Virginia Murray, Sukaina Bharwani, Dave MacLeod, Rachel James, Lora Fleming, Andrew P. Morse, Bernd Eggen, Richard Graham, Erik Kjellström, Emily Becker, Kathleen V. Pegion, Neil J. Holbrook, Darryn McEvoy, Michael Depledge, Sarah Perkins-Kirkpatrick, Timothy J. Brown, Roger Street, Lindsey Jones, Tomas A. Remenyi, Indi Hodgson-Johnston, Carlo Buontempo, Rob Lamb, Holger Meinke, Berit Arheimer, and Stephen E. Zebiak · 2017
Cited alongside, same era.
Madden—Julian Oscillation prediction and teleconnections in the S2S database
Frédéric Vitart · 2017
Cited alongside, same era.
Mixed precision training, 2018
Paulius Micikevicius, Sharan Narang, Jonah Alben, Gregory Diamos, Erich Elsen, David Garcia, Boris Ginsburg, Michael Houston, Oleksii Kuchaiev, Ganesh Venkatesh, and Hao Wu · 2018
Cited alongside, same era.
The sub-seasonal to seasonal prediction project (s2s) and the prediction of extreme events
Frédéric Vitart and Andrew W. Robertson · 2018
Cited alongside, same era.
A 50-member ensemble of data assimilations
S. T. K. Lang, E. Hólm, M. Bonavita, and Y. Trémolet · 2019
Cited alongside, same era.
Ensemble size: How suboptimal is less than infinity?
Martin Leutbecher · 2019
Cited alongside, same era.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
Cited alongside, same era.
The ERA5 global reanalysis
H. Hersbach, B. Bell, P. Berrisford, et al · 2020
Cited alongside, same era.
Later among the works it cites.
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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IFS upgrade brings many improvements and unifies medium-range resolutions
Simon Lang, Mark Rodwell, and Dinand Schepers · 2023
Later among the works it cites.
Euro-Atlantic weather regimes and their modulation by tropospheric and stratospheric teleconnection pathways in ECMWF reforecasts
Christopher D Roberts, Magdalena A Balmaseda, Laura Ferranti, and Frederic Vitart · 2023
Later among the works it cites.
Dynamical tests of a deep-learning weather prediction model
Gregory J Hakim and Sanjit Masanam · 2024
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An ensemble of data-driven weather prediction models for operational sub-seasonal forecasting
Jonathan A Weyn, Divya Kumar, Jeremy Berman, Najeeb Kazmi, Sylwester Klocek, Pete Luferenko, and Kit Thambiratnam · 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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Enter the ensembles
Simon Lang, Matthew 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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Data-driven ensemble forecasting with the AIFS, 10/2024 2024a
Mihai Alexe, Simon Lang, Mariana Clare, Martin Leutbecher, Christopher Roberts, Linus Magnusson, Matthew Chantry, Rilwan Adewoyin, Ana Prieto-Nemesio, Jesper Dramsch, Florian Pinault, and Baudouin Raoult · 2024
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Probabilistic forecasting with generative networks via scoring rule minimization
Lorenzo Pacchiardi, Rilwan A Adewoyin, Peter Dueben, and Ritabrata Dutta · 2024
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Unbiased evaluation and calibration of ensemble forecast anomalies
Christopher D Roberts and Martin Leutbecher · 2024
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Aardvark weather: end-to-end data-driven weather forecasting
Anna Vaughan, Stratis Markou, Will Tebbutt, James Requeima, Wessel P Bruinsma, Tom R Andersson, Michael Herzog, Nicholas D Lane, Matthew Chantry, J Scott Hosking, et al · 2024
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AI-based data assimilation: Learning the functional of analysis estimation
Jan D Keller and Roland Potthast · 2024
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Generative data assimilation of sparse weather station observations at kilometer scales
Peter Manshausen, Yair Cohen, Jaideep Pathak, Mike Pritchard, Piyush Garg, Morteza Mardani, Karthik Kashinath, Simon Byrne, and Noah Brenowitz · 2024
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An update on AI-DOP: Skilful weather forecasts produced directly from observations
Tony McNally, Christian Lessig, Peter Lean, Eulalie Boucher, Mihai Alexe, Ewan Pinnington, Patrick Laloyaux, Simon Lang, Florian Pinault, Matthew Chantry, Chris Burrows, Ethel Villeneuve, Marcin Chrust, Niels Bormann, and Sean Healy · 2025
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