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Data-driven weather forecast based on machine learning (ML) has experienced rapid development and demonstrated superior performance in the global medium-range forecast compared to traditional physics-based dynamical models.
A closer look at the optimization landscapes of generative adversarial networks
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Temperature changes in the mid-and high-latitudes of the Southern Hemisphere
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Interpretation of rank histograms for verifying ensemble forecasts
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The maximum value distribution in a reverberation chamber
Wellander, N.; Lundén, O.; and Backstrom, M. 2001 · 2001
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Detecting region outliers in meteorological data
Zhao, J.; Lu, C.-T.; and Kou, Y. 2003 · 2003
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Weather forecasting with ensemble methods
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General maximum likelihood empirical Bayes estimation of normal means
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Minimum sample size determination for generalized extreme value distribution
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Extremal dependence indices: Improved verification measures for deterministic forecasts of rare binary events
Ferro, C. A.; and Stephenson, D. B. 2011 · 2011
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On the estimation of hyperparameters for empirical bayes estimators: Maximum marginal likelihood vs minimum MSE
Aravkin, A.; Burke, J. V.; Chiuso, A.; and Pillonetto, G. 2012 · 2012
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Evidence linking Arctic amplification to extreme weather in mid-latitudes
Francis, J. A.; and Vavrus, S. J. 2012 · 2012
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A unified view of performance metrics: Translating threshold choice into expected classification loss
Hernández-Orallo, J.; Flach, P.; and Ferri Ramírez, C. 2012 · 2012
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Attribution of extreme weather and climate events overestimated by unreliable climate simulations
Bellprat, O.; and Doblas-Reyes, F. 2016 · 2016
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Attention is all you need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; and Polosukhin, I. 2017 · 2017
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Generative adversarial networks: An overview
Creswell, A.; White, T.; Dumoulin, V.; Arulkumaran, K.; Sengupta, B.; and Bharath, A. A. 2018 · 2018
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Multi-task learning using uncertainty to weigh losses for scene geometry and semantics
Kendall, A.; Gal, Y.; and Cipolla, R. 2018 · 2018
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Regional forecasting of wind speeds during typhoon landfall in Taiwan: A case study of westward-moving typhoons
Wei, C.-C.; Peng, P.-C.; Tsai, C.-H.; and Huang, C.-L. 2018 · 2018
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Better and faster: Exponential loss for image patch matching
Machine learning approaches to extreme weather events forecast in urban areas: Challenges and initial results
Porto, F.; Ferro, M.; Ogasawara, E.; Moeda, T.; de Barros, C. D. T.; Silva, A. C.; Zorrilla, R.; Pereira, R. S.; Castro, R. N.; Silva, J. V.; et al. 2022 · 2022
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Interaction of Cloud Dynamics and Microphysics During the Rapid Intensification of Super-Typhoon Nanmadol (2022) Based on Multi-Satellite Observations
Wu, Z.; Zhang, Y.; Zhang, L.; and Zheng, H. 2023 · 2022
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Algorithmic hallucinations of near-surface winds: Statistical downscaling with generative adversarial networks to convection-permitting scales
Annau, N. J.; Cannon, A. J.; and Monahan, A. H. 2023 · 2023
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The rise of data-driven weather forecasting
Ben-Bouallegue, Z.; Clare, M. C.; Magnusson, L.; Gascon, E.; Maier-Gerber, M.; Janousek, M.; Rodwell, M.; Pinault, F.; Dramsch, J. S.; Lang, S. T.; et al. 2023 · 2023
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Wang, S.; Li, Y.; Liang, X.; Quan, D.; Yang, B.; Wei, S.; and Jiao, L. 2019 · 2019
Cited alongside, same era.
Using numerical weather model outputs to forecast wind gusts during typhoons
Yang, T.-H.; and Tsai, C.-C. 2019 · 2019
Cited alongside, same era.
Denoising diffusion probabilistic models
Ho, J.; Jain, A.; and Abbeel, P. 2020 · 2020
Cited alongside, same era.
WeatherBench: a benchmark data set for data-driven weather forecasting
Rasp, S.; Dueben, P. D.; Scher, S.; Weyn, J. A.; Mouatadid, S.; and Thuerey, N. 2020 · 2020
Cited alongside, same era.
Survey on the application of deep learning in extreme weather prediction
Fang, W.; Xue, Q.; Shen, L.; and Sheng, V. S. 2021 · 2021
Cited alongside, same era.
Adaptive fourier neural operators: Efficient token mixers for transformers
Guibas, J.; Mardani, M.; Li, Z.; Tao, A.; Anandkumar, A.; and Catanzaro, B. 2021 · 2021
Cited alongside, same era.
Evaluating precipitation, streamflow, and inundation forecasting skills during extreme weather events: A case study for an urban watershed
Li, X.; Rankin, C.; Gangrade, S.; Zhao, G.; Lander, K.; Voisin, N.; Shao, M.; Morales-Hernández, M.; Kao, S.-C.; and Gao, H. 2021 · 2021
Cited alongside, same era.
Accurate medium-range global weather forecasting with 3D neural networks
Bi, K.; Xie, L.; Zhang, H.; Chen, X.; Gu, X.; and Tian, Q. 2023 · 2023
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Machine learning for numerical weather and climate modelling: a review
de Burgh-Day, C. O.; and Leeuwenburg, T. 2023 · 2023
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Fourcastnet: Accelerating global high-resolution weather forecasting using adaptive fourier neural operators
Kurth, T.; Subramanian, S.; Harrington, P.; Pathak, J.; Mardani, M.; Hall, D.; Miele, A.; Kashinath, K.; and Anandkumar, A. 2023 · 2023
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Learning skillful medium-range global weather forecasting
Lam, R.; Sanchez-Gonzalez, A.; Willson, M.; Wirnsberger, P.; Fortunato, M.; Alet, F.; Ravuri, S.; Ewalds, T.; Eaton-Rosen, Z.; Hu, W.; et al. 2023 · 2023
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Global extreme heat forecasting using neural weather models
Lopez-Gomez, I.; McGovern, A.; Agrawal, S.; and Hickey, J. 2023 · 2023
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CMIP X-MOS: Improving Climate Models with Extreme Model Output Statistics
Morozov, V.; Galliamov, A.; Lukashevich, A.; Kurdukova, A.; and Maximov, Y. 2023 · 2023
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Kunyu: A High-Performing Global Weather Model Beyond Regression Losses
Ni, Z. 2023 · 2023
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GenCast: Diffusion-based ensemble forecasting for medium-range weather
Price, I.; Sanchez-Gonzalez, A.; Alet, F.; Ewalds, T.; El-Kadi, A.; Stott, J.; Mohamed, S.; Battaglia, P.; Lam, R.; and Willson, M. 2023 · 2023
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Diffusion models: A comprehensive survey of methods and applications
Yang, L.; Zhang, Z.; Song, Y.; Hong, S.; Xu, R.; Zhao, Y.; Zhang, W.; Cui, B.; and Yang, M.-H. 2023 · 2023
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FuXi-Extreme: Improving extreme rainfall and wind forecasts with diffusion model
Zhong, X.; Chen, L.; Liu, J.; Lin, C.; Qi, Y.; and Li, H. 2023 · 2023
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CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling
Gong, J.; Bai, L.; Ye, P.; Xu, W.; Liu, N.; Dai, J.; Yang, X.; and Ouyang, W. 2024 · 2024
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Han, T.; Guo, S.; Xu, W.; Bai, L.; et al. 2024 · 2024
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The ERA5 global reanalysis
Hersbach, H.; Bell, B.; Berrisford, P.; Hirahara, S.; Horányi, A.; Muñoz-Sabater, J.; Nicolas, J.; Peubey, C.; Radu, R.; Schepers, D.; et al. 2020 · 2049
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