A machine learning model that outperforms conventional global subseasonal forecast models
Author
Abstract
Suggested Citation
DOI: 10.1038/s41467-024-50714-1
Download full text from publisher
References listed on IDEAS
- Soukayna Mouatadid & Paulo Orenstein & Genevieve Flaspohler & Judah Cohen & Miruna Oprescu & Ernest Fraenkel & Lester Mackey, 2023. "Adaptive bias correction for improved subseasonal forecasting," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
- H. Kim & Y. G. Ham & Y. S. Joo & S. W. Son, 2021. "Deep learning for bias correction of MJO prediction," Nature Communications, Nature, vol. 12(1), pages 1-7, December.
- Kaifeng Bi & Lingxi Xie & Hengheng Zhang & Xin Chen & Xiaotao Gu & Qi Tian, 2023. "Author Correction: Accurate medium-range global weather forecasting with 3D neural networks," Nature, Nature, vol. 621(7980), pages 45-45, September.
- Nick Dunstone & Doug M. Smith & Steven C. Hardiman & Paul Davies & Sarah Ineson & Shipra Jain & Chris Kent & Gill Martin & Adam A. Scaife, 2023. "Windows of opportunity for predicting seasonal climate extremes highlighted by the Pakistan floods of 2022," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
- Judah Cohen & Dim Coumou & Jessica Hwang & Lester Mackey & Paulo Orenstein & Sonja Totz & Eli Tziperman, 2019. "S2S reboot: An argument for greater inclusion of machine learning in subseasonal to seasonal forecasts," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 10(2), March.
- Kaifeng Bi & Lingxi Xie & Hengheng Zhang & Xin Chen & Xiaotao Gu & Qi Tian, 2023. "Accurate medium-range global weather forecasting with 3D neural networks," Nature, Nature, vol. 619(7970), pages 533-538, July.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Fabian Dvorak & Regina Stumpf & Sebastian Fehrler & Urs Fischbacher, 2024. "Generative AI Triggers Welfare-Reducing Decisions in Humans," Papers 2401.12773, arXiv.org.
- Hang Gao & Chun Shen & Xuesong Wang & Pak-Wai Chan & Kai-Kwong Hon & Jianbing Li, 2024. "Interpretable semi-supervised clustering enables universal detection and intensity assessment of diverse aviation hazardous winds," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
- Huijun Zhang & Mingjie Zhang & Ran Yi & Yaxin Liu & Qiuzi Han Wen & Xin Meng, 2024. "Growing Importance of Micro-Meteorology in the New Power System: Review, Analysis and Case Study," Energies, MDPI, vol. 17(6), pages 1-33, March.
- Mattia Cavaiola & Federico Cassola & Davide Sacchetti & Francesco Ferrari & Andrea Mazzino, 2024. "Hybrid AI-enhanced lightning flash prediction in the medium-range forecast horizon," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
- Chu, Yinghao & Wang, Yiling & Yang, Dazhi & Chen, Shanlin & Li, Mengying, 2024. "A review of distributed solar forecasting with remote sensing and deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 198(C).
- Florian Achermann & Thomas Stastny & Bogdan Danciu & Andrey Kolobov & Jen Jen Chung & Roland Siegwart & Nicholas Lawrance, 2024. "WindSeer: real-time volumetric wind prediction over complex terrain aboard a small uncrewed aerial vehicle," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
- Zhenjia Chen & Zhenyuan Lin & Ji Yang & Cong Chen & Di Liu & Liuting Shan & Yuanyuan Hu & Tailiang Guo & Huipeng Chen, 2024. "Cross-layer transmission realized by light-emitting memristor for constructing ultra-deep neural network with transfer learning ability," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
- Soukayna Mouatadid & Paulo Orenstein & Genevieve Flaspohler & Judah Cohen & Miruna Oprescu & Ernest Fraenkel & Lester Mackey, 2023. "Adaptive bias correction for improved subseasonal forecasting," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
- Francesco Carlucci & Francesco Fiorito, 2024. "Simulation of Responsive Envelopes in Current and Future Climate Scenarios: A New Interactive Computational Platform for Energy Analyses," Energies, MDPI, vol. 17(21), pages 1-26, October.
- Wang, Tao & Zhou, Hanxu & Fang, Qing & Han, Yanan & Guo, Xingxing & Zhang, Yahui & Qian, Chao & Chen, Hongsheng & Barland, Stéphane & Xiang, Shuiying & Lippi, Gian Luca, 2024. "Reservoir computing-based advance warning of extreme events," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
- Cheng Yang & Jun Jia & Ke He & Liang Xue & Chao Jiang & Shuangyu Liu & Bochao Zhao & Ming Wu & Haoyang Cui, 2023. "Comprehensive Analysis and Evaluation of the Operation and Maintenance of Offshore Wind Power Systems: A Survey," Energies, MDPI, vol. 16(14), pages 1-39, July.
- Fenghua Ling & Jing-Jia Luo & Yue Li & Tao Tang & Lei Bai & Wanli Ouyang & Toshio Yamagata, 2022. "Multi-task machine learning improves multi-seasonal prediction of the Indian Ocean Dipole," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-50714-1. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.