Machine Learning Methods for Weather Forecasting: A Survey Article Swipe
Huijun Zhang
,
Yaxin Liu
,
Chongyu Zhang
,
Ningyun Li
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/atmos16010082
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/atmos16010082
Weather forecasting, a vital task for agriculture, transportation, energy, etc., has evolved significantly over the years. Comprehensive surveys play a crucial role in synthesizing knowledge, identifying trends, and addressing emerging challenges in this dynamic field. In this survey, we critically examines machine learning (ML)-based weather forecasting methods, which demonstrate exceptional capability in handling complex, high-dimensional datasets and leveraging large volumes of historical and real-time data, enabling the identification of subtle patterns and relationships among weather variables. Research on specific tasks such as global weather forecasting, downscaling, extreme weather prediction, and how to combine machine learning methods with physical principles are very active in the current field. However, several unresolved or challenging issues remain, including the interpretability of models and the ability to predict rare weather events. By identifying these gaps, this research provides a roadmap for advancing machine learning-based weather forecasting techniques to complement and enhance weather prediction results.
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Metadata
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- article
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- en
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- https://doi.org/10.3390/atmos16010082
- OA Status
- gold
- Cited By
- 33
- References
- 162
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https://openalex.org/W4406362609Canonical identifier for this work in OpenAlex
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https://doi.org/10.3390/atmos16010082Digital Object Identifier
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Machine Learning Methods for Weather Forecasting: A SurveyWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-01-14Full publication date if available
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Huijun Zhang, Yaxin Liu, Chongyu Zhang, Ningyun LiList of authors in order
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https://doi.org/10.3390/atmos16010082Publisher landing page
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goldOpen access status per OpenAlex
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https://doi.org/10.3390/atmos16010082Direct OA link when available
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Meteorology, Weather prediction, Weather forecasting, Environmental science, Climatology, Computer science, Geography, GeologyTop concepts (fields/topics) attached by OpenAlex
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33Total citation count in OpenAlex
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2025: 33Per-year citation counts (last 5 years)
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162Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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