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DOI10.3390/atmos13020180
Machine Learning in Weather Prediction and Climate Analyses-Applications and Perspectives
Bochenek, Bogdan; Ustrnul, Zbigniew
发表日期2022
EISSN2073-4433
卷号13期号:2
英文摘要In this paper, we performed an analysis of the 500 most relevant scientific articles published since 2018, concerning machine learning methods in the field of climate and numerical weather prediction using the Google Scholar search engine. The most common topics of interest in the abstracts were identified, and some of them examined in detail: in numerical weather prediction research-photovoltaic and wind energy, atmospheric physics and processes; in climate research-parametrizations, extreme events, and climate change. With the created database, it was also possible to extract the most commonly examined meteorological fields (wind, precipitation, temperature, pressure, and radiation), methods (Deep Learning, Random Forest, Artificial Neural Networks, Support Vector Machine, and XGBoost), and countries (China, USA, Australia, India, and Germany) in these topics. Performing critical reviews of the literature, authors are trying to predict the future research direction of these fields, with the main conclusion being that machine learning methods will be a key feature in future weather forecasting.
英文关键词machine learning; weather; numerical weather prediction; climate
语种英语
WOS研究方向Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS类目Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号WOS:000763879500001
来源期刊ATMOSPHERE
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/280527
作者单位Institute of Meteorology & Water Management; Jagiellonian University
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Bochenek, Bogdan,Ustrnul, Zbigniew. Machine Learning in Weather Prediction and Climate Analyses-Applications and Perspectives[J],2022,13(2).
APA Bochenek, Bogdan,&Ustrnul, Zbigniew.(2022).Machine Learning in Weather Prediction and Climate Analyses-Applications and Perspectives.ATMOSPHERE,13(2).
MLA Bochenek, Bogdan,et al."Machine Learning in Weather Prediction and Climate Analyses-Applications and Perspectives".ATMOSPHERE 13.2(2022).
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