Machine Learning in Weather Prediction and Climate Analyses—Applications and Perspectives

Published in

Atmosphere(2022)

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TL;DR

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 concluded that machineLearning methods will be a key feature in future weather forecasting.

Abstract

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.

Authors

B. Bochenek

1 papers

Z. Ustrnul

1 papers

References114 items

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Climate-invariant machine learning

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A GPU-Accelerated Radiation Transfer Model Using the Lattice Boltzmann Method

Machine Learning in Weather Prediction and Climate Analyses—Applications and Perspectives

Published in

Atmosphere(2022)

External Links:

Generate Graph DownloadPDF

TL;DR

Abstract

Authors

B. Bochenek

1 papers

Z. Ustrnul

1 papers

References114 items

Machine Learning Algorithms: A Review

Climate-invariant machine learning

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Journal Information

Name

Atmosphere

Venue Information

Name

Atmosphere

Type

journal

URL

http://www.e-helvetica.nb.admin.ch/directAccess?callnumber=bel-187315

Alternate Names

ATMOSPHERE