Literature DB >> 33583261

Opportunities and challenges for machine learning in weather and climate modelling: hard, medium and soft AI.

Matthew Chantry1, Hannah Christensen1, Peter Dueben2, Tim Palmer1.   

Abstract

In September 2019, a workshop was held to highlight the growing area of applying machine learning techniques to improve weather and climate prediction. In this introductory piece, we outline the motivations, opportunities and challenges ahead in this exciting avenue of research. This article is part of the theme issue 'Machine learning for weather and climate modelling'.

Keywords:  climate modelling; machine learning; weather prediction

Year:  2021        PMID: 33583261     DOI: 10.1098/rsta.2020.0083

Source DB:  PubMed          Journal:  Philos Trans A Math Phys Eng Sci        ISSN: 1364-503X            Impact factor:   4.226


  2 in total

1.  Densely Connected Neural Networks for Nonlinear Regression.

Authors:  Chao Jiang; Canchen Jiang; Dongwei Chen; Fei Hu
Journal:  Entropy (Basel)       Date:  2022-06-25       Impact factor: 2.738

2.  Sensitivity of Air Pollution Exposure and Disease Burden to Emission Changes in China Using Machine Learning Emulation.

Authors:  Luke Conibear; Carly L Reddington; Ben J Silver; Ying Chen; Christoph Knote; Stephen R Arnold; Dominick V Spracklen
Journal:  Geohealth       Date:  2022-06-01
  2 in total

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