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Opportunities and challenges for machine learning in weather and climate modelling: hard, medium and soft AI.
Chantry, Matthew; Christensen, Hannah; Dueben, Peter; Palmer, Tim.
Afiliação
  • Chantry M; Atmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford, UK.
  • Christensen H; Atmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford, UK.
  • Dueben P; European Centre for Medium Range Weather Forecasts, Reading, UK.
  • Palmer T; Atmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford, UK.
Philos Trans A Math Phys Eng Sci ; 379(2194): 20200083, 2021 Apr 05.
Article em En | MEDLINE | ID: mdl-33583261
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'.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article