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Introduction. Stochastic physics and climate modelling
Author(s) -
T. N. Palmer,
Paul D. Williams
Publication year - 2008
Publication title -
philosophical transactions of the royal society a mathematical physical and engineering sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.074
H-Index - 169
eISSN - 1471-2962
pISSN - 1364-503X
DOI - 10.1098/rsta.2008.0059
Subject(s) - climate model , climate state , statistical physics , stochastic modelling , scale (ratio) , general circulation model , meteorology , eddy , representation (politics) , atmosphere (unit) , climate change , climatology , environmental science , physics , global warming , mathematics , geology , turbulence , effects of global warming , oceanography , statistics , quantum mechanics , politics , political science , law
Finite computing resources limit the spatial resolution of state-of-the-art global climate simulations to hundreds of kilometres. In neither the atmosphere nor the ocean are small-scale processes such as convection, clouds and ocean eddies properly represented. Climate simulations are known to depend, sometimes quite strongly, on the resulting bulk-formula representation of unresolved processes. Stochastic physics schemes within weather and climate models have the potential to represent the dynamical effects of unresolved scales in ways which conventional bulk-formula representations are incapable of so doing. The application of stochastic physics to climate modelling is a rapidly advancing, important and innovative topic. The latest research findings are gathered together in the Theme Issue for which this paper serves as the introduction.

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