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Stochastic Parameterization: Towards a new view of Weather and Climate Models

Authors :
Berner, Judith
Achatz, Ulrich
Batte, Lauriane
Bengtsson, Lisa
De La Camara, Alvaro
Crommelin, Daan
Christensen, Hannah
Colangeli, Matteo
Dolaptchiev, Stamen
Franzke, Christian L. E.
Friederichs, Petra
Imkeller, Peter
Jarvinen, Heikki
Juricke, Stephan
Kitsios, Vassili
Lott, Franois
Lucarini, Valerio
Mahajan, Salil
Palmer, Timothy N.
Penland, Cecile
Von Storch, Jin-Song
Sakradzija, Mirjana
Weniger, Michael
Weisheimer, Antje
Williams, Paul D.
Yano, Jun-Ichi
Publication Year :
2015

Abstract

The last decade has seen the success of stochastic parameterizations in short-term, medium-range and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to better represent model inadequacy and improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing longstanding climate biases and relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups which show that the stochastic representation of unresolved processes in the atmosphere, oceans, land surface and cryosphere of comprehensive weather and climate models (a) gives rise to more reliable probabilistic forecasts of weather and climate and (b) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics and turbulence is reviewed, its relevance for the climate problem demonstrated, and future research directions outlined.<br />Comment: 26 pages, 15 figures. Final published version

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1510.08682
Document Type :
Working Paper
Full Text :
https://doi.org/10.1175/BAMS-D-15-00268.1