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Taking climate model evaluation to the next level

Authors :
Ronald J. Stouffer
William D. Collins
Mark S. Williamson
Joellen L. Russell
Angeline G. Pendergrass
Bettina K. Gier
Gerald A. Meehl
Robert Pincus
Alex C. Ruane
Veronika Eyring
Peter M. Caldwell
Gregory M. Flato
Peter M. Cox
Benjamin D. Santer
George C. Hurtt
Isla R. Simpson
Steven C. Sherwood
Alexandra Jahn
Lester Kwiatkowski
Eric D. Maloney
Peter J. Gleckler
Stephen A. Klein
Chris D. Jones
Ruth Lorenz
Alex Hall
Benjamin M. Sanderson
Forrest M. Hoffman
John P. Krasting
Gab Abramowitz
Source :
Nature Climate Change, Nature Climate Change, vol 9, iss 2, Nature Climate Change, 9 (2)
Publication Year :
2019
Publisher :
Springer Science and Business Media LLC, 2019.

Abstract

Earth system models are complex and represent a large number of processes, resulting in a persistent spread across climate projections for a given future scenario. Owing to different model performances against observations and the lack of independence among models, there is now evidence that giving equal weight to each available model projection is suboptimal. This Perspective discusses newly developed tools that facilitate a more rapid and comprehensive evaluation of model simulations with observations, process-based emergent constraints that are a promising way to focus evaluation on the observations most relevant to climate projections, and advanced methods for model weighting. These approaches are needed to distil the most credible information on regional climate changes, impacts, and risks for stakeholders and policy-makers. ISSN:1758-6798

Details

ISSN :
17586798 and 1758678X
Volume :
9
Database :
OpenAIRE
Journal :
Nature Climate Change
Accession number :
edsair.doi.dedup.....fc28c959de1b43caa2ad239103dd5e2b
Full Text :
https://doi.org/10.1038/s41558-018-0355-y