Taking climate model evaluation to the next level

Veronika Eyring (1) , Peter M. Cox (2) , Gregory M. Flato (3) , Peter J. Gleckler (4) , Gab Abramowitz (5) , Peter Caldwell (4) , William D. Collins (6, 7) , Bettina K. Gier (1, 8) , Alex D. Hall (9) , Forrest M. Hoffman (10, 11) , George C. Hurtt (12) , Alexandra Jahn (13) , Chris D. Jones (14) , Stephen A. Klein (4) , John P. Krasting (15) , Lester Kwiatkowski (16) , Ruth Lorenz , Eric Maloney , Gerald A. Meehl , Angeline G. Pendergrass , Robert Pincus , Alex C. Ruane , Joellen L. Russell , Benjamin M. Sanderson , Benjamin D. Santer , Steven C. Sherwood , Isla R. Simpson , Ronald J. Stouffer , Mark S. Williamson

1 IPA - DLR Institut für Physik der Atmosphäre
2 EMPS - College of Engineering, Mathematics and Physical Sciences [Exeter]
3 CCCma - Canadian Centre for Climate Modelling and Analysis
4 Program for Climate Model Diagnosis and Intercomparison
5 CCRC - Climate Change Research Centre [Sydney]
6 Climate and Ecosystem Sciences Division
7 EPS - Department of Earth and Planetary Science [UC Berkeley]
8 IUP - Institute of Environmental Physics [Bremen]
9 UC - University of California
10 ORNL - Oak Ridge National Laboratory [Oak Ridge]
11 Department of Civil and Environmental Engineering [Knoxville]
12 Department of Geographical Sciences [College Park]
13 Department of Atmospheric and Oceanic Sciences and Institute of Arctic and Alpine Research
14 MOHC - Met Office Hadley Centre for Climate Change
15 GFDL - NOAA Geophysical Fluid Dynamics Laboratory
16 LMD - Laboratoire de Météorologie Dynamique (UMR 8539)

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.

Domains: Sciences of the Universe [physics]

Veronika Eyring, Peter M. Cox, Gregory M. Flato, Peter J. Gleckler, Gab Abramowitz, et al.. Taking climate model evaluation to the next level. Nature Climate Change, 2019, 9, pp.102-110. ⟨10.1038/s41558-018-0355-y⟩. ⟨insu-03727027⟩