A climate model projection weighting scheme accounting for performance and interdependence

Uncertainties of climate projections are routinely assessed by considering simulations from different models. Observations are used to evaluate models, yet there is a debate about whether and how to explicitly weight model projections by agreement with observations. Here we present a straightforward...

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Bibliographic Details
Published in:Geophysical Research Letters
Main Authors: Knutti, Reto, Sedláček, Jan, Sanderson, Benjamin M., Lorenz, Ruth, Fischer, Erich M., Eyring, Veronika
Format: Article in Journal/Newspaper
Language:German
Published: Wiley 2017
Subjects:
Online Access:https://elib.dlr.de/114948/
https://elib.dlr.de/114948/1/Knutti_Eyring-et_al-2017-Geophysical_Research_Letters.pdf
https://doi.org/10.1002/2016GL072012
Description
Summary:Uncertainties of climate projections are routinely assessed by considering simulations from different models. Observations are used to evaluate models, yet there is a debate about whether and how to explicitly weight model projections by agreement with observations. Here we present a straightforward weighting scheme that accounts both for the large differences in model performance and for model interdependencies, and we test reliability in a perfect model setup. We provide weighted multimodel projections of Arctic sea ice and temperature as a case study to demonstrate that, for some questions at least, it is meaningless to treat all models equally. The constrained ensemble shows reduced spread and a more rapid sea ice decline than the unweighted ensemble. We argue that the growing number of models with different characteristics and considerable interdependence finally justifies abandoning strict model democracy, and we provide guidance on when and how this can be achieved robustly.