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Is the strong future warming found in several next-generation #CMIP6 climate models realistic? We apply weights based on the models’ historical performance and independence to find out.
Our study is now published in @EGU_ESD
https://doi.org/10.5194/esd-11-995-2020
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Our study is now published in @EGU_ESD
https://doi.org/10.5194/esd-11-995-2020
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We calculate distributions of change in different variables, like the Transient Climate Response (a comparable measure for how much a model warms due to CO2 
). Weighting can considerably shift these distributions and increase their skill.
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). Weighting can considerably shift these distributions and increase their skill. 2/
We find the multi-model distributions of Transient Climate Response as well as future warming to be shifted downward by applying the combined performance-independence weights. Decisive climate action is still needed but the most extreme warming might be less realistic. 
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Our results hold for both, the low emission pathway SSP1-2.6 as well as the high emission pathway SSP5-8.5 and during the entire 21st century. 
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A large effect comes from several high-warming models (orange labels) receiving systematically lower weights.
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What about independence of information (when calculating statistics)? Some climate models are "related" due to, e.g., shared components. We identify them based on their output, cluster them in a #CMIP6 family tree 
, and account for the dependence.
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, and account for the dependence. 6/
Evaluation of the method: since there are no observations from the future we use all the last-generation #CMIP5 models as pseudo observations. Median skill increases for all cases by 12-22%! 
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We also provide additional information such as weights and warming per model in the supplement to our study. 
https://doi.org/10.5194/esd-11-995-2020-supplement
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https://doi.org/10.5194/esd-11-995-2020-supplement
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Bonus: The Climate model Weighting by Independence and Performance (ClimWIP) method is freely available on @github:
https://github.com/lukasbrunner/ClimWIP
And now also within the @ESMValTool:
https://docs.esmvaltool.org/en/latest/recipes/recipe_climwip.html
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https://github.com/lukasbrunner/ClimWIP
And now also within the @ESMValTool:
https://docs.esmvaltool.org/en/latest/recipes/recipe_climwip.html
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Thanks a lot to all the collaborators in this project! 
@apuffycloud @ClimateFlavors @AnnaMerrifield1 Ruth Lorenz and @Knutti_ETH
Thanks also to @EU_H2020 for funding @EUCP_H2020 & @CRESCENDO_H2020 and to all the data and software providers!
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@apuffycloud @ClimateFlavors @AnnaMerrifield1 Ruth Lorenz and @Knutti_ETHThanks also to @EU_H2020 for funding @EUCP_H2020 & @CRESCENDO_H2020 and to all the data and software providers!
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