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  Rethinking the default construction of multi-model climate ensembles

Rauser, F., Gleckler, P., & Marotzke, J. (2015). Rethinking the default construction of multi-model climate ensembles. Bulletin of the American Meteorological Society, 96, 911-919. doi:10.1175/BAMS-D-13-00181.1.

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 Creators:
Rauser, Florian1, Author           
Gleckler, Peter, Author
Marotzke, Jochem2, Author                 
Affiliations:
1Director’s Research Group AES, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society, Bundesstraße 53, 20146 Hamburg, DE, ou_913570              
2Director’s Research Group OES, The Ocean in the Earth System, MPI for Meteorology, Max Planck Society, Bundesstraße 53, 20146 Hamburg, DE, ou_913553              

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 Abstract: We discuss the current code of practice in the climate sciences to routinely create climate model ensembles as ensembles of opportunity from the newest phase of the Coupled Model Intercomparison Project (CMIP). We give a two-step argument to rethink this process. First, the differences between generations of ensembles corresponding to different CMIP phases in key climate quantities are not large enough to warrant an automatic separation into generational ensembles for CMIP3 and CMIP5. Second, we suggest that climate model ensembles cannot continue to be mere ensembles of opportunity but should always be based on a transparent scientific decision process. If ensembles can be constrained by observation, then they should be constructed as target ensembles that are specifically tailored to a physical question. If model ensembles cannot be constrained by observation, then they should be constructed as cross-generational ensembles, including all available model data to enhance structural model diversity and to better sample the underlying uncertainties. To facilitate this, CMIP should guide the necessarily ongoing process of updating experimental protocols for the evaluation and documentation of coupled models. With an emphasis on easy access to model data and facilitating the filtering of climate model data across all CMIP generations and experiments, our community could return to the underlying idea of using model data ensembles to improve uncertainty quantification, evaluation, and cross-institutional exchange.

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Language(s): eng - English
 Dates: 2014-1220152015-06
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1175/BAMS-D-13-00181.1
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Title: Bulletin of the American Meteorological Society
Source Genre: Journal
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Publ. Info: American Meteorological Society
Pages: - Volume / Issue: 96 Sequence Number: - Start / End Page: 911 - 919 Identifier: ISSN: 0003-0007
CoNE: https://pure.mpg.de/cone/journals/resource/954925377920