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Journal Articles Science Year : 2016

Using climate models to estimate the quality of global observational data sets

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François Massonnet
Omar Bellprat
  • Function : Author
Francisco J. Doblas-Reyes
  • Function : Author

Abstract

Observational estimates of the climate system are essential to monitoring and understanding ongoing climate change and to assessing the quality of climate models used to produce near- and long-term climate information. This study poses the dual and unconventional question: Can climate models be used to assess the quality of observational references? We show that this question not only rests on solid theoretical grounds but also offers insightful applications in practice. By comparing four observational products of sea surface temperature with a large multimodel climate forecast ensemble, we find compelling evidence that models systematically score better against the most recent, advanced, but also most independent product. These results call for generalized procedures of model-observation comparison and provide guidance for a more objective observational data set selection.

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Dates and versions

insu-03668325 , version 1 (14-05-2022)

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François Massonnet, Omar Bellprat, Virginie Guemas, Francisco J. Doblas-Reyes. Using climate models to estimate the quality of global observational data sets. Science, 2016, 354, pp.452-455. ⟨10.1126/science.aaf6369⟩. ⟨insu-03668325⟩
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