Climate forecast data (Nino3.4 SST, Arctic sea ice extent) and observational references, link to files in Rdata format
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| Auteurs principaux: | , , , |
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| Format: | Dataset Open Access |
| Langue: | en |
| Publié: |
PANGAEA
2016
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| _version_ | 1867170993041047552 |
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| author | Massonnet, François Bellprat, Omar Guemas, Virginie Doblas-Reyes, Francisco J |
| author_facet | Massonnet, François Bellprat, Omar Guemas, Virginie Doblas-Reyes, Francisco J |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | 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. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_864680 |
| institution | PANGAEA |
| language | en |
| publishDate | 2016 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Climate forecast data (Nino3.4 SST, Arctic sea ice extent) and observational references, link to files in Rdata format Massonnet, François Bellprat, Omar Guemas, Virginie Doblas-Reyes, Francisco J arctic-Pacific 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. |
| title | Climate forecast data (Nino3.4 SST, Arctic sea ice extent) and observational references, link to files in Rdata format |
| topic | arctic-Pacific |
| url | https://doi.org/10.1594/PANGAEA.864680 |