Assessing the regional variability of GCM simulations
While General Circulation Models (GCM) generally converge well at the global level, results for individual regions usually show a wide range of variation. This study assesses the performance of seventeen GCMs regarding their simulation of temperature and precipitation based on hindcasts for the peri...
| Autores principales: | , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
American Geophysical Union
2009
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| Acceso en línea: | https://hdl.handle.net/10568/21526 |
| _version_ | 1855529963530223616 |
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| author | Xueliang Cai Wang, D. Zhu, T. Ringler, Claudia |
| author_browse | Ringler, Claudia Wang, D. Xueliang Cai Zhu, T. |
| author_facet | Xueliang Cai Wang, D. Zhu, T. Ringler, Claudia |
| author_sort | Xueliang Cai |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | While General Circulation Models (GCM) generally converge well at the global level, results for individual regions usually show a wide range of variation. This study assesses the performance of seventeen GCMs regarding their simulation of temperature and precipitation based on hindcasts for the periods of 1961–1990 and 1931–1960. Skill scores are plotted on a 2° × 2° grid to present “zones” of GCM performance. An overlay of these skill score maps with global climate zones, land cover, and elevation maps shows correlations between GCM performance and the distribution of these geographic variables. No GCM is superior in predicting temperature or precipitation for the whole world, although some GCMs score better in particular regions. For researchers working with GCM results and policymakers who need to make decisions based on GCM projections, the skill score maps may provide useful guidance; while for GCM developers, the skill score maps may open areas for further study to improve their models. |
| format | Journal Article |
| id | CGSpace21526 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2009 |
| publishDateRange | 2009 |
| publishDateSort | 2009 |
| publisher | American Geophysical Union |
| publisherStr | American Geophysical Union |
| record_format | dspace |
| spelling | CGSpace215262025-12-08T09:54:28Z Assessing the regional variability of GCM simulations Xueliang Cai Wang, D. Zhu, T. Ringler, Claudia While General Circulation Models (GCM) generally converge well at the global level, results for individual regions usually show a wide range of variation. This study assesses the performance of seventeen GCMs regarding their simulation of temperature and precipitation based on hindcasts for the periods of 1961–1990 and 1931–1960. Skill scores are plotted on a 2° × 2° grid to present “zones” of GCM performance. An overlay of these skill score maps with global climate zones, land cover, and elevation maps shows correlations between GCM performance and the distribution of these geographic variables. No GCM is superior in predicting temperature or precipitation for the whole world, although some GCMs score better in particular regions. For researchers working with GCM results and policymakers who need to make decisions based on GCM projections, the skill score maps may provide useful guidance; while for GCM developers, the skill score maps may open areas for further study to improve their models. 2009-01 2012-08-02T12:58:55Z 2012-08-02T12:58:55Z Journal Article https://hdl.handle.net/10568/21526 en Open Access American Geophysical Union Cai, X., Wang, D., Zhu, T. and Ringler, C. 2009. Assessing the regional variability of GCM simulations Geophys. Res. Lett. 36(2): 6p. doi:https://doi.org/10.1029/2008gl036443 |
| spellingShingle | Xueliang Cai Wang, D. Zhu, T. Ringler, Claudia Assessing the regional variability of GCM simulations |
| title | Assessing the regional variability of GCM simulations |
| title_full | Assessing the regional variability of GCM simulations |
| title_fullStr | Assessing the regional variability of GCM simulations |
| title_full_unstemmed | Assessing the regional variability of GCM simulations |
| title_short | Assessing the regional variability of GCM simulations |
| title_sort | assessing the regional variability of gcm simulations |
| url | https://hdl.handle.net/10568/21526 |
| work_keys_str_mv | AT xueliangcai assessingtheregionalvariabilityofgcmsimulations AT wangd assessingtheregionalvariabilityofgcmsimulations AT zhut assessingtheregionalvariabilityofgcmsimulations AT ringlerclaudia assessingtheregionalvariabilityofgcmsimulations |