Methods and resources for climate impacts research
The prediction of climate variability and change requires the use of a range of simulation models. Multiple climate model simulations are needed to sample the inherent uncertainties in seasonal to centennial prediction. Because climate models are computationally expensive, there is a tradeoff betwee...
| Main Authors: | , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
American Meteorological Society
2009
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/25161 |
| _version_ | 1855538977834008576 |
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| author | Challinor, Andrew J. Osborne, Tom M. Shaffrey, Len Weller, Hilary Morse, Andy Wheeler, Tim Vidale, Pier Luigi |
| author_browse | Challinor, Andrew J. Morse, Andy Osborne, Tom M. Shaffrey, Len Vidale, Pier Luigi Weller, Hilary Wheeler, Tim |
| author_facet | Challinor, Andrew J. Osborne, Tom M. Shaffrey, Len Weller, Hilary Morse, Andy Wheeler, Tim Vidale, Pier Luigi |
| author_sort | Challinor, Andrew J. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | The prediction of climate variability and change requires the use of a range of simulation models. Multiple climate model simulations are needed to sample the inherent uncertainties in seasonal to centennial prediction. Because climate models are computationally expensive, there is a tradeoff between complexity, spatial resolution, simulation length, and ensemble size. The methods used to assess climate impacts are examined in the context of this trade-off. An emphasis on complexity allows simulation of coupled mechanisms, such as the carbon cycle and feedbacks between agricultural land management and climate. In addition to improving skill, greater spatial resolution increases relevance to regional planning. Greater ensemble size improves the sampling of probabilities. Research from major international projects is used to show the importance of synergistic research efforts.
The primary climate impact examined is crop yield, although many of the issues discussed are relevant to hydrology and health modeling. Methods used to bridge the scale gap between climate and crop models are reviewed. Recent advances include large-area crop modeling, quantification of uncertainty in crop yield, and fully integrated crop–climate modeling. The implications of trends in computer power, including supercomputers, are also discussed. |
| format | Journal Article |
| id | CGSpace25161 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2009 |
| publishDateRange | 2009 |
| publishDateSort | 2009 |
| publisher | American Meteorological Society |
| publisherStr | American Meteorological Society |
| record_format | dspace |
| spelling | CGSpace251612024-05-01T08:19:30Z Methods and resources for climate impacts research Challinor, Andrew J. Osborne, Tom M. Shaffrey, Len Weller, Hilary Morse, Andy Wheeler, Tim Vidale, Pier Luigi climate models agriculture The prediction of climate variability and change requires the use of a range of simulation models. Multiple climate model simulations are needed to sample the inherent uncertainties in seasonal to centennial prediction. Because climate models are computationally expensive, there is a tradeoff between complexity, spatial resolution, simulation length, and ensemble size. The methods used to assess climate impacts are examined in the context of this trade-off. An emphasis on complexity allows simulation of coupled mechanisms, such as the carbon cycle and feedbacks between agricultural land management and climate. In addition to improving skill, greater spatial resolution increases relevance to regional planning. Greater ensemble size improves the sampling of probabilities. Research from major international projects is used to show the importance of synergistic research efforts. The primary climate impact examined is crop yield, although many of the issues discussed are relevant to hydrology and health modeling. Methods used to bridge the scale gap between climate and crop models are reviewed. Recent advances include large-area crop modeling, quantification of uncertainty in crop yield, and fully integrated crop–climate modeling. The implications of trends in computer power, including supercomputers, are also discussed. 2009-06 2013-02-05T09:37:55Z 2013-02-05T09:37:55Z Journal Article https://hdl.handle.net/10568/25161 en Open Access application/pdf American Meteorological Society Challinor AJ, Osborne T, Shaffrey L, Weller H, Morse A, Wheeler T, Vidale PL. 2009. Methods and resources for climate impacts research. Bulletin of the American Meteorological Society 90: 836-848. |
| spellingShingle | climate models agriculture Challinor, Andrew J. Osborne, Tom M. Shaffrey, Len Weller, Hilary Morse, Andy Wheeler, Tim Vidale, Pier Luigi Methods and resources for climate impacts research |
| title | Methods and resources for climate impacts research |
| title_full | Methods and resources for climate impacts research |
| title_fullStr | Methods and resources for climate impacts research |
| title_full_unstemmed | Methods and resources for climate impacts research |
| title_short | Methods and resources for climate impacts research |
| title_sort | methods and resources for climate impacts research |
| topic | climate models agriculture |
| url | https://hdl.handle.net/10568/25161 |
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