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Methods and resources for climate impacts research: achieving synergy

Challinor, A., Osborne, T. M., Morse, A., Shaffrey, L. C. ORCID: https://orcid.org/0000-0003-2696-752X, Wheeler, T. R., Weller, H. ORCID: https://orcid.org/0000-0003-4553-7082 and Vidale, P. L. ORCID: https://orcid.org/0000-0002-1800-8460 (2009) Methods and resources for climate impacts research: achieving synergy. Bulletin of the American Meteorological Society, 90 (6). pp. 836-848. ISSN 1520-0477

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To link to this item DOI: 10.1175/2008BAMS2403.1

Abstract/Summary

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.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > NCAS
Life Sciences > School of Agriculture, Policy and Development
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:1775
Publisher:American Meteorological Society

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