Downscaling Global Circulation Model Projections of Climate Change for the United Arab Emirates
Publication: Journal of Water Resources Planning and Management
Volume 141, Issue 9
Abstract
Future projection of air temperature and precipitation due to climate change plays an important role in shaping the water resources management plans in arid and semi-arid countries such as the United Arab Emirates (UAE). The effect of local topography, land use, and sea-land contrasts are generally dwarfed in the coarse global circulation models [ocean atmosphere global climate models (OAGCMs)] results. Statistical downscaling (SD) is a statistical tool relating OAGCM outputs (predictors) to finer local observed weather data (predictands) to improve future predictions. SD is used in this study to downscale the Hadley Model (HadCM3) predictors using local observations at two stations representing the dominating bioclimatic zones in the UAE. The paper proposes a rigorous and systematic methodology to guide the selection of dominant predictors in the projection scenarios. The proposed methodology is applied for the UAE but can be easily adopted for any other area. The calibrated model, used to project future scenarios in the region, revealed a range of increase of the annual mean maximum temperature of 2.79–3.80°C and a range of reduction of annual precipitation of 16.80–37.00% by 2080 at the considered stations. Impacts of climate change on the UAE’s water resources management are discussed in light of the downscaled estimates for temperature and precipitation. Because a major portion of the water resources is devoted to agriculture, temperature impacts are quite significant. However, the impacts of precipitation are hardly detectable at the national scale. Instead, the impacts of reduced precipitation will be of more localized significance in mountainous regions that are critically dependent on precipitation for water resources.
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Acknowledgments
Acknowledgment is extended to Abu Dhabi and Sharjah Aviation Authorities for providing data used in this study.
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Journal of Water Resources Planning and Management
Volume 141 • Issue 9 • September 2015
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Jun 17, 2013
Accepted: Dec 3, 2014
Published online: Jan 28, 2015
Discussion open until: Jun 28, 2015
Published in print: Sep 1, 2015
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