Evaluating the Utility of IPCC AR4 GCMs for Hydrological Application in South Korea

Thanh Le and Deg-Hyo Bae ()

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2013, vol. 27, issue 9, 3227-3246

Abstract: Understanding the uncertainty of climate models in space and time is necessary to help water resources managers and hydrologists in the selection of appropriate model for a specific application. In this paper, we use three separate methods to evaluate and compare the utility of 14 climate models for seven basins with area range of 2,656–26,355 km 2 on the South Korean Peninsula. On the one hand, the method of probabilistic uncertainty analysis is used to evaluate the capability of the studied General Circulation Models (GCMs) in recognizing the extreme events. On the other hand, we use two statistical tests (correlation coefficient and root mean square error) to examine the capability of the GCMs in simulating quantitatively each event. The results show that, for the first method, the performance of climate model varies depending on the number of climate model nodes used for a specific application of given basin, especially for monthly time scale. In addition, we find that, there are several GCMs showing good results for the probabilistic uncertainty test but poor results for the statistical test and conversely. Therefore, climate models should be evaluated for specific applications and specific regions. The results indicated quite clearly that, it is not easy to select an optimal climate model which can satisfy both applications using precipitation and temperature projections. However, the results of this study suggest that, there are several GCMs which are more useful than the others for general hydrological application in South Korean peninsula. Copyright Springer Science+Business Media Dordrecht 2013

Keywords: Extreme events; Correlation coefficient; Root mean square error; Comparisons; Overall effectiveness (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/s11269-013-0338-8

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