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Utility of Ten-Day Climate Model Ensemble Simulations for Water Resources Applications in Korean Watersheds
Authors:Email author" target="_blank">Konstantine?P?GeorgakakosEmail author  Deg-Hyo?Bae  Chang-Sam?Jeong
Affiliation:(1) Hydrologic Research Center, 12780 High Bluff Drive, Suite 250, San Diego, California, 92130, U.S.A.;(2) Department of Civil and Environment Engineering, Sejong University, 98 Gunja-Dong, Gwangjin-Gu, Seoul, 143-747, Republic of Korea;(3) Department of Civil Engineering, Yonsei University, 134 Shinchon, Seodaemun-Gu, Seoul, 120-749, Republic of Korea
Abstract:We demonstrate the use of a quantitative measure of the effectiveness of using climate model simulations of surface precipitation and temperature for water resources applications involving extremes of watershed average precipitation and temperature, and watershed discharge. This diagnostic measure is considered in association with the use of climate information to condition ensemble seasonal predictions of watershed variables. Seven watersheds in the Korean peninsula constitute the application sites. The climate model effectiveness is expressed by a utility index EP that measures the ability of the climate model simulations of an indicator variable (i.e., nodal precipitation or temperature) to discriminate observed distributions of the highs and lows of a watershed target variable (i.e., mean areal precipitation and temperature as well as outlet discharge). Monte Carlo simulations provide estimates of the significance of the Ep values. For apparently the first time, ten-member ensemble simulations of daily surface precipitation and temperature from the Korean Meteorological Agency climate model are used to evaluate the climate-model utility index EP for a temporal interval of 10 days for each application watershed. The results show that, in spite of the high uncertainty of climate simulations, there are several Korean watersheds that can benefit from the use of climate model simulations of high temporal resolution for planning and management studies that involve precipitation, temperature and discharge. In particular, seasonal ensemble prediction of watershed variables stands to gain from conditioning on high-temporal resolution climate forecasts.
Keywords:climate prediction  uncertainty analysis  water resource planning and management
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