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자료유형
학술저널
저자정보
저널정보
한국기상학회 Asia-Pacific Journal of Atmospheric Sciences Asia-Pacific Journal of Atmospheric Sciences Vol.44 No.4
발행연도
2008.11
수록면
325 - 339 (15page)

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This paper investigates the ability of a regional climate model to provide the characteristics of East Asian summer monsoon (EASM) using the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM). To this end, the RSM with newly-developed physical processes is applied to the 25 summers (June, July, and August) from 1979 to 2003. The initial atmospheric conditions and lateral boundary data used in this study are from the NCEP reanalysis data. The RSM can reproduce large scale features associated with the EASM, including the subtropical high, midlatitude trough, and low-level jet in terms of the 25-year seasonal mean climate. However, a discernible bias has been identified in the model which causes estimations of an enhanced southerly low level jet and an intensified subtropical high over land. The warm bias leads to a high estimation for precipitation over land. The overestimation of precipitation and surface temperature over land occur regardless of geographical position, but the model underestimates these values over the ocean. When ocean areas are included, the 25-year summer mean biases of the simulated surface temperature and daily precipitation rate are about 0.4 K and 0.5 mm day<SUB>-1</SUB>, respectively. The interannual variations in precipitation show good agreement with the CMAP data over the South, Central China, and Mongolia. Furthermore, the interannual variations in the flow patterns are also well simulated. The anomaly values of surface temperature, geopotential height, and wind over the 25-year mean, which have distinct interannual variability, are also fairly well reproduced, as are the intraseasonal variations in the simulated climatology in terms of precipitation and large-scale features.

목차

Abstract
1. Introduction
2. Model and Experimental Design
3. Twenty-five year summer simulation
4. Interannual and intraseasonal variability
5. Summary and concluding remarks
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