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SNURCM을 이용한 CORDEX-동아시아 실험에서 동아시아 기온 모의에 대한 수평해상도의 영향

Impact of Horizontal Resolution on Near-surface Air Temperature over East Asia simulated in CORDEX-East Asia Experiments using SNURCM

이민규|김가영|김태형|박창용|차동현|신석우
기후연구소 (KU Climate Research Institute)|2022.03|기후연구 (Journal of Climate Research)|제17권 제1호|pp. 35-52|DOI 10.14383/cri.2022.17.1.35

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키워드

평가evaluationSNURCMCORDEX-동아시아 2단계수평해상도지상기온CORDEX-East Asia Phase IIhorizontal resolutionnear-surface air temperature

초록

In this study, regional climate simulation using the Seoul National University Regional Climate Model (SNURCM) forced by ERA-Interim was conducted under the evaluation framework of the CORDEX-East Asia (EA) Phase II. The near-surface air temperature (SAT) of the SNURCM2 (25-km horizontal resolution in CORDEXEA Phase II) over the East Asian region for 20 years (1989-2008) was analyzed compared to that of SNURCM1 (50km horizontal resolution in CORDEX-EA Phase II). According to our results, SNURCM1 and 2 reproduced the spatial distribution of temperature reasonably, displaying high spatial and temporal correlations with observation data. However, both SNURCM1 and 2 tended to have cold biases in the annual average (ANN) and winter (DJF) season, particularly in Manchuria, and to do warm biases in summer (JJA) season. The systematic biases in SNURCM2 were notably improved by reducing cold biases in SNURCM1 as well as the results in annual cycles and interannual variations through statistical summaries. In the composite map analysis of extreme years selected from observation data, we confirmed that the degree of cold biases in DJF of the extreme cold years over Manchuria was significantly large, and this was more reduced in SNURCM2 compared to SNURCM1. In environment field analysis, temperature advections related to the main wind (ANN and DJF: north wind, JJA: south wind) affected DJF cold (JJA warm) biases of the model. Throughout the analyses, SNURCM2 showed better accuracy than SNURCM1. Furthermore, we confirmed that the reduced warm biases of SNURCM2 over SCC in JJA compared to SNURCM1 were related to the cooling effect by increased precipitation. However, further analyses focusing on radiation, land surface model, and diurnal cycle associated with SAT may be needed to understand systematic biases and to improve model accuracy.

Abstract

In this study, regional climate simulation using the Seoul National University Regional Climate Model (SNURCM) forced by ERA-Interim was conducted under the evaluation framework of the CORDEX-East Asia (EA) Phase II. The near-surface air temperature (SAT) of the SNURCM2 (25-km horizontal resolution in CORDEXEA Phase II) over the East Asian region for 20 years (1989-2008) was analyzed compared to that of SNURCM1 (50km horizontal resolution in CORDEX-EA Phase II). According to our results, SNURCM1 and 2 reproduced the spatial distribution of temperature reasonably, displaying high spatial and temporal correlations with observation data. However, both SNURCM1 and 2 tended to have cold biases in the annual average (ANN) and winter (DJF) season, particularly in Manchuria, and to do warm biases in summer (JJA) season. The systematic biases in SNURCM2 were notably improved by reducing cold biases in SNURCM1 as well as the results in annual cycles and interannual variations through statistical summaries. In the composite map analysis of extreme years selected from observation data, we confirmed that the degree of cold biases in DJF of the extreme cold years over Manchuria was significantly large, and this was more reduced in SNURCM2 compared to SNURCM1. In environment field analysis, temperature advections related to the main wind (ANN and DJF: north wind, JJA: south wind) affected DJF cold (JJA warm) biases of the model. Throughout the analyses, SNURCM2 showed better accuracy than SNURCM1. Furthermore, we confirmed that the reduced warm biases of SNURCM2 over SCC in JJA compared to SNURCM1 were related to the cooling effect by increased precipitation. However, further analyses focusing on radiation, land surface model, and diurnal cycle associated with SAT may be needed to understand systematic biases and to improve model accuracy.

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