Evaluation of multiple regional climate models for summer climate extremes over East Asia

In this study, five regional climate models (RCMs) participating in the CORDEX-East Asia project (HadGEM3-RA, RegCM4, SNU-MM5, SNU-WRF, and YSU-RSM) are evaluated in terms of their performances in simulating the climatology of summer extremes in East Asia. Seasonal maxima of daily mean temperature a...

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Veröffentlicht in:Climate dynamics 2016-04, Vol.46 (7-8), p.2469-2486
Hauptverfasser: Park, Changyong, Min, Seung-Ki, Lee, Donghyun, Cha, Dong-Hyun, Suh, Myoung-Seok, Kang, Hyun-Suk, Hong, Song-You, Lee, Dong-Kyou, Baek, Hee-Jeong, Boo, Kyung-On, Kwon, Won-Tae
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container_end_page 2486
container_issue 7-8
container_start_page 2469
container_title Climate dynamics
container_volume 46
creator Park, Changyong
Min, Seung-Ki
Lee, Donghyun
Cha, Dong-Hyun
Suh, Myoung-Seok
Kang, Hyun-Suk
Hong, Song-You
Lee, Dong-Kyou
Baek, Hee-Jeong
Boo, Kyung-On
Kwon, Won-Tae
description In this study, five regional climate models (RCMs) participating in the CORDEX-East Asia project (HadGEM3-RA, RegCM4, SNU-MM5, SNU-WRF, and YSU-RSM) are evaluated in terms of their performances in simulating the climatology of summer extremes in East Asia. Seasonal maxima of daily mean temperature and precipitation are analyzed using the generalized extreme value method. RCMs show systematic bias patterns in both seasonal means and extremes. A cold bias is located along the coast, whereas a warm bias occurs in northern China. Overall, wet bias occurs in East Asia, but with a substantial dry bias centered in South Korea. This dry bias appears to be related to the colder ocean surface around South Korea, positioning the monsoonal front further south compared to observations. Taylor diagram analyses reveal that the models simulate temperature means more accurately compared to extremes because of the higher spatial correlation, whereas precipitation extremes are simulated better than their means because of the higher spatial variability. The latter implies that extreme rainfall events can be captured more accurately by RCMs compared to the driving GCM despite poorer simulation of mean rainfall. Inter-RCM analysis indicates a close relationship between the means and extremes in terms of model skills, but it does not show a clear relationship between temperature and precipitation. Sub-regional analysis largely supports the mean–extreme skill relationship. Analyses of frequency and intensity distributions of daily data for three selected sub-regions suggest that overall shifts of temperature distribution and biases in moderate–heavy precipitations contribute importantly to the seasonal mean biases.
doi_str_mv 10.1007/s00382-015-2713-z
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Seasonal maxima of daily mean temperature and precipitation are analyzed using the generalized extreme value method. RCMs show systematic bias patterns in both seasonal means and extremes. A cold bias is located along the coast, whereas a warm bias occurs in northern China. Overall, wet bias occurs in East Asia, but with a substantial dry bias centered in South Korea. This dry bias appears to be related to the colder ocean surface around South Korea, positioning the monsoonal front further south compared to observations. Taylor diagram analyses reveal that the models simulate temperature means more accurately compared to extremes because of the higher spatial correlation, whereas precipitation extremes are simulated better than their means because of the higher spatial variability. The latter implies that extreme rainfall events can be captured more accurately by RCMs compared to the driving GCM despite poorer simulation of mean rainfall. 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Seasonal maxima of daily mean temperature and precipitation are analyzed using the generalized extreme value method. RCMs show systematic bias patterns in both seasonal means and extremes. A cold bias is located along the coast, whereas a warm bias occurs in northern China. Overall, wet bias occurs in East Asia, but with a substantial dry bias centered in South Korea. This dry bias appears to be related to the colder ocean surface around South Korea, positioning the monsoonal front further south compared to observations. Taylor diagram analyses reveal that the models simulate temperature means more accurately compared to extremes because of the higher spatial correlation, whereas precipitation extremes are simulated better than their means because of the higher spatial variability. The latter implies that extreme rainfall events can be captured more accurately by RCMs compared to the driving GCM despite poorer simulation of mean rainfall. 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subjects Analysis
Atmospheric models
Climate change
Climate models
Climatology
Earth and Environmental Science
Earth Sciences
Extreme weather
Geophysics/Geodesy
Marine
Oceanography
Precipitation
Regional analysis
Regional planning
Summer
Temperature
Temperature distribution
title Evaluation of multiple regional climate models for summer climate extremes over East Asia
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