Regional quantile delta mapping method using regional frequency analysis for regional climate model precipitation

2020 ◽  
pp. 125685
Author(s):  
Sunghun Kim ◽  
Kyungwon Joo ◽  
Hanbeen Kim ◽  
Ju-Young Shin ◽  
Jun-Haeng Heo
SOLA ◽  
2016 ◽  
Vol 12 (0) ◽  
pp. 165-169 ◽  
Author(s):  
Masaya Nosaka ◽  
Hidetaka Sasaki ◽  
Akihiko Murata ◽  
Hiroaki Kawase ◽  
Mitsuo Oh'izumi

2019 ◽  
Vol 124 (24) ◽  
pp. 14220-14239 ◽  
Author(s):  
Daniel Bannister ◽  
Andrew Orr ◽  
Sanjay K. Jain ◽  
Ian P. Holman ◽  
Andrea Momblanch ◽  
...  

2013 ◽  
Vol 57 (3) ◽  
pp. 173-186 ◽  
Author(s):  
X Wang ◽  
M Yang ◽  
G Wan ◽  
X Chen ◽  
G Pang

2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.


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