Title: Present climate evaluation and added value analysis of dynamically downscaled simulations of CORDEX-East Asia
Authors: LI DELEIYIN BAOSHUFENG JIANLONGDOSIO ALESSANDROGEYER BEATEQI JIFENGSHI HONGYUANXU ZHENHUA
Citation: JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY vol. 57 no. 10 p. 2317-2341
Publisher: AMER METEOROLOGICAL SOC
Publication Year: 2018
JRC N°: JRC112928
ISSN: 1558-8424 (online)
URI: https://journals.ametsoc.org/doi/10.1175/JAMC-D-18-0008.1
http://publications.jrc.ec.europa.eu/repository/handle/JRC112928
DOI: 10.1175/JAMC-D-18-0008.1
Type: Articles in periodicals and books
Abstract: In this study, we investigate the skills of the regional climate model Consortium for Small-Scale Modeling in Climate Mode (CCLM) in reproducing historical climatic features and their added value to the driving global climate models (GCMs) of the Coordinated Regional Climate Downscaling Experiment—East Asia (CORDEX-EA) domain. An ensemble of climate simulations, with a resolution of 0.448, was conducted by downscaling four GCMs: CNRM-CM5, EC-EARTH, HadGEM2, and MPI-ESM-LR. The CCLM outputs were compared with different observations and reanalysis datasets. Results showed strong seasonal variability of CCLM’s ability in reproducing climatological means, variability, and extremes. The bias of the simulated summer temperatures is generally smaller than that of the winter temperatures; in addition, areas where CCLM adds value to the driving GCMs in simulating temperature are larger in the winter than in the summer. CCLM outperforms GCMs in terms of generating climatological precipitation means and daily precipitation distributions for most regions in the winter, but this is not always the case for the summer. It was found that CCLM biases are partly inherited from GCMs and are significantly shaped by structural biases of CCLM. Furthermore, downscaled simulations show added value in capturing features of consecutive wet days for the tropics and of consecutive dry days for areas to the north of 308N. We found considerable uncertainty from reanalysis and observation datasets in temperatures and precipitation climatological means for some regions that rival bias values of GCMs and CCLM simulations.We recommend carefully selecting reference datasets when evaluating modeled climate means.
JRC Directorate:Space, Security and Migration

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