4.4 Article

Present Climate Evaluation and Added Value Analysis of Dynamically Downscaled Simulations of CORDEX-East Asia

期刊

JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY
卷 57, 期 10, 页码 2317-2341

出版社

AMER METEOROLOGICAL SOC
DOI: 10.1175/JAMC-D-18-0008.1

关键词

Asia; Climate models; Ensembles; Model evaluation; performance

资金

  1. National Key Research and Development Program of China [2017YFA0604101]
  2. National Natural Science Foundation of China [41706019]
  3. Youth Innovation Promotion Association of the Chinese Academy of Sciences (CAS)
  4. CAS Interdisciplinary Innovation Team, through the Key Research Program of Frontier Sciences of the CAS
  5. China Postdoctoral Science Foundation [2017T100520]
  6. [2017M612357]

向作者/读者索取更多资源

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 0.44 degrees, 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 30 degrees N. 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.

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