Asia-Pacific Journal of Atmospheric Sciences

, Volume 52, Issue 2, pp 107–127

Evaluation of regional climate simulations over the CORDEX-EA-II domain using the COSMO-CLM model

  • Weidan Zhou
  • Jianping Tang
  • Xueyuan Wang
  • Shuyu Wang
  • Xiaorui Niu
  • Yuan Wang
Article

DOI: 10.1007/s13143-016-0013-0

Cite this article as:
Zhou, W., Tang, J., Wang, X. et al. Asia-Pacific J Atmos Sci (2016) 52: 107. doi:10.1007/s13143-016-0013-0
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Abstract

The COSMO-CLM (CCLM) model is applied to perform regional climate simulation over the second phase of CORDEX-East Asia (CORDEX-EA-II) domain in this study. Driven by the ERAInterim reanalysis data, the model was integrated from 1988 to 2010 with a high resolution of 0.22°. The model’s ability to reproduce mean climatology and climatic extremes is evaluated based on various aspects. The CCLM model is capable of capturing the basic features of the East Asia climate, including the seasonal mean patterns, interannual variations, annual cycles and climate extreme indices for both surface air temperature and precipitation. Some biases are evident in certain areas and seasons. Warm and wet biases appear in the arid and semi-arid areas over the northwestern and northern parts of the domain. The simulated climate over the Tibetan Plateau is colder and wetter than the observations, while South China, East China, and India are drier. The model biases may be caused by the simulated anticyclonic and cyclonic biases in low-level circulations, the simulated water vapor content biases, and the inadequate physical parameterizations in the CCLM model. A parallel 0.44° simulation is conducted and the comparison results show some added value introduced by the higher resolution 0.22° simulation. As a result, the CCLM model could be an adequate member for the next stage of the CORDEX-EA project, while further studies should be encouraged.

Key words

Regional climate modeling Model evaluation CORDEXEast Asia COSMO-CLM ERA-Interim 

Copyright information

© Korean Meteorological Society and Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Weidan Zhou
    • 1
    • 2
  • Jianping Tang
    • 1
    • 2
    • 3
    • 4
  • Xueyuan Wang
    • 1
  • Shuyu Wang
    • 1
    • 3
  • Xiaorui Niu
    • 1
    • 3
  • Yuan Wang
    • 1
    • 2
  1. 1.School of Atmospheric SciencesNanjing UniversityNanjingChina
  2. 2.Key Laboratory of Mesoscale Severe Weather/Ministry of EducationNanjing UniversityNanjingChina
  3. 3.Institute for Climate and Global Change ResearchNanjing UniversityNanjingChina
  4. 4.School of Atmospheric SciencesNanjing UniversityNanjingChina

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