Meteorology and Atmospheric Physics

, Volume 111, Issue 1, pp 41–53

Comparison of four ensemble methods combining regional climate simulations over Asia

  • Jinming Feng
  • Dong-Kyou Lee
  • Congbin Fu
  • Jianping Tang
  • Yasuo Sato
  • Hisashi Kato
  • John L. Mcgregor
  • Kazuo Mabuchi
Original Paper

DOI: 10.1007/s00703-010-0115-7

Cite this article as:
Feng, J., Lee, D., Fu, C. et al. Meteorol Atmos Phys (2011) 111: 41. doi:10.1007/s00703-010-0115-7

Abstract

A number of uncertainties exist in climate simulation because the results of climate models are influenced by factors such as their dynamic framework, physical processes, initial and driving fields, and horizontal and vertical resolution. The uncertainties of the model results may be reduced, and the credibility can be improved by employing multi-model ensembles. In this paper, multi-model ensemble results using 10-year simulations of five regional climate models (RCMs) from December 1988 to November 1998 over Asia are presented and compared. The simulation results are derived from phase II of the Regional Climate Model Inter-comparison Project (RMIP) for Asia. Using the methods of the arithmetic mean, the weighted mean, multivariate linear regression, and singular value decomposition, the ensembles for temperature, precipitation, and sea level pressure are carried out. The results show that the multi-RCM ensembles outperform the single RCMs in many aspects. Among the four ensemble methods used, the multivariate linear regression, based on the minimization of the root mean square errors, significantly improved the ensemble results. With regard to the spatial distribution of the mean climate, the ensemble result for temperature was better than that for precipitation. With an increasing number of models used in the ensembles, the ensemble results were more accurate. Therefore, a multi-model ensemble is an efficient approach to improve the results of regional climate simulations.

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Jinming Feng
    • 1
  • Dong-Kyou Lee
    • 2
  • Congbin Fu
    • 1
  • Jianping Tang
    • 3
  • Yasuo Sato
    • 4
  • Hisashi Kato
    • 5
  • John L. Mcgregor
    • 6
  • Kazuo Mabuchi
    • 4
  1. 1.Key Laboratory of Regional Climate-Environment for East AsiaInstitute of Atmospheric Physics, Chinese Academy of SciencesBeijingChina
  2. 2.School of Earth and EnvironmentSeoul National UniversitySeoulKorea
  3. 3.Department of Atmospheric PhysicsNanjing UniversityNanjingChina
  4. 4.Atmospheric Environment and Applied Meteorology Research DepartmentMeteorological Research Institute/JMATsukubaJapan
  5. 5.Central Research Institute of Electric Power IndustryTokyoJapan
  6. 6.Division of Atmospheric ResearchCommonwealth Scientific and Industrial Research OrganizationAspendaleAustralia