PROGRESS IN GEOGRAPHY ›› 2010, Vol. 29 ›› Issue (7): 818-826.doi: 10.11820/dlkxjz.2010.07.007

• Original Articles • Previous Articles     Next Articles

Simulation Evaluation and Uncertainty Analysis for Climate Change Projections in East China Made by IPCC-AR4 Models

GU Wen1,2, CHEN Baode2, YANG Yuhua2, DONG Guangtao3   

  1. 1. Nanjing University of Information Science and Technology, Nanjing 210044, China|
    2. Shanghai Typhoon Institute/Key Open Laboratory of Typhoon Forecast Technique, CMA, Shanghai 200030, China|
    3. Shanghai Climate Center, Shanghai 200030, China
  • Received:2009-09-01 Revised:2010-03-01 Online:2010-07-25 Published:2010-07-25


In this paper, the climate change projections in East China made by the climate models in the IPCC-AR4 were assessed by simulation evaluation and uncertainty analysis. By comparing individual simulation of the 21 IPCC AR4 models with the observations and with each other as well, it is demonstrated that the simulation abilities of different models vary widely. Only models of NCAR-CCSM3 and MRI-CGCM2.3.2 have small root mean square errors for both temperature and precipitation simulations in East China. It has been shown that, under the scenario A1B, multi-model ensemble mean can fairly well illustrate the spatial patterns of annual mean temperature and precipitation. Nevertheless, it can hardly reflect local fine structure of the distributions because of their low spatial resolutions. Moreover, there is a significant systematic deviation in multi-model ensemble mean for temperature projection. It underestimates the annual mean temperature by more than 1.6℃, and the difference between simulation and observation exceeds the extent of the uncertainty which is defined by one-fold standard deviation of inter-models’ simulations. The standard deviation of annual precipitation is up to 26.7% of the multi-model ensemble mean. Therefore it would be quite questionable if IPCC-AR4 multi-model ensemble means of temperature and precipitation in East China are directly used as climate change projection.

Key words: climate models, East China, scenarios projection, uncertainty