Zhou Xin, Li Qingquan, Sun Xiubo, et al. Simulation and projection of temperature in China with BCC_CSM1.1 model. J Appl Meteor Sci, 2014, 25(1): 95-106.
Citation: Zhou Xin, Li Qingquan, Sun Xiubo, et al. Simulation and projection of temperature in China with BCC_CSM1.1 model. J Appl Meteor Sci, 2014, 25(1): 95-106.

Simulation and Projection of Temperature in China with BCC_CSM1.1 Model

  • Received Date: 2013-03-21
  • Rev Recd Date: 2013-10-29
  • Publish Date: 2014-01-31
  • Inter-annual and inter-decadal variability are two kinds of different timescale variability existing at the same time in climate system found in previous studies. Affected by the global warming, the inter-decadal signal of climate change becomes more and more significant. The next 10 to 30 years of climate change, namely inter-decadal time scales climate change and their impacts on the global environment, society and economic development, draw more and more attention. Climate change features of inter-decadal scale become one of the most important content of the IPCC AR5. The 10 to 30 years' timescale of inter-decadal forecast experiment which is listed as one of the main experiment content has joined the 5th Coupled Model Inter-comparison Project (CMIP5). More in-depth research will be carried out on predictability of inter-decadal timescale.The air temperature data of 541 stations in China from 1960 to 2010 as well as the CMIP5 historical and decadal experiment results of Beijing Climate Center Climate System Model (BCC_CSM1.1) are utilized to evaluate the simulation ability of the model. The model results are interpolated to the corresponding latitude and longitude of 541 stations use bilinear interpolation method. Whether the pattern of regional prediction ability could improve by the decadal experiment of BCC_CSM1.1 which initialed the SST (sea surface temperature) is discussed. Bias corrections to the decadal experiment results are done and the preliminary projection of the changes of the air temperature of China for the next 10—20 years is presented. Results show that both historical and decadal experiments can capture the warming trend in accordance with the observations, but the warming tendency of the experiments are less significant than those of observations. Results of historical experiments are slightly better than those of decadal experiments of the model. On the inter-decadal timescales, simulations in the eastern part of China are better than those in the western part of China. On the inter-annual timescales, the high prediction skills are located in the southwestern and eastern parts of northwest region, and southwest of China. Distributions of temperature in China are well simulated in both of historical and decadal experiments, such as the spatial correlation coefficients of 0.9 or above. After bias correction, results of decadal experiments are much better. By the corrected result of decadal experiments, the result of temperature spatial distribution simulation is better. The model projects that the rising rate of the mean temperature of China will be 0.48℃/10 a during 2011—2030, which is more significant than the warming rate of 0.27℃/10 a during 1960—2010 on the basis of observations. And the forecast results of the model show that the air temperature of China during 2001—2010 grows more slowly and fluctuate less compared with the period of 2011—2030.
  • Fig. 1  The 10-year mean of China temperature (a) and their anomalies (b)

    Fig. 2  Correlation coefficients between 10-year means of 9 experiments and corresponding observations (a) decadal experiment, (b) bias-revised decadal experiment, (c) historical experiment

    Fig. 3  Root mean square error 10-year mean of temperature and its anomalies from 9-group experiments and corresponding observations

    (a) temperature from decadal experiment, (b) temperature from bias-revised decadal experiment, (c) temperature from historical experiment, (d) temperature anomalies from decadal experiment, (e) temperature anomalies from bias-revised decadal experiment, (f) temperature anomalies from historical experiment

    Fig. 4  Correlation coefficients between 5-group decadal experiments and corresponding observations

    (a)1961—1990 group decadal experiment, (b) bias-revised 1961—1990 group decadal experiment, (c)1966—1995 group decadal experiment, (d) bias-revised 1966—1995 group decadal experiment, (e)1971—2000 group decadal experiment, (f) bias-revised 1971—2000 group decadal experiment, (g)1976—2005 group decadal experiment, (h) bias-revised 1976—2005 group decadal experiment, (i)1981—2010 group decadal experiment, (j) bias-revised 1981—2010 group decadal experiment

    Fig. 5  The time series of correlation of 5-group decadal experiments and historical experiment to their corresponding

    Fig. 6  Annual mean temperature of 1960—2010 observations and 2001—2030 model forecast and model bias-revised forecast results

    Table  1  Positive correlation and significantly correlation of stations number contrast between 5-group decadal experiments and their bias-revised results

    试验组别 正相关站点百分比/% 0.05显著性水平正相关站点百分比/%
    订正后 订正前 差值 订正后 订正前 差值
    1961—1990年 84.7 60.4 24.3 36.4 1.7 34.7
    1966—1995年 98.0 42.0 56.0 41.9 0.6 41.3
    1971—2000年 98.3 35.5 62.8 57.1 2.8 54.3
    1976—2005年 100.0 53.8 46.2 90.0 2.2 87.8
    1981—2010年 99.1 78.7 20.4 90.7 19.4 71.3
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    Table  2  The correlation and root mean square error of historical experiment and 5 decadal experiments (un-revised and bias-revised) with their corresponding observations for 30-year means

    试验组别 历史试验 订正前的年代际试验 订正后的年代际试验
    相关系数 均方根误差/℃ 相关系数 均方根误差/℃ 相关系数 均方根误差/℃
    1961—1990年 0.912 4.24 0.912 4.25 0.999 0.31
    1966—1995年 0.912 4.25 0.913 4.24 0.999 0.27
    1971—2000年 0.912 4.25 0.913 4.29 0.999 0.18
    1976—2005年 0.912 4.25 0.913 4.31 0.999 0.11
    1981—2010年 0.912 4.26 0.913 4.32 0.999 0.05
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    • Received : 2013-03-21
    • Accepted : 2013-10-29
    • Published : 2014-01-31

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