Evaluation of Surface Air Temperature Change over China and the Globe during the Twentieth Century in IAP AGCM4.0

Based on time series and linear trend analysis, the authors evaluated the performance of the fourth generation atmospheric general circulation model developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP AGCM4.0), in simulating surface air temperature (SAT) during the twentieth century over China and the globe. The numerical experiment is conducted by driving the model with the observed sea surface temperature and sea ice. It is shown that IAP AGCM4.0 can simulate the warming trend of the global SAT, with the major warming regions in the high latitudes of the Northern Hemisphere and the mid-latitudes of the Southern Hemisphere. While the simulated trend over the whole globe is close to the observation, the model under-estimates the observed trend over the continents. More-over, the model simulates the spatial distribution of SAT in China, with a bias of approximately-2°C in eastern China, but with a more serious bias in western China. Compared with the global mean, however, the correlation coefficient between the simulation and observation in China is significantly lower, indicating that there is large uncertainty in simulating regional climate change.

Based on time series and linear trend analysis, the authors evaluated the performance of the fourth gen- eration atmospheric general circulation model developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences （IAP AGCM4.0）, in simulating surface air temperature （SAT） during the twentieth century over China and the globe. The numerical experiment is con- ducted by driving the model with the observed sea surface temperature and sea ice. It is shown that IAP AGCM4.0 can simulate the warming trend of the global SAT, with the major wanning regions in the high latitudes of the Northern Hemisphere and the mid-latitudes of the South- ern Hemisphere. While the simulated trend over the whole globe is close to the observation, the model trader- estimates the observed trend over the continents. More- over, the model simulates the spatial distribution of SAT in China, with a bias of approximately -2℃ in eastern China, but with a more serious bias in western China. Compared with the global mean, however, the correlation coefficient between the simulation and observation in China is significantly lower, indicating that there is large uncertainty in simulating regional climate change.