With the deepening of climate change research, more attention has been paid to vulnerability to climate change. Compared with water resources, forests and other natural ecosystems, agriculture is more vulnerable to cl...With the deepening of climate change research, more attention has been paid to vulnerability to climate change. Compared with water resources, forests and other natural ecosystems, agriculture is more vulnerable to climate change, thereby scientifically assessing agricultural vulnerability to climate change is of great significance to the formulation of rational and effective adaptation strategies. In this paper, the authors give a comprehensive review of the research from the perspective of the definition of climate change vulnerability and agricultural vulnerability to climate change, research topics, and evaluation methodologies. Existing problems in current research, including scenario application, methods, and uncertainties, are analyzed, and meanwhile, a vision of the direction for future research in assessment of agricultural vulnerability is also presented.展开更多
Using series of daily average temperature observations over the period of 1961-1999 of 701 meteorological stations in China, and simulated results of 20 global climate models (such as BCCR_BCM2.0, CGCM3T47) during t...Using series of daily average temperature observations over the period of 1961-1999 of 701 meteorological stations in China, and simulated results of 20 global climate models (such as BCCR_BCM2.0, CGCM3T47) during the same period as the observation, we validate and analyze the simulated results of the models by using three factor statistical method, achieve the results of mul- ti-model ensemble, test and verify the results of multi-model ensemble by using the observation data during the period of 1991-1999. Finally, we analyze changes of the annual mean temperature result of multi-mode ensemble prediction for the period of 2011-2040 under the emission scenarios A2, A1B and B 1. Analyzed results show that: (1) Global climate models can repro- duce Chinese regional spatial distribution of annual mean temperature, especially in low latitudes and eastern China. (2) With the factor of the trend of annual mean temperature changes in reference period, there is an obvious bias between the model and the observation. (3) Testing the result of multi-model ensemble during the period of 1991-1999, we can simulate the trend of temper- ature increase. Compared to observation, the result of different weighing multi-model ensemble prediction is better than the same weighing ensemble. (4) For the period of 20ll-2040, the growth of the annual mean temperature in China, which results from multi-mode ensemble prediction, is above 1℃. In the spatial distribution of annual mean temperature, under the emission scenarios of A2, A1B and B 1, the trend of growth in South China region is the smallest, the increment is less than or equals to 0.8℃; the trends in the northwestern region and south of the Qinghai-Tibet Plateau are the largest, the increment is more than 1℃.展开更多
基金supported by the China Meteorological Administration(NoGYHY200806008)the China-UK -Swiss ACCC Project
文摘With the deepening of climate change research, more attention has been paid to vulnerability to climate change. Compared with water resources, forests and other natural ecosystems, agriculture is more vulnerable to climate change, thereby scientifically assessing agricultural vulnerability to climate change is of great significance to the formulation of rational and effective adaptation strategies. In this paper, the authors give a comprehensive review of the research from the perspective of the definition of climate change vulnerability and agricultural vulnerability to climate change, research topics, and evaluation methodologies. Existing problems in current research, including scenario application, methods, and uncertainties, are analyzed, and meanwhile, a vision of the direction for future research in assessment of agricultural vulnerability is also presented.
基金supported by Adapting Climate Change in China (ACCC) Project:Climate Science (Project No.ACCC/003)
文摘Using series of daily average temperature observations over the period of 1961-1999 of 701 meteorological stations in China, and simulated results of 20 global climate models (such as BCCR_BCM2.0, CGCM3T47) during the same period as the observation, we validate and analyze the simulated results of the models by using three factor statistical method, achieve the results of mul- ti-model ensemble, test and verify the results of multi-model ensemble by using the observation data during the period of 1991-1999. Finally, we analyze changes of the annual mean temperature result of multi-mode ensemble prediction for the period of 2011-2040 under the emission scenarios A2, A1B and B 1. Analyzed results show that: (1) Global climate models can repro- duce Chinese regional spatial distribution of annual mean temperature, especially in low latitudes and eastern China. (2) With the factor of the trend of annual mean temperature changes in reference period, there is an obvious bias between the model and the observation. (3) Testing the result of multi-model ensemble during the period of 1991-1999, we can simulate the trend of temper- ature increase. Compared to observation, the result of different weighing multi-model ensemble prediction is better than the same weighing ensemble. (4) For the period of 20ll-2040, the growth of the annual mean temperature in China, which results from multi-mode ensemble prediction, is above 1℃. In the spatial distribution of annual mean temperature, under the emission scenarios of A2, A1B and B 1, the trend of growth in South China region is the smallest, the increment is less than or equals to 0.8℃; the trends in the northwestern region and south of the Qinghai-Tibet Plateau are the largest, the increment is more than 1℃.