Social computing, as the technical foundation of future computational smart societies, has the potential to improve the effectiveness of opensource big data usage, systematically integrate a variety of elements includ...Social computing, as the technical foundation of future computational smart societies, has the potential to improve the effectiveness of opensource big data usage, systematically integrate a variety of elements including time, human, resources, scenarios, and organizations in the current cyber-physical-social world, and establish a novel social structure with fair information, equal rights, and a flat configuration. Meanwhile, considering the big modeling gap between the model world and the physical world, the concept of parallel intelligence is introduced. With the help of software-defined everything, parallel intelligence bridges the big modeling gap by means of constructing artificial systems where computational experiments can be implemented to verify social policies, economic strategies, and even military operations. Artificial systems play the role of ＂social laboratories＂ in which decisions are computed before they are executed in our physical society. Afterwards, decisions with the expected outputs are executed in parallel in both the artificial and physical systems to interactively sense, compute, evaluate and adjust system behaviors in real-time, leading system behaviors in the physical system converging to those proven to be optimal in the artificial ones. Thus, the smart guidance and management for our society can be achieved.展开更多
The climate system models from Beijing Climate Center, BCC_CSM1.1 and BCC_CSM1.1-M, are used to carry out most of the CMIP5 experiments. This study gives a general introduction of these two models, and provides main i...The climate system models from Beijing Climate Center, BCC_CSM1.1 and BCC_CSM1.1-M, are used to carry out most of the CMIP5 experiments. This study gives a general introduction of these two models, and provides main information on the experiments including the experiment purpose, design, and the external forcings. The transient climate responses to the CO2 concentration increase at 1% per year are presented in the simulation of the two models. The BCC_CSM1.1-M result is closer to the CMIP5 multiple models ensemble. The two models perform well in simulating the historical evolution of the surface air temperature, globally and averaged for China. Both models overestimate the global warming and underestimate the warming over China in the 20th century. With higher horizontal resolution, the BCC_CSM1.1-M has a better capability in reproducing the annual evolution of surface air temperature over China.展开更多
文摘Social computing, as the technical foundation of future computational smart societies, has the potential to improve the effectiveness of opensource big data usage, systematically integrate a variety of elements including time, human, resources, scenarios, and organizations in the current cyber-physical-social world, and establish a novel social structure with fair information, equal rights, and a flat configuration. Meanwhile, considering the big modeling gap between the model world and the physical world, the concept of parallel intelligence is introduced. With the help of software-defined everything, parallel intelligence bridges the big modeling gap by means of constructing artificial systems where computational experiments can be implemented to verify social policies, economic strategies, and even military operations. Artificial systems play the role of ＂social laboratories＂ in which decisions are computed before they are executed in our physical society. Afterwards, decisions with the expected outputs are executed in parallel in both the artificial and physical systems to interactively sense, compute, evaluate and adjust system behaviors in real-time, leading system behaviors in the physical system converging to those proven to be optimal in the artificial ones. Thus, the smart guidance and management for our society can be achieved.
基金supported by the National Basic Research Program of China (973 Program) under No. 2010CB951903the National Science Foundation of China under Grant No. 41105054, 41205043the China Meteorological Administration under Grant No.GYHY201106022, GYHY201306048, CMAYBY2012-001
文摘The climate system models from Beijing Climate Center, BCC_CSM1.1 and BCC_CSM1.1-M, are used to carry out most of the CMIP5 experiments. This study gives a general introduction of these two models, and provides main information on the experiments including the experiment purpose, design, and the external forcings. The transient climate responses to the CO2 concentration increase at 1% per year are presented in the simulation of the two models. The BCC_CSM1.1-M result is closer to the CMIP5 multiple models ensemble. The two models perform well in simulating the historical evolution of the surface air temperature, globally and averaged for China. Both models overestimate the global warming and underestimate the warming over China in the 20th century. With higher horizontal resolution, the BCC_CSM1.1-M has a better capability in reproducing the annual evolution of surface air temperature over China.
