According to current huge data requirements for the global climate change assessment, DBAR Data Sharing Principles, as well as the national policymaking in response to the global agreement (Framework Convention on Climate Change (FCCC)) on combating climate change, to reform the research mode of carbon data based exploration, to integrate carbon satellite data, models and computing technologies to advance interdisciplinary study, and to implement a big earth data e-science platform for global carbon researches are very essential and necessary. Cooperation on the Analysis of carbon Satellites data (CASA), a new international scientific programme, was approved by the Chinese Academy of Sciences (CAS) in 2018, which was participated by CAS/Institute of Atmospherics Physics and National Super Computer Center in Wuxi. Massive data resources (standard, value-added carbon satellite products and auxiliary data), relevant analysis models, and the super-computing capacity (100 trillion FLOPs computing power and 1 PB of storage) has been integrating into the CASA big e-science platform. Forthcoming products, including carbon satellites standard products, higher precision CO<sub>2</sub> reprocessed products, and application dataset based on above two kinds of CO<sub>2</sub> products, are processed and analyzed online on the CASA e-science platform. The first global XCO<sub>2</sub> product produced from TanSat will be released at September of 2019. Research mode of carbon data-based is going to be reformed under the support of big data and supercomputing power.
To study the spatial and temporal distribution characteristics of near-surface CO<sub>2</sub> concentration over China, the data of GOSAT L4B and auxiliary data of Mt Waliguan background observations, population density, total energy consumption (coal) and GDP in 2009 were applied to this study. The ArcGIS Geostatistical Analytical Method was used. The ground-based validation was processed by comparing GOSAT data with Mt Waliguan background observations. The variation characteristics of the near-surface CO<sub>2</sub> concentration over China was analysed spatially and temporally. The results show that: GOSAT retrieved near-surface products are consistent with Mt Waliguan ground-based measurement; Near-surface CO<sub>2</sub> concentration over China is relatively concentrated, and has significant differences between the East and the West, with a overall characteristic that CO<sub>2</sub> concentration in the east of China is high and in the west is low; Near-surface CO<sub>2</sub> concentration over China has a significant seasonal variation characteristic, and the monthly average concentration rise to the highest value of 396.512 ppmv in April (spring), which is significantly higher than other seasons, decline to the lowest value of 382.781 ppmv in July (summer); All relationships illustrate a big uncertainty, resulting a conclusion that the reasons causing the spatial distribution of near-surface CO<sub>2</sub> concentration may be varied, could not be easily determined as anthropogenic or natural ressons, which need further study.