A step forward to global segment CO 2 flux estimation benefiting from large swath of coordinated CO 2 and SIF measurement from TanSat-2 mission

To improve understanding of the global carbon cycle, China is preparing to launch the next generation carbon monitoring satellite, TanSat-2, which will collect column measurements of carbon dioxide (CO2) and methane (CH4). In this paper, we investigate the potential of TanSat-2 observations for assessing anthropogenic carbon emissions and ecosystem carbon sinks. To achieve this objective, we introduce a new carbon flux estimation method that combines atmospheric measurements of CO2 and solar induced fluorescence (SIF) to jointly constrain net primary production (NPP) and fossil fuel combustion (FF). We apply empirical orthogonal functions (EOF) analysis to the NPP and FF inventories to identify dominant spatial–temporal patterns to reduce the size of state vector and to help disaggregate the natural and fossil fuel combustion sources of CO2. Using closed-loop numerical experiments, Observing System Simulation Experiment (OSSE), we find that TanSat-2 CO2 and SIF observations lead to an NPP error reduction of up to 95% over Siberia and Amazon, and to error reductions of about 80% for FF emissions over Siberia, North Aisa, US and South Africa if measurement bias could be eliminated. However, our OSSE experiments show that presence of even a small XCO2 bias can cause serious of distortion or mis-allocation of CO2 sources and sinks. Therefore systematic observation bias needs to be properly addressed n retrieval and data application. We also explore the importance of adopting a large across-track swath in delivering robust CO2 flux estimates and develop an error matrix tool that could be used in future mission assessment.