Combining XCO2 Measurements Derived from SCIAMACHY and GOSAT for Potentially Generating Global CO2 Maps with High Spatiotemporal Resolution.

Global warming induced by atmospheric CO₂ has attracted increasing attention of researchers all over the world. Although space-based technology provides the ability to map atmospheric CO₂ globally, the number of valid CO₂ measurements is generally limited for certain instruments owing to the presence of clouds, which in turn constrain the studies of global CO₂ sources and sinks. Thus, it is a potentially promising work to combine the currently available CO₂ measurements. In this study, a strategy for fusing SCIAMACHY and GOSAT CO₂ measurements is proposed by fully considering the CO₂ global bias, averaging kernel, and spatiotemporal variations as well as the CO₂ retrieval errors. Based on this method, a global CO₂ map with certain UTC time can also be generated by employing the pattern of the CO₂ daily cycle reflected by Carbon Tracker (CT) data. The results reveal that relative to GOSAT, the global spatial coverage of the combined CO₂ map increased by 41.3% and 47.7% on a daily and monthly scale, respectively, and even higher when compared with that relative to SCIAMACHY. The findings in this paper prove the effectiveness of the combination method in supporting the generation of global full-coverage XCO₂ maps with higher temporal and spatial sampling by jointly using these two space-based XCO₂ datasets. [ABSTRACT FROM AUTHOR]