Browsing by Author "Yu, Ping"

Due to its long lifetime and relatively low variability compared with its background values, it is of great significance to precisely measure the concentration of CO2 in the atmosphere. In the high latitude regions, permafrost and boreal forest serve as large carbon reservoirs. Capturing the carbon concentration there helps us understand the process of climate change and provide accurate data to the carbon flux models. However, the measurement there is facing significant challenges. Sparse observation coverage and low-quality data are still major problems to be solved. In this thesis, we are looking into these problems from satellite-based OCO-2 XCO2 retrievals in high latitude regions. XCO2 data acquired above 45°N were used to compare the version updates, validate the results with ground-based TCCON site data and come up with a colocation method for boreal areas trying to tackle the issue caused by slant solar radiation. The comparison of version 10 and version 9 datasets shows improvements of version 10 in data volume and precision level. Yet the changes are not as significant for sites near polar areas. It also reveals that the current advances mainly focus on reducing systematic errors. In the validation with TCCON data, from OCO-2 displays lower seasonal fluctuations. The quality filters are shown to be too tight for boreal sites in filtering lower values. It provides information for new approaches when adjusting the filters. The global distribution of averaged XCO2 reveals that standard deviation is higher for nadir mode land observation in mountain areas. This might be lowered with an improved surface pressure correction method. Averaging kernel correction is applied when comparing with TCCON to standardize the sensitivity profile. It enhances the accuracy of the results and also stresses the significance of integration scheme. A new colocation method is implemented for better locating of TCCON observations in high latitudes but did not return good results. Further adjustments for the algorithm and tests in more areas are needed.