| Summary: | Space-based measurements of atmospheric carbon dioxide (CO2) provide global coverage with repetition times on the order of days. These measurements are used in combination with flux inversion models to track and identify sources and sinks of carbon. The ultimate goal is a better understanding of natural and anthropogenic contributions to the global carbon cycle, from which mitigation strategies and policies can be derived to deal with the effects of climate change. The algorithms responsible for inferring the atmospheric concentrations of CO2 from the high-resolution spectroscopic measurements are the so-called retrieval algorithms. This thesis focuses on two main aspects that are important for a successful retrieval strategy, and both have applications beyond CO2 retreivals. The first part of this thesis is centred around solar-induced chlorophyll fluorescence (SIF), a naturally occurring radiance signal produced by vegetation as a by-product of photosynthesis. Due to its spectral signature, it is observed by satellite measurements in the O2 A-band at 0.76 μm. Based on an established retrieval concept, the SIF retrieval was implemented and its impact on CO2 retrievals has been evaluated. The SIF retrievals themselves are of great interest to carbon cycle science, and have been used for two case studies: relating SIF to primary production, and tracking the biosphere response to the 2012 North American drought. In the second part, the focus of the thesis is on fast radiative transfer (RT) methods, which are acceleration techniques to speed up the computationally very expensive line-by-line RT calculations. A novel method based on principal component analysis has been implemented and further advanced. This allowed for the PCA-based method to be used in CO2 retrievals for measurements from the OCO-2 instrument. Finally, for the first time, a comparison of three popular fast RT schemes has been performed in a consistent way using the same retrieval algorithm.
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