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The objective of this thesis is to evaluate the sources of the differences between the NO2 satellite retrieval products provided by the Royal Dutch Meteorological Institute (KNMI) and the National Aeronautics and Space Administration (NASA). Ground studies have shown that although both products use the same satellite, these products yield different observations for NO2 tropospheric columns concentrations. This study does not validate either retrieval product, but rather indentifies the main sources for the discrepancy. There are several parameters which allow successful retrieval of NO2 vertical columns. For this study, only the difference between the radiative models and the a priori NO2 chemical transport models were considered relevant. All other parameters, such as cloud properties, slant columns, stratospheric serration and their assumptions, were held constant. Here, the models are referred to by their proprietor's acronym: "TOMRAD" refers to the radiative model used by NASA, "DAK" refers to the radiative model used by KNMI, "TM4" refers to the a priori chemical transport model used by KNMI, and "REAM" refers to the a priori chemical transport model maintained by the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology. Mixing these parameters creates four retrievals for comparison. Many significant differences were identified after comparing these four retrievals. First, there are viewing geometry biases between the port side and the starboard side of the satellite retrieval for each swath. These viewing geometry biases lead to artificial periodicities in the retrievals of NO2 tropospheric vertical columns over a specific coordinate or site, such as a city. Furthermore, there were significant differences found after using different a priori NO2 chemical transport models. The low horizontal resolution of TM4 and the satellite retrieval/TM4 coupling effect compared to REAM leads to considerable questioning of the near real time application of the KNMI NO2 retrieval product. Though the TM4 model performs poorly, TM4 retrievals do perform nearly as well as REAM retrievals at capturing day-to-day variability and the spatial variability of the cities used as examples here. The retrievals using TOMRAD outperformed the retrievals using DAK when compared to the high resolution, hourly REAM a priori chemical transport model. In sum, these findings should lead to better optimizations of both the KNMI and NASA retrievals, and thus make their publicly available data products more reliable and accurate for general use. |
