Abstract: Trace gases comprise less than 1% of Earth’s atmosphere, yet they dominate the radiation budget and drive atmospheric chemistry. The Infrared Atmospheric Sounding Interferometer (IASI) is a set of two nadir viewing Fourier transform spectrometers aboard the MetOp-A and B satellites in polar orbit that measure spectral radiances in the thermal infrared and, therefore, observe the spectroscopic signatures of numerous trace gases. This thesis focuses on the practicalities of fully utilizing the vast amounts of data recorded via satellite with limited computational resources and prior knowledge of the target gas. First, a method for selecting a vertical retrieval grid is presented that minimizes the amount of prior knowledge appearing in the estimate due to applied constraints. This selection method uses the information content of the retrieval to optimally determine the number and spacings of vertical levels, while accounting for correlations between the various layers. Failing to select an appropriate vertical grid for water vapour and temperature retrievals, such as using levels equally spaced in pressure, was found to reduce the information content by as much as 30% on average. Overwhelmingly, the slowest part of an iterative retrieval is evaluating the forward model. As a result, the computation may fail to keep pace with data acquisition. Procedures to parametrise the Reference Forward Model (RFM) by creating a set of pre-tabulated look-up tables (LUTs) of absorption cross-sections for individual gases were developed. Since such LUTs can be unruly in size, a simple compression scheme based on linear interpolation was analysed that reduced the total LUT size to just 4.4% of the original. Additionally, the fine spectral grid for radiative transfer was also reduced using similar methods. Model comparisons to a global atmospheric ensemble showed negligible increases in error compared to IASI instrument noise and a factor of 130 increase in computational speed. These LUTs are openly available for use by the ...
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