Abstract
D.Phil. (Geography)
The Infrared Atmospheric Sounding Interferometer (lASI), operational in polar-orbit
since 2006 on the European MetOp-A satellite, is the most advanced of its kind in space. It has been designed to provide soundings of the troposphere and lower stratosphere at nadir in a spectral interval of 0.25 em" across the range 645-2 760 em". Fine spectral sampling such as this is imperative in the sounding of trace gases. Since its launch, the routine retrievals of greenhouse, species from IASI measurements have made a valuable contribution to atmospheric chemistry studies at a global scale. The main contribution of this thesis is the development of a new trace gas retrieval scheme for IASI measurements. The goal was to improve on the global operational scheme in terms of the algorithm complexity, speed of calculation and spatial resolution achieved in the final solution. This schemedirectly retrieves column integrated trace gas densities at single field-of-view (FOV) from IASI measurements within a 10% accuracy limit. The scheme is built on the Bayesian framework of probability and based on the assumption that the inversion of total column values, as apposed to gas profiles, is a near-linear problem. Performance of the retrieval scheme is demonstrated on simulated noisy measurements for carbon monoxide (CO). Being a linear solution, the scheme is'highly dependent on the accuracy of the a priori. A statistical estimate of the a priori was computed using a principal component regression analysis with 50 eigenvectors. The corresponding root-mean-square (RMS) error of the a priori was calculated to be 9.3%. In general terms, the physical retrieval improved on the a priori, and sensitivity studies were performed to demonstrate the accuracy and stability of the retrieval scheme under a numberof perturbations. A full system characterization and error analysis is additionally preformed to elicidate the nature of this complex problem. The hyperspectral IASI measurements introduce a significant correlation error in the retrieval. The
Absorption Line Cluster (ALC) channel selection method was developed in this thesis, to
address the correlation error explicitly. When a first neighbour correlation factor of 0.71 is assumed in the measurement error covariance for the clusters of ALC channels, then most of the correlation error is removed in the retrieval. In conclusion, the total column trace gas retrieval scheme developed here is fast, simple, intuitive, transparent and robust. These characteristics together make it highly suitable for implementation in an operational environment intended for air quality monitoring on a regional scale.