This dissertation analyzes the retrieval of water vapor profiles via microwave radiometry; in particular it determines the information content of spectral data and identifies optimal measurement frequencies using an information content technique. The vertical resolution and estimate variance of water vapor profiles derived from the linear inversion of atmospheric data is examined and the effects of measurement noise on these quantities is considered. The Microwave Remote Sensing Laboratory at the University of Massachusetts has developed a unique K-Band Spectral Radiometer (KSR) system that simultaneously monitors eighteen frequencies near the 22.235 GHz water vapor absorption line and is designed to retrieve atmospheric water vapor density profiles by inverting spectral radiance measurements. This system is unique in its measurement speed and breadth. The dissertation discusses calibration techniques, system parameters, and the derivation of a statistical estimation algorithm is that is applied to KSR measurements taken during a field experiment in Lamont, Oklahoma. The resulting water vapor profiles are presented, along with a comparison of in-situ and independent observations.
| Identifer | oai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:dissertations-3007 |
| Date | 01 January 1998 |
| Creators | Scheve, Timothy M |
| Publisher | ScholarWorks@UMass Amherst |
| Source Sets | University of Massachusetts, Amherst |
| Language | English |
| Detected Language | English |
| Type | text |
| Source | Doctoral Dissertations Available from Proquest |
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