Type of Document	Thesis
Author	Veenhuis Jr., Bruce Albert
URN	etd-03182009-151712
Title	A Stereoscopic Technique to Estimate Cloud-Top Height Using Combined Geostationary and Low Earth Orbiting Satellites
Degree	Master of Science
Department	Meteorology, Department of
Advisory Committee	Advisor Name Title Guosheng Liu Committee Chair Robert Ellingson Committee Member Robert Hart Committee Member
Keywords	Cloud-top Height Remote Sensing Satellites
Date of Defense	2009-01-22
Availability	unrestricted
Abstract Accurate knowledge of cloud-top height is important for a range of meteorological applications. Uses include cloud classification and the assignment of height levels to cloud drift winds. Such data may also be useful for monitoring tropical cyclone intensity over observation sparse oceans. A new method to retrieve cloud-top height has been developed in order to improve the temporal and spatial coverage of cloud-top height data compared to currently available sources. The technique is a stereoscopic retrieval algorithm which uses visible wavelength data from the GOES-IM and MODIS instruments. Stereoscopic techniques utilize multiple views of the same cloud feature from different viewing angles to retrieve cloud-top height. Since clouds occur above the surface of the earth, when viewed from distinct angles a cloud will map to different positions creating a location parallax. The magnitude of location parallax is a function of the cloud altitude above the earth’s surface and therefore may be used to determine cloud-top height. Data from the CloudSat and the Multiangle Imaging Spectroradiometer (MISR) have been used to validate the algorithm developed by this study. The overall mean and median algorithm bias relative to CloudSat and MISR are significantly different from 0 at the 95% confidence level however the bias are only ~200 m suggesting the algorithm is accurate. The algorithm is also evaluated by binning clouds according to optical thickness and the degree of cloud-top texture. Bias statistics are then calculated for each cloud bin. Results indicate biases are only statistically significantly different from 0 for clouds with little cloud top texture. To test the feasibility of using cloud-top height data to estimate tropical cyclone intensity the algorithm is used to retrieve cloud heights for tropical cyclones Katrina 2005 and Dennis 2005. Some predictive skill is apparent; however, additional work is needed draw definitive conclusions.
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