As reported by the University of Central Florida (UCF), Florida nearly leads the nation in fatal vehicle crashes due to fog and smoke conditions. Between 2002 and 2009, 299 deaths were due to vehicle crashes related to fog and smoke conditions. This is more than the amount of deaths by hurricanes and lightning strikes combined. It may be possible to reduce the number of fatalities and crashes by implementing an effective early warning system. A warning of impending fog conditions would allow DOT and other agencies the ability to monitor specific locations. However, fog is both spatially and temporally variable and surface observation equipment is widely dispersed. The challenge lies in the ability to forecast and detect the occurrence of fog from surface observations far removed from the location of fog occurrence. The spatial variability of fog frequency over the state of Florida is explored based on an evaluation of GOES Imager satellite data. A nighttime fog detection algorithm employing a bispectral thresholding technique involving brightness temperature differences (BTD) between two channels: 4 (10.7-μm) and 2 (3.9-μm) is presented. The performance of the fog product is validated using one year of AWOS/ASOS station observations in the period right before daybreak, showing moderate skill. The frequency of fog in Florida for 2012 is analyzed through application of this technique and is compared to interpolated fog frequencies based on ground observations. Seasonal and annual bias corrections are implemented to calibrate the satellite fog product observations and provide spatially continuous data of fog occurrence in Florida. While the satellite-derived fog product generally overestimated fog frequency, the pattern of fog occurrences agreed with the general spatial patterns found in station-derived climatologies, providing encouraging results. This analysis sets a basis for a satellite-based fog climatology that provides spatially continuous information of underlying fog dynamics. Future work involving assessments of satellite fog products over a multi-year period, as well as improved spatial resolution in the forthcoming GOES-R, will assist in furthering knowledge regarding regional fog risks and potentials. / A Thesis submitted to the Department of Earth, Ocean, and Atmospheric Sciences in partial fulfillment of the requirements for the degree of Master of Science. / Spring Semester, 2015. / April 7, 2015. / Algorithm, Climatology, Florida, Fog, Remote Sensing, Satellite / Includes bibliographical references. / Peter S. Ray, Professor Directing Thesis; Ming Cai, Committee Member; Zhaohua Wu, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_252986 |
| Contributors | Lefran, Daphne (authoraut), Ray, Peter S. (professor directing thesis), Cai, Ming, 1957- (committee member), Wu, Zhaohua (committee member), Florida State University (degree granting institution), College of Arts and Sciences (degree granting college), Department of Earth, Ocean, and Atmospheric Science (degree granting department) |
| Publisher | Florida State University, Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text |
| Format | 1 online resource (87 pages), computer, application/pdf |
| Rights | This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). The copyright in theses and dissertations completed at Florida State University is held by the students who author them. |
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