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Analysis of Prospective Fog Warning Systems Using AWOS/ASOS Station Data Throughout the State of Florida

Title: Analysis of Prospective Fog Warning Systems Using AWOS/ASOS Station Data Throughout the State of Florida.
Name(s): Rivard, Justin, author
Ray, Peter S., professor directing thesis
Chagnon, Jeffrey M., committee member
Hart, Robert Edward, 1972-, 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
Type of Resource: text
Genre: Text
Issuance: monographic
Date Issued: 2014
Publisher: Florida State University
Florida State University
Place of Publication: Tallahassee, Florida
Physical Form: computer
online resource
Extent: 1 online resource (84 pages)
Language(s): English
Abstract/Description: Fog and smoke can combine to form dangerous zero visibility conditions along roadways throughout the state of Florida. The ability to forecast when and where fog will occur is problematic. Fog can occur over large and small scales, and is dependent on many meteorological and geographic variables. This study used Automated Weather Observation Stations (AWOS) and Automated Surface Observing Systems (ASOS) throughout the state of Florida to develop a climatology to ascertain what conditions are necessary for radiation fog development. Forecasted dewpoint depression, wind speed, cooling rates, the derived vertical hydrolapse, and other variables were shown to all affect fog formation. Using this information, a fog forecasting model was developed. The model was used to determine a three-hour binary forecast for the early morning hours, every day, at the location of the mesonet stations used. The model would predict fog if meteorological conditions preceding the forecasting time met a series of threshold levels. The goal was to make the model easy to deploy so that law enforcement can make a fast decision of whether to warn the public about potentially dangerous road conditions. The model was compared to other forecasting techniques such as the Model Output Statistics (MOS) fog product and climatology. After comparing the model to reference forecasts, it was found that the model outperformed climatology by a significant margin and was able to detect more fog events than MOS. However, the model had a higher false alarm rate and lower percent forecasts correct compared to MOS .
Identifier: FSU_migr_etd-9236 (IID)
Submitted Note: A Thesis submitted to the Department of Earth, Ocean, and Atmospheric Science in partial fulfillment of the requirements for the degree of Master of Science.
Degree Awarded: Summer Semester, 2014.
Date of Defense: July 17, 2014.
Bibliography Note: Includes bibliographical references.
Advisory Committee: Peter Ray, Professor Directing Thesis; Jeffrey Chagnon, Committee Member; Robert Hart, Committee Member.
Subject(s): Meteorology
Persistent Link to This Record:
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Host Institution: FSU

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Rivard, J. (2014). Analysis of Prospective Fog Warning Systems Using AWOS/ASOS Station Data Throughout the State of Florida. Retrieved from