Date of Award

3-2-2004

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Engineering Physics

First Advisor

Steven T. Fiorino, PhD

Abstract

Dust storms are extreme weather events that have strong winds laden with visibility reducing and operations limiting dust, The Central Command Air Forces (CENTAF) 28th Operational Weather Squadron (OWS) is ultimately responsible for forecasting weather in the vast, data denied region of Southwest Asia in support of daily military and humanitarian operations. As a result, the 28th OWS requests a simplified forecasting tool to help predict mesoscale dust events that affect coalition operations at Al Udeid AB, Qatar. This research satisfies the 28th OWS request through an extensive statistical analysis of observational data depicting seasonal dust events over the past 2 years. The resultant multiple linear regression best fit model combines 28 easily attainable model outputs, satellite imagery, surface and upper air observations, and applies a linear transformation equation. The best fit model derived provides the end user with a numerical visibility prediction tool for Al Udeid AB that is verified against a seasonally divided and independent validation data set that yields an R2 of 0.79 while maintaining < 800 m accuracy.

AFIT Designator

AFIT-GM-ENP-04-01

DTIC Accession Number

ADA422645

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