Integrating a Geographic Information System into Storm Assessment: The Southeast Alabama Tornado Outbreak of 1 March 2007
J. Parks Camp, NOAA/NWS, Tallahassee, FL
On March 1, 2007 a tornadic supercell moved across southeast Alabama. The supercell spawned two tornadoes in Alabama before crossing into southwest Georgia. The first, and most damaging, tornado touched down southwest of the city of Enterprise, Alabama, and moved through the heart of the town, causing extensive damage and killing nine people, including eight at Enterprise High School. Following an extensive storm survey by National Weather Service personnel, the tornado was rated EF-4 on the enhanced Fujita scale.
As part of the storm survey, two teams of investigators took damage photographs from the air and on the ground. More than 250 photographs were taken of the damage in and around Enterprise. While the on-site teams and individual damage photographs provided ample data to determine the EF-scale intensity, the sheer amount of data made it difficult to gain an overall view of the tornado track and distribution of damage. Such a spatial overview has the potential to provide valuable information concerning the structure of the tornado, and variations in intensity along the track. While the on-ground and aerial datasets are independently useful, each also has inherent limitations. Photos from ground level are very useful in documenting the extent of damage to structures and vegetation. However, the spatial location of individual photographs can be difficult to ascertain. In addition, with limited time and manpower, on ground surveys can be limited in area. Damage seen from aerial photographs is much easier to locate spatially using key landmarks (over urban areas). However, the degree of damage is not as readily identifiable, and locating damage over rural areas can prove difficult.
Geographical Information System (GIS) software allows for the integration and analysis of multiple spatial datasets. For the Enterprise tornado, 1-meter resolution ortho-imagery for southeast Alabama was obtained from the U.S. Geological Survey and displayed in a GIS environment. The photographs from the two aerial surveys were analyzed and geolocated through a comparison of landmarks with the ortho-imagery. One of the aerial survey teams provided a Global Positioning System log of the flight track, which was overlaid on the ortho-imagery. These data were key in pinpointing damage, especially over the rural areas. With the damage located from the aerial photography, an attempt was then made to roughly categorize the damage in both the aerial and ground-based data. The locations of most of the ground-based photographs were determined through a comparison with damage seen from the air, as well as by locating identifiable landmarks. A rough estimate of the degree of damage within each photograph was made, and added to the attribute table of the damage point. Using this method, the areas of more significant damage could be highlighted within the overall damage swath.
Several benefits emerged from the GIS analysis of the tornado damage. Accurate path length and width were easily determined. This included identifying the points along the path where the tornado touched down intermittently. Interesting aspects of the damage distribution also emerged from the GIS analysis. The distribution indicated that at several points along the path, the damage was more severe in the northern half of the tornado circulation. This is contrary to the distribution one might expect from a cyclonic tornado moving rapidly to the northeast. Overlaying the base reflectivity from the Fort Rucker WSR-88D clearly showed the location of the tornado circulation within the supercell. A decrease in the damage signature northeast of the city of Enterprise corresponded to a weakening in the radar signature.
The benefits of GIS technology in the meteorological community are just beginning to be uncovered. The mapping of storm damage has the potential to enhance the assessment of strong tornadoes, and provide further insights into their intensity and structure. While the process used in this study was somewhat tedious, further integration of Global Positioning System data with damage surveys would significantly enhance the feasibility. A more rigorous analysis of the damage in the photographs, using the Enhanced Fujita scale, would also improve the visualization of the distribution of damage.
Extended Abstract (1.9M)
Poster Session 1, IIPS Poster Session I
Monday, 21 January 2008, 2:30 PM-4:00 PM, Exhibit Hall B
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