scholarly journals Tornado Damage and Damage Assessment of Houses

2008 ◽  
Vol 2008 (115) ◽  
pp. 99-102
Author(s):  
Yasushi UEMATSU ◽  
Yasuo OKUDA
Keyword(s):  
Damage Assessment ◽  
Tornado Damage

scholarly journals A Multiscale Overview of the El Reno, Oklahoma, Tornadic Supercell of 31 May 2013

2015 ◽  
Vol 30 (3) ◽  
pp. 525-552 ◽  
Author(s):  
Howard B. Bluestein ◽  
Jeffrey C. Snyder ◽  
Jana B. Houser
Keyword(s):  
Damage Assessment ◽  
Cross Correlation ◽  
Doppler Radar ◽  
Vertical Shear ◽  
Convective Storms ◽  
Rapid Scan ◽  
Oklahoma Mesonet ◽  
Beam Height ◽  
Tornado Damage ◽  
Gust Front

Abstract On 31 May 2013 a broad, intense, cyclonic tornado and a narrower, weaker companion anticyclonic tornado formed in a supercell in central Oklahoma. This paper discusses the synoptic- and mesoscale environment in which the parent storm formed, based on data from the operational network of surface stations, rawinsondes, and WSR-88D radars, and from the Oklahoma Mesonet, a Doppler radar wind profiler, Rapid Refresh (RAP) analyses, and photographs. It also documents the overall behavior of the tornadoes and their relationships to features in their parent supercell based on data from a nearby, rapid-scan, polarimetric, mobile Doppler radar. The supercell formed near the intersection of a cold front and a dryline in an environment of moderately strong vertical shear and high CAPE, at the southern end of a line of multicell convective storms. The tornado damage path was as wide as 4.2 km according to the NWS damage assessment and ground-relative Doppler velocities of at least 135 m s−1 were found at the theoretical beam height of <20 m AGL. The tornado debris signature in the copolar cross-correlation coefficient ρhv was as wide as ~4–5 km. After the strong tornado formed, at least one additional cyclonic tornado formed and rotated cyclonically around the main tornado; it was then absorbed by it and the main tornado broadened. Smaller subvortices, which rotated cyclonically around a common axis of rotation, were subsequently observed. The tornado then weakened but remained broad, while the anticyclonic tornado formed to the southeast along the rear-flank gust front.

scholarly journals Categorizing natural disaster damage assessment using satellite-based geospatial techniques

2008 ◽  
Vol 8 (4) ◽  
pp. 707-719 ◽  
Author(s):  
S. W. Myint ◽  
M. Yuan ◽  
R. S. Cerveny ◽  
C. Giri
Keyword(s):  
Natural Disaster ◽  
Damage Assessment ◽  
Emergency Services ◽  
Satellite Image ◽  
Image Data ◽  
Linear Regression Models ◽  
Spatial Indices ◽  
Geospatial Techniques ◽  
Tornado Damage ◽  
Damage Categories

Abstract. Remote sensing of a natural disaster's damage offers an exciting backup and/or alternative to traditional means of on-site damage assessment. Although necessary for complete assessment of damage areas, ground-based damage surveys conducted in the aftermath of natural hazard passage can sometimes be potentially complicated due to on-site difficulties (e.g., interaction with various authorities and emergency services) and hazards (e.g., downed power lines, gas lines, etc.), the need for rapid mobilization (particularly for remote locations), and the increasing cost of rapid physical transportation of manpower and equipment. Satellite image analysis, because of its global ubiquity, its ability for repeated independent analysis, and, as we demonstrate here, its ability to verify on-site damage assessment provides an interesting new perspective and investigative aide to researchers. Using one of the strongest tornado events in US history, the 3 May 1999 Oklahoma City Tornado, as a case example, we digitized the tornado damage path and co-registered the damage path using pre- and post-Landsat Thematic Mapper image data to perform a damage assessment. We employed several geospatial approaches, specifically the Getis index, Geary's C, and two lacunarity approaches to categorize damage characteristics according to the original Fujita tornado damage scale (F-scale). Our results indicate strong relationships between spatial indices computed within a local window and tornado F-scale damage categories identified through the ground survey. Consequently, linear regression models, even incorporating just a single band, appear effective in identifying F-scale damage categories using satellite imagery. This study demonstrates that satellite-based geospatial techniques can effectively add spatial perspectives to natural disaster damages, and in particular for this case study, tornado damages.

scholarly journals 20 May 2013 Moore, Oklahoma, Tornado: Damage Survey and Analysis

2014 ◽  
Vol 29 (5) ◽  
pp. 1229-1237 ◽  
Author(s):  
Donald Burgess ◽  
Kiel Ortega ◽  
Greg Stumpf ◽  
Gabe Garfield ◽  
Chris Karstens ◽  
...  
Keyword(s):  
Damage Assessment ◽  
Extreme Event ◽  
Surrounding Area ◽  
Private Companies ◽  
Damage Survey ◽  
Future Studies ◽  
Survey Team ◽  
Damage Indicators ◽  
Survey Results ◽  
Tornado Damage

Abstract The tornado that affected Moore, Oklahoma, and the surrounding area on 20 May 2013 was an extreme event. It traveled 23 km and damage was up to 1.7 km wide. The tornado killed 24 people, injured over 200 others, and damaged many structures. A team of surveyors from the Norman, Oklahoma, National Weather Center and two private companies performed a detailed survey (all objects/structures) of the tornado to provide better documentation than is normally done, in part to aid future studies of the event. The team began surveying tornado damage on the morning of 21 May and continued the survey process for the next several weeks. Extensive ground surveys were performed. The surveys were aided by use of high-resolution aerial and satellite imagery. The survey process utilized the enhanced Fujita (EF) scale and was facilitated by use of a National Weather Service (NWS) software package: the Damage Assessment Toolkit (DAT). The survey team defined a “well built” house that qualified for an EF5 rating. Survey results document 4253 objects damaged by the tornado, 4222 of them EF-scale damage indicators (DIs). Of the total DIs, about 50% were associated with EF0 ratings. Excluding EF0 damage, 38% were associated with EF1, 24% with EF2, 21% with EF3, 17% with EF4, and only 0.4% associated with EF5. For the strongest level of damage (EF5), only nine homes were found. Survey results are similar to other documented tornadoes, but the amount of EF1 damage is greater than in other cases. Also discussed is the use of non-DI objects that are damaged and ways in which to improve future surveys.

WSR-88D Tornado Intensity Estimates. Part I: Real-Time Probabilities of Peak Tornado Wind Speeds

2020 ◽  
Vol 35 (6) ◽  
pp. 2479-2492
Author(s):  
Bryan T. Smith ◽  
Richard L. Thompson ◽  
Douglas A. Speheger ◽  
Andrew R. Dean ◽  
Christopher D. Karstens ◽  
...  
Keyword(s):  
United States ◽  
Life Cycle ◽  
Wind Speed ◽  
Real Time ◽  
Tilt Angle ◽  
Damage Assessment ◽  
Rotational Velocity ◽  
Wind Speeds ◽  
Damage Indicators ◽  
Tornado Damage

AbstractThe Storm Prediction Center (SPC) has developed a database of damage-surveyed tornadoes in the contiguous United States (2009–17) that relates environmental and radar-derived storm attributes to damage ratings that change during a tornado life cycle. Damage indicators (DIs), and the associated wind speed estimates from tornado damage surveys compiled in the Damage Assessment Toolkit (DAT) dataset, were linked to the nearest manual calculations of 0.5° tilt angle maximum rotational velocity Vrot from single-site WSR-88D data. For each radar scan, the maximum wind speed from the highest-rated DI, Vrot, and the significant tornado parameter (STP) from the SPC hourly objective mesoscale analysis archive were recorded and analyzed. Results from examining Vrot and STP data indicate an increasing conditional probability for higher-rated DIs (i.e., EF-scale wind speed estimate) as both STP and Vrot increase. This work suggests that tornadic wind speed exceedance probabilities can be estimated in real time, on a scan-by-scan basis, via Vrot and STP for ongoing tornadoes.

Automated Tornado Damage Assessment and Wind Speed Estimation Based on Terrestrial Laser Scanning

2015 ◽  
Vol 29 (3) ◽  
pp. 04014051 ◽  
Author(s):  
Alireza G. Kashani ◽  
Patrick S. Crawford ◽  
Sufal K. Biswas ◽  
Andrew J. Graettinger ◽  
David Grau
Keyword(s):  
Wind Speed ◽  
Damage Assessment ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Speed Estimation ◽  
Tornado Damage

Aircraft Battle Damage Assessment and Repair (ABDAR). Volume 3: Field Test Report

2000 ◽  
Author(s):  
Scott MacBeth ◽  
Johnnie Jernigan ◽  
Jackie Grody ◽  
Donald L. Thomas ◽  
Michael E. Clark
Keyword(s):  
Field Test ◽  
Damage Assessment ◽  
Test Report ◽  
Battle Damage Assessment

Wildfire Damage Assessment of a Young Oak Forest in Pennsylvania

2013 ◽  
Vol 23 (1) ◽  
pp. 91-104 ◽  
Author(s):  
Marc D. Abrams ◽  
Sarah E. Johnson
Keyword(s):  
Damage Assessment ◽  
Oak Forest
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