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Carolyn Kousky

across the disasters. In no case is the approval rate over 50%. This suggests that many households are applying for disaster aid when they are not actually eligible. Either people hope to get aid anyway, or there is widespread lack of awareness on the conditions for receiving HA. This is worthy of further investigation. There are limited data available on how these approval percentages compare with other disasters. A GAO report on Hurricanes Katrina and Rita found that for those events, the approval

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Kevin D. Ash, Ronald L. Schumann III, and Gregg C. Bowser

modeled tornado event, a simple symmetrical warning design was deemed the most defensible as a starting point. It must be acknowledged, however, that variations in supercell structure, direction of movement, and mesoscale environmental conditions may lead to tornado probability models with asymmetrical shapes. The warning designs represent a southwest-to-northeast direction of movement due to the high frequency of this track orientation in the United States; this is another necessary simplification as

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Walker S. Ashley, Stephen Strader, Troy Rosencrants, and Andrew J. Krmenec

a buffer, neighborhood boundary, or similar administrative overlay. Dasymetric mapping, which applies ancillary information (e.g., land use/cover data) to inform the areal estimation and interpolation of attributes such as population or housing units, is also suggested in the literature ( Holt et al. 2004 ; Mennis 2009 ). Although arguably superior for appraising demographic attributes ( Wu et al. 2005 ), it suffers from illogical stationarity when, for example, only one time stamp of ancillary

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Joseph T. Ripberger, Hank C. Jenkins-Smith, Carol L. Silva, Deven E. Carlson, and Matthew Henderson

warning issued each day. These estimates are relatively easy to calculate for tornado watches—we simply matched each county that was included in a watch to the most recent (2011) county-level population estimates provided by the U.S. Census Bureau and then aggregated by day (total n = 354 697 498 people; census data available at ). Storm-based warnings, by comparison, do not align with political boundaries (i.e., counties), which made it more

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