A real-time automated method to determine forecast confidence associated with tornado warnings
John L. Cintineo, CIMMS/Univ. of Oklahoma, Norman, OK; and T. M. Smith, V. Lakshmanan, and K. L. Ortega
This presentation describes the use of severe weather products derived from the coterminous United States (CONUS) radar network and model analysis fields to determine the confidence-level of National Weather Service-issued tornado warnings. Severe weather attributes such as low-level shear, reflectivity at -20C and the size of the convective core were extracted (within the geographic and temporal extent of the warning polygons) from the real-time grids produced by the Warning Decision Support System -- Integrated Information (WDSS-II). The initial values of these severe weather parameters at the time the warning was issued were used to determine the conditional probability that a tornado would occur within the spatial and temporal bounds of the warning. The results are based on NWS tornado warnings from May and July of 2008, and also based on verification data from the Storm Prediction Center's storm data, which were preliminary at the time the analysis was performed. Conditional probabilities are shown from two products: 0-2km azimuthal shear, and vertically integrated liquid. Once a warning is issued, it is possible to use this conditional probability to objectively assign a confidence value with the warning in real-time.
Extended Abstract (292K)
Session 4B, Applications in Meteorology, Oceanography, Hydrology and Climatology
Tuesday, 13 January 2009, 8:30 AM-9:45 AM, Room 122BC
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