9 Evaluation of Severe Weather Diagnostic Variables as Forecast Parameters

Tuesday, 6 August 2013
Holladay-Halsey (DoubleTree by Hilton Portland)
Chad M. Shafer, Univ. of South Alabama, Mobile, AL; and M. W. Stanford, C. B. Hulsey, and A. N. Kabeiseman

Severe weather diagnostic variables (SWDVs) are used commonly as forecast parameters (variables valid presently that are used to forecast various phenomena up to several hours in advance of their occurrence). Several SWDVs are tested to determine (1) how far in advance the variables exhibit skill identifying locations in which severe weather of various types occur, (2) the relative skill with which these locations are identified, and (3) the trends in probabilities of severe weather given the same magnitude of the SWDV with increasing forecast length. North American Regional Reanalysis data are used to obtain spatial fields of the SWDVs from 2001–2010. Practically perfect probabilities of severe weather are determined using the SPC severe weather database for 6-, 3-, and 1-h time windows. A probability is assigned to the SWDV magnitude based on the skill with which it identifies locations that meet or exceed the given probability. Preliminary findings suggest several SWDVs exhibit skill in identifying locations with severe weather up to 6 hours after they are analyzed, most SWDVs that combine thermodynamic instability and vertical wind shear exhibit relatively similar skill, and probabilities of severe weather rapidly decrease with increasing time between analysis and observation of severe weather.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner