Yilian Martínez Rodríguez


This paper describes the concept of the proper use of diagnostic variables in severe hail storm forecasting. The utility of 5 diagnostic variables as forecast parameters is discussed. The database was gathered from atmospheric soundings from hail storms identifi ed during the period 1981-1996 in Camagüey. We have used Multivariate Analysis techniques to discriminate between hail occurrence (C) and non-hail occurrence (NC) environments. Applying those methods on one aleatory sample selected before. Hindcasting the hail events based upon height of the wet bulb zero thresholds produced the highest probability of detection (POD) with 85% and the lowest false alarm ratio (FAT): 15%. Finally, although the current sample size is limited and the conclusions drawn from it should be considered preliminary, it appears may be able to use thermodynamics conditions to distinguish days on which there is a higher threat of storms producing hail.


Thermodynamic forecast parameters, severe hail storms


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