Multivaried Index DCPIM (Deep Convection Process Identification Model) to forecasting and hailstorm clouds seeding operative decision

It is well known that severe convection conditions are determined mainly by the vertical thermodynamic structure of the atmosphere and its evolution. In any hail mitigation operational program these data should be updated continuously in order to make better reassessment of decision-making situations, but this is practically impossible, because of the high cost of radiosondes. Motivated by these limitations, a new index has been developed in order to make operational decisions cheaper, faster and more efficient. This index is constructed based on surface meteorological data that are correlated with the deep convection process.

The multivaried index is defined as:

DCPIM = 3.(- 0,00118887.P + 0,0372169.R + 0,057063.T - 0,0546601.UV)

Where P is the surface pressure in mb., R is the Dew Point in ºC at ground level , T is the temperature in ºC at the surface level and UV is the ultraviolet solar radiation index.

A data set of almost 1700 elements has been used to define a multiple regression model which has an excellent statistical adjust (P-value = 0).

The validation of this index has been carried out during the 2006-2007 hail season in Mendoza (Argentina). The obtained results were in very good agreement with the kind of deep convective events occurred in Mendoza.