Investigating ground-based radar and spaceborne infrared radiometer synergy for lightning areal prediction in complex orography

Abstract

A new multi-sensor approach, named PoLCast (Probability of Lightning foreCast), for predicting the lightning activity in a complex orography geographical area is proposed and discussed. The PoLCast input information are the ground-based weather radar horizontally polarized reflectivity factor and the atmospheric instability indexes, derived from the Spin Enhanced Visible Infrared Imager (SEVIRI) radiometer onboard the Meteosat Second Generation (MSG) satellite. The weather radar data are used to calculate the probability of lightning following a direct relation between the maximum values of the reflectivity factor and the lightning occurrence, whereas the atmospheric instability indexes from SEVIRI are used to constrain the probability of lighting, derived from weather radar data, and enhance such probability in cases of more unstable troposphere. To test the PoLCast methodology, the output of the Blitzortung and the “Sistema Italiano Rilevamento Fulmini” (SIRF) ground-based lightning sensor networks are used together with the C-band Mt. Midia weather radar within its 180 km diameter coverage over the Central Italy area. Both satellite and radar data are pre-processed into PoLCast to obtain a single time series in terms of the areal probability of lightning (PoL). PoLCast performances are evaluated in terms of statistical scores using 12 heterogeneous case studies over Central Italy. Even though the number of available cases is relatively limited, quantitative results show high areal PoL (from 0 to 100%) with a case-by-case variability of false alarm rate from 3 to 72%. The advantage of a multi-sensor technique, such as PoLCast, with respect to an approach using weather radar data only, becomes more evident when lightning activity is not present and the leading time of lightning forecast exceeds 2.5 h.