Development of a calibrated proxy for thunderstorm occurrence using reanalysis and lightning data

We would like to model the occurrence of severe convective weather events such as large hail, tornadoes and severe wind gusts using climate models and reanalysis data. To do so one can use predictors such as CAPE and shear-related parameters. The big unknown of such an approach is the factor of convective initiation. Storms may not occur even though the atmosphere is in an area of CAPE/shear space that would support severe storms once initiated. We would like to take convective initiation explicitly into account. The probability of a severe storm is the product of the probability that a storm forms and the likelihood of it becoming severe:

P(severe storm) = P(storm initiation) x P(severe|storm initiation)

Our main goal is to find the best function P(storm initiation) in order to improve P(severe storm). To that aim we calculated several parameters related to instability, moisture or shear in Central Europe in the time period 2007-2013 from the ERA-Interim global atmospheric reanalysis. We investigated the relation between these parameters and the lightning occurrence using data from the EUropean Cooperation for LIghtning Detection (EUCLID).

Our results include the following three findings:

First, higher lightning probabilities can be observed with increasing CAPE values with a saturation, or even slight decrease setting in from approximately 800 J/kg, followed by strong increase at values in excess of 2500 J/kg.

Second, for a given CAPE value, lightning probability is relatively large both for very low (< 5 m/s) and high values (> 15 m/s) of 0-6 km bulk shear. Apparently there are two shear regimes that favor storm initiation and/or sustenance.

Last, high CAPE and low CIN values combine to highest lighting probabilities whereas for small CAPE values, higher probabilities are found in midrange CIN values. Last, lightning probabilities are highest for large CAPE and small CIN values but for small CAPE values, higher probabilities are found in midrange CIN values.