Detecting Severe Weather Trends Using an Additive Regressive Convective Hazard Model (AR-CHaMo)

Abstract

A statistical model for the occurrence of convective hazards was developed and applied to reanalysis data to detect multidecadal trends in hazard frequency. The modeling framework is based on an additive logistic regression for observed hazards that exploits predictors derived from numerical model data. The regression predicts the probability of a severe hazard, which is considered as a product of two components: the probability that a storm occurs and the probability of the severe hazard, given the presence of a storm [P(severe) 5 P(storm) 3 P(severejstorm)]. The model was developed using lightning data as an indication of thunderstorm occurrence and hazard reports across central Europe. Although it uses only two predictors per component, it is capable of reproducing the observed spatial distribution of lightning and yields realistic annual cycles of lightning, hail, and wind fairly accurately. The model was applied to ERA-Interim (1979 across Europe to detect any changes in lightning, hail, and wind hazard occurrence. The frequency of conditions favoring lightning, wind, and large hail has increased across large parts of Europe, with the exception of the southwest. The resulting predicted occurrence of 6-hourly periods with lightning, wind, and large hail has increased by 16%, 29%, and 41%, respectively, across western and central Europe and by 23%, 56%, and 86% across Germany and the Alps during the period considered. It is shown that these changes are caused by increased instability in the reanalysis rather than by changes in midtropospheric moisture or wind shear.

Investigation of the temporal variability of thunderstorms in central and western Europe and the relation to large‐scale flow and teleconnection patterns

“…Overall, a positive gradient in WMILX frequency is identified both in north‐to‐west and west‐to‐east directions, that is, along the coastlines of the North Atlantic and the Baltic Sea. This general distribution of convective environments is confirmed by similar studies based on reanalysis (Mohr et al ., ; Prein and Holland, ; Rädler et al ., ; Taszarek et al ., ), lightning (PK17; Taszarek et al ., ), and satellite (Punge et al ., ) data. However, there are major differences in the area of the Alps and their surroundings, mainly because orographically induced circulations and resulting convergence zones, which are mainly relevant for the triggering of convection, are not sufficiently resolved by the coastDat‐2 reanalysis.…”

“…Piper, ). This increase of convection‐favouring conditions for thunderstorm or hail development since the 1980s has been already observed by other studies (Kapsch et al ., ; Mohr and Kunz, ; Rädler et al ., ).…”

Relationship between atmospheric blocking and warm‐season thunderstorms over western and central Europe

“…; Rädler et al . ). Due to its persistence, blocking might contribute to improved thunderstorm potential predictability on sub‐seasonal time scales beyond the classical weather forecast time scale of a few days, and complement current activities that investigate the connection of water vapour transport on the sub‐seasonal predictability of extremes (e.g., Lavers et al .…”

“…In contrast to teleconnection patterns, which capture the annual variability, atmospheric blocking affects the prevailing (stationary) environmental conditions, such as atmospheric stability and the moisture content of air masses. Nevertheless, blocking is not suitable as a single predictor for convection; other approaches should be pursued for this purpose (e.g., Doswell et al, 1996;Sánchez et al, 2009;Mohr et al, 2015b;Púčik et al, 2015;Rädler et al, 2018). Due to its persistence, blocking might contribute to improved thunderstorm potential predictability on sub-seasonal time scales beyond the classical weather forecast time scale of a few days, and complement current activities that investigate the connection of water vapour transport on the sub-seasonal predictability of extremes (e.g., Lavers et al, 2016aLavers et al, , 2016bPasquier et al, 2018).…”

“…Additionally, we investigate DLS during both blocking situations because high DLS values are often related to severe convective weather such as (large) hailstorms, severe wind gusts or tornadoes in Europe (Brooks et al, 2003;Púčik et al, 2015;Rädler et al, 2018;Kunz et al, 2019). Strong vertical wind shear enables longer storm lifetime and supports organised convective systems and thus storm severity (Markowski and Richardson, 2010).…”