Quantifying damage contributions from convective and stratiform weather types: How well do precipitation and discharge data indicate the risk?

Abstract

Convective precipitation is intensifying in many regions, but potential implications of shifts in precipitation types on impacts have not been quantified. Furthermore, risk assessments often focus on rare extremes, but also more frequent hydro‐meteorological events burden private and public budgets. Here synoptic, hydrological, meteorological, and socio‐economic data are merged to analyse 25 years of damage claims in 480 Austrian municipalities. Exceedance probabilities of discharge and precipitation associated with damage reports are calculated and compared for convective and stratiform weather patterns. During April to November, 60% of claims are reported under convective conditions. Irrespective of the weather type, most of the accumulated cost links to minor hazard levels, not only indicating that frequent events are a highly relevant expense factor, but also pointing to deficiencies in observational data. High uncertainty in damage costs attributable to extreme events demonstrates the questionable reliability of calculating low‐frequency event return levels. Significant differences exist among weather types. Stratiform weather types are up to 10 times more often associated with damaging extreme discharge or precipitation, while convective weather shows the highest nuisance level contributions. The results show that changes in convective precipitation are pertinent to risk management as convective weather types have contributed significantly to damage in the past.

Hailstorms in the Alpine region: Diurnal cycle, 4D‐characteristics, and the nowcasting potential of lightning properties

“…Climatological studies on severe convective weather events are still rare, but can reveal important information relevant to forecasting, such as their substantial contribution to total losses (e.g. Schroeer and Tye, 2019). For severe convective weather and hailstorms in particular, radar data provide one of the most important and reliable sources of observational data.…”

Small Catchment Runoff Sensitivity to Station Density and Spatial Interpolation: Hydrological Modeling of Heavy Rainfall Using a Dense Rain Gauge Network

“…We selected heavy precipitation events observed with the WEGN during the extended summer (May-September) period in 2009-2014 (see also [11]). We first defined rain events with a minimum inter-event time of 6 h [64,65] and then selected the top 10% of the heaviest rainfall events. Finally, for the case studies, the three most extreme, small-scale, short-duration and the three most extreme, large-scale, long-duration events were selected (see also Figure A3 in Appendix A).…”

Changes in convective and stratiform precipitation over the Tibetan Plateau projected by global and regional climate models

“…According to different precipitation types, precipitations can be categorized into convective and stratiform precipitation, as these two types of precipitation was thought to be formed by different precipitation growth mechanisms with very different mass and heating profiles (Dai, 2006; Houze, 1997; Schumacher et al, 2004). Several studies have reported historical convective and stratiform precipitation changes based on the observational data, and these results are beneficial for the understanding of cloud dynamics, cloud microphysics, distributions of precipitation latent heat release and their relationships with atmospheric circulations at the regional scales (Fu et al, 2017; Schroeer & Tye, 2018; Schumacher & Houze, 2006; Yu et al, 2010). For example, the convective precipitation responded more sensitively the changes in surface temperature than stratiform precipitation based on observational data, as it is influenced by both thermodynamic and dynamic processes (Berg et al, 2013; Loriaux et al, 2013).…”