Quantifying Hail and Lightning Risk Factors Using Long‐Term Observations Around Australia

Abstract

There is a growing need to better understand and quantify risks associated with extreme weather, including severe thunderstorm-related hazards such as hail and lightning. Hail occurrence based on a long-term archive of radar observations is presented for the first time in many temperate and subtropical regions of Australia, together with lightning observations from a ground-based network of sensors. Mean monthly and hourly occurrence frequencies are examined for hail and lightning. Environmental conditions obtained from hourly reanalysis data indicate stronger wind shear on average for hail than lightning. The environmental conditions also indicate higher freezing levels on average for lightning than hail. These environmental differences provide plausible physical reasons for observed differences between hail and lightning climatology through the year. The study results are intended to help inform future planning and preparedness for thunderstorm-related risks, including for severe weather forecasting and climate risk applications. Plain Language Summary Natural hazards caused by thunderstorms, such as hail and lightning, can have severe impacts on society. Radar data are used to examine hail events at 10 Australian locations, and comparisons are made with lightning observations. Results are averaged over several years to calculate average annual values, including for the hourly and the monthly number of the hail and the lightning events. We find differences between hail and lightning events in the environmental conditions that they occur in. These environmental differences are found to help explain differences through the year in the average risk of occurrence of hail or lightning. The results are intended to enhance resilience in relation to thunderstorm-related risks and provide guidance for extreme weather modeling and climate adaptation purposes.

An Object-based Climatology of Precipitation Systems in Sydney, Australia

“…Using an atmospheric general circulation model, Ashok et al (2003) showed that IOD has significant negative partial correlations with rainfall over the western and southern regions of Australia. Dowdy et al (2020) employed ERA-Interim data along with lightning and rainfall observations to examine the influence of large-scale drivers such as the ENSO, IOD and SAM on thunderstorm activities over Australia, finding no strong relations between them, consistent with findings of Allen and Karoly (2014). In another reanalysis-based study, Hauser et al (2020) investigated the winter-spring rainfall variability in southeastern Australia (SEA) during El Niño events by quantifying the contribution of clustered mid-latitude weather systems to monthly precipitation anomalies.…”

“…For instance, Warren et. al (2020) studied the hail climatology in multiple cities in Australia (including the Sydney region) using a radar-based hail product (Maximum Expected Size of Hail;MESH;(Witt et al 1998)), and found that, on average, damaging hail storms over Sydney occur 32 days per year with a peak during the warm season (November-March), consistent with the findings of similar study by Dowdy et al (2020). Similar radar-based studies have been conducted over other parts of the globe like Europe (Junghänel et al 2016;Nisi et al 2016;Fluck et al 2021;Lukach et al 2017;Saltikoff et al 2010) and the United States (Cintineo et al 2012;Murillo et al 2021).…”

“…This study uses data from a Bureau of Meteorology operational S-band weather radar located near Wollongong, NSW (34.26° S, 150.88° E, 471 m altitude; (Soderholm et al 2020)). The site experiences partial blocking up to 3 dB in the lowest scan (0.5° elevation) from the northwest to the southeast due to the significant terrain associated with the Great Dividing Range.…”

The differing role of weather systems in southern Australian rainfall between 1979–1996 and 1997–2015

“…These verification statistics as detailed in Dowdy (2020) demonstrate that this dataset of thunderstorm environments performs well against observations. While thunderstorm environments are most common in the warmer months, they can occur at any time of year, with wind shear playing a larger role in some low-CAPE environments during the cooler months of the year (Dowdy et al 2020).…”

An object-based climatology of precipitation systems in Sydney, Australia

“…RxorzJ Using coarse-resolution datasets, previous authors have tried to investigate the effect of natural climate variability (e.g., El Niño-Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD)) and Southern Annular Mode (SAM) on the rainfall over Australia (Ashok et al 2003;Hauser et al 2020). Dowdy et al (2020) employed ERA-Interim data along with lightning and rainfall observations to examine the influence of large-scale drivers such as the ENSO, IOD and SAM on thunderstorm activities over Australia, finding no strong relations between them, consistent with findings of Allen and Karoly (2014). Since precipitation in some regions can be correlated with more than one large-scale driver, and indices are often correlated with each other, some studies such as Maher and Sherwood (2014) used a multivariate rather than bivariate approach to this problem.…”