A review of early severe weather applications of high‐resolution regional reanalysis in Australia

Abstract

High‐resolution regional reanalysis datasets have the potential to provide valuable guidance to emergency management agencies, highlighting areas at risk of severe weather, including estimates of return periods of various hazardous weather phenomena. The BARRA regional reanalysis for Australia comprises a reanalysis for a broad region around Australia at moderately high spatial and temporal resolution (12 km/hourly), together with four subdomains at high resolution (1.5 km/1 h). Here, we document four applications of BARRA developed for emergency management: optimal placement of portable automatic weather stations for fire weather monitoring; climatology of low‐level wind shear conducive to cool‐season tornadogenesis; development of rainfall intensity–frequency–duration curves based on the gridded reanalysis data; and development of a climatology across Australia of parameters associated with severe thunderstorm occurrence.

Weather, Vol. 79, no. 6, June 2024, pp. 174‐204

“…The spatially varying estimated return period can then be utilised to produce an estimated event return period (Figure 5). High-resolution reanalysis data has previously been used to estimate return periods for extreme weather events (Della-Marta et al, 2009;Fox-Hughes et al, 2022). However, the calculation of rainfall return period is nontrivial, requiring consideration of data resolution, record length and climate change (Buishand et al, 2008;Milly et al, 2008;Griffin et al, 2019;Poschlod et al, 2021;Slater et al, 2021).…”

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“…The spatially varying estimated return period can then be utilised to produce an estimated event return period (Figure 5). High‐resolution reanalysis data has previously been used to estimate return periods for extreme weather events (Della‐Marta et al ., 2009; Fox‐Hughes et al ., 2022). However, the calculation of rainfall return period is non‐trivial, requiring consideration of data resolution, record length and climate change (Buishand et al ., 2008; Milly et al ., 2008; Griffin et al ., 2019; Poschlod et al ., 2021; Slater et al ., 2021).…”