Preprints
https://doi.org/10.5194/egusphere-2024-322
https://doi.org/10.5194/egusphere-2024-322
04 Apr 2024
 | 04 Apr 2024
Status: this preprint is open for discussion.

Convection-permitting climate model representation of severe convective wind gusts and future changes in southeastern Australia

Andrew Brown, Andrew Dowdy, and Todd P. Lane

Abstract. Previous research has suggested that the frequency and intensity of surface hazards associated with thunderstorms and convection, such as severe convective winds (SCWs), could potentially change in a future climate due to global warming. However, because of the small spatial scales associated with SCWs, they are unresolved in global climate models, and future climate projections are uncertain. Here, we evaluate the representation of SCW events in a convection-permitting climate model (Bureau of Meteorology Regional Projections for Australia, BARPAC-M), run over southeastern Australia for December–February months. We also assess changes in SCW event frequency in a projected future climate for the year 2050, and compare this with an approach based on identifying large-scale environments favourable for SCWs from a regional parent model (BARPA-R). This is done for three different types of SCW events that have been identified in this region, based on clustering of the large-scale environment. Results show that BARPAC-M representation of the extreme daily maximum wind gust distribution is improved relative to the gust distribution simulated by the regional parent model. This is due to the high spatial resolution of BARPAC-M output, as well as partly resolving strong and short-lived gusts associated with convection. However, BARPAC-M significant overestimates the frequency of simulated SCW events, particularly in environments having steep low-level temperature lapse rates. A future decrease in SCW frequency under steep lapse rate conditions is projected by BARPAC-M, along with less frequently favourable large-scale environments. In contrast, an increase in SCW frequency is projected under high surface moisture conditions, with more frequently favourable large-scale environments. Therefore, overall changes in SCWs for this region remain uncertain, due to different responses between event types, combined with historical model biases.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Andrew Brown, Andrew Dowdy, and Todd P. Lane

Status: open (until 08 Jun 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-322', Andreas F. Prein, 27 Apr 2024 reply
  • RC2: 'Comment on egusphere-2024-322', Andreas F. Prein, 27 Apr 2024 reply
Andrew Brown, Andrew Dowdy, and Todd P. Lane

Data sets

Simulated severe convective wind events and environments from the Bureau of Meteorology Atmospheric Regional Projections for Australia (BARPA) Andrew Brown, Andrew Dowdy, Todd P. Lane, Chun-Hsu Su, Christian Stassen, and Harvey Ye https://zenodo.org/records/10521068

Andrew Brown, Andrew Dowdy, and Todd P. Lane

Viewed

Total article views: 220 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
153 52 15 220 21 8 10
  • HTML: 153
  • PDF: 52
  • XML: 15
  • Total: 220
  • Supplement: 21
  • BibTeX: 8
  • EndNote: 10
Views and downloads (calculated since 04 Apr 2024)
Cumulative views and downloads (calculated since 04 Apr 2024)

Viewed (geographical distribution)

Total article views: 206 (including HTML, PDF, and XML) Thereof 206 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 20 May 2024
Download
Short summary
A computer model that simulates the climate of south-eastern Australia is shown here to represent extreme wind events associated with convective storms. This is useful as it allows us to investigate possible future changes in the occurrences of these events, and we find in the year 2050 that our model simulates a decrease in the number of occurrences. However, the model also simulates too many events in the historical climate compared with observations, so these future changes are uncertain.