Preprints
https://doi.org/10.5194/egusphere-2023-2799
https://doi.org/10.5194/egusphere-2023-2799
19 Dec 2023
 | 19 Dec 2023
Status: this preprint is open for discussion.

GC Insights: Open R-code to communicate the impact of co-occurring natural hazards

John Hillier, Adrian Champion, Tom Perkins, Freya Garry, and Hannah Bloomfield

Abstract. Hydro-meteorological hazard is often estimated by university-based scientists using publicly funded climate models, whilst the ensuing risk quantification uses proprietary insurance sector models, which can inhibit the effective translation of risk-related environmental science into modified practice or policy. For co-occurring hazards, this work proposes as an interim solution open R-code that deploys a metric (i.e., correlation coefficient r) obtainable from scientific research, usable in practice without restricted data (climate or risk) being exposed. This tool is evaluated for a worked example that estimates the impact on joint risk at an annual 1-in-200 year level of wet and windy weather in the UK co-occurring rather than being independent, and the approach can be applied to other multi-hazards and compound events in various sectors (e.g. road, rail, telecommunications).

John Hillier, Adrian Champion, Tom Perkins, Freya Garry, and Hannah Bloomfield

Status: open (until 07 Apr 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-2799', Anonymous Referee #1, 05 Feb 2024 reply
John Hillier, Adrian Champion, Tom Perkins, Freya Garry, and Hannah Bloomfield
John Hillier, Adrian Champion, Tom Perkins, Freya Garry, and Hannah Bloomfield

Viewed

Total article views: 225 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
147 61 17 225 20 13 15
  • HTML: 147
  • PDF: 61
  • XML: 17
  • Total: 225
  • Supplement: 20
  • BibTeX: 13
  • EndNote: 15
Views and downloads (calculated since 19 Dec 2023)
Cumulative views and downloads (calculated since 19 Dec 2023)

Viewed (geographical distribution)

Total article views: 225 (including HTML, PDF, and XML) Thereof 225 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 04 Mar 2024
Download
Short summary
To allow more effective use of climate science this work proposes and evaluates open R-code that deploys a measure of how natural hazards (e.g. extreme wind, flooding) co-occur, obtainable from scientific research, that is usable in practice without restricted data (climate or risk) being exposed. The approach can be applied to hazards in various sectors (e.g. road, rail, telecommunications).