the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 19 Dec 2023
GC Insights: Open R-code to communicate the impact of co-occurring natural hazards
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).
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RC1: 'Comment on egusphere-2023-2799', Anonymous Referee #1, 05 Feb 2024
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The paper demonstrates a pragmatic approach to the combination of single-hazard losses. It is laudable to see that the underlying code is open-source and freely available. The paper would have benefited from reviewing existing literature of compounding hazards beyond cited Zscheischler (where I would rather suggest to cite https://doi.org/10.1038/s41558-018-0156-3), e.g. https://zenodo.org/records/7135138, https://doi.org/10.5194/esd-7-659-2016, https://doi.org/10.5194/nhess-22-1487-2022 and https://doi.org/10.1016/j.jenvman.2015.11.011 (most findings also hold rue w/o climate change) and to (if possible) include latest contributions based on event loss tables (e.g. https://eartharxiv.org/repository/view/5286), approaches quite close to the one presented here. In addition to what the paper covers, where r is determined from UKCP ’today’, what about climate change? You could determine the r for different GCMs under select RCPs at time-horizons.... and possibly contribute to physical risk disclosure. Might be worth a few sentences at least as an outlook.
In detail, a few minor points:
line 50: ..analysis with a second pair of commercial risk models… ‘second’ is hard to understand here. It becomes clear once one looks at Figure 1b.line 91: [AON] at the end of the sentence. You state above that the loss table stems from a model run by AON. AON here in brackets cannot be a citation, and with above statement(s) of caution, I do not see any need to reference AON here - what does it exactly stand for? Could it be you only missed to put it in italic font, so it would be a quote as you explain in lines 81-83?
line 96: Co-opetition. UK’s Flood Re is a good example of a public-private-partnership solution that also bears fruits to all market competitors. Might be worth mentioning (especially as you use flood as a demonstrating hazard)
line 104, [AON, Reto Office, Bank]: Again, what does this imply, as it is not in italic, hence does not look like a quote? Is it the entities that endorsed the statement? Did others (e.g. Verisk) not? Would it be an option to clarify this upfront (above, line 81ff, where you make the general statement, add that […] means endorsement of a statement) and the reader would then know how to interpret these listings. And as a minor detail, should it not be Bank of England throughout the text (or you state first time that you will abbreviate).
line 116/117: This statement holds for any tool
Citation: https://doi.org/10.5194/egusphere-2023-2799-RC1
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