Learning from the 2018 heatwave in the context of climate change: are high-temperature extremes important for adaptation in Scotland?

Undorf, Sabine; Allen, Kathleen; Hagg, Joseph; Li, Sihan; Lott, Fraser C.; Metzger, Marc J.; Sparrow, Sarah; Tett, Simon F. B.

doi:10.1088/1748-9326/ab6999

Cited by 12 publications

(9 citation statements)

References 28 publications

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“…Climate change is unmistakeably evident in Scotland, with average temperatures between 2011–2020 being 0.9 °C warmer than the 1961–1990 average [ 54 ]. The mean temperature in Scotland is projected to continue rising with heatwaves projected to become more frequent [ 71 , 94 ], yet little is known about the impacts of high temperatures on human health in Scotland. Even though England has had a Heatwave Plan and Heat-Health Warning System in operation for almost 20 years now [ 85 ], there are still no such measures in the devolved countries of the UK, including Scotland.…”

Section: Introductionmentioning

confidence: 99%

Temperature-related mortality and associated vulnerabilities: evidence from Scotland using extended time-series datasets

et al. 2022

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Background Adverse health impacts have been found under extreme temperatures in many parts of the world. The majority of such research to date for the UK has been conducted on populations in England, whilst the impacts of ambient temperature on health outcomes in Scottish populations remain largely unknown. Methods This study uses time-series regression analysis with distributed lag non-linear models to characterise acute relationships between daily mean ambient temperature and mortality in Scotland including the four largest cities (Aberdeen, Dundee, Edinburgh and Glasgow) and three regions during 1974–2018. Increases in mortality risk under extreme cold and heat in individual cities and regions were aggregated using multivariate meta-analysis. Cold results are summarised by comparing the relative risk (RR) of death at the 1st percentile of localised temperature distributions compared to the 10th percentile, and heat effects as the RR at the 99th compared to the 90th percentile. Results Adverse cold effects were observed in all cities and regions, and heat effects were apparent in all cities and regions except northern Scotland. Aggregate all-cause mortality risk in Scotland was estimated to increase by 10% (95% confidence interval, CI: 7%, 13%) under extreme cold and 4% (CI: 2%, 5%) under extreme heat. People in urban areas experienced higher mortality risk under extreme cold and heat than those in rural regions. The elderly had the highest RR under both extreme cold and heat. Males experienced greater cold effects than females, whereas the reverse was true with heat effects, particularly among the elderly. Those who were unmarried had higher RR than those married under extreme heat, and the effect remained after controlling for age. The younger population living in the most deprived areas experienced higher cold and heat effects than in less deprived areas. Deaths from respiratory diseases were most sensitive to both cold and heat exposures, although mortality risk for cardiovascular diseases was also heightened, particularly in the elderly. Cold effects were lower in the most recent 15 years, which may be linked to policies and actions in preventing the vulnerable population from cold impacts. No temporal trend was found with the heat effect. Conclusions This study assesses mortality risk associated with extreme temperatures in Scotland and identifies those groups who would benefit most from targeted actions to reduce cold- and heat-related mortalities.

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Section: Introductionmentioning

confidence: 99%

Temperature-related mortality and associated vulnerabilities: evidence from Scotland using extended time-series datasets

et al. 2022

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“…Similarly, research by King et al (2015) showed that w@h ANZ model simulations indicated a rise of hot and extreme hot days in November by at least 25 and 44%, respectively, in Brisbane. Numerous attribution studies from different parts of the world using w@h ensembles also identify the effects of anthropogenic forcing on extreme temperature events, such as Vautard et al (2020) and Undorf et al (2020) for European heat events, Philip et al (2018) in the United States and (Sparrow et al, 2018;Van Oldenborgh et al, 2018;Min et al, 2020) for different regions over Asia.…”

Section: Discussionmentioning

confidence: 99%

Increasing temperature extremes in New Zealand and their connection to synoptic circulation features

Thomas

McDonald

Renwick

et al. 2022

Intl Journal of Climatology

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Extreme temperature events (ETEs) have evolved alongside the warming climate over most parts of the world. This study provides a statistical quantification of how human influences have changed the frequencies of extreme temperatures in New Zealand, depending on the synoptic weather types. We use the ensembles under pre‐industrial conditions (natural scenarios with no human‐induced changes) and present‐day conditions (anthropogenic scenarios) from the weather@home regional climate model. The ensemble simulations under these two scenarios are used to identify how human influences have impacted the frequency and intensity of extreme temperatures based on their connection to different large‐scale circulation patterns derived using self‐organizing maps (SOMs). Over New Zealand, an average two to three fold rise in frequencies of extremes occurs irrespective of seasons due to anthropogenic influence with a mean temperature increase close to 1°C. For some synoptic situations, the frequency of extremes are especially enhanced; in particular, for low‐pressure centres to the northeast of New Zealand where the frequency of occurrence of daily temperature extremes has increased by a factor of 7 between anthropogenic and natural ensembles for the winter season, though these synoptic patterns rarely occur. For low‐pressure centres to the northwest of New Zealand, we observe high temperatures frequently in both anthropogenic and natural ensembles which we expect is probably associated with warm air advection from the Tropics. The frequency of occurrence of high temperatures in these synoptic patterns has also increased by a factor of 2 between the natural and anthropogenic ensembles. For these synoptic states, the extremes are observed in the North Island and along the east coast of the country with the highest temperature along the Canterbury coast and Northland. The change between the natural and anthropogenic ensembles is largest on the west coast along the Southern Alps for all the synoptic circulation types.

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“…The speed at which the overall trend declines within these regions increases until late 2017, where it continues to rapidly decrease at the same pace. This could be a result of extreme weather events during 2017 and 2018 from which the peatland has yet to recover (Fenner and Freeman, 2011;Stirling et al, 2020;Undorf et al, 2020). If the trend gradients were included in the clustering, a different region, which may not have exhibited such weather events, with different trend gradients would be classed as degraded when compared to the Flow Country.…”

Section: Discussionmentioning

confidence: 99%

Object oriented data analysis of surface motion time series in peatland landscapes

Mitchell¹,

Dryden²,

Fallaize³

et al. 2022

Preprint

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Peatlands account for 10% of UK land area, 80% of which are degraded to some degree, emitting carbon at a similar magnitude to oil refineries or landfill sites. A lack of tools for rapid and reliable assessment of peatland condition has limited monitoring of vast areas of peatland and prevented targeting areas urgently needing action to halt further degradation. Measured using interferometric synthetic aperture radar (InSAR), peatland surface motion is highly indicative of peatland condition, largely driven by the eco-hydrological change in the peatland causing swelling and shrinking of the peat substrate. The computational intensity of recent methods using InSAR time series to capture the annual functional structure of peatland surface motion becomes increasingly challenging as the sample size increases. Instead, we utilize the behavior of the entire peatland surface motion time series using object oriented data analysis to assess peatland condition. In a Gibbs sampling scheme, our cluster analysis based on the functional behavior of the surface motion time series finds features representative of soft/wet peatlands, drier/shrubby peatlands and thin/modified peatlands align with the clusters. The posterior distribution of the assigned peatland types enables the scale of peatland degradation to be assessed, which will guide future cost-effective decisions for peatland restoration.

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Learning from the 2018 heatwave in the context of climate change: are high-temperature extremes important for adaptation in Scotland?

Cited by 12 publications

References 28 publications

Temperature-related mortality and associated vulnerabilities: evidence from Scotland using extended time-series datasets

Temperature-related mortality and associated vulnerabilities: evidence from Scotland using extended time-series datasets

Increasing temperature extremes in New Zealand and their connection to synoptic circulation features

Object oriented data analysis of surface motion time series in peatland landscapes

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