On the Measurement of Heat Waves

Perkins, S. E.; Alexander, Lisa V.

doi:10.1175/jcli-d-12-00383.1

Cited by 867 publications

(790 citation statements)

References 42 publications

(64 reference statements)

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“…Metrics used to represent the selected climate hazards are crucial for the resulting impact scenarios: changes in return periods depend on the time scale selected to characterize an event type, e.g. 1-day temperature extremes, weekly heatwaves or seasonal heat anomalies experience different changes in return periods (Perkins and Alexander 2012;Trenberth et al 2014). In our approach we focus on hazard-specific metrics of impact relevance that have been documented in recent literature.…”

Section: Sources Of Uncertaintymentioning

confidence: 99%

Multi-hazard assessment in Europe under climate change

et al. 2016

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While reported losses of climate-related hazards are at historically high levels, climate change is likely to enhance the risk posed by extreme weather events. Several regions are likely to be exposed to multiple climate hazards, yet their modeling in a joint scheme is still at the early stages. A multi-hazard framework to map exposure to multiple climate extremes in Europe along the twenty-first century is hereby presented. Using an ensemble of climate projections, changes in the frequency of heat and cold waves, river and coastal flooding, streamflow droughts, wildfires and windstorms are evaluated. Corresponding variations in expected annual exposure allow for a quantitative comparison of hazards described by different process characteristics and metrics. Projected changes in exposure depict important variations in hazard scenarios, especially those linked to rising temperatures, and spatial patterns largely modulated by local climate conditions. Results show that Europe will likely Climatic Change (2016)

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Section: Sources Of Uncertaintymentioning

confidence: 99%

Multi-hazard assessment in Europe under climate change

et al. 2016

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“…Perkins and Alexander (2013), Min et al (2013) and Alexander and Arblaster (2009) have explored the effect of ENSO on the distribution of annual and seasonal maxima temperatures in Australia. They fit the generalised extreme value distribution with covariates in the location and scale parameters and map return level estimates over sites to produce spatial plots.…”

Section: Introductionmentioning

confidence: 99%

Modelling the effect of the El Niño-Southern Oscillation on extreme spatial temperature events over Australia

Winter¹,

Tawn²,

Brown³

2016

Ann. Appl. Stat.

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When assessing the risk posed by high temperatures, it is necessary to consider not only the temperature at separate sites but also how many sites are expected to be hot at the same time. Hot events that cover a large area have the potential to put a great strain on health services and cause devastation to agriculture, leading to high death tolls and much economic damage. South-eastern Australia experienced a severe heatwave in early 2009; 374 people died in the state of Victoria and Melbourne recorded its highest temperature since records began in 1859 (Nairn and Fawcett, 2013). One area of particular interest in climate science is the effect of large scale climatic phenomena, such as the El Niño-Southern Oscillation (ENSO), on extreme temperatures. Here, we develop a framework based upon extreme value theory to estimate the effect of ENSO on extreme temperatures across Australia. This approach permits us to estimate the change in temperatures with ENSO at important sites, such as Melbourne, and also whether we are more likely to observe hot temperatures over a larger spatial extent during a particular phase of ENSO. To this end, we design a set of measures that can be used to effectively summarise many important spatial aspects of an extreme temperature event. These measures are estimated using our extreme value framework and we validate whether we can accurately replicate the 2009 Australian heatwave, before using the model to estimate the probability of having a more severe event than has been observed.

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“…A heatwave is typically defined as a period of consecutive extremely hot days (22,23), such as five consecutive days with temperature above the 90th percentile. Here, we use the 85th, 90th, and 95th percentiles of the warm season (May-October) temperature as extreme thresholds, and three heatwave durations (3 d, 5 d, and 7 d).…”

mentioning

confidence: 99%

Substantial increase in concurrent droughts and heatwaves in the United States

Mazdiyasni

AghaKouchak

2015

Proc. Natl. Acad. Sci. U.S.A.

508

311

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A combination of climate events (e.g., low precipitation and high temperatures) may cause a significant impact on the ecosystem and society, although individual events involved may not be severe extremes themselves. Analyzing historical changes in concurrent climate extremes is critical to preparing for and mitigating the negative effects of climatic change and variability. This study focuses on the changes in concurrences of heatwaves and meteorological droughts from 1960 to 2010. Despite an apparent hiatus in rising temperature and no significant trend in droughts, we show a substantial increase in concurrent droughts and heatwaves across most parts of the United States, and a statistically significant shift in the distribution of concurrent extremes. Although commonly used trend analysis methods do not show any trend in concurrent droughts and heatwaves, a unique statistical approach discussed in this study exhibits a statistically significant change in the distribution of the data.

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On the Measurement of Heat Waves

Cited by 867 publications

References 42 publications

Multi-hazard assessment in Europe under climate change

Multi-hazard assessment in Europe under climate change

Modelling the effect of the El Niño-Southern Oscillation on extreme spatial temperature events over Australia

Substantial increase in concurrent droughts and heatwaves in the United States

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