2011
DOI: 10.1007/s10584-011-0370-8
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Climate change: a new metric to measure changes in the frequency of extreme temperatures using record data

Abstract: Consensus on global warming is the result of multiple and varying lines of evidence, and one key ramification is the increase in frequency of extreme climate events including record high temperatures. Here we develop a metriccalled "record equivalent draws" (RED)-based on record high (low) temperature observations, and show that changes in RED approximate changes in the likelihood of extreme high (low) temperatures. Since we also show that this metric is independent of the specifics of the underlying temperatu… Show more

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Cited by 11 publications
(13 citation statements)
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“…Lower, night time temperatures and atmospheric components are employed as they are the best indicators for local climate change (Davy et al 2016), and in particular, because they show the least day-to-day variation (Munasinghe et. al.…”
Section: Methodsmentioning
confidence: 99%
“…Lower, night time temperatures and atmospheric components are employed as they are the best indicators for local climate change (Davy et al 2016), and in particular, because they show the least day-to-day variation (Munasinghe et. al.…”
Section: Methodsmentioning
confidence: 99%
“…More frequent and prolonged drought periods combined with elevated air temperatures are to be expected (Jentsch and Beierkuhnlein 2008;Lintner et al 2012;Munasinghe et al 2012). As a consequence, average and peak leaf temperatures of tropical plants will increase.…”
Section: Introductionmentioning
confidence: 99%
“…Due to the distributional invariance, simplicity of underlying concepts, and frequently striking results, e.g., Meehl et al (2009), the use of record-breaking events (records) in analysis of temperature trends has become more widespread in the past decade, e.g., Benestad (2004), Redner and Petersen (2006), Newman et al (2010), Wergen and Krug (2010), Munasinghe et al (2011), Rahmstorf and Coumou (2011), and Rowe and Derry (2012). By way of brief summary, the statistics are based on the following result: for a time series with independent and identically distributed values from a continuous distribution, X = x 1 , x 2 , x 3 .…”
Section: Introductionmentioning
confidence: 99%