Circulation analogues and uncertainty in the time-evolution of extreme event probabilities: evidence from the 1947 Central European heatwave

Abstract

The science of extreme event attribution has rapidly expanded in recent years, with numerous studies dedicated to determining whether and to what extent anthropogenic climate change has increased the likelihood of specific extreme weather events occurring. However, the majority of such studies have focussed on extreme events which have occurred in the recent past (usually within the past 10 years) while minimal research efforts have considered the multitude of high-impact extreme climatic events which occurred throughout the instrumental record. This study proposes a framework to quantify how the likelihood of witnessing meteorological characteristics reminiscent of the 1947 Central European heatwave have evolved over time. We specifically examine circulation analogues as a tool to understand the relative role of dynamical and thermodynamic contributions to changes in the probability of experiencing similar heatwave events. Using a reanalysis-based dataset, our results show changes in the frequency of 1947-like extreme heat throughout the twentieth century to be highly sensitive to methodological choices, particularly in the context of disaggregating dynamic and thermodynamic changes in the risk of extreme heat. Evidence also suggests clear decadal variability in the occurrence of circulation patterns conducive to the 1947 heatwaves. Finally, we discuss how to appropriately consider the time-evolution of attribution statements, as well as the broader limitations of employing circulation analogues as a method to interrogate the dynamical contribution to the probability ratio of an extreme event.

Atmospheric tropical modes are important drivers of Sahelian springtime heatwaves

“…The significance of the modulation patterns is tested at each grid-point and for each phase of the modes through bootstrap resampling (Wang et al 2008;Mazdiyasni and AghaKouchak 2015;Nissan et al 2017;Harrington et al 2019). Let N be the number of days where a given mode is in phase × (or one mode in phase × and another in phase y for the superposition case).…”

Concurrent Hydroclimatic Hazards from Catchment to Global Scales

“…However, since the sc_PDSI_pm dataset is computed by making use of temperature and precipitation data, both dynamical and thermodynamic changes in the large-scale atmospheric configuration (e.g. Harrington et al, 2019;Pfahl et al, 2017) can affect the spatiotemporal patterns of sc_PDSI_pm wet and dry extremes. This implies for example that storm tracks, blocking, localised convection, along with the increased water-holding capacity of the atmosphere due to warmer temperatures (Trenberth, 2011) may have played a role in shaping the observed predominance of wet and dry extremes.…”

Amplified Risk of Compound Heat Stress-Dry Spells in Urban India

“…Further, the definition of heatwaves as adopted here and also followed elsewhere (Mazdiyasni et al, 2019;Ouarda & Charron, 2018;Saeed et al, 2021), allows modeling of annual occurrence probability of consecutive warm days and resulting dry spells associated with this event. While subjective, the choice of the 2 to 10-day time window for analyzing heat stress, is typically followed in the literature (Khaliq et al 2005;Mazdiyasni et al 2019;Harrington et al 2019). Recently, Harrington et al (2019) have chosen a continuous 12-day period in the middle of the summer to define the '1947 heatwave' over central Europe during which temperature was found to be persistently high with a similar circulation state throughout.…”

“…While subjective, the choice of the 2 to 10-day time window for analyzing heat stress, is typically followed in the literature (Khaliq et al 2005;Mazdiyasni et al 2019;Harrington et al 2019). Recently, Harrington et al (2019) have chosen a continuous 12-day period in the middle of the summer to define the '1947 heatwave' over central Europe during which temperature was found to be persistently high with a similar circulation state throughout. Further, in south Asia, atmospheric patterns during heatwaves are often linked to large-scale blocking in mid-latitudes that may persist several consecutive days to weeks (Li et al 2019;Min et al 2020), which justifies our choice of a 10day time window to define the evolution of heatwaves.…”