Nonstationary Temperature-Duration-Frequency curves

Ouarda, Taha B. M. J.; Charron, Christian

doi:10.1038/s41598-018-33974-y

Cited by 41 publications

(41 citation statements)

References 37 publications

(43 reference statements)

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“…While the analysis so far has focused on individual heatwave metric trends, studies indicate that a multivariate approach considering all metrics in a more comprehensive manner may better represent the full impact of heatwave events (Mazdiyasni et al, 2019; Ouarda & Charron, 2018). Quantifying the likelihood of heatwave events occurring with different intensities and durations can have practical applications.…”

Section: Resultsmentioning

confidence: 99%

Rising Trends in Heatwave Metrics Across Southern California

2020

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Research on heatwaves has gained significant impetus over the past decade due to a warming planet and rapid 21st century urbanization. This study examines driving factors influencing heatwave trends and interannual variability across Southern California (SoCal) from 1950–2020. Inland urban areas of Los Angeles county are the most susceptible to heatwaves with strong increasing trends in frequency, duration, and intensity that are closely tied to nighttime warming. Coastal and rural areas are less impacted but show a significant increase in heatwave frequency over the past two decades. Heatwave nighttime temperatures combined with high humidity have been increasing at a rapid rate of ~1°C/decade since the 1980s—elevating heat stress and mortality risk to vulnerable urban communities. The increased nighttime humidity is associated with an anomalous moisture source off the coast of Baja California that has intensified over the past decade and is linked to ocean warming trends and changes in the California current system. Heatwaves are starting earlier and ending later in the year for urban regions. This augments public health risks and sets the stage for more intense fall wildfires by enhancing the drying of fuels. Droughts and heatwaves are strongly linked, particularly in inland urban and rural areas that have a high statistical probability of heatwaves increasing in frequency (42%), duration (26%), and daily mean temperature (2.2%) during severe drought conditions. Better understanding of heatwave climate drivers and underlying physical processes could help with prediction skill, in addition to providing effective data‐driven recommendations for mitigation efforts in SoCal's vulnerable urban regions.

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Section: Resultsmentioning

confidence: 99%

Rising Trends in Heatwave Metrics Across Southern California

2020

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“…Current metrics evaluate individual heat wave characteristics, such as the hottest day of each year or longest duration of consecutive hot days 7,17,22,29,31,33 . However, current univariate indicators often underestimate the impacts of heat waves because they fail to characterize the extreme event in a comprehensive manner 23,34,35 . The impacts of individual heat wave characteristics can be amplified when considered concurrently (e.g.…”

Section: Introductionmentioning

confidence: 99%

Heat wave Intensity Duration Frequency Curve: A Multivariate Approach for Hazard and Attribution Analysis

Mazdiyasni

Sadegh

Chiang

et al. 2019

Sci Rep

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Atmospheric warming is projected to intensify heat wave events, as quantified by multiple descriptors, including intensity, duration, and frequency. While most studies investigate one feature at a time, heat wave characteristics are often interdependent and ignoring the relationships between them can lead to substantial biases in frequency (hazard) analyses. We propose a multivariate approach to construct heat wave intensity, duration, frequency (HIDF) curves, which enables the concurrent analysis of all heat wave properties. Here we show how HIDF curves can be used in various locations to quantitatively describe the likelihood of heat waves with different intensities and durations. We then employ HIDF curves to attribute changes in heat waves to anthropogenic warming by comparing GCM simulations with and without anthropogenic emissions. For example, in Los Angeles, CA, HIDF analysis shows that we can attribute the 21% increase in the likelihood of a four-day heat wave (temperature > 31 °C) to anthropogenic emissions.

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“…On the other hand, according to climate projections and due to climate change, the probability of heat waves occurring early or late in the season should increase [17,18]). Ouarda and Charron [19] studied over 50 years of heat waves in six stations distributed across the Province of Québec and found a non-negligible trend of the intensity, magnitude, and duration of these events. Another study reported that the number of heat-wave days could increase by up to 13 days in the period 2021 to 2050 and even by up to 40 days in the period 2071 to 2100 in the Iberian Peninsula and the Mediterranean region [20].…”

Section: Introductionmentioning

confidence: 99%

A Heat-Health Watch and Warning System with Extended Season and Evolving Thresholds.

Issa

Chebana

Masselot

et al. 2020

Preprint

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BackgroundMany countries have developed heat-health watch and warning systems (HHWWS) or early-warning systems in an attempt to mitigate the health consequences of extreme heat events. HHWWS usually focus on the four hottest months of the year and impose the same threshold over these months. However, according to climate projections, hot season is expected to extend and/or shift. Some studies demonstrated that health impacts of heat waves are more severe when the human body is not acclimatized to heat. In order to adapt those systems to potential heat waves occurring outside the hottest months of the season, this study proposes specific health-based monthly heat indicators and thresholds over an extended season from April to October in the northern hemisphere. MethodsThe proposed approach, an extension of the HHWWS methodology currently adopted in the province of Quebec, Canada, was developed in the Greater Montreal area (current population 4.3 million) based on historical health and meteorological data over the years. This approach consists of determining excess mortality episodes and then choosing indicators and thresholds that may involve excess mortality.ResultsWe obtain thresholds for the maximum and minimum temperature couple (in °C) that range from (23 and 12, respectively) in April, to (32 and 21) in July and back to (25 and 13) in October. The resulting HHWWS is flexible, with health-related thresholds taking into account the seasonality as well as the monthly variability of temperatures in the threshold definition process for an extended summer season. ConclusionsThis adaptive system has the potential to prevent, by data-driven health alerts, heat-related mortality outside the typical July-August months of heat waves. The proposed methodology is general and can be applied or adapted to other regions and situations.

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Nonstationary Temperature-Duration-Frequency curves

Cited by 41 publications

References 37 publications

Rising Trends in Heatwave Metrics Across Southern California

Rising Trends in Heatwave Metrics Across Southern California

Heat wave Intensity Duration Frequency Curve: A Multivariate Approach for Hazard and Attribution Analysis

A Heat-Health Watch and Warning System with Extended Season and Evolving Thresholds.

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