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Taha B M J Ouarda1, Christian Charron2

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Area of Science:

  • Climatology
  • Extreme weather event analysis
  • Statistical modeling

Background:

  • Persistent extreme heat events are a growing global concern, exacerbated by climate change.
  • Increasing intensity, frequency, and duration of heat waves necessitate advanced analytical tools.
  • Global climate variability modes influence temperature extremes.

Purpose of the Study:

  • To develop a nonstationary approach to Temperature-Duration-Frequency (TDF) curves accounting for climate external forcings.
  • To introduce indices for temporal trends and teleconnections in heat event analysis.
  • To enable adaptive management strategies in public health, safety, and energy sectors.

Main Methods:

  • Development of a nonstationary TDF modeling framework.
  • Integration of indices representing temporal trends and climate teleconnections.
  • A one-step composite likelihood maximization method for model calibration.
  • Application to heat event data from Quebec, Canada.

Main Results:

  • The nonstationary TDF model effectively integrates climate change and climate oscillation information.
  • Atlantic Multidecadal Oscillations (AMO) were found to have a more significant influence on heat events in Quebec than the temporal trend.
  • Demonstrated the importance of considering both long-term trends and climate variability in heat event analysis.

Conclusions:

  • Nonstationary TDF modeling provides crucial insights into heat extreme dynamics.
  • Climate oscillations, such as AMO, play a critical role in modulating heat event characteristics.
  • Findings support enhanced adaptive management strategies for climate-related risks.