Defining and predicting heat waves in Bangladesh

Hannah Nissan*, Katrin Burkart, Erin Coughlan de Perez, Maarten Van Aalst, Simon Mason

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

19 Citations (Scopus)

Abstract

This paper proposes a heat-wave definition for Bangladesh that could be used to trigger preparedness measures in a heat early warning system (HEWS) and explores the climate mechanisms associated with heat waves. A HEWS requires a definition of heat waves that is both related to human health outcomes and forecastable. No such definition has been developed for Bangladesh. Using a generalized additive regression model, a heat-wave definition is proposed that requires elevated minimum and maximum daily temperatures over the 95th percentile for 3 consecutive days, confirming the importance of nighttime conditions for health impacts. By this definition, death rates increase by about 20% during heat waves; this result can be used as an argument for public-health interventions to prevent heat-related deaths. Furthermore, predictability of these heat waves exists from weather to seasonal time scales, offering opportunities for a range of preparedness measures. Heat waves are associated with an absence of normal premonsoonal rainfall brought about by anomalously strong low-level westerly winds and weak southerlies, detectable up to approximately 10 days in advance. This circulation pattern occurs over a background of drier-than-normal conditions, with below-average soil moisture and precipitation throughout the heat-wave season from April to June. Low soil moisture increases the odds of heat-wave occurrence for 10-30 days, indicating that subseasonal forecasts of heat-wave risk may be possible by monitoring soil-moisture conditions.

Original languageEnglish
Pages (from-to)2653-2670
Number of pages18
JournalJournal of applied meteorology and climatology
Volume56
Issue number10
DOIs
Publication statusPublished - 1 Oct 2017
Externally publishedYes

Keywords

  • Asia
  • Climate prediction
  • Emergency preparedness
  • Policy
  • Seasonal forecasting
  • Short-range prediction

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