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Defining and Predicting Heat Waves in Bangladesh



Details

  • Journal Title:
    Journal of Applied Meteorology and Climatology
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    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.
  • Keywords:
  • Source:
    Journal of Applied Meteorology and Climatology, 56(10), 2653-2670
  • DOI:
  • ISSN:
    1558-8424 ; 1558-8432
  • Format:
  • Publisher:
  • Document Type:
  • Funding:
  • Rights Information:
    Other
  • Compliance:
    Library
  • Main Document Checksum:
    urn:sha256:98f1cb5be93042633c056670343ed42324489f7bb839176d2127be71cc6fb61e
  • Download URL:
  • File Type:
    Filetype[PDF - 2.62 MB ]
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