<p>Heatwaves, characterized by prolonged high temperatures, have become a recurrent and severe phenomenon in Bangladesh, posing significant risks to public health, agriculture, and socioeconomic stability. This study analyzed the characterization and long-term projections of heatwave patterns in Bangladesh’s western and northwestern climatic zones, addressing a critical gap in understanding regional vulnerabilities to extreme temperature events. Heatwave thresholds were defined using the Bangladesh Meteorological Department Criterion, a percentile-based criterion, and the Indian Meteorological Department Criterion, providing a comprehensive framework for assessing heatwave intensity and frequency. Using nine bias-corrected general circulation models from CMIP6 (Coupled Model Intercomparison Project Phase 6), the study examined historical heatwave patterns (1990–2014) across five cities, Bogra, Chuadanga, Dinajpur, Ishwardi, and Rajshahi, and evaluated future projections for three epochs: Epoch<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11356_2025_36209_Article_IEq1.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="8" /> </InlineMediaObject> <EquationSource Format="TEX">$_{1}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>1</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation> (2026–2050), Epoch<InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11356_2025_36209_Article_IEq2.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="8" /> </InlineMediaObject> <EquationSource Format="TEX">$_{2}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>2</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation> (2051–2075), and Epoch<InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11356_2025_36209_Article_IEq3.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="8" /> </InlineMediaObject> <EquationSource Format="TEX">$_{3}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>3</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation> (2076–2100). The findings revealed a significant increase in heatwave days under the high-emission Shared Socioeconomic Pathway<InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11356_2025_36209_Article_IEq4.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">$_{585}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>585</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation> (SSP<InlineEquation ID="IEq5"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11356_2025_36209_Article_IEq5.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">$_{585}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>585</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation>) scenario compared to SSP<InlineEquation ID="IEq6"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11356_2025_36209_Article_IEq6.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">$_{245}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>245</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation>, with SSP<InlineEquation ID="IEq7"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11356_2025_36209_Article_IEq7.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">$_{585}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>585</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation> projected to have 46.7% more heatwave days on average across the three epochs. The largest disparities are observed in Chuadanga (49.4%) and Rajshahi (44.5%), with Chuadanga emerging as the most vulnerable region, experiencing 1629 cumulative heatwave days under SSP<InlineEquation ID="IEq8"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11356_2025_36209_Article_IEq8.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">$_{585}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>585</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation> in Epoch<InlineEquation ID="IEq9"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11356_2025_36209_Article_IEq9.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="8" /> </InlineMediaObject> <EquationSource Format="TEX">$_{3}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>3</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation>, compared to 1301 under SSP<InlineEquation ID="IEq10"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11356_2025_36209_Article_IEq10.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">$_{245}$</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mn>245</mn> <mrow /> </mmultiscripts> </math></EquationSource> </InlineEquation>—a 25.2% increase. These findings underscore the profound impact of human activities on heatwave frequency and emphasize the urgent need for climate change mitigation. By offering a novel approach to heatwave characterization, this study provides critical insights to inform regional climate resilience planning and develop targeted adaptation measures.</p>

Characterization of heatwave pattern and its long-run predictions using CMIP6 model in western and north-western climatic zones of Bangladesh

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发表日期：

2025年3月11日

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Rayhan Ahmad,
Md. Khalid Hasan,
Chowdhury Sarwar Jahan

摘要

Heatwaves, characterized by prolonged high temperatures, have become a recurrent and severe phenomenon in Bangladesh, posing significant risks to public health, agriculture, and socioeconomic stability. This study analyzed the characterization and long-term projections of heatwave patterns in Bangladesh’s western and northwestern climatic zones, addressing a critical gap in understanding regional vulnerabilities to extreme temperature events. Heatwave thresholds were defined using the Bangladesh Meteorological Department Criterion, a percentile-based criterion, and the Indian Meteorological Department Criterion, providing a comprehensive framework for assessing heatwave intensity and frequency. Using nine bias-corrected general circulation models from CMIP6 (Coupled Model Intercomparison Project Phase 6), the study examined historical heatwave patterns (1990–2014) across five cities, Bogra, Chuadanga, Dinajpur, Ishwardi, and Rajshahi, and evaluated future projections for three epochs: Epoch $_{1}$ $_{1}$ (2026–2050), Epoch $_{2}$ $_{2}$ (2051–2075), and Epoch $_{3}$ $_{3}$ (2076–2100). The findings revealed a significant increase in heatwave days under the high-emission Shared Socioeconomic Pathway $_{585}$ $_{585}$ (SSP $_{585}$ $_{585}$ ) scenario compared to SSP $_{245}$ $_{245}$ , with SSP $_{585}$ $_{585}$ projected to have 46.7% more heatwave days on average across the three epochs. The largest disparities are observed in Chuadanga (49.4%) and Rajshahi (44.5%), with Chuadanga emerging as the most vulnerable region, experiencing 1629 cumulative heatwave days under SSP $_{585}$ $_{585}$ in Epoch $_{3}$ $_{3}$ , compared to 1301 under SSP $_{245}$ $_{245}$ —a 25.2% increase. These findings underscore the profound impact of human activities on heatwave frequency and emphasize the urgent need for climate change mitigation. By offering a novel approach to heatwave characterization, this study provides critical insights to inform regional climate resilience planning and develop targeted adaptation measures.