Climate change-driven compound dust storm and heatwave extremes in Central Asia under future CMIP6 scenarios

Central Asia (CA) faces rising temperatures and shifting atmospheric conditions, increasing the urgency to address extreme events like heatwaves and dust storms. This study examines the co-evolution and regional co-variability of heatwaves and atmospheric dust loading, represented by dust extinction aerosol optical thickness (AOT). Using a multi-model ensemble of CMIP6 General Circulation Models (GCMs) and high-resolution reanalysis datasets, we analyzed heatwave indices alongside AOT across six clusters from 1992 to 2100. Results show a substantial rise in heatwave activity, with increases in heatwave frequency and intensity projected across much of CA, particularly under future emission scenarios. AOT trends vary regionally, with both increasing and decreasing trends across clusters, periods, and emission scenarios. Spatial and temporal correlations, evaluated with Benjamini–Hochberg False Discovery Rate (BH-FDR) correction for multiple location-level tests, show regionally heterogeneous dust–heatwave co-variability, with both positive and negative associations across clusters and scenarios. The strongest FDR-supported relationships occur in selected cluster–index combinations, indicating localized and scenario-dependent co-variability rather than a uniform compound dust–heatwave signal across CA. These findings highlight the need for targeted adaptation strategies for CA, which faces intensifying heatwaves and spatially variable dust-related atmospheric conditions. This study supports early warning systems, risk assessments, and mitigation and resilience measures to safeguard vulnerable communities and ecosystems and strengthen resilience to these hazards in line with the Sendai Framework for Disaster Risk Reduction 2015–2030.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2026-11-04
DOI
https://doi.org/10.1371/journal.pone.0359347
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Climate change-driven compound dust storm and heatwave extremes in Central Asia under future CMIP6 scenarios

Michael Leuchner, Nick Middleton, Ali Mozhdehi Fard, Jong Ryeol Kim et al.
PLoS ONE
Climate variability and models
article

Climate change-driven compound dust storm and heatwave extremes in Central Asia under future CMIP6 scenarios

Michael Leuchner, Nick Middleton, Ali Mozhdehi Fard, Jong Ryeol Kim, Dorna Gholamzade Ledari, Mehdi Bagheri, Parya Broomandi, Aram Fathian, Ivan Radelyuk, Vadim Yapiyev
article en

Abstract

Central Asia (CA) faces rising temperatures and shifting atmospheric conditions, increasing the urgency to address extreme events like heatwaves and dust storms. This study examines the co-evolution and regional co-variability of heatwaves and atmospheric dust loading, represented by dust extinction aerosol optical thickness (AOT). Using a multi-model ensemble of CMIP6 General Circulation Models (GCMs) and high-resolution reanalysis datasets, we analyzed heatwave indices alongside AOT across six clusters from 1992 to 2100. Results show a substantial rise in heatwave activity, with increases in heatwave frequency and intensity projected across much of CA, particularly under future emission scenarios. AOT trends vary regionally, with both increasing and decreasing trends across clusters, periods, and emission scenarios. Spatial and temporal correlations, evaluated with Benjamini–Hochberg False Discovery Rate (BH-FDR) correction for multiple location-level tests, show regionally heterogeneous dust–heatwave co-variability, with both positive and negative associations across clusters and scenarios. The strongest FDR-supported relationships occur in selected cluster–index combinations, indicating localized and scenario-dependent co-variability rather than a uniform compound dust–heatwave signal across CA. These findings highlight the need for targeted adaptation strategies for CA, which faces intensifying heatwaves and spatially variable dust-related atmospheric conditions. This study supports early warning systems, risk assessments, and mitigation and resilience measures to safeguard vulnerable communities and ecosystems and strengthen resilience to these hazards in line with the Sendai Framework for Disaster Risk Reduction 2015–2030.

PLoS ONEVol. 21(11)
University of Calgary (CA), University of Oxford (GB), Toraighyrov University (KZ), Nazarbayev University (KZ), RWTH Aachen University (DE)
Openalex Percentile: Top 20%
Climate variability and models
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon