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<p>Sand and dust storms (SDSs) pose a significant threat to air quality, health, and transportation safety across Northern Africa (NA). This study adopts an impact-based, dust-induced visibility (<i>V</i>) threshold to categorize dust haze (DH) into Thick (TDH; <i>V</i> ≤ 1000&#xa0;m), Moderate (MDH; 1000&#xa0;m &lt; <i>V</i>≤ 5000&#xa0;m), and Light (LDH; 5000&#xa0;m &lt; <i>V</i>&lt; 10,000&#xa0;m) based on surface observations from stations across NA from 2013 to 2024. We analyzed the spatiotemporal patterns of DH and quantified the skill of the World Meteorological Organization Sand and Dust Storm Warning Advisory and Assessment System (WMO SDS-WAS) Multi-Model Ensemble (MME) dust forecast products (DFPs) in simulating these patterns. The results revealed distinct seasonal patterns of DH, with prevalent TDH downwind of the Bodélé depression and towards the West African coast in winter, while TDH is more spatially homogenous in summer. A marked absence of DH south of 10°N in summer is attributed to the moist monsoon incursion. Overall, DH showed moderate correlation with MME DFPs, notably stronger with dust surface concentration (SCON_DUST; ρ≈-0.4), compared to dust optical depth (OD550_DUST; ρ≈-0.3). The correlations exhibit variability across stations, seasons, and forecast lead time, being strongest in winter. Leveraging this relationship, we developed an empirical model to calibrate DFPs into operational visibility alerts. This study provides a valuable step toward integrating dust forecasts into early warnings for improved public safety.</p>

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Seasonality of dust haze over Northern Africa and its predictability in multi-model ensemble forecasts

  • 期刊论文

  • 发表日期：

    2026年3月9日

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  • Bilikis Alege-Ibrahim,
  • Ahmad Abdullahi Bello,
  • Tahir Aderemi Alaka,
  • Aminu Dalhatu Datti

摘要

Sand and dust storms (SDSs) pose a significant threat to air quality, health, and transportation safety across Northern Africa (NA). This study adopts an impact-based, dust-induced visibility (V) threshold to categorize dust haze (DH) into Thick (TDH; V ≤ 1000 m), Moderate (MDH; 1000 m < V≤ 5000 m), and Light (LDH; 5000 m < V< 10,000 m) based on surface observations from stations across NA from 2013 to 2024. We analyzed the spatiotemporal patterns of DH and quantified the skill of the World Meteorological Organization Sand and Dust Storm Warning Advisory and Assessment System (WMO SDS-WAS) Multi-Model Ensemble (MME) dust forecast products (DFPs) in simulating these patterns. The results revealed distinct seasonal patterns of DH, with prevalent TDH downwind of the Bodélé depression and towards the West African coast in winter, while TDH is more spatially homogenous in summer. A marked absence of DH south of 10°N in summer is attributed to the moist monsoon incursion. Overall, DH showed moderate correlation with MME DFPs, notably stronger with dust surface concentration (SCON_DUST; ρ≈-0.4), compared to dust optical depth (OD550_DUST; ρ≈-0.3). The correlations exhibit variability across stations, seasons, and forecast lead time, being strongest in winter. Leveraging this relationship, we developed an empirical model to calibrate DFPs into operational visibility alerts. This study provides a valuable step toward integrating dust forecasts into early warnings for improved public safety.