Oyegbile, Ollamilekan Oluwatobi
(2025)
Modeling the influence of biomass burning haze on extreme rainfall events.
PhD thesis, University of Nottingham.
Abstract
Biomass burning is a major contributor to atmospheric aerosols globally, releasing over 2 Pg C annually, with West Africa experiencing widespread biomass burning during the December-February dry season that results in a thick haze layer known as the "Harmattan." This seasonal phenomenon significantly impacts air quality and regional climate across the region, with major cities like Lagos, Nigeria (population exceeding 14 million) being particularly vulnerable to compounding impacts of seasonal biomass burning pollution. Devastating flood events, such as those occurring on July 10, 2011, and July 16, 2021, have resulted in significant infrastructural damage and loss of human life in Lagos. While growing evidence suggests that the Saharan Air Layer and Harmattan haze may play a crucial role in modulating West African monsoon patterns and rainfall intensity, there remains a critical knowledge gap regarding the specific impacts of biomass burning emissions on extreme precipitation events and urban flooding in rapidly developing coastal megacities. Despite emerging insights into aerosol-climate interactions, limited research has quantified the direct influence of long-range transported biomass-burning aerosols within the Harmattan haze layer on anomalous precipitation and flooding in coastal population centers.
This research aims at studying the intercorrelation between biomass burning haze and regional climate in Lagos, Nigeria, with particular focus on extreme rainfall events that led to devastating floods in July 2011 and July 2021 using numerical modeling and simulations. Despite growing evidence of the influence of atmospheric aerosols on weather patterns, there remains a critical knowledge gap regarding the specific impacts of biomass burning emissions on extreme precipitation events and urban flooding in rapidly developing coastal megacities like Lagos. This study addresses this gap by using a numerical model, Weather Research and Forecasting (WRF) model to simulate these significant flooding episodes and examining the underlying meteorological mechanisms that contribute to urban flooding.
Using the WRF model with different microphysics schemes (Thompson and WSM6), the research evaluates the model's capability to simulate extreme precipitation events and examines the complex interactions between biomass burning haze, atmospheric dynamics, and precipitation processes. The study employs a multi-faceted methodological approach combining satellite remote sensing, numerical modeling, and statistical validation. The Thompson scheme showed superior overall performance, achieving RMSE reductions of 15-31% during the 2011 event and 11-25% during 2021 compared to the WSM6 scheme. Analysis revealed significant changes in precipitation patterns between the two events, with maximum flood intensity decreasing from 1,053.37mm in 2011 to 760.47mm in 2021, accompanied by a spatial shift in flood vulnerability from western to eastern districts.
Key findings indicate substantial transformations in Lagos's urban climate system over the decade, including modifications in Land Surface Temperature (LST) patterns, with maximum LST in western regions decreasing from 42.85°C to 39.47°C, coinciding with increased surface albedo from 0.15 to 0.22. The research also identified strengthened correlations between aerosol patterns and precipitation (ρ = 0.468, p = 1.44e-28 in 2021, compared to ρ = -0.215, p = 1.17e-06 in 2011), suggesting enhanced aerosol-cloud-precipitation interactions.
The spatiotemporal evolution of fire events showed significant changes between the 2011 and 2021 study periods. In 2011, the pre-flood period recorded 11 fire events with a mean daily occurrence of 2.75, while the subsequent flood period showed an increase to 20 events and a mean daily occurrence of 5.00. In contrast, the 2021 data exhibited a different pattern with 21 fire events in the pre-flood period (mean daily occurrence of 10.50), followed by a sharp decline to just 1 event during the flood period. Statistical comparisons confirmed significant differences between the pre-flood and flood periods in both years (Mann-Whitney U test, p < 0.05).
Further analysis of fire characteristics revealed notable changes over the decade. The mean Fire Radiative Power (FRP) decreased from 26.88 MW in 2011 to 17.09 MW in 2021, while the spatial clustering of fire events intensified (Moran's I increased from 0.38 to 0.45, p < 0.001). The relationship between fire metrics also strengthened, with regression models showing improved predictive power (R² increasing from 0.80 to 0.981). These evolving fire patterns, including decreased intensity but increased spatial clustering, coincided with the transformation in flood characteristics observed between the two study periods.
The research also revealed complex interactions between microphysical processes, land-sea dynamics, and urban effects that fundamentally influence extreme precipitation events in Lagos. Aerosol-cloud interactions demonstrated significant impact on precipitation efficiency. Cloud condensation nuclei (CCN) concentrations increased by 35% from 2011 to 2021 (550 cm⁻³ to 742 cm⁻³), modifying cloud microphysical properties. This enhancement correlates with increased cloud liquid water content (r = 0.84, p < 0.001) and reduced warm rain efficiency in shallow convection.
The study's findings have significant implications for flood prediction and management in rapidly growing coastal cities, highlighting the need for enhanced monitoring systems, updated infrastructure specifications, and adaptive urban planning strategies. The research shows that successful operational implementation of flood forecasting requires real-time monitoring of sea surface temperatures and urban heat island intensity which has become crucial for accurate prediction of convective initiation and evolution.
This research contributes to the understanding of the complex interactions between biomass burning, urban development, and extreme weather events in tropical coastal environments, providing valuable insights for improving flood resilience in vulnerable urban areas. The findings suggest that significant improvements in flood prediction and response are achievable, provided appropriate consideration is given to local conditions and resources.
| Item Type: |
Thesis (University of Nottingham only)
(PhD)
|
| Supervisors: |
Anwar, Mohammed Parvez
Abdullahi, Anwar
Chan, Andy |
| Keywords: |
biomass burning; weather research and forecasting (WRF) model; extreme precipitation; urban flooding; lagos; microphysics schemes; aerosol-cloud interactions |
| Subjects: |
T Technology > TP Chemical technology |
| Faculties/Schools: |
University of Nottingham, Malaysia > Faculty of Science and Engineering — Engineering > Department of Civil Engineering |
| Item ID: |
81588 |
| Depositing User: |
Oyegbile, Olamilekan
|
| Date Deposited: |
26 Jul 2025 04:40 |
| Last Modified: |
26 Jul 2025 04:40 |
| URI: |
https://eprints.nottingham.ac.uk/id/eprint/81588 |
Actions (Archive Staff Only)
 |
Edit View |
Tools
Tools
