Effects of Aerosols Transport on Mesoscale Convective Systems over West Africa

Abstract

It is believed that these pollutants are available in the atmosphere all year round but are more prevalent at certain seasons of the year. Some source points can be close or far from the locations where the aerosols are prevalent, but their transportation from a long distance is mostly aided through meteorological means. Although, it is a known fact that the resultant aerosol particles from human activities (anthropogenic) such as biomass burning, carbonaceous, etc., have contributed substantially to the global mean aerosol burden since the pre-industrial era, the aerosol particles can be said to affect climate systems via different mechanisms. Aerosols’ influence on Earth’s climate can occur during clear sky which allows it to reflect incoming sunlight to outer space – the direct effect, or the ability to act as condensation nuclei – the indirect effect. Aside from these stated ways of aerosols’ influence on Earth’s climate, it is also known to absorb radiation which leads to hindering cloud formation. The fact remains that the aerosol can be said to influence meteorological variables, thus leading to climate influence. This can be a kind of feedback mechanism between these atmospheric phenomena. In determining the effect of aerosols’ transport on convective systems, there is a need to determine the variability of aerosols and their relationship with climatic parameters, evaluate the capability of the COSMO-MUSCAT coupling model to simulate past episodes, assess the impact of aerosols on convection initiation and propagation, andnthe impact of non-local plumes on simulated cloud properties, relative humidity and temperature. This study covers the whole of West Africa, with some ten (10) selected stations for detailed analyses, namely: Abidjan, Accra, Agoufou, Banizoumbou, Dakar, Freetown, Ikeja, Kano, Ouagadougou and Praia. The work made use of concentration/aerosol (biomass burning, carbonaceous, dust and PM2.5) and meteorological (convective precipitation, wind speed and water vapor) data for a period of 30 years. Other data used were the initial data for some selected episodes for both concentration and meteorology. The selected episodes were; Dust and smoke episode of December 24 -27, 2015 over West Africa. The dust layer extended from the ground upto 2000m while the smoke layer occurred from 2000m – 4000m range, Dust pollution outbreak of March 20 – 29, 2010 over West Africa and spread up to the coastal cities of Lagos and southwestern Nigeria, and Convective activities of 30th August – 2nd September 2009 over Ouagadougou and other West African countries. The statistical analyses employed in achievingone of the objectives were Pearson’s correlation method and the probability value (p-value). The graphical analyses were done with python and ferret. The result showed that most aerosols are predominant in the dry months of December, January and February, but dust was found to be present all throughout the months of the year around Bodele depression, over Chad. The monthly trend of dust and PM2.5 exhibited same pattern. Putting the p-value into consideration, there exists a 60% - 90% statistically significant relationship between the selected climatic parameters and aerosols used in the study. In the validation of the COSMO-MUSCAT coupling model output, the EUMETSAT images showed a similar pattern of dust mobilization and southward dispersion of the aerosol (dust) from the Bodele depression. The inability of the model to capture the aerosols around the Gulf of Guinea area of Freetown up to Dakar showed that there was an influx of moisture as observed from EUMETSAT images, leading to precipitation which may have suppressed the aerosols. The wind profiles over each of the locations exhibited continuous vertical wind shear which has showed to be responsible for increasing intensity of convective systems. The non-local plumes showed that the radiative feedback mechanism had more impacts on the climatic parameters (cloud properties, relative humidity, and temperature) especially around the surfacethan the non-feedback mechanism.