Satellite Based Top-Down Approach for Modelling Aerosol Source Strength and its Application in Discerning Rainfall Trends

Abstract

This thesis is dedicated to study the possible relationship between the distribution of aerosols and rainfall patterns. The thesis proposes a new approach, wherein aerosol sources are investigated rather than the aerosol loading in a region to understand its variation with rainfall. The study first investigates the influence of meteorological parameters indicating both advection and diffusion on the spatiotemporal distribution of aerosols over the Indian subcontinent and the adjacent Indian Ocean. The research inferences are then used to develop a model to estimate aerosol emissions using satellite data. Further, the spatial aerosol source distribution is used to investigate rainfall variability over southern India. The prevailing meteorological conditions that influence the advection and diffusion of the atmosphere govern the distribution of atmospheric particles from its sources. The present study first explores the spatiotemporal distribution of atmospheric aerosols over the Indian subcontinent and its dependence on the prevailing meteorological conditions. Eleven years of Aerosol Optical Depth obtained from the Moderate Resolution Imaging Spectroradiometer along with meteorological parameters extracted from reanalysis data are analysed at monthly timescales. Wind speed, wind divergence and planetary boundary layer height are studied as parameters for advection and diffusion of atmospheric aerosols. The result shows the importance of both advection and diffusion in distributing aerosols over the region. The result shows higher aerosol loading during the monsoon season with increased spatial variability.Wind speed and divergence correlate with AOD values both over land (R = 0.75) and ocean (R = 0.82) with increased aerosol loading at higher wind speeds, which are converging in nature. Owing to the varied climatology of the Indian subcontinent, land and ocean areas were classified into subregions. Analysis was carried out over these subregions to infer the influence of meteorological conditions on aerosol loading. Results are indicative of a distinct characteristic in the prevailing meteorological conditions that influence the distribution of ii certain aerosol types. Further, the PBLH was analysed as an indicator of atmospheric diffusion to infer its importance in aerosol distribution. The results indicate that PBLH explains almost 30 to 90% of the total variance in AOD over the subregions which is particularly evident during the winter and pre-monsoon seasons. The study further uses a Lagrangian approach to the Advection Diffusion Equation to estimate the transported aerosols and hence the Aerosol Source Strength using satellite-measured Aerosol Optical Depth (AOD) and reanalysis wind data. This top-down approach is based on the advection and diffusion of atmospheric aerosols considering wind circulation and atmospheric conditions rather than using indicative parameters. To validate the current top down approach, the study first utilises the AOD measurements from the GOES-16 for California and then applies the methodology over southern India using MODIS to identify aerosol hotspots. The results over California are indicative of higher ASS around wildfire locations. The ASS values also show good correlation (R2 = 0.886) with Fire Radiative Power (FRP) obtained from TerraMODIS fire product. Themethodwas further applied to investigate the spatial correlation of ASS with power plant density, which reveals a steady increase in ASS with power plant density (R2 = 0.82). Finally the study investigates the possible relationship between rainfall and aerosol source distribution over southern India during the pre-monsoon season. Aerosol and rainfall trends are computed using Mann Kendall trend test and are correlated spatially with AOD and ASS. To further understand the relationship, cloud microphysics is also investigated. The results indicate that, though the aerosol loading initially supports cloud formation resulting in deeper and wider clouds, higher aerosol loading inhibits cloud formation resulting in narrow and shallow clouds. This in turn decreases rainfall at higher aerosol loading with smaller cloud radius.