Speaker
Description
This research investigates the impact of aerosol-solar radiation interaction on atmospheric stability and lightning activity in the Metropolitan Region of São Paulo (RMSP). Literature provides evidence of a boomerang-shaped behavior in lightning activity due to increasing aerosol concentrations. While aerosols influence clouds through both microphysical (indirect) and radiative (direct) effects, this study focuses mainly on the direct effect, where aerosol scattering and absorption generate a cooling effect in the lower troposphere.
To elucidate the mechanisms behind this effect, the research methodology has evolved from a purely observational approach to the integration of numerical modeling. Previously, in master’s research, a range of 5 years of clear-sky data were analyzed to isolate the radiative interactions without cloud coverage interference. PM10 concentration data from CETESB were utilized alongside lightning observations from GLM and ENTLN, while the Clarity Index (Kt) and ASHRAE model were employed to quantify atmospheric transparency. The observational baseline demonstrated a clear boomerang-shaped trend: lightning activity increases proportionally with PM10 up to a threshold of 60 µg/m³, beyond which severe solar radiation attenuation occurs, increasing atmospheric stability and suppressing subsequent lightning.
Currently, the research seeks to demonstrate that the aerosol-solar radiation interaction stabilizes the lower troposphere and suppresses the lightning activity. To physically quantify this stability suppression and expand upon the observational findings, the current methodological framework incorporates the CATT-BRAMS system as a primary data source. By extracting vertical thermodynamic profiles and atmospheric stability indices from the model outputs, it becomes possible to dynamically isolate the direct radiative forcing. This presentation discusses this methodological evolution, detailing how the integration of surface observations, satellite data, and structured numerical datasets allows for a deeper understanding of the physical mechanisms driving aerosol-induced atmospheric stabilization.