Airborne and model data comparison of aerosol optical properties to improve understanding and forecasting of aerosol in Southeast Asia

Abstract:

This work employs a k-means cluster analysis of airborne aerosol measurements observed during the Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP²Ex) in Southeast Asia during the 2019 southwestern monsoon season. Major air mass types within the mixed layer were identified and their characteristics are presented. Key microphysical properties for each air mass were entered into a global aerosol forecast model, Navy Aerosol Analysis and Prediction System (NAAPS), for possible improvement in microphysical and optical characterization of aerosols in the model. The modelled AOT was compared to AOT derived from High Spectral Resolution Lidar (HSRL) retrievals during flight periods pertinent to each air mass type. Comparing the in-situ and modelled AOT for a given air mass allowed for (i) testing of the model’s sensitivity to changes in certain aerosol microphysical properties and (ii) revealing degeneracy in the model’s AOT predictions (i.e., identical AOT output for differing inputs of microphysical properties). Results from this work provide insight for improvements in the AOT forecast. Since this study focuses on how certain microphysical properties influence the predicted AOT, any improvements made in the model are likely to apply to locations beyond Southeast Asia.