Estimating surface visibility at Hong Kong from ground-based LIDAR, sun photometer and operational MODIS products

Surface visibility has decreased in recent years in Hong Kong due to increased air pollution attributed to speedy social and economical development in the region. Aside from deteriorating health standards as a result of air pollution increase, reduced visibility adversely impacts even the most routine civil and public operations, most notably including transportation and aviation. Regional estimates of visibility solved operationally using available ground and satellite-based estimates of aerosol optical properties and vertical distribution may prove more effective than standard reliance on a few existing surface visibility monitoring stations. It has been demonstrated that such satellite measurements correlate well with near-surface optical properties, despite these sensors providing no range-resolved information and the use of indirect parameterizations necessary to solve relevant parameters. Therefore, by expanding such analysis to include vertically-resolved aerosol profile information from an autonomous ground-based lidar instrument, this work is to develop an algorithm for automated assessment of surface visibility. Regional visibility is estimated using co-incident ground-based lidar, sun photometer and MODIS aerosol optical depth datasets. Using a 355 nm extinction coefficient profile solved from the lidar, MODIS AOD (Aerosol Optical Depth) is scaled down to the surface to generate a regional composite depiction of surface visibility. Our results demonstrate the potential for applying passive satellite depictions of broad-scale aerosol optical properties together with a ground-based surface lidar and zenith-viewing sun photometer data for improving quantitative assessments of visibility in a city such as Hong Kong.