Clear-sky aerosol optical depth over East China estimated from visibility measurements and chemical transport modeling

Horizontal visibility measured at ground meteorological stations provides an under-exploited source of information for studying the interdecadal variation of aerosols and their climatic impacts. Here we propose to use a 3-hourly visibility dataset to infer aerosol optical depth (ACID) over East China, using the nested GEOS-Chem chemical transport model to interpret the spatiotemporally varying relations between columnar and near-surface aerosols. Our analysis is focused in 2006 under cloud-free conditions. We evaluate the visibility-inferred ADD using MODIS/Terra and MODIS/Aqua ADD datasets, after validating MODIS data against three ground ADD measurement networks (AERONET, CARSNET and CSHNET). We find that the two MODIS datasets agree with ground-based AOD measurements, with negative mean biases of 0.05-0.08 and Reduced Major Axis regression slopes around unity. Visibility-inferred ADD roughly capture the general spatiotemporal patterns of the two MODIS datasets with negligible mean differences. The inferred ADD reproduce the seasonal variability (correlation exceeds 0.9) and the slight ADD growth from the late morning to early afternoon shown in the MODIS datasets, suggesting the validity of our ADD inference method. Future research will extend the visibility-based ADD inference to study the long-term variability of ADD. (C) 2014 The Authors. Published by Elsevier Ltd.