Articles | Volume 12, issue 13
https://doi.org/10.5194/acp-12-5719-2012
https://doi.org/10.5194/acp-12-5719-2012
Research article
 | 
02 Jul 2012
Research article |  | 02 Jul 2012

Regional and global modeling of aerosol optical properties with a size, composition, and mixing state resolved particle microphysics model

F. Yu, G. Luo, and X. Ma

Abstract. There exist large uncertainties in the present modeling of physical, chemical, and optical properties of atmospheric particles. We have recently incorporated an advanced particle microphysics (APM) model into a global chemistry transport model (GEOS-Chem) and a regional weather forecasting and chemistry model (WRF-Chem). Here we develop a scheme for calculating regional and global aerosol optical depth (AOD) from detailed aerosol information resolved by the APM model. According to GEOS-Chem-APM simulations, in most parts of the globe, the mass of secondary species resides mainly within secondary particles (60–90%), but in certain regions a large fraction (up to 50–80%) can become coated on various primary particles. Secondary species coated on black carbon and primary organic carbon particles significantly increase the size and hygroscopicity of these particles and thus impact their optical properties. The GEOS-Chem-APM model captures the global spatial distributions of AOD derived from AERONET, MODIS, and MISR measurements, generally within a factor of ~2. Our analysis indicates that modeled annual mean AODs at all sky and clear sky conditions differ by ~20% globally averaged and by >50% in some regions. The time series of WRF-Chem-APM predicted AOD over the northeastern United States in June 2008 have been compared to those from seven AERONET sites. Overall, the model mostly captures the absolute values as well as the variations of AOD at the AERONET sites (including dramatic changes associated with the crossing of high AOD plumes). Both GEOS-Chem and WRF-Chem simulations indicate that AOD over the northeastern US is dominated by secondary particles and have large spatiotemporal variations.

Download
Altmetrics
Final-revised paper
Preprint