1Center for Global and Regional Environmental Research (CGRER), University of Iowa, Iowa City, Iowa, USA
2National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA
3Global Modeling and data Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
4Marine Meteorology Division, Naval Research Laboratory (NRL), Monterey, California, USA
Abstract. An aerosol optical depth (AOD) three-dimensional variational data assimilation technique is developed for the Gridpoint Statistical Interpolation (GSI) system when WRF-Chem forecasts are performed with a detailed sectional model (MOSAIC). Within GSI, forward AOD and adjoint sensitivities are performed using Mie computations from the WRF-Chem optical properties module providing consistency with the forecast. GSI tools such as recursive filters and weak constraints are used to provide correlation within aerosol size bins and upper and lower bounds for the optimization. The system is used to perform assimilation experiments with fine vertical structure and no data thinning or re-gridding on a 12 km horizontal grid over the region of California, USA. A first set of simulations is performed comparing the assimilation impacts of operational MODIS dark target retrievals to observationally constrained ones (i.e. calibrated with AERONET data), the latter ones showing higher error reductions and increased fraction of improved PM2.5 and AOD ground-based monitors. A second set of experiments reveals that the use of fine mode fraction AOD and ocean multi-wavelength retrievals can improve the representation of the aerosol size distribution, while assimilating only 550 nm AOD retrievals produces no or at times degraded impact. While assimilation of multi-wavelength AOD shows positive impacts on all analyses performed, future work is needed to generate observationally constrained multi-wavelength retrievals, which when assimilated will generate size distributions more consistent with AERONET data and will provide better aerosol estimates.