Disclaimer: This material is being kept online for historical purposes. Though accurate at the time of publication, it is no longer being updated. The page may contain broken links or outdated information, and parts may not function in current web browsers. Visit https://espo.nasa.gov for information about our current projects.


GOES 8 aerosol optical thickness assimilation in a mesoscale model: Online...

Wang, J., U. S. Nair, and S. Christopher (2004), GOES 8 aerosol optical thickness assimilation in a mesoscale model: Online integration of aerosol radiative effects, J. Geophys. Res., 109, D23203, doi:10.1029/2004JD004827.

To investigate the importance of aerosol radiative effects in the troposphere, numerical simulation of a dust event during the Puerto Rico Dust Experiment is presented by using the Colorado State University Regional Atmospheric Modeling System (RAMS). Through assimilation of geostationary satellite-derived aerosol optical thickness (AOT) into the RAMS, spatial and temporal aerosol distribution is optimally characterized, facilitating direct comparison with surface observations of downwelling radiative energy fluxes and 2 m air temperature that is not possible with a free-running mesoscale model. Two simulations with and without consideration of aerosol radiative effects are performed. Comparisons against observations show that direct online integration of aerosol radiative effects produces realistic downwelling shortwave and longwave fluxes at the surface but minimal improvement on 2 m air temperature at the observation location. Numerical simulations show that for the dust loading considered in this study (AOT = 0.45 at 0.67 mm), if the dust radiative effects are not properly represented, the uncertainty in the simulated AOT is about ±5 to ±10%, the surface radiative energy is overestimated by 30–40 W m-2 during the day and underestimated by 10 W m-2 during the night, and the bias in air temperatures near the surface could be up to ±0.5°C, though these biases also depend on local time, AOT values, and surface properties. The results from this study demonstrate that the assimilation of satellite aerosol retrievals not only improves the aerosol forecasts but also has the potential to reduce the uncertainties in modeling the surface energy budget and other associated atmospheric processes.

PDF of Publication: 
Download from publisher's website.
Research Program: 
Atmospheric Composition Modeling and Analysis Program (ACMAP)
Radiation Science Program (RSP)