Assessing remote polarimetric measurement sensitivities to aerosol emissions using the geos-chem adjoint model
- 1University of Colorado – Boulder, Mechanical Engineering Dept., Boulder, CO 80309, USA
- 2University of Nebraska – Lincoln, Dept. of Earth and Atmospheric Sciences, Lincoln, NE 68588, USA
Abstract. Uncertainties in aerosol sources, microphysical properties, and global distributions undermine efforts to evaluate the radiative impacts of atmospheric aerosols. In this work, we investigate the feasibility of using remote polarimetric measurements for constraining aerosol and aerosol precursor emissions in light of these uncertainties. A model that incorporates a radiative transfer model with forward and adjoint chemical transport models has been applied to quantify the sensitivity of the reflectance at the top of atmosphere over land to aerosol emissions and microphysical properties. A set of simulated satellite observations, one intensity based and one capable of polarimetric measurements, are used to illustrate differences in the assimilation potential between the two. It is found that the sensitivity of the polarized reflectance to aerosol and aerosol precursor emissions tends to be significantly higher than that of the intensity for cases of non-absorbing aerosols. This is true even when the polarimetric sampling scheme is spatially sparser than that of the intensity sampling. This framework allows us to quantify upper limits on the uncertainties in the aerosol microphysical properties for which a 50% change in aerosol emissions is detectable using these simulated observations. It was found that although typical current remote sensing instrumentation provides retrievals of the refractive index and effective radius with accuracies within acceptable limits to detect a 50% change in emissions, retrievals of the effective variance contain uncertainties too large to detect these changes in emissions. These results may guide new applications of polarimetric measurements to constrain aerosol sources, and thus reduce uncertainty in our broader understanding of the impacts of aerosols on climate.