An efficient algorithm for polarization in the SASKTRAN radiative transfer framework.

Techniques for remote sensing of atmospheric composition often involve the minimization of the residual between spectrally-resolved atmospheric radiometry and the output of a radiative transfer model which solves the equations of radiative transfer in a candidate atmosphere. Here, SASKTRAN, a framework of climatologies, optical property calculators, and scalar radiative transfer models specifically designed for modeling limb scattering observations, is upgraded to solve the vector radiative transfer equations. In particular, the Monte Carlo and High Resolution Successive Orders modules of the SASKTRAN framework are extended to handle polarized scattering of light in a fully spherical atmosphere, with the assumption of a Lambertian earth underneath. The fast, polarized, High Resolution module is validated against the statistically exact polarized Monte Carlo module for limb-scatter observations in the UV–visible–NIR spectral range and is found to be accurate to within 0.2% in its fully polarized mode. An approximate method to solve the vector radiative transfer equations is introduced; in this mode, the high resolution engine is accurate for limb-scatter geometries to within about 0.2% in almost all cases with minimal degradation in performance as compared to the scalar mode. The models are used to show that scalar simulations of limb-observed UV–vis radiances may contain absolute radiometric errors of up to 5% for typical stratospheric aerosol loads. Furthermore, limb-observed radiances may have nearly any linear polarization, and this is in general altitude and wavelength dependent. [ABSTRACT FROM AUTHOR]