# A Geostationary Instrument Simulator for Aerosol Observing System Simulation Experiments
## Appendix A VLIDORT Benchmarking and TOA Radiance Uncertainty Estimate  
Here we present uncertainty estimates of the vector radiative transfer calculations from VLIDORT by comparing TOA radiances calculated with VLIDORT to that of five other polarized radiative transfer models. [PERSON] [46] and [PERSON] et al. [11] reported on benchmarking results against the solutions of [PERSON] et al. [66] and [PERSON] [67] for the Rayleigh and aerosol slab problems, respectively, and found that VLIDORT was able to reproduce their results to the reported level of accuracy of the benchmark datasets. In the following, VLIDORT is benchmarked for five additional scenarios, including realistic atmospheric profiles and spheroidal aerosol particles. Table 10 describes the seven scenarios that were considered, consisting of four single layer problems, and three 32-layer problems containing various configurations of Rayleigh scattering, aerosol scattering, and molecular absorption. For this analysis, VLIDORT was run in the same configuration as described in Section 2.4.2.  
Table 10 lists the various RTMs considered in the intercomparison and their solution strategies, which were either discrete ordinates (similar to VLIDORT), or rigorous Monte Carlo solutions. In general, all models in Table 10 were run in high accuracy mode (e.g., 128 streams for spheroidal aerosol cases), and the results provide a good dataset for analyzing the accuracy of the low (6) stream VLIDORT approximation. Details of each model can be found in [PERSON] et al. [68], and the model outputs for all scenarios were downloaded from the following website: [[http://www.meteo.physik.uni-muenchen.de/~iprt/doku.php?id=intercomparisons:intercomparisons](http://www.meteo.physik.uni-muenchen.de/~iprt/doku.php?id=intercomparisons:intercomparisons)]([http://www.meteo.physik.uni-muenchen.de/~iprt/doku.php?id=intercomparisons:intercomparisons](http://www.meteo.physik.uni-muenchen.de/~iprt/doku.php?id=intercomparisons:intercomparisons)).  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Name** & **Solution Method** & **Reference** \\ \hline MYSTIC & Monte Carlo & [PERSON] [69] [PERSON] et al. [70] \\ PSTAR & Discrete Ordinate & [PERSON] et al. [71] \\ SPARTA & Monte Carlo & [PERSON] et al. [72] \\ SHDOM & Discrete Ordinate & [PERSON] [73] \\ IPOL & Discrete Ordinate & [[ftp://climate1.gsfc.nasa.gov/skorkin/IPOL](ftp://climate1.gsfc.nasa.gov/skorkin/IPOL)]([ftp://climate1.gsfc.nasa.gov/skorkin/IPOL](ftp://climate1.gsfc.nasa.gov/skorkin/IPOL)) \\ \hline \hline \end{tabular}
\end{table}
Table 10: Benchmark intercomparison polarized radiative transfer models.  
Figure 14 shows the difference between VLIDORT and the Monte Carlo model, MYSTIC, which is generally the median the of the five benchmark models, for the aerosol vertical profile scenario (B3). The VLIDORT solutions fall within the 2-sigma uncertainty reported by the Monte Carlo RTM for nearly all scattering geometries. Table 13 shows the root mean square error between VLIDORT and the six benchmark RTMs for all seven radiative transfer scenarios considered. For all the benchmark scenarios the VLIDORT 6 stream approximation generally agrees to within at least 0.1% of most models. The largest mean error between the benchmark models and VLIDORT is 0.68%, which is comparable to the measurement errors in the UV-Vis for sensors such as OMI [74].