# A Geostationary Instrument Simulator for Aerosol Observing System Simulation Experiments
## 2 Methodology and Data
### GEOS-5 Nature Run Aerosol Simulation
#### 2.2.2 Evaluation of G5 NR Aerosols
Time-averaged values for DJF, MAM, JJA, and SON are organized from top to bottom. The observed similarities between G5 NR and MERRAero in the temporal patterns of the speciated 550 nm AODs enables us to derive global scaling factors for each of the aerosol species. The global scaling factors were computed from linear regression of the G5 NR and MERRAero AOD\({}_{550}\) while constraining the intercept to zero, and are listed in Table 3. On a global scale, BC, OC, sulfate, and sea salt AOD\({}_{550}\) should be increased by the factors 1.43, 1.36, 1.30, and 1.08, respectively, to match MERRAero. Meanwhile, dust AOD\({}_{550}\) should be decreased by a factor of 0.67. For certain applications of the G5 NR data, such as sampling studies to quantify the likelihood that an orbit will encounter certain aerosol mixtures, it is recommended that users apply these scaling factors to adjust the speciated AOD\({}_{550}\). Figure 4: Time series of global monthly mean 550 nm AOD. Results from the G5 NR simulation are in black. The monthly mean climatology from the MERRAero reanalysis is shown in gray; the shaded area encloses the minimum and maximum monthly means from the 14-year time series (2002–2016), while the gray line represents the mean. G5 NR simulated aerosol vertical distributions were compared to cloud-cleared CALIOP Level 1.5 aerosol attenuated backscatter vertical profile data [34] in Figures 5 and 6. This is a spatially averaged cloud cleared product suitable for comparison to aerosol transport models. We focused our analysis on two different regions during the month of July, when large plumes of dust and biomass burning aerosol are found off the west coast of Africa. The dust dominated region included the Sahara and the North Atlantic Ocean (\(60^{\circ}\) W \(-20^{\circ}\) E, \(0^{\circ}\) N \(-30^{\circ}\) N), and the biomass burning region covered southern Africa (\(10^{\circ}\) W \(-30^{\circ}\) E, \(0^{\circ}\) S \(-30^{\circ}\) S). Figure 5 shows the monthly mean comparison over the Saharan dust region between CALIOP and G5 NR aerosol attenuated backscatter at 532 nm. The monthly mean for the model was calculated with data for July 2006, while for CALIOP observations from July 2011 were used. Only one observation year was considered due to the limited availability of Level 1.5 data at the time of this analysis. This comparison should be viewed as a qualitative assessment of the G5 NR aerosol vertical distributions because the Nature Run has not been sampled along the CALIPSO orbit track. Furthermore, as G5 NR is a free running simulation, it does not represent a prediction for a specific observation year. Nevertheless, the observed and simulated aerosol backscatter vertical profiles have similar vertical structures, with a dust plume that extends to roughly 6 km over the Sahara and descends westward to the Caribbean over a shallow marine aerosol layer. However, the magnitude of the attenuated backscatter of the elevated dust plume in G5 NR is higher than what is observed by CALIOP. This further indicates that dust emissions in G5 NR over this region are likely overestimated. However, these differences could also be due to interannual variability in the spatial distribution of elevated dust in the North Atlantic. Figure 6 shows the comparison between CALIOP and G5 NR over the southern Africa biomass burning region. The simulation and observations again have a similar vertical structure. In this case, the smoke plume extends up to 4 km above a marine aerosol layer that can reach an altitude of \(\sim\)1.5 km for both G5 NR and CALIOP. While the magnitude of the simulated aerosol backscatter for the smoke plume is in the range of the CALIOP estimates, the simulated backscatter for the marine aerosol layer tends to be weaker than what is observed. \begin{table}
\begin{tabular}{c c} \hline \hline
**Aerosol Species** & **Scaling Factor** \\ \hline Organic Carbon & 1.43 \\ Black Carbon & 1.36 \\ Sulfate & 1.30 \\ Sea Salt & 1.08 \\ Dust & 0.67 \\ \hline \hline \end{tabular}
\end{table}