## 2 Assessment of Satellite-Based Remote Sensing for Cloud Property Retrievals
### Preliminary Comparisons between GOES-VISST and Ground Based Techniques  
While the satellite comparisons themselves are consistent with no appreciable bias observed, it is important to assess the validation performance against independent approaches making use of entirely different methodologies. To do this, we make use of the extensive ground based retrievals from the SGP site [12], which we will refer to in this study as based on the Min method, which will be explained in much greater detail in Section 4. Since the VISST algorithm has gone through different versions, we concentrate on the latest version (V4). The pixel level datasets are given at 4 km resolution that is commensurate with the MFRSR FOV. However, to ensure some extra homogeneity in the observation scenes, we look at 20 km regions. The resultant data within the 20 km domain  
Figure 2: Comparison plots of Moderate Resolution Imaging Spectroradiometer (MODIS) and Geostationary Operational Environmental Satellites (GOES) derived Cloud Optical Depth (COD) and Cloud Droplet Effective Radius (REFF) with 10 km (**a**,**b**) and 20 km (**c**,**d**) averaging centering ARM SGP site Lamont (Oklahoma) for the data covering 2007–2010.  
consists of 20 pixels. At the same time, the ground products provide data every 20 s. Using a 30-min interval, this leads to 90 ground measurements. With these caveats in mind, we use the following matchup protocol between the ground based and GOES VISST algorithm.  
1. Only those cases where number of water phase cloud pixels (out of 20) in the 5 \(\times\) 5 box (20-km resolution) is greater than 15 are used and no ice phase clouds are detected.
2. The variability (standard deviation) of the COD \(<\)50% of the mean COD.
3. The ground-based retrievals are acceptable only if all 90 measurements are cloud flagged.  
These severe constraints were applied to the VISST V4 retrievals from 1 July 2011 to 22 November 2011 and the comparisons of both the COD (left column) and R\({}_{\mathrm{eff}}\) (right column) are illustrated in Figure 3. The upper row was restricted to observations where the solar zenith angle, \(\theta_{\mathrm{sun}}<50\) degrees while the bottom row was filtered in the range 50 degrees \(<\) 0\({}_{\mathrm{sun}}<70\) degrees.  
The most important observation is that although the COD retrievals are fairly robust over all solar zenith angles especially for COD \(<50\), the effective radius shows very strong bias and poor correlation to ground retrievals when 0\({}_{\mathrm{sun}}>50\) degrees. Specifically, GOES retrieved R\({}_{\mathrm{eff}}\) is larger than ground  
Figure 3: Comparison of VISST GOES cloud products against ground based retrievals—columns are respectively for COD and R\({}_{\mathrm{eff}}\). The upper row is filtered for solar zenith angle \(\theta_{\mathrm{sun}}<50\) degrees while the bottom row was filtered in the range 50 degrees \(<\) 0\({}_{\mathrm{sun}}\)\(<70\) degrees. The horizontal and vertical error bars represent the standard deviations in ground and GOES retrievals respectively corresponding to both COD and R\({}_{\mathrm{eff}}\).  
retrieved R\({}_{\rm eff}\). To understand this, we note that as the solar zenith angle increases, the 'effective' cloud optical depth also becomes larger. For this reason, photons incident on a water cloud will be more likely to be reflected back to satellite from an upper part of the cloud without penetrating into a lower part of the cloud. On the other hand, photons transmitted through the cloud encounter the entire vertical profile regardless of the cloud optical depth. Since many researchers [31, 32, 33, 34, 35, 36] have reported that cloud droplet effective radius increases from cloud base to cloud top, the GOES retrieved R\({}_{\rm eff}\) based on reflection geometry is biased high. These difficulties make it even more important that ground approaches are explored.