## 3 Science Data Product Performance
### The Visible Infrared Imaging Radiometer Suite (VIIRS) Instrument and Science Data Products
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Occan** & **Snow-Free Land** & **Desert** & **Snow-Covered Land** & **Sea Ice** & **Antarctic and Greenland** \\ \hline Global & & & & 0.888 (0.87) & & \\ Day & 0.95 (0.92) & 0.912 (0.90) & 0.864 (0.85) & 0.896 (0.88) & 0.908 (0.82) & 0.741 (0.80) \\ Night & 0.912 (0.90) & 0.883 (0.88) & 0.858 (0.85) & 0.878 (0.85) & 0.799 (0.72) & 0.701 (0.70) \\ \hline \hline \end{tabular}  
* Product performance and specification data (in parenthesis) summarized in the table are obtained from the Enterprise Clouds Algorithms Readiness Review presented on 15 December 2015.  
\end{table} 
Table 2: S-NPP VIIRS cloud mask performance versus specifications *. Figure 3: An example of VIIRS daytime cloud mask generated using the VIIRS enterprise cloud algorithm (Figure Courtesy: [PERSON], NOAA). \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Product** & **Requirement** & **Performance** \\ \hline Cloud Phase \% correct classification data & & 80\% & \textgreater{}82.6\% \\ Cloud Type \% correct classification & & 60\% & \textgreater{}72.6\% \\  & Accuracy & Precision & Accuracy & Precision \\ Cloud Base Height & 2 km & 2 km & 0.3 km & 1.7 km \\ Cloud Optical Depth & & & \\ Day, water & 2 or 20\% & 3 or 30\% & 1.59/0.9\% & 4.43/25.7\% \\ Day, ice & 2 or 20\% & 3 or 30\% & 1.81/3.6\% & 5.02/31.1\% \\ Night & 30\% & 0.8 or 30\% & \(-0.12/7.3\%\) & 0.63 \\ Cloud Particle Size & & & \\ Water & 4 \(\mu\)m & 4 \(\mu\)m & 3.03 \(\mu\)m & 4.30 \(\mu\)m \\ Ice & 10 \(\mu\)m & 10 \(\mu\)m & 5.69 \(\mu\)m & 5.23 \(\mu\)m \\ \hline \hline \end{tabular}
\end{table} 
Table 3: S-NPP VIIRS cloud products performance (accuracy: magnitude of the mean measurement errors; precision: the standard deviation of the measurement errors [27]). A suite of land products (e.g., surface reflectance, VIIRS vegetation, surface albedo, land surface temperature, surface type, and active fire products) is derived from the VIIRS instrument channels. These products are used for a wide variety of applications, including land use management and monitoring, ecosystem dynamics, atmospheric chemistry, human health, biomass burning emissions, operational air quality forecasting, etc. [45; 46; 47]. All S-NPP land products have met the maturity requirements (Table 5) and have been declared validated, and many have been transitioned to enterprise algorithms for NDE operations. Figure 4 gives a glimpse into the NDE enterprise Vegetation Product Suite (NVPS), which includes a variety of VI products and the GVF product. The GVF product is used for monitoring drought, vegetation health monitoring, crop conditions, and global food supply and demand [47]. The VIIRS VI products consist of the Normalized Difference Vegetation Index (NDVI) derived from top-of-the-atmosphere (TOA) reflectances and the Enhanced Vegetation Index (EVI) derived from atmospherically corrected, top-of-canopy (TOC) reflectances, NDVI from TOC reflectances (an additional product from NOAA-20) [48]. The VIIRS VI and GVF algorithm performance has been evaluated using MODIS products, along with 35 Flux Tower sites providing in situ data from Earth Observing System (EOS) Land Validation Core sites. The GVF products have been validated with the EOS data sets and Google Earth derived GVF [49]. Other land products are at various stages of operational use in weather and climate forecasting systems (e.g., VIIRS GVF, GCOM Soil Moisture in National Center for Environmental Prediction (NCEP) Land and Coupled Models, and High-Resolution Rapid Refresh, HRRR models) and are used in crop forecasts generated by the United States Department of Agriculture (USDA, e.g., Vegetation Health and GCOM Soil Moisture in the US Drought Monitor). The