## 3 Science Data Product Performance
### The GCOM-AMSR2 Instrument and Science Data Products  
The GCOM AMSR2 instrument is a dual-polarized, conical scanning, passive microwave radiometer and provides a variety of products exploiting the availability of dual-polarized measurements with central frequencies at 6.925, 10.65, 18.7, 23.8, 36.5, and 89.0 GHz. AMSR2 provides data continuity with several enhancements for the AMSR for Earth Observing System (AMSR-E) on NASA's Aqua satellite [104]. Under the collaborative agreements between the JPSS and the JAXA Program, the IDPS processing system generates RDRs from G-COM data received in real time through Svalbard. The NDE operational system generates G-COM AMSR2 Level-1 data sets (equivalent to SDRs) using the software provided by JAXA and derives a variety of Level-1 and Level-2 products that include: calibrated microwave brightness temperatures, total precipitable water, cloud liquid water, precipitation type/rate, sea surface temperature, and sea surface wind speed [105]. Some of these products serve as standalone AMSR2 baseline products, while others are blended products with a multitude of sensors (e.g., ATMS) [106]. The baseline suite of products from AMSR2 includes cloud properties, rain rate, soil moisture, and snow and ice products (Table 15). Examples of blended products include total precipitable water and rain rate. The processing systems of MIRS, Interactive Multisensor Snow and Ice Mapping System (IMS), and Soil Moisture Operational Product System (SMOPS) produce these hydrological products and use enterprise solutions to derive products from JPSS ATMS, GCOM-AMSR2, and other instrument complements. Some JPSS hydrological products  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Attribute**} & \multicolumn{2}{c}{**OMP-NM**} & \multicolumn{2}{c}{**OMPS-NP**} \\  & **LIRDS** & **Performance** & **LIRDS** & **Performance** \\  & **Thresholds** & & **Thresholds** & **Performance** \\ \hline Non-linearity accuracy & \textless{}0.2\% & \textless{}0.2\% & \textless{}0.2\% & \textless{}0.2\% \\ SNR & 1000 & \textgreater{}1000 & \textless{}45–400 channel & \textgreater{}1000 \\ Straylight Out-of-band and Out-of-Field & & & & dependent \\  & \textless{}2\% & \textless{}2\% & \textless{}2\% & \textless{}2\% \\ \multicolumn{2}{c}{} \\ Orbital thermal wavelength shift & 0.02 nm & \textless{}0.006 nm & 0.02 nm & \textless{}0.006 nm \\ Absolute irradiance calibration accuracy & \textless{}7\% & \textless{}7\% for most & \textless{}7\% for most & \textless{}7\% for most \\ \multicolumn{2}{c}{} \\ Absolute radiance calibration accuracy & \textless{}8\% & \textless{}8\% & \textless{}8\% & \textless{}8\% \\ \multicolumn{2}{c}{} \\ Albedo calibration accuracy & \textless{}2\% & \textless{}2\% For most & \textless{}2\% For most & \textless{}2\% For most & \textless{}2\% \\ \multicolumn{2}{c}{} \\ \multicolumn{2}{c}{} \\ \end{tabular}
\end{table}
Table 14: S-NPP OMPS SDR performance.  
Figure 15: UV index forecast product (18 November 2016) utilizing S-NPP OMPS observations. (Figure courtesy: [PERSON], NWS).  
have been utilized in Earth system modeling and data assimilation, such as snow cover and soil moisture [107].