8 May 2018 Evaluating the long-term stability and response versus scan angle effect in the SNPP VIIRS SDR reflectance product using a deep convective cloud technique
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Abstract
The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite has operated successfully since its launch in October, 2011. The calibration using regular solar diffuser (SD) observations for the 14 reflective solar bands facilitates the generation of high-quality calibrated products, known as sensor data records (SDR). As SNPP VIIRS nears six years on-orbit, monitoring the on-orbit calibration performance using multiple techniques is vital. One such technique, using the deep convective clouds (DCC), has been widely used to monitor the on-orbit calibration performance of earth observing sensors, such as the MODIS instrument on Terra and Aqua spacecrafts. In this study, the DCC technique is utilized to evaluate the stability of SNPP VIIRS SDR reflectance product for 10 moderate resolution bands (M-bands, M1–M5 and M7– M11) and three imaging bands (I-bands, I1–I3). An empirical Bidirectional Reflectance Distribution Function (BRDF) correction for the long-term reflectance measurements over DCC is formulated and implemented. The fluctuation in the long-term trending is analyzed to evaluate the uncertainties. The BRDF-corrected reflectances over DCC are used to evaluate the stability of the response versus scan-angle (RVS) and its effects in the SDR products. The RVS effects are analyzed based on the difference in mode reflectances over DCC among six different frame zones. Results indicate that the RVS effects should be monitored for an improved VIIRS RSB calibration in the future.
Conference Presentation
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Qiaozhen Mu, Qiaozhen Mu, Tiejun Chang, Tiejun Chang, Aisheng Wu, Aisheng Wu, Xiaoxiong Xiong, Xiaoxiong Xiong, } "Evaluating the long-term stability and response versus scan angle effect in the SNPP VIIRS SDR reflectance product using a deep convective cloud technique", Proc. SPIE 10644, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV, 106440O (8 May 2018); doi: 10.1117/12.2304395; https://doi.org/10.1117/12.2304395
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