Improving the Operational Calibration Stability of VIIRS SDR Using Advanced Kalman Filtering

The operationally produced VIIRS sensor data records (SDR) from the Suomi NPP satellite have been widely used for a variety of studies by users globally. While overall the VIIRS SDR products remain excellent seven years after launch, there is a gradual drift in the reflective solar band calibration which is affecting operationally produced real time VIIRS SDR data especially for ocean color applications which requires a stability on the order of 0.1%. The challenge is how to accurately account for and correct the residual degradation which can not be captured by the onboard calibration system alone. To meet this challenge, the NOAA VIIRS SDR team has developed a novel method using an offline Kalman filtering model to accurately estimate the residual degradation by assimilating inputs from a number of sources, including lunar calibration, weekly deep convective cloud observations, desert calibration, and simultaneous nadir overpass calibration to ensure the operational calibration stability. This paper will present the progress made in developing and testing the Kalman filtering model, as well as its concept of operations in support of the realtime operational production of the VIIRS SDR to meet all user needs.