21OESS Advances in Integrated Calibration Validation System (ICVS) ATMS Instrument Performance and Science Data Quality Monitoring

It is an important calibration/validation activity to keep track of satellite spacecraft and onboard instruments’ near-real time (NRT) operational health status and long-term (LT) variation trending during the entire mission. In addition, a comprehensive assessment system is highly desired to provide the LT stability information of onboard sensor performance and scientific data (e.g., Raw Data Record or RDR, Temperature Data Record or TDR, Sensor Data Record or SDR) quality. In the Center for Satellite Application and Research (STAR) at National Oceanic and Atmospheric Administration (NOAA), an operational Integrated Calibration/Validation System (ICVS) Long-Term Monitoring (LTM) System has been developed and is running in an NRT mode for more than a decade to support the instrument performance and science data quality monitoring of Joint Polar Satellite System (JPSS) instruments (e.g., ATMS, CrIS, OMPS, VIIRS), and legacy Polar-orbiting Operational Environmental Satellite program (POES) instruments (e.g., AMSU-A, MHS, AVHRR, and HIRS) [Yan et al., 2021 AMS]. To provide a comprehensive on-orbit instrument science data quality monitoring, multiple inter-sensor comparison method results are now available in the ICVS monitoring system to public users along with the well-recognized advanced instrument health status and performance monitoring functions [Yan et. al., 2025 AMS]. The combination of the instrument status and science data quality monitoring provides a more flexible ability to support satellite science data quality variation and improvement study for different users.

As the new generation microwave radiometer, ATMS aboard Soumi National Polar-orbiting Partnership (S-NPP)/Joint Polar Satellite System (JPSS) of NOAA low earth orbit (LEO) satellites has provided high valuable data for weather forecasting and atmospheric studies since the launch of the first ATMS aboard S-NPP in 2011. Therefore, in this study, the newly developed functions and findings of Advanced Technology Microwave Sounder (ATMS), as an example, are introduced and analyzed to demonstrate the value of ICVS-LTM in monitor LT radiometric calibration performance of ATMS SDR data. For example, a recent S-NPP ATMS scan drive compensator motor stall event makes the ATMS radiance systematically decreased, as observed in the daily global mean observations vs. radiative transfer model simulation bias trending time series product. Another S-NPP GPS error at the early July led to a significant degradation of ATMS geolocation accuracy, which caused another unusual variation of global bias distribution pattern. It is also realized that the cross verification among different science data quality long term assessment results can, in turn, help identify defects in assessment tools, such as the application of measured or boxcar SRF in radiative transfer simulation vs. observation bias studies. The discrepancies observed between O-B bias double difference and 32-day direct inter-sensor bias initiate the study of SRF for Cal/Val teams. It is also worthwhile to mention that the implementation of vector data display function can even share selected lifetime orbital data with users for additional analysis.

As a cutting-edge technology experiment testbed, AI/ML-based ATMS scan drive anomaly detection/prediction study [Porter et al., 2023] and OMPS geolocation accuracy degradation detection [Porter et al., 2025 AMS] has also been introduced within the ICVS framework. Further exploration on the application of AI/ML technology in instrument health status, performance, and science data quality assessment will be conducted to improve the ICVS monitoring capability.