National Oceanic and Atmospheric Administration (NOAA) operational Advanced Technology Microwave Sounder (ATMS) and Advanced Microwave Sounding Unit-A (AMSU-A) data used in numerical weather prediction and climate analysis are essential to protect life and property and maintain safe and efficient commerce. Routine data quality monitoring and anomaly assessment is important to sustain data effectiveness. One valuable parameter used to monitor microwave sounder data quality is the antenna temperature (Ta) difference (O-B) computed between direct instrument Ta measurements and forward radiative transfer model (RTM) brightness temperature (Tb) simulations. This requires microwave radiometer data to be collocated with atmospheric temperature and moisture sounding profiles, so that representative boundary conditions are used to produce the RTM-simulated Tb values. In this study, Constellation Observing System for Meteorology, Ionosphere, and Climate/Formosa Satellite Mission 3 (COSMIC) Global Navigation Satellite System (GNSS) Radio Occultation (RO) soundings over the ocean and equatorward of 60° latitude are used as input to the Community RTM (CRTM) to generate simulated NOAA-18, NOAA-19, Metop-A, and Metop-B AMSU-A and S-NPP and NOAA-20 ATMS Tb values. These simulated Tb values, together with observed Ta values that are nearly simultaneous in space and time, are used to compute Ta O-B statistics on monthly time scales for each instrument. In addition, the CRTM-simulated Tb values based on the COSMIC GNSS RO soundings can be used as a transfer standard to inter-compare Ta values from different microwave radiometer makes and models that have the same bands. For example, monthly Ta O-B statistics for NOAA-18 AMSU-A Channels 4–12 and NOAA-20 ATMS Channels 5–13 can be differenced to estimate the “double-difference” Ta biases between these two instruments for the corresponding frequency bands. This study reveals that the GNSS RO soundings are critical to monitoring and trending individual instrument O-B Ta biases and inter-instrument “double-difference” Ta biases and also to estimate impacts of some sensor anomalies on instrument Ta values.
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