Quantifying EOS Aqua and NOAA POES AMSU-A Brightness Temperature Biases for Weather and Climate Applications Utilizing the SNO Method

Abstract

Abstract Systematic biases between brightness temperature (Tb) measurements made from concurrently operational Advanced Microwave Sounding Unit-A (AMSU-A) instruments can introduce errors into weather and climate applications. For this reason, in this study the ability of the simultaneous nadir overpass (SNO) method to estimate relative Tb biases between operational Earth Observing System (EOS) Aqua and Polar-orbiting Operational Environmental Satellites (POES) NOAA-15, NOAA-16, and NOAA-18 AMSU-A instruments is evaluated. From an analysis of SNO events occurring from 21 May 2005 to 31 July 2006, AMSU-A SNO-ensemble mean Tb biases could not be statistically determined for window channels, while significant bias detection to within about 0.02 K is accomplished in some low-noise sounding channels. These results are shown to be a consequence of the decrease of the earth-scene Tb variability with increasing atmospheric zenith opacity, which is a function of microwave frequency. Examination of SNO-ensemble mean Tb biases for two independent AMSU-A instrument components—AMSU-A1–1 and AMSU-A1–2—exposed a significant cold (warm) bias on the order of 0.4 K (0.2 K) in the AMSU-A1–1 unit on board the NOAA-18 (Aqua) satellite. This analysis also revealed on average a significant cold bias on the order of 0.1 K in the NOAA-16 AMSU-A1–2 component. Furthermore, the individual SNO mean Tb biases were often found to be a function of the SNO earth-scene average Tb, which is a manifestation of instrument calibration errors. On the other hand, it was found that determining the root cause of such errors is inhibited by the lack of postlaunch quality control of the AMSU-A calibration-related hardware. Based on the results of this study, a need to reduce impacts of surface emissivity and temperature inhomogeneities on the SNO method in microwave radiometer window channels becomes evident. In addition, the unparalleled ability of the SNO method to isolate and quantify intersatellite, instrument-related Tb biases is demonstrated in most sounding channels, which is necessary to improve weather and climate applications.