An automated algorithm to detect MODIS, VIIRS and GEO sensor L1B radiance anomalies

摘要

The Clouds and the Earth's Radiant Energy System (CERES) project provides observed flux and cloud products for the climate community. To accomplish this goal, the CERES project must merge six CERES instruments, along with two MODIS sensors, two VIIRS sensors, and twenty GEO imagers in order to produce a climate-quality dataset. The input satellite sensors must be properly calibrated and known sensor anomalies must be removed before operational processing. The GEO imager radiances are radiometrically scaled to the Aqua-MODIS C6.1 calibration reference using all-sky tropical ocean ray-matched (ATO-RM) coincident radiance pairs. However, monthly-ATO-RM calibration analysis is inadequate for detecting sensor L1B radiance anomalies, which may span only a few days. The CERES monthly-ATO-RM calibration method was modified to increase the number of ray-matched pairs in order to apply the ATO-RM calibration method on a daily basis. The goal of the daily-ATO-RM calibration method is to detect slight L1B radiance anomalies by limiting the daily gain noise over the record. To test the daily-ATO-RM calibration method, the GOES-16 record, with known L1B radiance anomalies, was evaluated. The GOES-16 channel 2 (0.65 μm) daily-ATORM gain standard error is 1% and thereby allows for confident identification of days with calibration anomalies greater 3%, or three standard deviations (σ). The daily-ATO-RM calibration method detected the three known L1B calibration anomalies, however, there were two daily gains that exceeded three σ that were not associated L1B anomalies. Similarly, the daily-ATO-RM was able to identify the calibration discontinuity of NOAA20-VIIRS in the Land SIPS L1B V001 processing.