GSICS Inter-Calibration of Infrared Channels of Geostationary Imagers Using Metop/IASI

TLDR

GSICS provides bias monitoring and calibration corrections for thermal IR channels of geostationary meteorological sensors, using IASI on Metop as a common reference and noting that some channels exhibit time‑varying biases from thermal, stray‑light, and contamination effects. The paper presents a weighted linear regression algorithm to compare collocated radiances between each geostationary‑LEO instrument pair. The method applies weighted linear regression to collocated radiances, illustrated with Meteosat, GOES, MTSAT, Fengyun‑2, and COMS imagers. Regression coefficients yield GSICS corrections with uncertainty‑based quality indicators, demonstrating that inter‑calibration can monitor and correct biases and diagnose their root causes.

Abstract

The first products of the Global Space-based Inter-Calibration System (GSICS) include bias monitoring and calibration corrections for the thermal infrared (IR) channels of current meteorological sensors on geostationary satellites. These use the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) on the low Earth orbit (LEO) Metop satellite as a common cross-calibration reference. This paper describes the algorithm, which uses a weighted linear regression, to compare collocated radiances observed from each pair of geostationary-LEO instruments. The regression coefficients define the GSICS Correction, and their uncertainties provide quality indicators, ensuring traceability to the selected community reference, IASI. Examples are given for the Meteosat, GOES, MTSAT, Fengyun-2, and COMS imagers. Some channels of these instruments show biases that vary with time due to variations in the thermal environment, stray light, and optical contamination. These results demonstrate how inter-calibration can be a powerful tool to monitor and correct biases, and help diagnose their root causes.