Intercalibration of satellite instruments is critical for detection and quantification of changes in the Earth's environment, weather forecasting, understanding climate processes, and monitoring climate and land cover change. These applications use data from many satellites; for the data to be interoperable, the instruments must be cross-calibrated. To meet the stringent needs of such applications, instruments must provide reliable, accurate, and consistent measurements over time. Robust techniques are required to ensure that observations from different instruments can be normalized to a common scale that the community agrees on. The long-term reliability of this process needs to be sustained in accordance with established reference standards and best practices. Furthermore, establishing physical meaning to the information through robust Système International d'unités traceable calibration and validation (Cal/Val) is essential to fully understand the parameters under observation. The processes of calibration, correction, stability monitoring, and quality assurance need to be underpinned and evidenced by comparison with “peer instruments” and, ideally, highly calibrated in-orbit reference instruments. Intercalibration between instruments is a central pillar of the Cal/Val strategies of many national and international satellite remote sensing organizations. Intercalibration techniques as outlined in this paper not only provide a practical means of identifying and correcting relative biases in radiometric calibration between instruments but also enable potential data gaps between measurement records in a critical time series to be bridged. Use of a robust set of internationally agreed upon and coordinated intercalibration techniques will lead to significant improvement in the consistency between satellite instruments and facilitate accurate monitoring of the Earth's climate at uncertainty levels needed to detect and attribute the mechanisms of change. This paper summarizes the state-of-the-art of postlaunch radiometric calibration of remote sensing satellite instruments through intercalibration.

A new set of reflectance calibration coefficients has been derived for channel 1 (0.63 μm) and channel 2 (0.86 μm) of the Advanced Very High Resolution Radiometer (AVHRR) flown on the National Oceanic and Atmospheric Administration (NOAA) and European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar orbiting meteorological satellites. This paper uses several approaches that are radiometrically tied to the observations from National Aeronautics and Space Administration's (NASA's) Moderate Resolution Imaging Spectroradiometer (MODIS) imager to make the first consistent set of AVHRR reflectance calibration coefficients for every AVHRR that has ever flown. Our results indicate that the calibration coefficients presented here provide an accuracy of approximately 2% for channel 1 and 3% for channel 2 relative to that from the MODIS sensor.

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.

The Advanced Baseline Imager (ABI) is the primary Earth observing sensor on the new generation Geostationary Operational Environmental Satellites (GOES-R) series, and provides significant spectral, spatial and temporal observational enhancements compared to the legacy GOES satellites. ABI also provides enhanced capabilities for operational sensor calibration and image navigation and registration (INR) to enable observations of the Earth with high spectral fidelity as well as creating images that are accurately mapped and co-registered over time. Unlike earlier GOES Imagers, ABI has onboard calibration capability for all sixteen bands in the reflective and emissive bands. The calibration process includes periodic and routine views of the internal reflective and blackbody targets as well as views of space and the moon. Improvements in INR are made possible by having a Global Positioning System (GPS) on board the spacecraft and routine measurements of stars through the sensor’s boresight for orbit and attitude determination through a Kalman filter. This paper describes how the sensor data are processed into calibrated and geolocated radiances that enable the generation of imagery and higher level products for both meteorological and non-meteorological Earth science applications. Some examples of ABI images and calibration are presented to demonstrate the capabilities and applications of the sensor.

Satellite detection of the global climate change signals as small as a few percent per decade in albedo critically depends on consistent and accurately calibrated Level 1B (L1B) data or Fundamental Climate Data Records (FCDRs). Detecting small changes in signal over decades is a major challenge not only to the retrieval of geophysical parameters from satellite observations, but more importantly to the current state‐of‐the‐art calibration, since such small changes can easily be obscured by erroneous variations in the calibration, especially for instruments with no onboard calibration, such as the Advanced Very High Resolution Radiometer (AVHRR). Without dependable FCDRs, its derivative Thematic Climate Data Records (TCDRs) are bound to produce false trends with questionable scientific value. This has been increasingly recognized by more and more remote sensing scientists. In this study we analyzed the consistency of calibrated reflectance from the operational L1B data between AVHRR on NOAA‐16 and ‐17 and between NOAA‐16/AVHRR and Aqua/MODIS, based on Simultaneous Nadir Overpass (SNO) observation time series. Analyses suggest that the NOAA‐16 and ‐17/AVHRR operationally calibrated reflectance became consistent two years after the launch of NOAA‐17, although they still differ by 9% from the MODIS reflectance for the 0.63 μm band. This study also suggests that the SNO method has reached a high level of relative accuracy (∼1.5%) for estimating the consistency for both the 0.63 and 0.84 μm bands between AVHRRs, and a 0.9% relative accuracy between AVHRR and MODIS for the 0.63 μm band. It is believed that the methodology is applicable to all historical AVHRR data for improving the calibration consistency, and work is in progress generating FCDRs from the nearly 30 years of AVHRR data using the SNO and other complimentary methods. A more consistent historical AVHRR L1B data set will be produced for a variety of geophysical products including aerosol, vegetation, cloud, and surface albedo to support global climate change detection studies.