Crosscalibration

Crosscalibration is the process of comparing and aligning measurements from two or more instruments or datasets to ensure that they report consistent values for the same quantities. It relies on time overlap, shared observation conditions, or a common reference target to derive correction factors or transfer functions that harmonize responses across instruments. The goal is to maintain data comparability when combining observations from different sensors or when extending historical records with new equipment.

Common approaches include direct comparison of simultaneous measurements from co-located observations, scene-based cross-calibration using well-characterized targets such as solar or stellar references, desert sites, or other stable radiometric targets, and transfer calibration using a reference instrument or radiometric source. The output is typically a set of calibration coefficients, spectral adjustments, and uncertainty estimates that are applied to one or more datasets.

Applications span satellite remote sensing radiometers (for example, MODIS, Landsat, and Sentinel missions), ground-based radiometers in networks such as AERONET, astronomical instruments, and laboratory sensors. In climate and earth science, cross-calibration enables multi-instrument time series, data fusion, and more reliable trend analysis.

Challenges include spectral and viewing-angle mismatches between instruments, detector nonlinearity, sensor aging, and differing environmental conditions. Robust uncertainty propagation and thorough documentation are essential to maintain trust in the resulting data.

Process steps typically involve planning the intercomparison, collecting concurrent observations, computing correction factors, validating with independent data, assessing uncertainties, and publishing versioned calibration records to guide future analyses.