Uncertainty analysis of remote sensing optical sensor data: guiding principles to achieve metrological consistency

Climate change monitoring requires decades-long time-series radiometric measurements using multiple optical sensors in multiple platforms covering the globe. The problem of achieving traceability to SI units for these measurements is discussed. A major challenge is to determine the result of a measurement and its associated uncertainty using various calibration and validation processes. These processes are plagued by systematic (non-statistical) uncertainties that are not well understood. In particular, different, but in principle equivalent, SI traceable measurements may differ by more than would be expected from the uncertainties associated with the individual measurements. We propose a methodology based on the International Organization for Standardization (ISO) Guide to the Expression of Uncertainty in Measurement (GUM) for the analysis of uncertainties in such measurements along with consistency checking. This allows the measurement result and its associated uncertainty to evolve as new knowledge is gained from additional experiments, and it promotes greater caution in drawing conclusions in view of the sparse measurements. We use data from ongoing total solar irradiance measurements from various instruments in orbit to illustrate the principles.