Uncertainties from Ancillary Data In Seadas Remote Sensing Reflectances Using the Era5 Ensemble

Atmospheric corrections introduce uncertainties in bottom-of-atmosphere Ocean Colour (OC) products. In this paper we have for the first time analysed the uncertainties in the atmospheric correction for OC arising from the uncertainties in the ancillary data (such as wind speed and column densities of gases and aerosols). The spread in the ERA5 ensemble is used as estimate for the uncertainty in the ancillary parameters, which is then propagated to uncertainties in remote sensing reflectances using the SeaDAS atmospheric correction algorithm. A metrological approach is followed, where first we illustrate the complete uncertainty budget using an uncertainty tree diagram. The uncertainties from the ancillary data are then propagated using a Monte Carlo approach. Wind speed and relative humidity are found to be the main contributors (among the ancillary parameters) to the remote sensing reflectance uncertainties. In total, the ancillary data add about 1 % uncertainty at 412nm, increasing to 2% for 555nm with significant variability as a function of observation conditions.