Rigorous Characterisation of a Novel, Statistically-Based Ocean Colour Algorithm for the PACE Mission

An approach based on empirical orthogonal function (EOF) analysis of ocean colour spectra has been shown to accurately derive inherent optical properties (IOPs) and chlorophyll concentration in scenarios, such as optically complex waters, where standard algorithms often perform poorly. The algorithm has been successfully used in a number of regional applications, and has also shown promise in a global implementation based on the NASA NOMAD data set. Additionally, it has demonstrated the unique ability to derive ocean colour products from top of atmosphere (TOA) signals with either no or minimal atmospheric correction applied. Due to its high potential for use over coastal and inland waters, the EOF approach is currently being rigorously characterised as part of a suite of approaches that will be used to support the new NASA ocean colour mission, PACE (Pre-Aerosol, Clouds and ocean Ecosystem). A major component in this model characterisation is the generation of a synthetic TOA data set using a coupled ocean-atmosphere radiative transfer model, which has been run to mimic PACE spectral resolution, and under a wide range of geographical locations, water constituent concentrations, and sea surface and atmospheric conditions. The resulting multidimensional data set will be analysed, and results presented on the sensitivity of the model to various combinations of parameters, and preliminary conclusions made regarding the optimal implementation strategy of this promising approach (e.g. on a global, optical water type or regional basis). This will provide vital guidance for operational implementation of the model for both existing satellite ocean colour sensors and the upcoming PACE mission.