Optimization of a semianalytical ocean color model for global-scale applications

TLDR

Semianalytical ocean color models can retrieve multiple ocean properties from a single radiance spectrum, but their complexity and limited tuning procedures have hindered operational use. The study proposes a global optimization procedure for SA ocean color models and discusses current limitations and future developments. The authors use a simulated‑annealing protocol to tune a SA model that simultaneously estimates chlorophyll, dissolved‑detrital absorption, and particulate backscatter from normalized water‑leaving radiance, validating the method on synthetic and in‑situ data. The globally optimized GSM01 model achieves retrieval accuracy comparable to SeaWiFS for chlorophyll and uniquely provides simultaneous estimates of absorption and backscatter, broadening its global application potential.

Abstract

Semianalytical (SA) ocean color models have advantages over conventional band ratio algorithms in that multiple ocean properties can be retrieved simultaneously from a single water-leaving radiance spectrum. However, the complexity of SA models has stalled their development, and operational implementation as optimal SA parameter values are hard to determine because of limitations in development data sets and the lack of robust tuning procedures. We present a procedure for optimizing SA ocean color models for global applications. The SA model to be optimized retrieves simultaneous estimates for chlorophyll (Chl) concentration, the absorption coefficient for dissolved and detrital materials [a(cdm)(443)], and the particulate backscatter coefficient [b(bp)(443)] from measurements of the normalized water-leaving radiance spectrum. Parameters for the model are tuned by simulated annealing as the global optimization protocol. We first evaluate the robustness of the tuning method using synthetic data sets, and we then apply the tuning procedure to an in situ data set. With the tuned SA parameters, the accuracy of retrievals found with the globally optimized model (the Garver-Siegel-Maritorena model version 1; hereafter GSM01) is excellent and results are comparable with the current Sea-viewing Wide Field-of-view sensor (SeaWiFS) algorithm for Chl. The advantage of the GSM01 model is that simultaneous retrievals of a(cdm)(443) and b(bp)(443) are made that greatly extend the nature of global applications that can be explored. Current limitations and further developments of the model are discussed.