Improving the Remote Sensing Retrieval of Phytoplankton Functional Types (PFT) Using Empirical Orthogonal Functions: A Case Study in a Coastal Upwelling Region

Abstract

An approach that improves the spectral-based PHYSAT method for identifying phytoplankton functional types (PFT) in satellite ocean-color imagery is developed and applied to one study case. This new approach, called PHYSTWO, relies on the assumption that the dominant effect of chlorophyll-a (Chl-a) in the normalized water-leaving radiance (nLw) spectrum can be effectively isolated from the signal of accessory pigment biomarkers of different PFT by using Empirical Orthogonal Function (EOF) decomposition. PHYSTWO operates in the dimensionless plane composed by the first two EOF modes generated through the decomposition of a space-nLw matrix at seven wavelengths (412, 443, 469, 488, 531, 547, and 555 nm). PFT determination is performed using orthogonal models derived from the acceptable ranges of anomalies proposed by PHYSAT but adjusted with the available regional and global data. In applying PHYSTWO to study phytoplankton community structures in the coastal upwelling system off central Chile, we find that this method increases the accuracy of PFT identification, extends the application of this tool to waters with high Chl-a concentration, and significantly decreases (~60%) the undetermined retrievals when compared with PHYSAT. The improved accuracy of PHYSTWO and its applicability for the identification of new PFT are discussed.

Global Chlorophyll a Concentrations of Phytoplankton Functional Types With Detailed Uncertainty Assessment Using Multisensor Ocean Color and Sea Surface Temperature Satellite Products

“…Radiance or reflectance signals leaving the ocean surface and measured by a satellite radiometer contain phytoplankton pigment information that can be related to community structure and size classes (Bracher et al., 2017; Mouw et al., 2017). Therefore, spectral‐based approaches have been developed to retrieve the concentrations of phytoplankton chlorophyll, pigments, and multiple PFTs from space (e.g., Alvain et al., 2005, 2008; Bracher et al., 2009; Correa‐Ramirez et al., 2018; Lange et al., 2020; Werdell et al., 2014; Xi et al., 2020). One such approach that has proven efficient is based on the empirical orthogonal function (EOF) analysis on the spectral R rs or water‐leaving radiance.…”

Geostationary satellite reveals increasing marine isoprene emissions in the center of the equatorial Pacific Ocean

“…The satellite PFT identification was performed on the MODIS-Aqua data using the PHYSTWO algorithm (Supplementary Fig. 1b), which is applicable to coastal and open oceans 54 . The six retrieved PFTs are Coccolithophorids bloom, Phaeocystis-like, Diatoms, Synechococcus, Prochlorococcus, and Nanoeukaryotes (see Supplementary Fig.…”

Changing Physical Conditions and Lower and Upper Trophic Level Responses on the US Northeast Shelf

“…The second approach used was an algorithm designed to estimate the dominant PFTs at a location. The method is called PHYSTWO and is described in Correa-Ramirez et al (2018). The approach uses Empirical Orthogonal Function (EOF) decomposition to relate pigment signatures to water-leaving radiances.…”