A Multivariable Empirical Algorithm for Estimating Particulate Organic Carbon Concentration in Marine Environments From Optical Backscattering and Chlorophyll-a Measurements

Abstract

Accurate estimates of the oceanic particulate organic carbon concentration (POC) from optical measurements have remained challenging because interactions between light and natural assemblages of marine particles are complex, depending on particle concentration, composition, and size distribution. In particular, the applicability of a single relationship between POC and the spectral particulate backscattering coefficient bbp(λ) across diverse oceanic environments is subject to high uncertainties because of the variable nature of particulate assemblages. These relationships have nevertheless been widely used to estimate oceanic POC using, for example, in situ measurements of bbp from Biogeochemical (BGC)-Argo floats. Despite these challenges, such an in situbased approach to estimate POC remains scientifically attractive in view of the expanding global-scale observations with the BGC-Argo array of profiling floats equipped with optical sensors. In the current study, we describe an improved empirical approach to estimate POC which takes advantage of simultaneous measurements of bbp and chlorophyll-a fluorescence to better account for the effects of variable particle composition on the relationship between POC and bbp. We formulated multivariable regression models using a dataset of field measurements of POC, bbp, and chlorophyll-a concentration (Chla), including surface and subsurface water samples from the Atlantic, Pacific, Arctic, and Southern Oceans. The analysis of this dataset of diverse seawater samples demonstrates that the use of bbp and an additional independent variable related to particle composition involving both bbp and Chla leads to notable improvements in POC estimations compared with a typical univariate regression model based on bbp alone. These multivariable algorithms are expected to be particularly useful for estimating POC with measurements from autonomous BGC-Argo floats operating in diverse oceanic environments. We demonstrate example results from the multivariable algorithm applied to depth-resolved vertical measurements from BGC-Argo floats surveying the Labrador Sea.

Optical Insight Into Riverine Influences on Dissolved and Particulate Organic Carbon in a Coastal Arctic Lagoon System

“…Our observations encompass a fairly homogenous assemblage of particulate materials, and our observed relationships appear fairly robust. Yet the large variations in the relationship between POC and backscatter reported by other researchers underscore the critical importance of understanding particle composition when deriving such relationships (Koestner et al., 2022; Reynolds et al., 2016; Stramski et al., 1999). Some mineral‐dominated samples exhibit strong correlations between POC and optical backscatter, but organic‐dominated particle assemblages deviate greatly from said trends.…”

Optical insight into riverine influences on dissolved and particulate organic carbon in a coastal Arctic lagoon system

“…Our data represent a fairly homogenous assemblage of particulate materials thus the relationships appear fairly good. However, large variations in the relationship between POC and backscatter exist in other studies indicating the importance of understanding the particle composition when deriving these relationships (Koestner et al, 2022;Reynolds et al, 2016;Stramski et al, 1999). Koestner et al (2021) indicates that while some mineral-dominated samples exhibit strong correlations between POC and optical backscatter, organic-dominated particle assemblages deviate greatly from said trends.…”

A Lagrangian perspective on the carbon and oxygen budget of an oceanic eddy

“…Particulate backscattering (b bp ) was considered representative of particles between 0.001-0.025 mm [40] and was converted to b bp POC concentration using the relationship recently obtained by Koestner et al [38], which performs better than previous ones (e.g. [73]).…”

“…The average POC content is calculated using a particulate backscatter b bp to carbon [38] and a UVP particle size to carbon relationship (Methods and ref.…”