A color-index-based empirical algorithm for determining particulate organic carbon concentration in the ocean from satellite observations

TitleA color-index-based empirical algorithm for determining particulate organic carbon concentration in the ocean from satellite observations
Publication TypeJournal Article
Year of Publication2018
AuthorsLe C.F, Zhou X.Y, Hu C.M, Lee Z.P, Li L., Stramski D
JournalJournal of Geophysical Research-Oceans
Volume123
Pagination7407-7419
Date Published2018/10
Type of ArticleArticle
ISBN Number2169-9275
Accession NumberWOS:000451274900025
Keywordsblue-green reflectance band ratio; global; global ocean; in-situ; inherent optical-properties; light-scattering; marine particles; matter; Ocean color remote sensing; oceanography; oceans; particulate organic carbon; phytoplankton; reflectance; seawifs; three-band reflectance difference; variability
Abstract

An empirical algorithm for estimating particulate organic carbon (POC) concentration in the surface ocean from satellite observations is formulated and validated using in situ POC data and remote-sensing reflectance (R-rs) data obtained from match-up satellite ocean color measurements. The algorithm builds upon the band-difference algorithm concept, which was originally developed for estimating chlorophyll-a concentration in clear waters. This algorithm utilizes three spectral bands centered approximately at 490, 550, and 670nm to determine a color index (CIPOC), from which POC can be estimated from satellite measurements. For comparison, the blue-green band-ratio algorithm is also formulated using the same data set of in situ POC and satellite-derived R-rs. Results show that the statistical parameters characterizing the differences between the satellite-derived POC and matchup in situ POC are similar when the CIPOC and band ratio algorithms are applied to open ocean waters where the values of CIPOC are relatively low. In coastal waters where the values of CIPOC are generally higher, the statistical parameters of algorithm performance are better for the CIPOC algorithm. In addition, because the CIPOC algorithm is less sensitive to errors and noise in the satellite-derived R-rs, the image quality obtained with this algorithm can be improved for both open-ocean and coastal waters. Particulate organic carbon (POC) in the global ocean is linked to many important ocean biogeochemical processes and is responsible for large carbon fluxes. POC variations occur over a broad range of spatial (from regional to global) and temporal (from seasonal to decadal) scales due to various factors. Ocean color data acquired from satellite sensors, such as Sea-viewing Wide-Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Medium-Resolution Imaging Spectrometer (MERIS), can be used to quantify POC, with the capability for uninterrupted long-term observations and global coverage. This study demonstrates that the color-index (band-difference) approach is applicable to the POC retrieval from remote-sensing reflectance in both open ocean and coastal waters.

DOI10.1029/2018jc014014
Short TitleJ Geophys Res-Oceans
Student Publication: 
No