title: Approach for determining the contributions of phytoplankton, colored organic material, and nonalgal particles to the total spectral absorption in marine waters.
abstract: Using a data set of 1333 samples, we assess the spectral absorption relationships of different wave bands for phytoplankton (ph) and particles. We find that a nonlinear model (second-order quadratic equations) delivers good performance in describing their spectral characteristics. Based on these spectral relationships, we develop a method for partitioning the total absorption coefficient into the contributions attributable to phytoplankton [a(ph)(λ)], colored dissolved organic material [CDOM; a(CDOM)(λ)], and nonalgal particles [NAP; a(NAP)(λ)]. This method is validated using a data set that contains 550 simultaneous measurements of phytoplankton, CDOM, and NAP from the NASA bio-Optical Marine Algorithm Dataset. We find that our method is highly efficient and robust, with significant accuracy: the relative root-mean-square errors (RMSEs) are 25.96%, 38.30%, and 19.96% for a(ph)(443), a(CDOM)(443), and the CDOM exponential slope, respectively. The performance is still satisfactory when the method is applied to water samples from the northern South China Sea as a regional case. The computed and measured absorption coefficients (167 samples) agree well with the RMSEs, i.e., 18.50%, 32.82%, and 10.21% for a(ph)(443), a(CDOM)(443), and the CDOM exponential slope, respectively. Finally, the partitioning method is applied directly to an independent data set (1160 samples) derived from the Bermuda Bio-Optics Project that contains relatively low absorption values, and we also obtain good inversion accuracy [RMSEs of 32.37%, 32.57%, and 11.52% for a(ph)(443), a(CDOM)(443), and the CDOM exponential slope, respectively]. Our results indicate that this partitioning method delivers satisfactory performance for the retrieval of a(ph), a(CDOM), and a(NAP). Therefore, this may be a useful tool for extracting absorption coefficients from in situ measurements or remotely sensed ocean-color data.
authors.affiliation: State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China.
authors.forename: Junfang
authors.initials: J
authors.lastname: Lin
authors.forename: Wenxi
authors.initials: W
authors.lastname: Cao
authors.forename: Guifeng
authors.initials: G
authors.lastname: Wang
authors.forename: Shuibo
authors.initials: S
authors.lastname: Hu
mesh_terms: D000042:Absorption; D000465:Algorithms; D004784:Environmental Monitoring / Q000295:instrumentation / Q000379:methods; D058086:Microalgae / Q000737:chemistry*; D055095:Optics and Photonics; D009930:Organic Chemicals / Q000737:chemistry*; D010839:Phytoplankton / Q000737:chemistry*; D058998:Remote Sensing Technology; D012623:Seawater / Q000737:chemistry; D014871:Water Microbiology
chemical_list: D009930:Organic Chemicals