Assessing the Impact of a Two-Layered Spherical Geometry of Phytoplankton Cells on the Bulk Backscattering Ratio of Marine Particulate Matter

Optical backscattering and linear polarization properties of the colony forming cyanobacterium Microcystis

Light scattering characteristics of the cyanobacterium Microcystis are investigated with numerical models for sphere aggregates. During summer bloom seasons, Microcystis is prevalent in many inland waters across the globe. Monitoring concentrations with remote sensing techniques requires knowledge of the inherent optical properties (IOPs), especially the backscattering properties of Microcystis cells and colonies in natural settings. In situ measurements in waters dominated by Microcystis blooms have previously detected extremely high backscattering ratios, i.e., b_b/b>0.043 at 443 nm [1], the highest to our knowledge in the natural environment. These highb_b/bvalues could hold promise as a diagnostic tool in identifying and monitoring Microcystis using optical approaches. However, it has been unclear how this type of optically 'soft' organic particle can generate such highb_b/bvalues. In this study, the Multiple Sphere T-matrix (MSTM) model is used to calculate the IOPs of model colonies, including b_b/b. Colony sizes in the model ranged from several cells to several hundred and both colony packing density and cell gas vacuole content were varied. Results are compared with model results for equivalent-volume spheres (EVS) and direct in situ measurements. Colony formation was required in the modeling to reproduce the high b_b/bconsistent with in situ measurements. The combination of moderate to very dense colony (packing density >30%) and high gas vacuole content in individual cells (volume percentage >20%) was the most favorable condition leading to rapid increases in b_b/bwith increasing number of cells N_cell of the colony. Significant linear correlations were observed betweenb_b/b and N_cell^1/3 for these colonies, whereb_b/b increased beyond 0.04 once cell number reached about 1000 cells in the case with the most densely packed cells and highest gas vacuole content. Within commonly observed colony sizes (N_cell <10⁶), colonies with high gas vacuole content exhibited b_b/bvalues up to 0.055, consistent with direct measurements from Lake Erie. Polarized scattering was also of interest as a diagnostic tool, particularly with future Earth-orbiting polarimeters being deployed for the NASA Plankton, Aerosols, Cloud, ocean Ecosystem (PACE) mission. The Degree of Linear Polarization (DoLP), expressed by the ratio of two Mueller matrix elements-P₁₂/P₁₁, decreased with increasing colony cell number for Microcystis. Another ratio of two Mueller matrix elementsP₂₂/P₁₁, an index for nonsphericity, also decreased with increasing colony size. In addition to higher relative backscattering, greater colony packing density and larger gas vacuole sizes both led to lower DoLP peak magnitude and lowerP₂₂/P₁₁. An optical opposition feature due to constructive phase interference that was observed previously for cosmic dusts is also present for these modeled colonies, manifested by a narrow intensity peak and negative polarization dip near exact backscattering direction, gradually forming as colony size increases.

Drivers of spectral optical scattering by particles in the upper 500 m of the Atlantic Ocean

Optical models have been proposed to relate spectral variations in the beam attenuation (c_p) and optical backscattering (b_bp) coefficients to marine particle size distributions (PSDs). However, due to limited PSD data, particularly in the open ocean, optically derived PSDs suffer from large uncertainties and we have a poor empirical understanding of the drivers of spectral c_p and b_bp coefficients. Here we evaluated PSD optical proxies and investigated their drivers by analyzing an unprecedented dataset of co-located PSDs, phytoplankton abundances and optical measurements collected across the upper 500 m of the Atlantic Ocean. The spectral slope of c_p was correlated (r>0.59) with the slope of the PSD only for particles with diameters >1 µm and also with eukaryotic phytoplankton concentrations. No significant relationships between PSDs and the spectral slope of b_bp were observed. In the upper 200 m, the b_bp spectral slope was correlated to the light absorption by particles (a_p; r<-0.54) and to the ratio of cyanobacteria to eukaryotic phytoplankton. This latter correlation was likely the consequence of the strong relationship we observed between a_p and the concentration of eukaryotic phytoplankton (r=0.83).

Deriving Particulate Organic Carbon in Coastal Waters from Remote Sensing: Inter-Comparison Exercise and Development of a Maximum Band-Ratio Approach

Recently, different algorithms have been developed to assess near-surface particulate organic matter (POC) concentration over coastal waters. In this study, we gathered an extensive in situ dataset representing various contrasted bio-optical coastal environments at low, medium, and high latitudes, with various bulk particulate matter chemical compositions (mineral-dominated, 50% of the data set, mixed, 40%, or organic-dominated, 10%). The dataset includes 606 coincident measurements of POC concentration and remote-sensing reflectance, Rrs, with POC concentrations covering three orders of magnitude. Twelve existing algorithms have then been tested on this data set, and a new one was proposed. The results show that the performance of historical algorithms depends on the type of water, with an overall low performance observed for mineral-dominated waters. Furthermore, none of the tested algorithms provided satisfactory results over the whole POC range. A novel approach was thus developed based on a maximum band ratio of Rrs (red/blue, red/yellow or red/green ratio). Based on the standard statistical metric for the evaluation of inverse models, the new algorithm presents the best performance. The root-mean square deviation for log-transformed data (RMSDlog) is 0.25. The mean absolute percentage difference (MAPD) is 37.48%. The mean bias (MB) and median ratio (MR) values are 0.54 μg L−1 and 1.02, respectively. This algorithm replicates quite well the distribution of in situ data. The new algorithm was also tested on a matchup dataset gathering 154 coincident MERIS (MEdium Resolution Imaging Spectrometer) Rrs and in situ POC concentration sampled along the French coast. The matchup analysis showed that the performance of the new algorithm is satisfactory (RMSDlog = 0.24, MAPD = 34.16%, MR = 0.92). A regional illustration of the model performance for the Louisiana continental shelf shows that monthly mean POC concentrations derived from MERIS with the new algorithm are consistent with those derived from the 2016 algorithm of Le et al. which was specifically developed for this region.