Remote Sensing of Particulate Organic Carbon Pools in the High-Latitude Oceans

The general goal of this project was to characterize spatial distributions at basin scales and variability on monthly to interannual timescales of particulate organic carbon (POC) in the high-latitude oceans. The primary objectives were: (1) To collect in situ data in the north polar waters of the Atlantic and in the Southern Ocean, necessary for the derivation of POC ocean color algorithms for these regions. (2) To derive regional POC algorithms and refine existing regional chlorophyll (Chl) algorithms, to develop understanding of processes that control bio-optical relationships underlying ocean color algorithms for POC and Chl, and to explain bio-optical differentiation between the examined polar regions and within the regions. (3) To determine basin-scale spatial patterns and temporal variability on monthly to interannual scales in satellite-derived estimates of POC and Chl pools in the investigated regions for the period of time covered by SeaWiFS and MODIS missions

Analysis of Photosynthetic Rate and Bio-Optical Components from Ocean Color Imagery

Our research over the last 5 years indicates that the successful transformation of ocean color imagery into maps of bio-optical properties will require continued development and testing of algorithms. In particular improvements in the accuracy of predicting from ocean color imagery the concentration of the bio-optical components of sea as well as the rate of photosynthesis will require progress in at least three areas: (1) we must improve mathematical models of the growth and physiological acclimation of phytoplankton; (2) we must better understand the sources of variability in the absorption and backscattering properties of phytoplankton and associated microparticles; and (3) we must better understand how the radiance distribution just below the sea surface varies as a function sun and sky conditions and inherent optical properties

Optical backscattering by particles in Arctic seawater and relationships to particle mass concentration, size distribution, and bulk composition

The magnitude and spectral shape of the optical backscattering coefficient of particles, b(bp)(lambda), is being increasingly used to infer information about the particles present in seawater. Relationships between b(bp) and particle properties in the Arctic are poorly documented, and may differ from other oceanic regions which contribute the majority of data used to develop and parameterize optical models. We utilize recent field measurements from the Chukchi and Beaufort Seas to examine relationships between the spectral backscattering coefficient of particles in seawater and the mass concentration, bulk composition, and size distribution of the suspended particle assemblage. The particle backscattering coefficient spanned six orders of magnitude from the relatively clear waters of the Beaufort Sea to extremely turbid waters on the Mackenzie shelf. This coefficient was highly correlated with the mass concentration of particles, and to a lesser extent with other measures of concentration such as particulate organic carbon or chlorophyll a. Increased backscattering and high mass-specific b(bp)(lambda) was associated with mineral-rich assemblages that tended to exhibit steeper size distributions, while reduced backscattering was associated with organic-dominated assemblages having a greater contribution of large particles. Our results suggest that algorithms which employ composition-specific relationships can lead to improved estimates of particle mass concentration from backscattering measurements. In contrast to theoretical models, however, we observe no clear relationship between the spectral slope of b(bp)(lambda) and the slope of the particle size distribution in this environment

Optical classification and characterization of marine particle assemblages within the western Arctic Ocean

We develop an optical classification of marine particle assemblages from an extensive dataset of particle optical properties collected in the Chukchi and Beaufort Seas. Hierarchical cluster analysis of the spectral particulate backscattering-to-absorption ratio partitioned the dataset into seven optically-distinct clusters of particle assemblages, each associated with different characteristics of particle concentration, composition, and phytoplankton taxonomic composition and size. Three phytoplankton-dominated clusters were identified. One was characterized by small-sized phytoplankton that are typically associated with regenerated production, and comprised samples from the subsurface chlorophyll-a maximum in oligotrophic waters of the Beaufort Sea. The other two clusters represented diatom-dominated particle assemblages in turbid shelf waters with differing contributions of photoprotective pigments. Such situations are generally associated with significant new production. Two clusters were dominated by organic nonalgal material, one representing clear waters off the shelf, the other representative of post-diatom bloom conditions in the Chukchi Sea. Another distinct cluster represented mineral-dominated particle assemblages that were observed in the Colville and Mackenzie River plumes and near the seafloor. Finally, samples in a cluster of mixed particle composition were scattered throughout all locations. Optical classification improved performance of predictive bio-optical relationships. These results demonstrate a capability to discriminate distinct assemblages of suspended particles associated with specific ecological conditions from hyperspectral measurements of optical properties, and the potential for identification of ecological provinces at synoptic time and space scales from optical sensors. Analogous analysis of multispectral optical data strongly reduced this capability

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

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.publishedVersio

The role of seawater constituents in light backscattering in the ocean

The significance of light backscattering in the ocean is wide ranging, especially in optical remote sensing. However, the complexity of natural seawater as an optical medium often obscures the measured optical signals to the point that our present-day interpretation and detailed understanding of major sources of backscattering and its variability in the ocean are uncertain and controversial. Here we review the roles played by various seawater constituents in light backscattering and we address a question of \u27missing\u27 backscattering. Historically, this question has resulted from a hypothesis that under non-bloom conditions in the open ocean, phytoplankton make a significantly smaller contribution to the particulate backscattering coefficient than to the particulate (total) scattering coefficient. By discussing the backscattering properties and potential contributions of the various water constituents (colloids, bacteria, phytoplankton, biogenic detritus, minerogenic particles, bubbles), we show that due to substantial variability in water composition, different types of constituents can explain the \u27missing\u27 backscattering. Under typical non-bloom conditions in the open ocean, the small-sized non-living particles appear to be the most important because of their high abundance relative to other particle types. These particles are believed to be primarily of organic origin but an important role of minerogenic particles cannot be excluded. Still, in the very clear ocean water the backscattering by water molecules themselves can contribute as much as 80% to the total backscattering coefficient in the blue spectral region. The general scenario of the dominance of molecules and small-sized particles can, however, be readily perturbed due to changes in local conditions. For example, bubbles entrained by breaking waves can intermittently dominate the backscattering at shallow depths below the sea surface, the calcifying phytoplankton (coccolithophores) producing calcite scales of high refractive index can dominate if present in sufficient concentration, and other plankton species can dominate during blooms. The role of phytoplankton could be generally greater than commonly assumed given the fact that real cells backscatter more light than predicted from homogeneous sphere models. In addition, high refractive index mineral particles can dominate in many coastal areas, and perhaps also in some open ocean areas during events of atmospheric dust deposition. It is likely that the different scenarios are quite widespread and frequent. Further improvements in quantitative understanding of the variability in light backscattering and its sources require an increased effort in basic research to better characterize the optical properties of the various seawater constituents and the variability in the detailed composition of seawater. Seawater is a complex optical medium containing a great variety of particle types and soluble species that vary in concentration and composition with time and location in the ocean, so ocean optics science must progress beyond the traditional overly simplified description, which has been based only on a few constituent categories defined broadly as molecular water, suspended particles (phytoplankton and non-algal particles), and dissolved organic matter. © 2004 Elsevier Ltd. All rights reserved

Optical modeling of ocean waters: Is the case 1 - case 2 classification still useful?

…two extreme cases can be identified and separated. Case 1 is that of a concentration of phytoplankton high compared to other particles…. In contrast, the inorganic particles are dominant in case 2.… In both cases dissolved yellow substance is present in variable amounts.… An ideal case 1 would be a pure culture of phytoplankton and an ideal case 2 a suspension of nonliving material with a zero concentration of pigments. Morel and Prieur emphasized that these ideal cases are not encountered in nature, and they suggested the use of high or low values of the ratio of pigment concentration to scattering coefficient as a basis for discriminating between Case 1 and Case 2 waters. Although no specific values of this ratio were proposed to serve as criteria for classification, their example data suggested that the ratio of chlorophyll a concentration (in mg m-3) to the scattering coefficient at 550 nm (in m-1) in Case 1 waters is greater than 1 and in Case 2 waters is less than 1. Importantly, however, Morel and Prieur also showed data classified as “intermediate waters” with the ratio between about 1 and 2.2. Although the original definition from 1977 did not imply a binary classification, the practice of most investigators in the following years clearly evolved toward a bipartite analysis

Why should we measure the optical backscattering coefficient?

In recent years commercial sensors for in situ determinations of optical backscattering coefficient, bb, have become available. The small size and low power requirements of these sensors permit deployment from small sensing platforms such as autonomous underwater vehicles, in addition to standard profiling packages. Given their rapid sampling time (sub second) they can collect data with high temporal and spatial resolution (sub meter). While these are attractive features of any sensor they do not answer the question: why should oceanographers measure bb? The short answer is that bb carries useful information about seawater constituents that scatter light. The potential to derive information about the abundance and the types of suspended marine particles, which play different roles in ocean ecosystems and biogeochemical cycling, is particularly attractive. To first order, the bb coefficient is a proxy for particle abundance but it also depends significantly on particle size distribution and particle composition, for example, on relative proportions of small and larger particles or on whether the particles are organic or inorganic. Most importantly, however, the spectral reflectance of the ocean (known as ocean color) is, to first order, proportional to bb. The measurements of ocean color from remote optical sensors on satellites provide a unique capability to monitor surface ocean properties (e.g., chlorophyll concentration and biological primary productivity) over extended spatial and temporal scales. Measurements and fundamental understanding of bb are required for understanding and successful applications of remotely sensed ocean color

Comparison of Near-Forward Light Scattering on Oceanic Turbulence and Particles

We examine and compare near-forward light scattering that is caused by turbulence and typical particulate assemblages in the ocean. The near-forward scattering by particles was calculated using Mie theory for homogeneous spheres and particle size distributions representative of natural assemblages in the ocean. Direct numerical simulations of a passive scalar with Prandtl number 7 mixed by homogeneous turbulence were used to represent temperature fluctuations and resulting inhomogeneities in the refractive index of water. Light scattering on the simulated turbulent flow was calculated using the geometrical-optics approximation. We found that the smallest temperature scales contribute the most to scattering, and that scattering on turbulence typically dominates over scattering on particles for small angles as large as 0.1°. The scattering angle deviation that is due to turbulence for a light beam propagating over a 0.25-m path length in the oceanic water can be as large as 0.1°. In addition, we carried out a preliminary laboratory experiment that illustrates the differences in the near-forward scattering on refractive-index inhomogeneities and particles

Hyperspectral optical absorption closure experiment in complex coastal waters

Accurate measurements of absorption data are required for the development and validation of inversion algorithms for upcoming hyperspectral ocean color imaging sensors, such as the NASA Phytoplankton, Aerosol, Cloud, and ocean Ecosystem mission. This study aims to provide uncertainty estimates associated with leading approaches to measure hyperspectral absorption coefficients in complex coastal waters. Absorption spectra were collected at 12 different stations, all located in the Indian River Lagoon, Florida, USA, between 09 January 2017 and 13 January 2017. Measurements included spectral absorption coefficients in the visible range (400–700 nm) associated with dissolved, a CDOM, total particulate, a p, and total nonwater, a nw, fractions, and were made both in situ and from discrete samples. Discrete sample approaches included dual-beam spectrophotometer, liquid waveguide capillary cell, point-source integrating cavity absorption meter (PSICAM) for dissolved matter absorption samples, and quantitative filter technique ICAM measurements and the dual-beam spectrophotometer with center-mounted integrating sphere filter pad technique, while the Turner Designs ICAM, and WET Labs AC-s, and AC-9 instruments were used to determine absorption coefficients in situ. The Gershun approach, determining absorption from measurement of the irradiance quartet with respect to depth was also assessed in situ. Measurement uncertainties and relative accuracies were quantified for each of these approaches. Results showed generally strong agreements between different discrete sample methods, with average percent absolute error %δ abs < 7% for a CDOM and < 9% for a p. In situ approaches showed higher variability and reduced accuracy. For a nw, %δ abs deviation relative to PSICAM data was on average 12% to 20%. Results help identify remaining technological gaps and need for improvements in the different absorption measurement approaches