Electromagnetic theory predicts spectral dependencies in extinction efficiency near a narrow absorption band for a particle with an index of refraction close to that of the medium in which it is immersed. These absorption band effects are anticipated in oceanographic beam-attenuation (beam-c) spectra, primarily due to the narrow red peak in absorption produced by the phytoplankton photopigment, chlorophyll a (Chl a). Here we present a method to obtain Chl a absorption and size information by analyzing an eigendecomposition of hyperspectral beam-c residuals measured in marine surface waters by an automatic underway system. We find that three principal modes capture more than 99% of the variance in beam-c residuals at wavelengths near the Chl a red absorption peak. The spectral shapes of the eigenvectors resemble extinction efficiency residuals attributed to the absorption band effects. Projection of the eigenvectors onto the beam-c residuals produces a time series of amplitude functions with absolute values that are strongly correlated to concurrent Chl a absorption line height (a_LH) measurements (r values of 0.59 to 0.83) and hence provide a method to estimate Chl a absorption. Multiple linear regression of a_LH on the amplitude functions enables an independent estimate of a_LH, with RMSE of 3.19⋅10^-3m^-1 (3.3%) or log₁₀-RMSE of 18.6%, and a raw-scale R² value of 0.90 based on the Tara Oceans Expedition data. Relationships between the amplitude functions and the beam-c exponential slopes are in agreement with theory relating beam-c to the particle size distribution. Compared to multispectral analysis of beam-c slope, hyperspectral analysis of absorption band effects is anticipated to be relatively insensitive to the addition of nonpigmented particles and to monodispersion.

Abstract: The spring bloom in the Southern Ocean is the rapid‐growth phase of the seasonal cycle in phytoplankton. Many previous studies have characterized the spring bloom using chlorophyll estimates from satellite ocean color observations. Assumptions regarding the chlorophyll‐to‐carbon ratio within phytoplankton and vertical structure of biogeochemical variables lead to uncertainty in satellite‐based estimates of phytoplankton carbon biomass. Here, we revisit the characterizations of the bloom using optical backscatter from biogeochemical floats deployed by the Southern Ocean Carbon and Climate Observations and Modeling and Southern Ocean and Climate Field Studies with Innovative Tools projects. In particular, by providing a three‐dimensional view of the seasonal cycle, we are able to identify basin‐wide bloom characteristics corresponding to physical features; biomass is low in Ekman downwelling regions north of the Antarctic Circumpolar Current region and high within and south of the Antarctic Circumpolar Current.

Field and laboratory characterization of marine particles is laborious and expensive. Proxies of particle properties have been developed that allow researchers to obtain high frequency distributions of such properties in space or time. We focus on optical techniques used to characterize marine particles in-situ, with a focus on GEOTRACES-relevant properties, such as bulk properties including particle mass, cross-sectional area, particle size distribution, particle shape information, and also single particle optical properties, such as individual particle type and size. We also address the use of optical properties of particles to infer particulate organic or inorganic carbon. In addition to optical sensors we review advances in imaging technology and its use to study marine particles in situ. This review addresses commercially available technology and techniques that can be used as a proxy for particle properties and the associated uncertainties with particular focus to open ocean environments, the focus of GEOTRACES.

Light emerging from natural water bodies and measured by radiometers contains information about the local type and concentrations of phytoplankton, non-algal particles and colored dissolved organic matter in the underlying waters. An increase in spectral resolution in forthcoming satellite and airborne remote sensing missions is expected to lead to new or improved capabilities for characterizing aquatic ecosystems. Such upcoming missions include NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission; the NASA Surface Biology and Geology designated observable mission; and NASA Airborne Visible/Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG) airborne missions. In anticipation of these missions, we present an organized dataset of geographically diverse, quality-controlled, high spectral resolution inherent and apparent optical property (IOP-AOP) aquatic data. The data are intended to be of use to increase our understanding of aquatic optical properties, to develop aquatic remote sensing data product algorithms, and to perform calibration and validation activities for forthcoming aquatic-focused imaging spectrometry missions. The dataset is comprised of contributions from several investigators and investigating teams collected over a range of geographic areas and water types, including inland waters, estuaries, and oceans. Specific in situ measurements include remote-sensing reflectance, irradiance reflectance, and coefficients describing particulate absorption, particulate attenuation, non-algal particulate absorption, colored dissolved organic matter absorption, phytoplankton absorption, total absorption, total attenuation, particulate backscattering, and total backscattering. The dataset can be downloaded from https://doi.org/10.1594/PANGAEA.902230 (Casey et al., 2019).

Ocean color measured from satellites provides daily global, synoptic views of spectral waterleaving reflectances that can be used to generate estimates of marine inherent optical properties (IOPs). These reflectances, namely the ratio of spectral upwelled radiances to spectral downwelled irradiances, describe the light exiting a water mass that defines its color. IOPs are the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents. Because of their dependence on the concentration and composition of marine constituents, IOPs can be used to describe the contents of the upper ocean mixed layer. This information is critical to further our scientific understanding of biogeochemical oceanic processes, such as organic carbon production and export, phytoplankton dynamics, and responses to climatic disturbances. Given their importance, the international ocean color community has invested significant effort in improving the quality of satellite-derived IOP products, both regionally and globally. Recognizing the current influx of data products into the community and the need to improve current algorithms in anticipation of new satellite instruments (e.g., the global, hyperspectral spectroradiometer of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission), we present a synopsis of the current state of the art in the retrieval of these core optical properties. Contemporary approaches for obtaining IOPs from satellite ocean color are reviewed and, for clarity, separated based their inversion methodology or the type of IOPs sought. Summaries of known uncertainties associated with each approach are provided, as well as common performance metrics used to evaluate them. We discuss current knowledge gaps and make recommendations for future investment for upcoming missions whose instrument characteristics diverge sufficiently from heritage and existing sensors to warrant reassessing current approaches.

Four North Atlantic Aerosol and Marine Ecosystems Study (NAAMES) field campaigns from winter 2015 through spring 2018 sampled an extensive set of oceanographic and atmospheric parameters during the annual phytoplankton bloom cycle. This unique dataset provides four seasons of open-ocean observations of wind speed, sea surface temperature (SST), seawater particle attenuation at 660 nm (cp,660, a measure of ocean particulate organic carbon), bacterial production rates, and sea-spray aerosol size distributions and number concentrations (NSSA). The NAAMES measurements show moderate to strong correlations (0.56 < R < 0.70) between NSSA and local wind speeds in the marine boundary layer on hourly timescales, but this relationship weakens in the campaign averages that represent each season, in part because of the reduction in range of wind speed by multiday averaging. NSSA correlates weakly with seawater cp,660 (R = 0.36, P << 0.01), but the correlation with cp,660, is improved (R = 0.51, P < 0.05) for periods of low wind speeds. In addition, NAAMES measurements provide observational dependence of SSA mode diameter (dm) on SST, with dm increasing to larger sizes at higher SST (R = 0.60, P << 0.01) on hourly timescales. These results imply that climate models using bimodal SSA parameterizations to wind speed rather than a single SSA mode that varies with SST may overestimate SSA number concentrations (hence cloud condensation nuclei) by a factor of 4 to 7 and may underestimate SSA scattering (hence direct radiative effects) by a factor of 2 to 5, in addition to overpredicting variability in SSA scattering from wind speed by a factor of 5.

Four North Atlantic Aerosol and Marine Ecosystems Study (NAAMES) field campaigns from winter 2015 through spring 2018 sampled an extensive set of oceanographic and atmospheric parameters during the annual phytoplankton bloom cycle. This unique dataset provides four seasons of open-ocean observations of wind speed, sea surface temperature (SST), seawater particle attenuation at 660 nm (c p,660, a measure of ocean particulate organic carbon), bacterial production rates, and sea-spray aerosol size distributions and number concentrations (N SSA). The NAAMES measurements show moderate to strong correlations (0.56 < R < 0.70) between N SSA and local wind speeds in the marine boundary layer on hourly timescales, but this relationship weakens in the campaign averages that represent each season, in part because of the reduction in range of wind speed by multiday averaging. N SSA correlates weakly with seawater cp,660 (R = 0.36, P << 0.01), but the correlation with cp,660, is improved (R = 0.51, P < 0.05) for periods of low wind speeds. In addition, NAAMES measurements provide observational dependence of SSA mode diameter (d m) on SST, with d m increasing to larger sizes at higher SST (R = 0.60, P << 0.01) on hourly timescales. These results imply that climate models using bimodal SSA parameterizations to wind speed rather than a single SSA mode that varies with SST may overestimate SSA number concentrations (hence cloud condensation nuclei) by a factor of 4 to 7 and may underestimate SSA scattering (hence direct radiative effects) by a factor of 2 to 5, in addition to overpredicting variability in SSA scattering from wind speed by a factor of 5.

Seasonal shifts in phytoplankton accumulation and loss largely follow changes in mixed layer depth, but the impact of mixed layer depth on cell physiology remains unexplored. Here, we investigate the physiological state of phytoplankton populations associated with distinct bloom phases and mixing regimes in the North Atlantic. Stratification and deep mixing alter community physiology and viral production, effectively shaping accumulation rates. Communities in relatively deep, early-spring mixed layers are characterized by low levels of stress and high accumulation rates, while those in the recently shallowed mixed layers in late-spring have high levels of oxidative stress. Prolonged stratification into early autumn manifests in negative accumulation rates, along with pronounced signatures of compromised membranes, death-related protease activity, virus production, nutrient drawdown, and lipid markers indicative of nutrient stress. Positive accumulation renews during mixed layer deepening with transition into winter, concomitant with enhanced nutrient supply and lessened viral pressure.

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will carry into space the Ocean Color Instrument (OCI), a spectrometer measuring at 5nm spectral resolution in the ultraviolet (UV) to near infrared (NIR) with additional spectral bands in the shortwave infrared (SWIR), and two multi-angle polarimeters that will overlap the OCI spectral range and spatial coverage, i. e., the Spectrometer for Planetary Exploration (SPEXone) and the Hyper-Angular Rainbow Polarimeter (HARP2). These instruments, especially when used in synergy, have great potential for improving estimates of water reflectance in the post Earth Observing System (EOS) era. Extending the top-of-atmosphere (TOA) observations to the UV, where aerosol absorption is effective, adding spectral bands in the SWIR, where even the most turbid waters are black and sensitivity to the aerosol coarse mode is higher than at shorter wavelengths, and measuring in the oxygen A-band to estimate aerosol altitude will enable greater accuracy in atmospheric correction for ocean color science. The multi-angular and polarized measurements, sensitive to aerosol properties (e.g., size distribution, index of refraction), can further help to identify or constrain the aerosol model, or to retrieve directly water reflectance. Algorithms that exploit the new capabilities are presented, and their ability to improve accuracy is discussed. They embrace a modern, adapted heritage two-step algorithm and alternative schemes (deterministic, statistical) that aim at inverting the TOA signal in a single step. These schemes, by the nature of their construction, their robustness, their generalization properties, and their ability to associate uncertainties, are expected to become the new standard in the future. A strategy for atmospheric correction is presented that ensures continuity and consistency with past and present ocean-color missions while enabling full exploitation of the new dimensions and possibilities. Despite the major improvements anticipated with the PACE instruments, gaps/issues remain to be filled/tackled. They include dealing properly with whitecaps, taking into account Earth-curvature effects, correcting for adjacency effects, accounting for the coupling between scattering and absorption, modeling accurately water reflectance, and acquiring a sufficiently representative dataset of water reflectance in the UV to SWIR. Dedicated efforts, experimental and theoretical, are in order to gather the necessary information and rectify inadequacies. Ideas and solutions are put forward to address the unresolved issues. Thanks to its design and characteristics, the PACE mission will mark the beginning of a new era of unprecedented accuracy in ocean-color radiometry from space.