Corrigendum to "Relationships between the surface concentration of particulate organic carbon and optical properties in the eastern South Pacific and eastern Atlantic Oceans'' published in Biogeosciences, 5, 171?201, 2008

International audienceNo abstract available

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

Optical backscattering properties of the "clearest" natural waters

International audienceDuring the BIOSOPE field campaign October–December 2004, measurements of inherent optical properties from the surface to 500 m depth were made with a ship profiler at stations covering over ~8000 km through the Southeast Pacific Ocean. Data from a ~3000 km section containing the very clearest waters in the central gyre are reported here. The total volume scattering function at 117°, ßt(117°), was measured with a WET Labs ECO-BB3 sensor at 462, 532, and 650 nm with estimated uncertainties of 2×10-5, 5×10-6, and 2×10-6 m-1 sr-1, respectively. These values were approximately 6%, 3%, and 3% of the scattering by pure seawater at their respective wavelengths. From a methodological perspective, there were several results: – bbp distributions were resolvable even though some of the values from the central gyre were an order of magnitude lower than the lowest previous measurements in the literature; – Direct in-situ measurements of instrument dark offsets were necessary to accurately resolve backscattering at these low levels; – accurate pure seawater backscattering values are critical in determining particulate backscattering coefficients in the open ocean (not only in these very clear waters); the pure water scattering values determined by Buiteveld et al. (1994) with a [1 + 0.3S/37] adjustment for salinity based on Morel (1974) appear to be the most accurate estimates, with aggregate accuracies as low as a few percent; and – closure was demonstrated with subsurface reflectance measurements reported by Morel et al. (2007) within instrument precisions, a useful factor in validating the backscattering measurements. This methodology enabled several observations with respect to the hydrography and the use of backscattering as a biogeochemical proxy: – The clearest waters sampled were found at depths between 300 and 350 m, from 23.5° S, 118° W to 26° S, 114° W, where total backscattering at 650 nm was not distinguishable from pure seawater; – Distributions of particulate backscattering bbp across the central gyre exhibited a broad particle peak centered ~100 m; – The particulate backscattering ratio typically ranged between 0.4% and 0.6% through the majority of the central gyre from the surface to ~210 m, indicative of "soft" water-filled particles with low bulk refractive index; and – bbp at 532 and 650 nm showed a distinct secondary deeper layer centered ~230 m that was absent in particulate attenuation cp data. The particulate backscattering ratio was significantly higher in this layer than in the rest of the water column, reaching 1.2% in some locations. This high relative backscattering, along with the pigment composition and ecological niche of this layer, appear to be consistent with the coccolithophorid F. profunda. Moreover, results were consistent with several expectations extrapolated from theory and previous work in oceanic and coastal regions, supporting the conclusion that particulate and total backscattering could be resolved in these extremely clear natural waters

A synthetic optical database generated by radiative transfer simulations in support of studies in ocean optics and optical remote sensing of the global ocean

Radiative transfer (RT) simulations have long been used to study the relationships between the inherent optical properties (IOPs) of seawater and light fields within and leaving the ocean, from which ocean apparent optical properties (AOPs) can be calculated. For example, inverse models used to estimate IOPs from ocean color radiometric measurements have been developed and validated using the results of RT simulations. Here we describe the development of a new synthetic optical database based on hyperspectral RT simulations across the spectral range of near-ultraviolet to near-infrared performed with the HydroLight radiative transfer code. The key component of this development is the generation of a synthetic dataset of seawater IOPs that serves as input to RT simulations. Compared to similar developments of optical databases in the past, the present dataset of IOPs is characterized by the probability distributions of IOPs that are consistent with global distributions representative of vast areas of open-ocean pelagic environments and coastal regions, covering a broad range of optical water types. The generation of synthetic data of IOPs associated with particulate and dissolved constituents of seawater was driven largely by an extensive set of field measurements of the phytoplankton absorption coefficient collected in diverse oceanic environments. Overall, the synthetic IOP dataset consists of 3320 combinations of IOPs. Additionally, the pure seawater IOPs were assumed following recent recommendations. The RT simulations were performed using 3320 combinations of input IOPs, assuming vertical homogeneity within an infinitely deep ocean. These input IOPs were used in three simulation scenarios associated with assumptions about inelastic radiative processes in the water column (not considered in previous synthetically generated optical databases) and three simulation scenarios associated with the sun zenith angle. Specifically, the simulations were made assuming no inelastic processes, the presence of Raman scattering by water molecules, and the presence of both Raman scattering and fluorescence of chlorophyll a pigment. Fluorescence of colored dissolved organic matter was omitted from all simulations. For each of these three simulation scenarios, the simulations were made for three sun zenith angles of 0, 30, and 60∘ assuming clear skies, standard atmosphere, and a wind speed of 5 m s−1. Thus, overall 29 880 RT simulations were performed. The output results of these simulations include radiance distributions, plane and scalar irradiances, and a whole set of AOPs, including remote-sensing reflectance, vertical diffuse attenuation coefficients, and mean cosines, where all optical variables are reported in the spectral range of 350 to 750 nm at 5 nm intervals for different depths between the sea surface and 50 m. The consistency of this new synthetic database has been assessed through comparisons with in situ data and previously developed empirical relationships involving IOPs and AOPs. The database is available at the Dryad open-access repository of research data (https://doi.org/10.6076/D1630T, Loisel et al., 2023).</p

Patterns of suspended particulate matter across the continental margin in the Canadian Beaufort Sea during summer

The particulate beam attenuation coefficient at 660&thinsp;nm, cp(660), was measured in conjunction with properties of suspended particle assemblages in August 2009 within the Canadian Beaufort Sea continental margin, a region heavily influenced by freshwater and sediment discharge from the Mackenzie River, but also by sea ice melt. The mass concentration of suspended particulate matter (SPM) ranged from 0.04 to 140&thinsp;g&thinsp;m−3, its composition varied from mineral to organic dominated, and the median particle diameter determined over the range 0.7–120&thinsp;µm varied from 0.78 to 9.45&thinsp;µm, with the fraction of particles &lt;1&thinsp;µm in surface waters reflecting the degree influenced by river water. Despite this range in particle characteristics, a strong relationship between SPM and cp(660) was found and used to determine SPM distributions across the shelf based on measurements of cp(660) taken during summer seasons of 2004, 2008, and 2009. SPM spatial patterns on the stratified shelf reflected the vertically sheared two-layer estuarine circulation and SPM sources (i.e., fluvial inputs, bottom resuspension, and biological productivity). Along-shelf winds generated lateral Ekman flows, isopycnal movements, and upwelling or downwelling at the shelf break. Cross-shelf transects measured during three summers illustrate how sea ice meltwater affects river plume extent, while the presence of meltwater on the shelf was associated with enhanced near-bottom SPM during return flow of upwelled Pacific-origin water. SPM decreased sharply past the shelf break with further transport of particulate matter occurring near the bottom and in interleaving nepheloid layers. These findings expand our knowledge of particle distributions in the Beaufort Sea controlled by river discharge, sea ice, and wind, each of which is sensitive to weather and climate variations.</p

Relationships between the surface concentration of particulate organic carbon and optical properties in the eastern South Pacific and eastern Atlantic Oceans

International audienceWe have examined several approaches for estimating the surface concentration of particulate organic carbon, POC, from optical measurements of remote-sensing reflectance, <i>R_rs(?)</i>, using field data collected in tropical and subtropical waters of the eastern South Pacific and eastern Atlantic Oceans. These approaches include a direct empirical relationship between POC and the blue-to-green band ratio of reflectance, <i>R_rs(?_B)/R_rs</i>(555), and two-step algorithms that consist of relationships linking reflectance to an inherent optical property IOP (beam attenuation or backscattering coefficient) and POC to the IOP. We considered two-step empirical algorithms that exclusively include pairs of empirical relationships and two-step hybrid algorithms that consist of semianalytical models and empirical relationships. The surface POC in our data set ranges from about 10 mg m^-3 within the South Pacific Subtropical Gyre to 270 mg m^-3 in the Chilean upwelling area, and data on phytoplankton pigments, suspended particulate matter, and the backscattering ratio suggest a considerable variation in the composition of particulate assemblages in the investigated waters. The POC algorithm based on the direct relationship between POC and <i>R_rs(?_B)/R_rs</i>(555) promises reasonably good performance in the vast areas of the open ocean covering different provinces from hyperoligotrophic and oligotrophic waters within subtropical gyres to eutrophic coastal upwelling regimes characteristic of eastern ocean boundaries. The best error statistics were found for power function fits to the data of POC vs. <i>R_rs</i>(443)<i>/R_rs</i>(555) and POC vs. <i>R_rs</i>(490)<i>/R_rs</i>(555). For our data set that includes over 50 data pairs, these relationships are characterized by the mean normalized bias of about 2% and the normalized root mean square error of about 20%. We recommend that these algorithms be implemented for routine processing of ocean color satellite data to produce maps of surface POC with the status of an evaluation data product for continued work on algorithm development and refinements. The two-step algorithms also deserve further attention because they can utilize various models for estimating IOPs from reflectance, offer advantages for developing an understanding of bio-optical variability underlying the algorithms, and provide flexibility for regional or seasonal parameterizations of the algorithms

Comparison of ocean-colour algorithms for particulate organic carbon in global ocean

This is the final version. Available on open access from Frontiers Media via the DOI in this recordData availability statement: The data sets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at https://www.bicep-project.org/DeliverablesIn the oceanic surface layer, particulate organic carbon (POC) constitutes the biggest pool of particulate material of biological origin, encompassing phytoplankton, zooplankton, bacteria, and organic detritus. POC is of general interest in studies of biologically-mediated fluxes of carbon in the ocean, and over the years, several empirical algorithms have been proposed to retrieve POC concentrations from satellite products. These algorithms can be categorised into those that make use of remote-sensing-reflectance data directly, and those that are dependent on chlorophyll concentration and particle backscattering coefficient derived from reflectance values. In this study, a global database of in situ measurements of POC is assembled, against which these different types of algorithms are tested using daily matchup data extracted from the Ocean Colour Climate Change Initiative (OC-CCI; version 5). Through analyses of residuals, pixel-by-pixel uncertainties, and validation based on optical water types, areas for POC algorithm improvement are identified, particularly in regions underrepresented in the in situ POC data sets, such as coastal and high-latitude waters. We conclude that POC algorithms have reached a state of maturity and further improvements can be sought in blending algorithms for different optical water types when the required in situ data becomes available. The best performing band ratio algorithm was tuned to the OC-CCI version 5 product and used to produce a global time series of POC between 1997–2020 that is freely available.European Space AgencySimons Collaboration on Computational Biogeochemical Modeling of Marine Ecosystems (CBIOMES)National Centre for Earth Observations (NCEO)OPERA projec

Comparison of ocean-colour algorithms for particulate organic carbon in global ocean

In the oceanic surface layer, particulate organic carbon (POC) constitutes the biggest pool of particulate material of biological origin, encompassing phytoplankton, zooplankton, bacteria, and organic detritus. POC is of general interest in studies of biologically-mediated fluxes of carbon in the ocean, and over the years, several empirical algorithms have been proposed to retrieve POC concentrations from satellite products. These algorithms can be categorised into those that make use of remote-sensing-reflectance data directly, and those that are dependent on chlorophyll concentration and particle backscattering coefficient derived from reflectance values. In this study, a global database of in situ measurements of POC is assembled, against which these different types of algorithms are tested using daily matchup data extracted from the Ocean Colour Climate Change Initiative (OC-CCI; version 5). Through analyses of residuals, pixel-by-pixel uncertainties, and validation based on optical water types, areas for POC algorithm improvement are identified, particularly in regions underrepresented in the in situ POC data sets, such as coastal and highlatitude waters. We conclude that POC algorithms have reached a state of maturity and further improvements can be sought in blending algorithms for different optical water types when the required in situ data becomes available. The best performing band ratio algorithm was tuned to the OC-CCI version 5 product and used to produce a global time series of POC between 1997–2020 that is freely available

Distributions of phytoplankton carbohydrate, protein and lipid in the world oceans from satellite ocean colour

Energy value of phytoplankton regulates the growth of higher trophic species, affecting the tropic balance and sustainability of marine food webs. Therefore, developing our capability to estimate and monitor, on a global scale, the concentrations of macromolecules that determine phytoplankton energy value, would be invaluable. Reported here are the first estimates of carbohydrate, protein, lipid, and overall energy value of phytoplankton in the world oceans, using ocean-colour data from satellites. The estimates are based on a novel bio-optical method that utilises satellite-derived bio-optical fingerprints of living phytoplankton combined with allometric relationships between phytoplankton cells and cellular macromolecular contents. The annually-averaged phytoplankton energy value, per cubic meter of sub-surface ocean, varied from less than 0.1 kJ in subtropical gyres, to 0.5–1.0 kJ in parts of the equatorial, northern and southern latitudes, and rising to more than 10 kJ in certain coastal and optically complex waters. The annually-averaged global stocks of carbohydrate, protein and lipid were 0.044, 0.17 and 0.108 gigatonnes, respectively, with monthly stocks highest in September and lowest in June, over 1997-2013. The fractional contributions of phytoplankton size classes e.g., picoplankton, nanoplankton and microplankton to surface concentrations and global stocks of macromolecules varied considerably across marine biomes classified as Longhurst provinces. Among these provinces, the highest annually-averaged surface concentrations of carbohydrate, protein, and lipid were in North-East Atlantic Coastal Shelves, whereas, the lowest concentration of carbohydrate or lipid were in North Atlantic Tropical Gyral, and that of protein was in North Pacific Subtropical Gyre West. The regional accuracy of the estimates and their sensitivity to satellite inputs are quantified from the bio-optical model, which show promise for possible operational monitoring of phytoplankton energy value from satellite ocean colour. Adequate in situ measurements of macromolecules and improved retrievals of inherent optical properties from high-resolution satellite images, would be required to validate these estimates at local sites, and to further improve their accuracy in the world oceans

Introduction to special section on Recent Advances in the Study of Optical Variability in the Near-Surface and Upper Ocean

Optical variability occurs in the near-surface and upper ocean on very short time and space scales (e.g., milliseconds and millimeters and less) as well as greater scales. This variability is caused by solar, meteorological, and other physical forcing as well as biological and chemical processes that affect optical properties and their distributions, which in turn control the propagation of light across the air-sea interface and within the upper ocean. Recent developments in several technologies and modeling capabilities have enabled the investigation of a variety of fundamental and applied problems related to upper ocean physics, chemistry, and light propagation and utilization in the dynamic near-surface ocean. The purpose here is to provide background for and an introduction to a collection of papers devoted to new technologies and observational results as well as model simulations, which are facilitating new insights into optical variability and light propagation in the ocean as they are affected by changing atmospheric and oceanic conditions