28 research outputs found

    Light Absorption by Suspended Particles in the Red Sea: Effect of Phytoplankton Community Size Structure and Pigment Composition

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    The light absorption properties of phytoplankton (aph(λ)) and non-algal particles (anap(λ)) associated with phytoplankton pigments were analyzed across the Red Sea, in the upper 200 m depth, between October 2014 and August 2016. The contribution by non-algal particles to the total particulate light absorption (aph(λ)+ anap(λ)) was highly variable (23 ± 17% at 440 nm) and no relationship between anap(440) and chlorophyll a concentration, [TChl a], was observed. Phytoplankton specific phytoplankton absorption coefficients at 440 and 676 nm for a given [TChl a], aph*(440) and aph*(676), were slightly higher than those derived from average relationships for open ocean waters within the surface layer as well as along the water column. Variations in the concentration of photosynthetic and photoprotective pigments were noticeable by changes in phytoplankton community size structure as well as in aph*(λ). This study revealed that a higher proportion of picophytoplankton and an increase in photoprotective pigments (mainly driven by zeaxanthin) tended to be responsible for the higher aph*(λ) values found in the Red Sea as compared to other oligotrophic regions with similar [TChl a]. Understanding this variability across the Red Sea may help improve the accuracy of biogeochemical parameters, such as [TChl a], derived from in situ measurements and ocean color remote sensing at a regional scale

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

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    Optical models have been proposed to relate spectral variations in the beam attenuation (cp) and optical backscattering (bbp) 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 cp and bbp 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 cp was correlated (r>0.59) with the slope of the PSD only for particles with diameters >1 ”m and also with eukaryotic phytoplankton concentrations. No significant relationships between PSDs and the spectral slope of bbp were observed. In the upper 200 m, the bbp spectral slope was correlated to the light absorption by particles (ap; 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 ap and the concentration of eukaryotic phytoplankton (r=0.83)

    On the discrimination of multiple phytoplankton groups from light absorption spectra of assemblages with mixed taxonomic composition and variable light conditions

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    According to recommendations of the international community of phytoplankton functional type algorithm developers, a set of experiments on marine algal cultures was conducted to (1) investigate uncertainties and limits in phytoplankton group discrimination from hyperspectral light absorption properties of assemblages with mixed taxonomic composition, and (2) evaluate the extent to which modifications of the absorption spectral features due to variable light conditions affect the optical discrimination of phytoplankton. Results showed that spectral absorption signatures of multiple species can be extracted from mixed assemblages, even at low relative contributions. Errors in retrieved pigment abundances are, however, influenced by the co-occurrence of species with similar spectral features. Plasticity of absorption spectra due to changes in light conditions weakly affects interspecific differences, with errors <21% for retrievals of pigment concentrations from mixed assemblages

    Correction of profiles of in-situ chlorophyll fluorometry for the contribution of fluorescence originating from non-algal matter

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    In situ chlorophyll fluorometers have been widely employed for more than half a century, and to date, it still remains the most used instrument to estimate chlorophyll-a concentration in the field, especially for measurements onboard autonomous observation platforms, e.g., Bio-Argo floats and gliders. However, in deep waters (> 300 m) of some specific regions, e.g., subtropical gyres and the Black Sea, the chlorophyll fluorescence profiles frequently reveal “deep sea red fluorescence” features. In line with previous studies and through the analysis of a large data set (cruise transect in the South East Pacific and data acquired by 82 Bio- Argo floats), we show that the fluorescence signal measured by a humic-like DOM fluorometer is highly correlated to the “deep sea red fluorescence.” Both fluorescence signals are indeed linearly related in deep waters. To remove the contribution of non-algal organic matter from chlorophyll fluorescence profiles, we introduce a new correction. Rather that removing a constant value (generally the deepest chlorophyll a fluorescence value from the profile, i.e., so-called “deep-offset correction”), we propose a correction method which relies on DOM fluorometry and on its variation with depth. This new method is validated with chlorophyll concentration extracted from water samples and further applied on the Bio-Argo float data set. More generally, we discuss the potential of the proposed method to become a standard and routine procedure in quality-control and correction of chlorophyll a fluorescence originating from Bio-Argo network

    Two databases derived from BGC-Argo float measurements for marine biogeochemical and bio-optical applications

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    Since 2012, an array of 105 Biogeochemical-Argo (BGC-Argo) floats has been deployed across the world’s oceans to assist in filling observational gaps that are required for characterizing open-ocean environments. Profiles of biogeochemical (chlorophyll and dissolved organic matter) and optical (single-wavelength particulate optical backscattering, downward irradiance at three wavelengths, and photosynthetically available radiation) variables are collected in the upper 1000m every 1 to 10 days. The database of 9837 vertical profiles collected up to January 2016 is presented and its spatial and temporal coverage is discussed. Each variable is quality controlled with specifically developed procedures and its time series is quality-assessed to identify issues related to biofouling and/or instrument drift. A second database of 5748 profile-derived products within the first optical depth (i.e., the layer of interest for satellite remote sensing) is also presented and its spatiotemporal distribution discussed. This database, devoted to field and remote ocean color applications, includes diffuse attenuation coefficients for downward irradiance at three narrow wavebands and one broad waveband (photosynthetically available radiation), calibrated chlorophyll and fluorescent dissolved organic matter concentrations, and single wavelength particulate optical backscattering. To demonstrate the applicability of these databases, data within the first optical depth are compared with previously established bio-optical models and used to validate remotely derived bio-optical products. The quality-controlled databases are publicly available from the SEANOE (SEA scieNtific Open data Edition) publisher at https://doi.org/10.17882/49388 and https://doi.org/10.17882/47142 for vertical profiles and products within the first optical depth, respectively

    Determination of the absorption coefficient of chromophoric dissolved organic matter from underway spectrophotometry

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    Measurements of the absorption coefficient of chromophoric dissolved organic matter (ay) are needed to validate existing ocean-color algorithms. In the surface open ocean, these measurements are challenging because of low ay values. Yet, existing global datasets demonstrate that ay could contribute between 30% to 50% of the total absorption budget in the 400–450 nm spectral range, thus making accurate measurement of ay essential to constrain these uncertainties. In this study, we present a simple way of determining ay using a commercially-available in-situ spectrophotometer operated in underway mode. The obtained ay values were validated using independent collocated measurements. The method is simple to implement, can provide measurements with very high spatio-temporal resolution, and has an accuracy of about 0.0004 m−1 and a precision of about 0.0025 m−1 when compared to independent data (at 440 nm). The only limitation for using this method at sea is that it relies on the availability of relatively large volumes of ultrapure water. Despite this limitation, the method can deliver the ay data needed for validating and assessing uncertainties in ocean-colour algorithms

    Determination of the absorption coefficient of chromophoric dissolved organic matter from underway spectrophotometry

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    This is the final version. Available on open access from Optical Society of America via the DOI in this recordMeasurements of the absorption coefficient of chromophoric dissolved organic matter (ay) are needed to validate existing ocean-color algorithms. In the surface open ocean, these measurements are challenging because of low ay values. Yet, existing global datasets demonstrate that ay could contribute between 30% to 50% of the total absorption budget in the 400-450 nm spectral range, thus making accurate measurement of ay essential to constrain these uncertainties. In this study, we present a simple way of determining ay using a commercially-available in-situ spectrophotometer operated in underway mode. The obtained ay values were validated using independent collocated measurements. The method is simple to implement, can provide measurements with very high spatio-temporal resolution, and has an accuracy of about 0.0004 m−1 and a precision of about 0.0025 m−1 when compared to independent data (at 440 nm). The only limitation for using this method at sea is that it relies on the availability of relatively large volumes of ultrapure water. Despite this limitation, the method can deliver the ay data needed for validating and assessing uncertainties in ocean-colour algorithms.European Space Agency (ESA)National Atmospheric and Space Administration (NASA

    Uncertainty in ocean-color estimates of chlorophyll for phytoplankton groups

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    This is the final version. Available from Frontiers Media via the DOI in this record.Over the past decade, techniques have been presented to derive the community structure of phytoplankton at synoptic scales using satellite ocean-color data. There is a growing demand from the ecosystem modeling community to use these products for model evaluation and data assimilation. Yet, from the perspective of an ecosystem modeler these products are of limited use unless: (i) the phytoplankton products provided by the remote-sensing community match those required by the ecosystem modelers; and (ii) information on per-pixel uncertainty is provided to evaluate data quality. Using a large dataset collected in the North Atlantic, we re-tune a method to estimate the chlorophyll concentration of three phytoplankton groups, partitioned according to size [pico- (20 ÎŒm)]. The method is modified to account for the influence of sea surface temperature, also available from satellite data, on model parameters and on the partitioning of microphytoplankton into diatoms and dinoflagellates, such that the phytoplankton groups provided match those simulated in a state of the art marine ecosystem model (the European Regional Seas Ecosystem Model, ERSEM). The method is validated using another dataset, independent of the data used to parameterize the method, of more than 800 satellite and in situ match-ups. Using fuzzy-logic techniques for deriving per-pixel uncertainty, developed within the ESA Ocean Colour Climate Change Initiative (OC-CCI), the match-up dataset is used to derive the root mean square error and the bias between in situ and satellite estimates of the chlorophyll for each phytoplankton group, for 14 different optical water types (OWT). These values are then used with satellite estimates of OWTs to map uncertainty in chlorophyll on a per pixel basis for each phytoplankton group. It is envisaged these satellite products will be useful for those working on the validation of, and assimilation of data into, marine ecosystem models that simulate different phytoplankton groups.National Centre for Earth Observation (NCEO)European Space Agency (ESA)NERC-UK ECOMA

    Uncertainty in ocean-colour estimates of chlorophyll for phytoplankton groups

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    Over the past decade, techniques have been presented to derive the community structure of phytoplankton at synoptic scales using satellite ocean-color data. There is a growing demand from the ecosystem modeling community to use these products for model evaluation and data assimilation. Yet, from the perspective of an ecosystem modeler these products are of limited use unless: (i) the phytoplankton products provided by the remote-sensing community match those required by the ecosystem modelers; and (ii) information on per-pixel uncertainty is provided to evaluate data quality. Using a large dataset collected in the North Atlantic, we re-tune a method to estimate the chlorophyll concentration of three phytoplankton groups, partitioned according to size [pico- (20 ÎŒm)]. The method is modified to account for the influence of sea surface temperature, also available from satellite data, on model parameters and on the partitioning of microphytoplankton into diatoms and dinoflagellates, such that the phytoplankton groups provided match those simulated in a state of the art marine ecosystem model (the European Regional Seas Ecosystem Model, ERSEM). The method is validated using another dataset, independent of the data used to parameterize the method, of more than 800 satellite and in situ match-ups. Using fuzzy-logic techniques for deriving per-pixel uncertainty, developed within the ESA Ocean Colour Climate Change Initiative (OC-CCI), the match-up dataset is used to derive the root mean square error and the bias between in situ and satellite estimates of the chlorophyll for each phytoplankton group, for 14 different optical water types (OWT). These values are then used with satellite estimates of OWTs to map uncertainty in chlorophyll on a per pixel basis for each phytoplankton group. It is envisaged these satellite products will be useful for those working on the validation of, and assimilation of data into, marine ecosystem models that simulate different phytoplankton groups

    Recommendations for obtaining unbiased chlorophyll estimates from in situ chlorophyll fluorometers: A global analysis of WET Labs ECO sensors

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    Chlorophyll fluorometers provide the largest in situ global data set for estimating phytoplankton biomass because of their ease of use, size, power consumption, and relatively low price. While in situ chlorophyll a (Chl) fluorescence is proxy for Chl a concentration, and hence phytoplankton biomass, there exist large natural variations in the relationship between in situ fluorescence and extracted Chl a concentration. Despite this large natural variability, we present here a global validation data set for the WET Labs Environmental Characterization Optics (ECO) series chlorophyll fluorometers that suggests a factor of 2 overestimation in the factory calibrated Chl a estimates for this specific manufacturer and series of sensors. We base these results on paired High Pressure Liquid Chromatography (HPLC) and in situ fluorescence match ups for which non-photochemically quenched fluorescence observations were removed. Additionally, we examined matches between the factory-calibrated in situ fluorescence and estimates of chlorophyll concentration determined from in situ radiometry, absorption line height, NASA’s standard ocean color algorithm as well as laboratory calibrations with phytoplankton monocultures spanning diverse species that support the factor of 2 bias. We therefore recommend the factor of 2 global bias correction be applied for the WET Labs ECO sensors, at the user level, to improve the global accuracy of chlorophyll concentration estimates and products derived from them. We recommend that other fluorometer makes and models should likewise undergo global analyses to identify potential bias in factory calibration
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