Revisiting <scp>O</scp>cean <scp>C</scp>olor algorithms for chlorophyll <i>a</i> and particulate organic carbon in the <scp>S</scp>outhern <scp>O</scp>cean using biogeochemical floats

Haëntjens, Nils; Boss, Emmanuel; Talley, Lynne D.

doi:10.1002/2017jc012844

Cited by 76 publications

(60 citation statements)

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“…The eastern Mediterranean Sea is about 14 %, while the South Atlantic subtropical gyre and surrounding areas contribute 6.3 % on average. The South Pacific Ocean represents only 3 to 5 % of the vertical profiles within BOPAD-prof, while polar and Because of the unique in situ spatial and temporal coverage, the international community of optical oceanographers (Claustre et al, 2010b;IOCCG, 2011IOCCG, , 2015Biogeochemical-Argo Planning Group, 2016) has recently recognized measurements collected by BGC-Argo floats as a fruitful resource of data for bio-optical applications, such as the identification of regions with optical properties departing from mean statistical relationships as well as the validation of ocean color reflectances (Gerbi et al, 2016) and bio-optical products (IOCCG, 2015;Haëntjens et al, 2017). In this context, BOPAD-surf has been compiled with 5748 stations of biogeochemical (i.e., Chl and FDOM) and bio-optical (i.e., K d (λ), K d (PAR), and b bp (700)) variables within the first optical depth (i.e., the layer of interest for ocean color) as derived from previously quality-controlled vertical profiles.…”

Section: Bopad-prof: Spatiotemporal Distribution Of the Biogeochemicamentioning

confidence: 99%

“…The spatial and temporal under-sampling of most of the world's oceans was considered the main cause of this limitation (Munk, 2000;Hall et al, 2010). The same community thus proposed the implementation of autonomous platforms, such as the Biogeochemical-Argo profiling floats (hereafter BGC-Argo floats), as one solution to fill this observational gap (Johnson et al, 2009;Claustre et al, 2010a).…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the array provided measurements of the underwater light field (i.e., irradiance) and of the inherent optical properties (i.e., particulate optical beam attenuation and backscattering coefficients) of the oceans. All these measurements, and derived quantities, are useful for both biogeochemical and bio-optical studies, to address the variability in biological processes (e.g., phytoplankton phenology and primary production; Lacour et al, 2015) and linkages with physical drivers (Boss et al, 2008;Boss and Behrenfeld, 2010;Lacour et al, 2017;Mignot et al, 2017;Stanev et al, 2017), to estimate particulate organic carbon concentrations and export (e.g., Bishop et al, 2002;Dall'Olmo and Mork, 2014;, and to support satellite missions through validation of bio-optical products retrieved from ocean color remote sensing (e.g., chlorophyll concentration; Claustre et al, 2010b;IOCCG, 2011IOCCG, , 2015Gerbi et al, 2016;Haëntjens et al, 2017) or by identification of those regions with bio-optical behaviors departing from mean-statistical trends (i.e., bio-optical anomalies; Organelli et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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

Organelli

Barbieux

Claustre

et al. 2017

Earth Syst. Sci. Data

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Abstract. 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 1000 m 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 singlewavelength 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.

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Section: Bopad-prof: Spatiotemporal Distribution Of the Biogeochemicamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Organelli

Barbieux

Claustre

et al. 2017

Earth Syst. Sci. Data

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“…Using a matchup length scale of 25 km (i.e. the ship and satellite observations must be within 25 km of each other on the same day), which is somewhat larger than the correlation length scale for chlorophyll in the Southern Ocean of 10-15 km (Haëntjens et al, 2017), allowed us to retain 116 matchups. These results, shown in Fig.…”

Section: Comparison To Satellite Pic (Spic) Estimatesmentioning

confidence: 99%

Distribution of planktonic biogenic carbonate organisms in the Southern Ocean south of Australia: a baseline for ocean acidification impact assessment

et al. 2018

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Abstract. The Southern Ocean provides a vital service by absorbing about one-sixth of humankind's annual emissions of CO 2 . This comes with a cost -an increase in ocean acidity that is expected to have negative impacts on ocean ecosystems. The reduced ability of phytoplankton and zooplankton to precipitate carbonate shells is a clearly identified risk. The impact depends on the significance of these organisms in Southern Ocean ecosystems, but there is very little information on their abundance or distribution. To quantify their presence, we used coulometric measurement of particulate inorganic carbonate (PIC) on particles filtered from surface seawater into two size fractions: 50-1000 µm to capture foraminifera (the most important biogenic carbonate-forming zooplankton) and 1-50 µm to capture coccolithophores (the most important biogenic carbonate-forming phytoplankton). Ancillary measurements of biogenic silica (BSi) and particulate organic carbon (POC) provided context, as estimates of the biomass of diatoms (the highest biomass phytoplankton in polar waters) and total microbial biomass, respectively. Results for nine transects from Australia to Antarctica in 2008-2015 showed low levels of PIC compared to Northern Hemisphere polar waters. Coccolithophores slightly exceeded the biomass of diatoms in subantarctic waters, but their abundance decreased more than 30-fold poleward, while diatom abundances increased, so that on a molar basis PIC was only 1 % of BSi in Antarctic waters. This limited importance of coccolithophores in the Southern Ocean is further emphasized in terms of their associated POC, representing less than 1 % of total POC in Antarctic waters and less than 10 % in subantarctic waters. NASA satellite ocean-colour-based PIC estimates were in reasonable agreement with the shipboard results in subantarctic waters but greatly overestimated PIC in Antarctic waters. Contrastingly, the NASA Ocean Biogeochemical Model (NOBM) shows coccolithophores as overly restricted to subtropical and northern subantarctic waters. The cause of the strong southward decrease in PIC abundance in the Southern Ocean is not yet clear. The poleward decrease in pH is small, and while calcite saturation decreases strongly southward, it remains well above saturation (> 2). Nitrate and phosphate variations would predict a poleward increase. Temperature and competition with diatoms for limiting iron appear likely to be important. While the future trajectory of coccolithophore distributions remains uncertain, their current low abundances suggest small impacts on overall Southern Ocean pelagic ecology.

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“…Szeto et al, 2011;Johnson et al, 2013;Haentjens et al, 2017). To explore this using the model, we again assumed a large dataset (i.e.…”

Section: Discussion and Summarymentioning

confidence: 99%

Modelling ocean-colour-derived chlorophyll <i>a</i>

2018

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Abstract. This article provides a proof of concept for using a biogeochemical/ecosystem/optical model with a radiative transfer component as a laboratory to explore aspects of ocean colour. We focus here on the satellite ocean colour chlorophyll a (Chl a) product provided by the often-used blue/green reflectance ratio algorithm. The model produces output that can be compared directly to the real-world ocean colour remotely sensed reflectance. This model output can then be used to produce an ocean colour satellite-like Chl a product using an algorithm linking the blue versus green reflectance similar to that used for the real world. Given that the model includes complete knowledge of the (model) water constituents, optics and reflectance, we can explore uncertainties and their causes in this proxy for Chl a (called "derived Chl a" in this paper). We compare the derived Chl a to the "actual" model Chl a field. In the model we find that the mean absolute bias due to the algorithm is 22 % between derived and actual Chl a. The real-world algorithm is found using concurrent in situ measurement of Chl a and radiometry. We ask whether increased in situ measurements to train the algorithm would improve the algorithm, and find a mixed result. There is a global overall improvement, but at the expense of some regions, especially in lower latitudes where the biases increase. Not surprisingly, we find that regionspecific algorithms provide a significant improvement, at least in the annual mean. However, in the model, we find that no matter how the algorithm coefficients are found there can be a temporal mismatch between the derived Chl a and the actual Chl a. These mismatches stem from temporal decoupling between Chl a and other optically important water constituents (such as coloured dissolved organic matter and detrital matter). The degree of decoupling differs regionally and over time. For example, in many highly seasonal regions, the timing of initiation and peak of the spring bloom in the derived Chl a lags the actual Chl a by days and sometimes weeks. These results indicate that care should also be taken when studying phenology through satellite-derived products of Chl a. This study also reemphasizes that ocean-colourderived Chl a is not the same as the real in situ Chl a. In fact the model derived Chl a compares better to real-world satellite-derived Chl a than the model actual Chl a. Modellers should keep this is mind when evaluating model output with ocean colour Chl a and in particular when assimilating this product. Our goal is to illustrate the use of a numerical laboratory that (a) helps users of ocean colour, particularly modellers, gain further understanding of the products they use and (b) helps the ocean colour community to explore other ocean colour products, their biases and uncertainties, as well as to aid in future algorithm development.

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Revisiting Ocean Color algorithms for chlorophyll a and particulate organic carbon in the Southern Ocean using biogeochemical floats

Cited by 76 publications

References 42 publications

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

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

Distribution of planktonic biogenic carbonate organisms in the Southern Ocean south of Australia: a baseline for ocean acidification impact assessment

Modelling ocean-colour-derived chlorophyll <i>a</i>

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Revisiting Ocean Color algorithms for chlorophyll a and particulate organic carbon in the Southern Ocean using biogeochemical floats

Cited by 76 publications

References 42 publications

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

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

Distribution of planktonic biogenic carbonate organisms in the Southern Ocean south of Australia: a baseline for ocean acidification impact assessment

Modelling ocean-colour-derived chlorophyll &lt;i&gt;a&lt;/i&gt;

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Modelling ocean-colour-derived chlorophyll <i>a</i>