A regional comparison of particle size distributions and the power law approximation in oceanic and estuarine surface waters

Buonassissi, Christopher J.; Dierssen, Heidi M.

doi:10.1029/2010jc006256

Cited by 91 publications

(121 citation statements)

References 68 publications

(108 reference statements)

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“…The results obtained by this study confirmed the fact that the PSD slopes carry information on the relative concentrations of small to large particles, namely the greater the slopes the less proportion of large particles, and the smaller the slopes the more proportion of large particles. This observation is consistent with findings reported by Buonassissi and Dierssen (2010) [34]. In addition, another parameter, namely the correction parameter in the power-law model, generally showed a positive relationship with the D v 50 (R 2 = 0.691, p < 0.01) (figure not shown).…”

Section: Spatial Variability In Psd In Surface Waterssupporting

confidence: 82%

“…The non-dimensional ξ is the PSD slope, or Junge exponent, and ω is a correction parameter (dimensionless) of the power-law model that varies among different stations. Calculations were done using the least-squares minimization on the log-transformed data of each sample, as performed in previous studies [2,34]. Then, the two PSD slopes (ξ) and the correction parameter (ω) were derived.…”

Section: Methods To Characterize Psdsmentioning

confidence: 99%

“…Because one function form sometimes cannot capture the full complexity of the PSD [2,4,11,29,34], two power-law models, without and with correction of the parameters (see Equations (3) and (4)), were combined to describe the PSD in the study region:…”

Section: Methods To Characterize Psdsmentioning

confidence: 99%

“…One way to show the variability in particle concentrations among samples is to use a particle concentration at a discrete size (such as N(D), where D = 37 µm) [34]. However, this only refers to a particle distribution at a specific size and does not contain information for all the other sizes.…”

Section: Auxiliary Descriptionmentioning

confidence: 99%

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Variability of Particle Size Distributions in the Bohai Sea and the Yellow Sea

Qiu

Sun

et al. 2016

Remote Sensing

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Particle size distribution (PSD) is an important parameter that is relevant to many aspects of marine ecosystems, such as phytoplankton functional types, optical absorption and scattering from particulates, sediment fluxes, and carbon export. However, only a handful of studies have documented the PSD variability in different regions. Here, we investigate the PSD properties and variability in two shallow and semi-enclosed seas (the Bohai Sea (BS) and Yellow Sea (YS)), using in situ laser diffraction measurements (LISST-100X Type C) and other measurements at 79 stations in November 2013. The results show large variability in particle concentrations (in both volume and number concentrations), with volume concentrations varying by 57-fold. The median particle diameter (D v 50 ) from each of the water samples also covers a large range (22.4-307.0 µm) and has an irregular statistical distribution, indicating complexity in the PSD. The PSD slopes (2.7-4.5), estimated from a power-law model, cover nearly the entire range reported previously for natural waters. Small mineral particles (with large PSD slopes) are characteristic of near-shore waters prone to sediment resuspension by winds and tides, while large biological particles (with small PSD slopes) dominate the total suspended particulates for waters away from the coast. For the BS and YS, this study provides the first report on the properties and spatial variability of the PSD, which may influence the optical properties of the ocean surface and remote sensing algorithms that are based on estimations of particle concentrations and sizes.

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Section: Spatial Variability In Psd In Surface Waterssupporting

confidence: 82%

Section: Methods To Characterize Psdsmentioning

confidence: 99%

Section: Methods To Characterize Psdsmentioning

confidence: 99%

Section: Auxiliary Descriptionmentioning

confidence: 99%

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Variability of Particle Size Distributions in the Bohai Sea and the Yellow Sea

Qiu

Sun

et al. 2016

Remote Sensing

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“…This model, however, remains the most frequently used in optical studies. Its goodness of fit is evaluated by the R 2 statistic, the relative deviation of the model from the observations, and the 95% confidence interval on the least-square estimation of c. Typical values of c range between 3 and 5 (Jonasz 1983;Buonassissi and Dierssen 2010;Reynolds et al 2010). …”

mentioning

confidence: 99%

In situ variability of mass‐specific beam attenuation and backscattering of marine particles with respect to particle size, density, and composition

Neukermans

Loisel

Mériaux

et al. 2011

Limnology & Oceanography

171

179

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This study analyzes relationships between concentration of suspended particles represented by dry mass, [SPM], or area, [AC], and optical properties including particulate beam attenuation (c p ), side scattering (b s ), and backscattering (b bp ), obtained from an intensive sampling program in coastal and offshore waters around Europe and French Guyana. First-order optical properties are driven by particle concentration with best predictions of [SPM] by b bp and b s , and of [AC] by c p . Second-order variability is investigated with respect to particle size, apparent density (dry weight-to-wet-volume ratio), and composition. Overall, the mass-specific particulate backscattering coefficient, b bp remains unexplained. Possible causes are the limitation of the measured size distributions to the 2-302-mm range and effects of particle shape and internal structure that affect b bp more than c p and were not accounted for.

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Global assessment of ocean carbon export by combining satellite observations and food‐web models

Siegel

Buesseler

Doney

et al. 2014

Global Biogeochemical Cycles

393

503

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The export of organic carbon from the surface ocean by sinking particles is an important, yet highly uncertain, component of the global carbon cycle. Here we introduce a mechanistic assessment of the global ocean carbon export using satellite observations, including determinations of net primary production and the slope of the particle size spectrum, to drive a food-web model that estimates the production of sinking zooplankton feces and algal aggregates comprising the sinking particle flux at the base of the euphotic zone. The synthesis of observations and models reveals fundamentally different and ecologically consistent regional-scale patterns in export and export efficiency not found in previous global carbon export assessments. The model reproduces regional-scale particle export field observations and predicts a climatological mean global carbon export from the euphotic zone of~6 Pg C yr À1. Global export estimates show small variation (typically < 10%) to factor of 2 changes in model parameter values. The model is also robust to the choices of the satellite data products used and enables interannual changes to be quantified. The present synthesis of observations and models provides a path for quantifying the ocean's biological pump.

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A regional comparison of particle size distributions and the power law approximation in oceanic and estuarine surface waters

Cited by 91 publications

References 68 publications

Variability of Particle Size Distributions in the Bohai Sea and the Yellow Sea

Variability of Particle Size Distributions in the Bohai Sea and the Yellow Sea

In situ variability of mass‐specific beam attenuation and backscattering of marine particles with respect to particle size, density, and composition

Global assessment of ocean carbon export by combining satellite observations and food‐web models

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