Optical Classification of Ocean Water

Jerlov, N. G.

doi:10.1515/9780824884918-009

Cited by 32 publications

(11 citation statements)

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“…According to this, N. Jerlov formally classified oceanic water types (Jerlov 1951). Type I waters were represented by extremely clear oceanic waters.…”

Section: Methodsmentioning

confidence: 99%

“…Most clear coastal waters were classified as Type II because attenuation tends to be greater than that for oceanic waters of low productivity. However, many water bodies were found to lie between Types I and II and subsequently were introduced intermediate Types IA and IB (Jerlov 1964). Type III waters are fairly turbid and some regions of coastal upwelling are so turbid that they were not initially classified.…”

Section: Methodsmentioning

confidence: 99%

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Short-term effects of gamma ray bursts on oceanic photosynthesis

Peñate

Martín

Cárdenas

et al. 2010

Astrophys Space Sci

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Abstract:We continue our previous work on the potential short-term influence of a gamma ray bursts on Earth's biosphere, focusing on the only important short-term effect on life: the ultraviolet flash which occurs as a result of the retransmission of the γ radiation through the atmosphere. Thus, in this work we calculate the ultraviolet irradiances penetrating the first hundred meters of the water column, for Jerlov's ocean water types I, II and III. Then we estimate the UV flash potential for photosynthesis inhibition, showing that it can be important in a considerable part of the water column with light enough for photosynthesis to be done, the so called photic zone.

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“…According to this, N. Jerlov formally classified oceanic water types (Jerlov 1951). Type I waters were represented by extremely clear oceanic waters.…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Short-term effects of gamma ray bursts on oceanic photosynthesis

Peñate

Martín

Cárdenas

et al. 2010

Astrophys Space Sci

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“…Although most of the dissolved exudates that form the DOM are non-absorbing (Mühlenbruch et al, 2018), part of the pool absorbs light mainly in the ultraviolet (UV) and blue spectral range of the electromagnetic radiation. This portion of the DOM is referred to as chromophoric dissolved organic matter (CDOM, Jerlov, 1951;Sieburth and Jensen, 1968). CDOM absorbs light depending on both the CDOM concentration and its mass-specific, spectral absorption coefficient aCDOM(λ).…”

Section: Introductionmentioning

confidence: 99%

Chromophoric dissolved organic matter dynamics revealed through the optimization of an optical-biogeochemical model in the NW Mediterranean Sea

Alvarez

Cossarini

Teruzzi

et al. 2023

Preprint

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Abstract. Chromophoric dissolved organic matter (CDOM) significantly contributes to the non-water absorption budget in the Mediterranean Sea. The absorption coefficient of CDOM, αCDOM(λ), is measurable in situ and remotely from different platforms and can be used as an indicator of the concentration of other relevant biogeochemical variables, e.g., dissolved organic carbon. However, our ability to model the biogeochemical processes that determine CDOM concentrations is still limited. Here we propose a novel parametrisation of the CDOM cycle that accounts for the interplay between the light- and nutrient-dependent dynamics of local CDOM production and degradation, as well as its vertical transport. The parameterization is included in a one-dimensional (1D) configuration of the Biogeochemical Flux Model (BFM), which is here coupled to the General Ocean Turbulence Model (GOTM) through the Framework for Aquatic Biogeochemical Models (FABM). Here BFM is augmented with a bio-optical component that revolves spectrally the underwater light transmission. We did run this new GOTM-FABM-BFM configuration to simulate the seasonal αCDOM(λ) cycle at the deep-water site of the BOUSSOLE project in the North-Western Mediterranean Sea. Our results show that accounting for both nutrient and light dependence of CDOM production improves the simulation of the seasonal and vertical dynamics of αCDOM(λ), including a subsurface maximum that forms in spring and progressively intensifies in summer. Furthermore, the model consistently reproduces the higher-than-average concentrations of CDOM per unit chlorophyll concentration observed at BOUSSOLE. The configuration, outputs and sensitivity analyses from this 1D model application will be instrumental for future applications of BFM to the entire Mediterranean Sea in a 3D configuration.

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“…The development of underwater radiometric equipment allowed for quantitative classification schemes to relate optical parameters to the observed variability of water transparency and color [ 29 ]. The Jerlov scale [ 33 ] established five oceanic water types (I, IA, IB, II, and III) and five coastal water types (1, 3, 5, 7, and 9) based on measurements of the light attenuation coefficient (

) (a parameter that describes the attenuation of light in the water column). The classification of Morel and Prieur [ 34 ] sorts seawater into two types—case 1 and optically complex waters—based on their reflectance and light absorption coefficient ( a(λ) ).…”

Section: Introductionmentioning

confidence: 99%

Use of Digital Images as a Low-Cost System to Estimate Surface Optical Parameters in the Ocean

Castillo-Ramírez

Santamaría-del-Ángel

González-Silvera

et al. 2023

Sensors

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Ocean color is the result of absorption and scattering, as light interacts with the water and the optically active constituents. The measurement of ocean color changes enables monitoring of these constituents (dissolved or particulate materials). The main objective of this research is to use digital images to estimate the light attenuation coefficient (Kd), the Secchi disk depth (ZSD), and the chlorophyll a (Chla), concentration and to optically classify plots of seawater using the criteria proposed by Jerlov and Forel using digital images captured at the ocean surface. The database used in this study was obtained from seven oceanographic cruises performed in oceanic and coastal areas. Three approaches were developed for each parameter: a general approach that can be applied under any optical condition, one for oceanic conditions, and another for coastal conditions. The results of the coastal approach showed higher correlations between the modeled and validation data, with rp values of 0.80 for Kd, 0.90 for ZSD, 0.85 for 𝐶ℎ𝑙𝑎, 0.73 for Jerlov, and 0.95 for Forel–Ule. The oceanic approach failed to detect significant changes in a digital photograph. The most precise results were obtained when images were captured at 45˚ (n = 22; Fr cal = 11.02 > Fr crit = 5.99). Therefore, to ensure precise results, the angle of photography is key. This methodology can be used in citizen science programs to estimate 𝑍𝑆𝐷, 𝐾𝑑, and the Jerlov scale.

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Optical Classification of Ocean Water

Cited by 32 publications

References 0 publications

Short-term effects of gamma ray bursts on oceanic photosynthesis

Short-term effects of gamma ray bursts on oceanic photosynthesis

Chromophoric dissolved organic matter dynamics revealed through the optimization of an optical-biogeochemical model in the NW Mediterranean Sea

Use of Digital Images as a Low-Cost System to Estimate Surface Optical Parameters in the Ocean

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