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Bio-optical relationships between inherent and apparent optical
properties, and between optical properties and phytoplankton pigment
concentration (C) averaged in a discrete layer, were developed. These
relationships were derived from analysis of data collected during the
period 1996–1998 in the Gulf of Aqaba (Eilat), a ‘Case 1’ type water
body. Parameterization of these relationships was accomplished by combining
Gershun’s equation, radiative transfer theory for average cosine of
underwater light field, and a set of different bio-optical models. An analysis
of the asymptotic light field was carried out. Semi-analytical single-wavelength
(at lambda~443 nm) algorithms for in situ and remote sensing (RS) estimation of
mean pigment concentration were developed, and evaluated by sensitivity and
error analysis. The advantages of RS single-wavelength algorithms in
comparison with current two- and multi-wavelengths RS algorithms are
discussed.

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... then the downwelling cosines were estimated as (Aas, 1978(Aas, , 1987Sokoletsky, 2003) ), ...

... computation was based on using the first two terms of the infinite chain fraction (Sokoletsky, 2003;Sokoletsky et al., 2003) The parameters for Eq. (5) were defined as follows (Aas, 1978(Aas, , 1987van de Hulst, 1980;Gordon, 1989;Haltrin, 1998;Sokoletsky et al., 2003Sokoletsky et al., , 2013: ...

... computation was based on using the first two terms of the infinite chain fraction (Sokoletsky, 2003;Sokoletsky et al., 2003) The parameters for Eq. (5) were defined as follows (Aas, 1978(Aas, , 1987van de Hulst, 1980;Gordon, 1989;Haltrin, 1998;Sokoletsky et al., 2003Sokoletsky et al., , 2013: ...

Transmission of light is one of the key optical processes in the Earth’s atmosphere and natural waters, and transmittance (T) is an optical parameter showing the rate of change of irradiance with the optical depth tau. A knowledge of T or another optical parameter, diffuse attenuation coefficient, Kd, steady connected with the T, allows many practical tasks to be solved regarding the ocean and atmospheric optics, such as water quality, primary production, and atmospheric correction. Therefore, knowledge of the reliable relationships between T (or Kd) and such parameters as incident illumination angle, cloud coverage, and inherent optical properties (such as backscattering probability B, scattering asymmetry parameter g, and single-scattering albedo omega_0) is crucial.
We have analyzed the impact of such parameters as the scattering phase function (having the strictly determined value of B and g), omega_0, t, incident solar zenith angle theta_0, cloudiness C, and diffuseness of irradiance d_E on the T and Kd. The benchmark method used for numerical simulations is the modified discrete ordinates method (MDOM) providing an accuracy of better than 1% and having the best speed among the known radiative transfer numerical methods (Budak & Korkin, 2008). We computed T and Kd using a synthetic dataset covering any possible values of parameters typical for the atmosphere and natural waters by MDOM and 21 analytical models and compared results with the MDOM solutions. An analysis of individual models has shown that the best of them yield average errors for T and Kd better than 10% for the majority of real optical conditions in the Earth’s atmosphere and natural waters.

... The average cosine μ λ ( ) z, of irradiance is of particular interest in marine optics and remote sensing since it describes the angular distribution of the underwater light field at a given point and serves as a factor relating an inherent optical property (IOPs, here absorption) with the apparent optical property (AOP, diffuse attenuation coefficient) (Berwald et al., 1995;Sokoletsky et al., 2003). where θ φ λ ( ) L z , , , is the radiance at nadir angle θ, azimuthal angle φ, depth z, and wavelength λ. ...

... which is a form of Gershun's equation (Gershun, 1939) and reveals that the product of the average cosine with another AOP, the irradiance attenuation coefficient λ ( ) K z, , yields the absorption coefficient λ μ λ λ ( ) = ( ) ( ) a z z K z , , , , an IOP which depends only on the medium itself. Note that the average cosine is itself an AOP despite its likely behavior as an inherent optical property independent of the ambient light field when the sun is in the zenith (Sokoletsky et al., 2003) that can be measured at any depth, provided one can now measure λ ( ) a z, and λ ( ) K z, routinely with existing instrumentations. The average cosine is fundamental to understanding how a water body transforms the light field and how that transformation is related to the absorption of light by the water (Maffione and Jaffe, 1995). ...

... Thus,Eq. (14) has potential applications in studies of phytoplankton light absorption and primary productivity (Sathyendranath and Platt, 1989;Morel, 1991;Berwald et al., 1995), underwater light field structure (Hojerslev and Zaneveld, 1977;Kirk, 1991;Berwald et al., 1995;Maffione and Jaffe, 1995;Haltrin, 1998Haltrin, , 2000, spectral bio-optical modeling (Berwald et al., 1995;Sokoletsky et al., 2003) and asymptotic light regime (Flatau et al., 1999), since it is now possible to verify predictions of the rate of vertical change of μ λ ( ) z, in the water column on the basis of observations of these quantities (Berwald et al., 1995). ...

An optical model is developed using experimental data of Inherent Optical Properties (IOP) from oceanic, coastal and productive lagoon waters in order to calculate vertical and spectral profiles of the average cosine in a wide variety of waters within coastal and shelf-sea environments. The results are compared with those generated using a radiative transfer numerical model based on the invariant imbedding technique (HydroLight) with realistic depth-dependent IOPs and appropriate surface and bottom boundary conditions and the results from three existing models (Haltrin, 1998; Timofeyeva, 1971; Talaulikar et al., 2014). The average cosine predicted by the new model shows good agreement with the values obtained directly from radiative transfer calculations for a broad range of the IOPs and solar zenith conditions. Good correlations with excellent linearity with significantly low errors demonstrate a good deal of confidence of the model for accomplishing further applications. Since knowledge of spatial and temporal structures of the average cosine is of great importance to our understanding of the particle dynamics of pelagic ecosystems and coastal processes, efforts were made to apply the present model to both multispectral MODIS-Aqua imagery and hyperspectral (HICO) images acquired over the Arabian Sea and coastal lagoons of the Bay of Bengal dominated by river plumes and phytoplankton blooms. Maps of the average cosine derived from these data demonstrated significant changes in the magnitude and spectral behavior of the average cosine (from nearly featureless to strong spectral features and inflections) from different water types. Substantial changes in its spatial and spectral structures associated with highly productive waters, phytoplankton blooms and sediment plumes, as compared with open ocean areas, are well supported by the theoretical and experimental studies. The advantages of the new model in comparison with existing models are its capability to predict the vertical, spatial, spectral and temporal structures of average cosine with greater accuracy.

... Primary productivity in the euphotic zone (100 m) decreases in parallel to nutrient levels, from a maximum of 3.38 mg C m À3 h À1 in winter to 0.05 mg C m À3 h À1 in summer. These relatively low primary productivity rates amounting to 76.2 -84.6 g C m À2 y À1 , place the northern Gulf of Eilat among the more moderately productive [Levanon-Spanier et al., 1979;Iluz, 1991], moderately oligotrophic (according to the classification of Berger et al. [1989]) or meso-oligotrophic marine systems [Sokoletsky et al., 2003;Labiosa et al., 2003;Sokoletsky et al., 2004]. The nutrients nitrite and phosphate are the major limiting factor in the Gulf [e.g., Genin et al., 1995;Al-Qutob, 2001;Al-Qutob et al., 2002;Labiosa et al., 2003]. ...

... Iluz et al. [2003] suggested an algorithm for chlorophyll estimation of the Gulf based on in situ spectral profiles. Sokoletsky et al. [2003Sokoletsky et al. [ , 2004 also developed a model for estimation of phytoplankton pigment concentration in the Gulf of Eilat (Aqaba) by in situ and remote sensing, using single-wavelength algorithms. In addition, the bio-optical properties of the Gulf of Eilat were compared to those of the northern Red Sea during winter [Stambler, 2005]. ...

... Based on total PAR attenuation, there was no significant correlation between chlorophyll concentration in the water column and euphotic depth (Figure 8). The low chlorophyll concentration has almost no influence on the total PAR attenuation compared to the effects of water and yellow substance, but was expressed in the blue attenuation, K d (443) [Sokoletsky et al., 2003[Sokoletsky et al., , 2004. ...

The underwater light field and phytoplankton abundance in the Gulf of Eilat were studied at station A1 during 1996–2000. In summer, a deep chlorophyll maximum developed at about 80 m, characterized by high concentrations of Prochlorococcus, while during the mixing time, Prochlorococcus, Synechococcus, and eukaryotic algae were found throughout the water column. Chlorophyll concentrations in the euphotic zone were low (0.1–0.6 μg L−1) and as such, the phytoplankton influence on light attenuation was minor. The vertical attenuation coefficient, Kd (PAR) (photosynthetically available radiation), showed seasonal fluctuation, with a summer minimum of ∼0.04 m−1 and a spring maximum of ∼0.065 m−1. The euphotic zone ranged to depths between 80 and 115 m. Phytoplankton absorption spectra were shown to be dependent on depth. During summer stratification, as a response to the exponential decrease of light in the water column, the phytoplankton exhibited photoacclimation, evident as a marked increase in cellular chlorophyll with increasing depth. Light in the Gulf is not a limiting factor even down to more than 100 m, except when combined with stratification, e.g., nutrient limitation, does it affect phytoplankton abundance and composition.

... Alternatively, respectively), and the average cosine of the scattering angle ("asymmetry parameter") g = <cos > (King and Harshvardhan, 1986;Kirk, 1999;Sokoletsky et al., 2003). ...

... Overall, at all values of g, the King and Harshvardhan (1986) model has an accuracy better than 9% at g ≥ 0.3 ( Fig. A.3a), which is the best result among all models tested (not shown here), and the Sokoletsky et al. (2013) model is superior at g ≤ 0.3 (Fig. A.3b) with a relative error less than 7%. Thus, the Kattawar and Plass (1976) and Sokoletsky et al. (2013) models were ultimately used for the quasi-Raleigh p() #1, while the Sobolev (1975) and King and Harshvardhan (1986) in the form similar to that was successfully used by Berwald et al. (1995), Sokoletsky et al. (2003), and Sokoletsky andBudak (2016b, 2017) : ...

The transmission of light is one of the key optical processes in the terrestrial environment (the atmosphere and underlying surfaces). The dependence of light transmittance on the illumination/observation conditions and optical properties of the atmosphere–underlying system can be studied using the integro-differential radiative transfer equation. However, for numerous applications a set of analytical equations is needed to describe the transmitted light intensity and flux. In this paper, we describe various analytical techniques to study light transmittance through light scattering and absorbing media. A physical significance and improved mathematical accuracy of approximations are provided using the analytical models for the diffusion exponent, average cosine of the light field, spherical and plane albedos. The accuracy of various approximations is studied using exact radiative transfer calculations with various scattering phase functions, single-scattering albedos, observational conditions, and optical depths.

... computation was based on using the first two terms of the infinite chain fraction [10,11]. The parameters for Eq. ...

... The parameters for Eq. (5) were defined as follows [5,9,[11][12][13][14] ...

... Previous studies suggested that both the northern Red Sea and the Gulf of Aqaba are Case-1 waters (8,88); that is, phytoplankton and their associated CDOM and detritus degradation products govern the optical properties (89,90). Our findings indicate that not just the northern Red Sea but rather the vast majority of the basin can be classified as Case-1 waters, since CDOM closely mirrors the optical properties of phytoplankton (see Figs 4 and 5) and the values of S 275-295 were larger than S 350-400 (i.e. S R > 1) (Table 1), which is typical for low molecular weight (LMW) CDOM in open ocean waters (63,91). ...

The tropical and subtropical oceans experience intense incident ultraviolet radiation (280–400 nm) while their water columns are thought to be highly transparent. This combination represents a high potential for harmful effects on organisms, yet only few reports on the UV penetration properties of oligotrophic tropical waters exist. Here, we present the pattern of UV attenuation over a wide latitudinal range of the oligotrophic Red Sea. We recorded spectroradiometer profiles of PAR and UV, together with chlorophyll‐a (Chl‐a) and light absorption by chromophoric dissolved organic matter (CDOM) to determine the contribution of phytoplankton and CDOM towards UV attenuation. Transparency to UV exhibited a distinct latitudinal gradient, with the lowest and highest diffuse attenuation coefficients at 313 nm (Kd(313)) of 0.130 m‐1 and 0.357 m‐1 observed at the northern coast off Duba, and in the south close to the Farasan islands, respectively. Phytoplankton and CDOM both modulated UV attenuation but CDOM was found to be the key driver despite the lack of riverine inputs. We confirm that ultraviolet radiation can reach deeper into the Red Sea than previously described, which means its potential to act as a stressor and selective driver for Red Sea organisms may have been underestimated to date.
This article is protected by copyright. All rights reserved.

... Despite the economic and ecological importance of the Red Sea, despite extensive knowledge on its physical characteristics (e.g. Sofianos & Johns, 2003;Yao, Hoteit, Pratt, Bower, Zhai, et al., 2014) given its strategic position as a commercial shipping route, and despite extensive studies analysing the bio-optical properties of the Gulf of Eilat (Iluz, Yacobi, & Gitelson, 2003;Labiosa, Arrigo, Genin, Monismith, & Van Dijken, 2003;Sokoletsky, Dubinsky, Shoshany, & Stambler, 2003;Sokoletsky, Dubinsky, Shoshany, & Stambler, 2004;Stambler, 2005Stambler, , 2006 located at the northern tip of the Red Sea, knowledge on large-scale biological dynamics in the region is limited to knowledge on the phytoplankton seasonal cycle, rates of uptake of carbon and nitrogen by phytoplankton, and the influence of coral reef ecosystems on Red Sea productivity (Acker, Leptoukh, Shen, Zhu, & Kempler, 2008;Qurban, Balala, Kumar, Bhavya, & Wafar, 2014;Racault et al., 2015;Raitsos, Pradhan, Hoteit, Brewin, & Stenchikov, 2013). ...

The Red Sea is a semi-enclosed tropical marine ecosystem that stretches from the Gulf of Suez and Gulf of Aqaba in the north, to the Gulf of Aden in the south. Despite its ecological and economic importance, its biological environment is relatively unexplored. Satellite ocean-colour estimates of chlorophyll concentration (an index of phytoplankton biomass) offer an observational platform to monitor the health of the Red Sea. However, little is known about the optical properties of the region. In this paper, we investigate the optical properties of the Red Sea in the context of satellite ocean-colour estimates of chlorophyll concentration. Making use of a new merged ocean-colour product, from the European Space Agency (ESA) Climate Change Initiative, and in situ data in the region, we test the performance of a series of ocean-colour chlorophyll algorithms. We find that standard algorithms systematically overestimate chlorophyll when compared with the in situ data. To investigate this bias we develop an ocean-colour model for the Red Sea, parameterised to data collected during the Tara Oceans expedition, that estimates remote-sensing reflectance as a function of chlorophyll concentration. We used the Red Sea model to tune the standard chlorophyll algorithms and the overestimation in chlorophyll originally observed was corrected. Results suggest that the overestimation was likely due to an excess of CDOM absorption per unit chlorophyll in the Red Sea when compared with average global conditions. However, we recognise that additional information is required to test the influence of other potential sources of the overestimation, such as aeolian dust, and we discuss uncertainties in the datasets used. We present a series of regional chlorophyll algorithms for the Red Sea, designed for a suite of ocean-colour sensors, that may be used for further testing.

... Using the conservation of energy, Gershun (1939) provided a relationship to derive inherent optical property, a(λ) = μ (λ) K E (λ), where the diffuse attenuation coefficient for net or vector irradiance, K E (λ) is approximated to K d (λ) under some assumptions and the same was also observed in our data. (Kirk 1981;Morel 1991;Sokoletsky et al. 2003;Darecki et al. 2003). There are several algorithms available for deriving K d (λ) from ocean color satellite sensors, which have been evaluated for the study area by Suresh et al. (2012). ...

The underwater average cosine is an apparent optical property of water that describes the angular distribution of radiance at a given point in water. Here, we present a simple empirical algorithm to estimate spectral underwater average cosine (mu) over bar (lambda) where the wavelength lambda ranges from 400 nm to 700 nm, based only on the apparent optical property, remote sensing reflectance, R-rs(lambda), and solar zenith angle. The algorithm has been developed using the measured optical parameters from the coastal waters off Goa, India, and eastern Arabian Sea and the optical parameters derived using the radiative transfer code using these measured data. The algorithm was compared with two earlier reported empirical algorithms of Haltrin (1998, 2000), and the performance of the algorithm was found to be better than these two empirical algorithms. The algorithm is based on single optical parameter; remote sensing reflectance, which can be easily measured in-situ, and is available from the ocean color satellite sensors; hence this algorithm will find applications in the ocean color remote sensing.

... An 'optical closure' between the radiometrically and inherent optical property (IOP)derived upwelling radiance or reflectance is an important step towards the development of geographically localized remote-sensing algorithms (Zaneveld 1989;Barnard, Zaneveld, and Pegau 1999;Sokoletsky et al. 2003;Tzortziou et al. 2006;Gallegos, Davies-Colley, and Gall 2008;Shen, Verhoef, et al. 2010). However, this closure is difficult to realize in practice due to several factors, including (1) difficulty in accounting an impact of sky and solar glitter in calculating the above-water spectral remote-sensing reflectance R rs (λ) = L w (λ)/E d (λ, 0+), where λ is the wavelength and L w (λ) and E d (λ, 0+) represent the waterleaving radiance, and the total downwelling (incoming) irradiance just above the surface level, respectively (Mobley 1999); (2) difficulty in taking into account a scattering impact on the measured IOPs (McKee, Piskozub, and Brown 2008); (3) problems with developing an adequate model for the underwater spectral remote-sensing reflectance r rs (λ) = L u (λ, 0−)/E d (λ, 0−), where L u (λ, 0−) and E d (λ, 0−) represent the upwelling radiance and the total downwelling irradiance just below the surface level, respectively (Sokoletsky et al. 2012); and (4) problems with the R rs (λ) vs. r rs (λ) modelling (Morel and Gentili 1996). ...

Optical closure exercises are pivotal for evaluating the accuracy of water quality remote sensing techniques. The agreement between radiometrically derived and inherent optical properties (IOPs)-derived above-water spectral remote-sensing reflectance Rrs(lambda) is necessary for resolving IOPs, the diffuse attenuation coefficient, and biogeochemical parameters from space. We combined spectral radiometric and IOPs measurements to perform an optical closure exercise for two optically contrasting Chinese waters — the Changjiang (Yangtze) River Estuary, and its adjacent coastal area in the East China Sea. The final aim of our investigation was to compare two derivations of Rrs(lambda): Rrs(lambda), derived from radiometric measurements; and Rrs(lambda), derived from simultaneous IOPs measurements. Five subsequent steps have been taken to achieve this goal, including: 1) estimation of the Rrs(lambda) from radiometric measurements; 2) scattering correction for the non-water spectral absorption coefficient a_pd(lambda); 3) estimation of the below-water spectral remote-sensing reflectance r_rs(lambda) from IOPs measurements; 4) the estimation of the Rrs(lambda) from the r_rs(lambda) values; and 5) the comparison between the Rrs(lambda) derived from radiometric and IOPs measurements. All steps were realized by using both direct measurements and different models based on radiative transfer theory. Results demonstrated that the impact of the errors caused by the scattering correction procedure and conversion of radiometric quantities into Rrs(lambda) may be rather significant, especially in the long-wavelength spectrum range. Nevertheless, spectral features were similar between these Rrs(lambda) sets for all waters — from relatively clear to very turbid. Exploiting this fact allows use of the spectral reflectance ratios for remote sensing of the estuarine and coastal Chinese waters.

... More frequently, it has been the northern part of the basin, and primarily the Gulf of Aqaba, that has been the subject of in-depth investigations of bio-optical properties, from both satellite and in situ measurements (Labiosa et al. 2003;Stambler 2005), or of site-specific algorithms for their derivation from RS radiance measurements (Iluz et al. 2003;Sokoletsky et al. 2003Sokoletsky et al. , 2004. Acker et al. (2008), finally, used seven years of SeaWiFS data (1998-2004), coupled to concurrent 2003-2004 Sea Surface Temperature (SST) data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS), on the Aqua orbital platform, to observe seasonal phytoplankon dynamics, local impacts of coastal features such as coral reefs, and surface circulation patterns described by optical tracers, primarily in the northern Red Sea, between 21.5 • N and 27.5 • N. ...

Patterns of algal blooming, described by variations in the abundance of planktonic agents, are considered to be indicators of basic ecosystem dynamics in marginal or enclosed seas. Time series of statistical maps of chlorophyll-like pigments concentration (chl) - which can be interpreted as a proxy of biomass and, under certain circumstances, productivity – derived from SeaWiFS data, from July 1999 to June 2009, were considered to explore the space and time heterogeneity of algal blooming in the Red Sea. The comparison with concurrent assessments of surface wind speed (ws), derived from QuikSCAT data, allowed to correlate such heterogeneity with patterns of atmospheric forcing. The observed chl seasonal pattern is essentially bimodal, with a fall-winter period of extended blooming, which progresses from south to north and back, followed by a spring-summer period of much reduced blooming, at least in the northern sub-basin. Overall, this annual cycle seems to match the climatic characteristics of the basin, the monsoon-driven wind regime in particular, and by the ensuing thermohaline circulation. The correlation with ws suggests that the general blooming pattern of the Red Sea is reminiscennt of the classical seasonal variation of phytoplankton biomass in sub-tropical basins, where producion is never limited by sunlight, but is always limited by nutrient availability – a condition relaxed only in the colder season, when (wind-driven) convection processes can enrich the euphotic zone with nutrients from deeper layers. However, at the same time, it appears that specific blooming episodes, in the southern Red Sea in particular, are not driven directly by the wind field variability, but rather by other factors such as the exchange of water with the Arabian Sea, via the Gulf of Aden and Bab-el-Mandeb.

A large data set containing coincident in situ chlorophyll and remote sensing reflectance measurements was used to evaluate the accuracy, precision, and suitability of a wide variety of ocean color chlorophyll algorithms for use by SeaWiFS (Sea-viewing Wide Field-of-view Sensor). The radiance-chlorophyll data were assembled from various sources during the SeaWiFS Bio-optical Algorithm Mini-Workshop (SeaBAM) and is composed of 919 stations encompassing chlorophyll concentrations between 0.019 and 32.79 μg L-1. Most of the observations are from Case I nonpolar waters, and ~20 observations are from more turbid coastal waters. A variety of statistical and graphical criteria were used to evaluate the performances of 2 semianalytic and 15 empirical chlorophyll/pigment algorithms subjected to the SeaBAM data. The empirical algorithms generally performed better than the semianalytic. Cubic polynomial formulations were generally superior to other kinds of equations. Empirical algorithms with increasing complexity (number of coefficients and wavebands), were calibrated to the SeaBAM data, and evaluated to illustrate the relative merits of different formulations. The ocean chlorophyll 2 algorithm (OC2), a modified cubic polynomial (MCP) function which uses Rrs490/Rrs555, well simulates the sigmoidal pattern evident between log-transformed radiance ratios and chlorophyll, and has been chosen as the at-launch SeaWiFS operational chlorophyll a algorithm. Improved performance was obtained using the ocean chlorophyll 4 algorithm (OC4), a four-band (443, 490, 510, 555 nm), maximum band ratio formulation. This maximum band ratio (MBR) is a new approach in empirical ocean color algorithms and has the potential advantage of maintaining the highest possible satellite sensor signal: noise ratio over a 3-orders-of-magnitude range in chlorophyll concentration.

To find the solution to problems in applied marine optics, we do not always need to compute the submarine irradiance at all
depths; in many cases, it is sufficient to know the average attenuation of light for finite layers of arbitrary thickness.
If multiple scattering can be neglected, the average attenuation of light in a finite layer of the water column depends only
on the vertical distribution of the attenuating substances; in open-ocean waters, the most important of these is phytoplankton.
It is shown how the average attenuation of monochromatic light in an arbitrary layer can be determined when the vertical pigment
profile takes one of two standardized forms: a shifted Gaussian or a triangle. The choice of efficient algorithms to compute
the attenuation in a layer using these models is discussed. The extension to polychromatic light involves the selection of
a function to represent the spectral distribution of the specific absorption coefficient for phytoplankton, as determined
by observation. Chebyshev polynomial representation is shown to be convenient for applications which require the calculation
of a weighted wavelength integral. An efficient procedure for the evaluation of these integrals, Gauss-Chebyshev quadrature,
is presented and evaluated. The extension to the computation of bulk properties for discrete layers is straightforward.

The purpose of this study was to assess the oceanic seasonal evolution and spatial distribution of photosynthetic carbon fixation. Computation of primary production from the upper ocean chlorophyll-like pigment concentrations were made from monthly global maps from the coastal zone color scanner data archive. Relative contributions of various oceans and zonal belts were identified. Depending on the ratio used for active pigments to total pigments, the calculated global annual production ranges from 36.5 and 45.6 G tons (metric) carbon per year. These values are among the highest estimates proposed to date; although the absolute values may be somewhat questionable, the relative contribution of the various zonal belts and oceans are considered to have a high degree of accuracy. 33 refs., 4 figs., 2 tabs.

The chlorophyll a specific light attenuation coefficient kc, (in m2mg-1 chl a), is an apparent optical property of the underwater light field, resulting from the interaction between sunlight and the phytoplankton suspended in natural waters. The determination of kc is carried out under the natural light conditions of a water body, whereas the specific light absorption coefficient of chlorophyll a, aph (in m2mg-1 chl a), is an inherent optical property of the phytoplankton. That parameter, aph, is determined using a laboratory spectrophotometer. Both kc and aph are necessary to calculate the quantum requirement of phytoplankton photosynthesis from α, the linear part of the photosynthesis versus irradiation curve. The spectral distribution of kc(λ) and aph(λ) contains information about the species composition of the phytoplankton community. Different ways to determine kc or aph are presented. It is relatively easy to evaluate k-c(= k-c(PAR)), the wavelength-average over the photosynthetically available radiation (PAR) range, assumed to be from 400 nm to 700 nm. Alternatively, in the literature such values were also calculated from the much more difficult to measure kc(λ)-spectrum, and the spectral distribution of underwater irradiance, E(λ). The values of kc and aph are influenced by technical, physical and biological factors: the method of chlorophyll determination, the filter loading, the light properties of the water bodies, the species composition of the phytoplankton community, including cell geometry and size, the ultrastructure of chloroplasts and the physiological status of the cells, resulting from senescence, nutrient limitation or photoacclimation.

The present volume is a compilation of knowledge on underwater irradiance as the factor controlling primary organic production in the sea. The spectral characteristics of underwater irradiance and an optical model for classifying water basins by the use of the chlorophyll a concentration as an index of the optical type of water are given. The text covers the conditions, characteristics, formulas and tables describing the distributions of irradiance and the light absorption in the water column, as well as the dependence of photosynthesis and its quantum yield on the irradiance. -from Author

Records of long term (14 months) fine temporal resolution (weekly) monitoring of the ambient water temperature, dissolved oxygen concentration and percent saturation, the inorganic nutrients ammonia, nitrate, nitrite, phosphate and silicate and chlorophyll a concentrations were generated to assess sea water quality within the Jordanian coast of the Gulf of Aqaba. Surface water (1 m) samples were collected from four coastal stations, contrasting in their natural benthic habitats and adjacent human activities. Offshore surface water was also concurrently sampled at two locations. The offshore stations were reference sites. Modifications in the coastal water quality were assessed as the difference between the magnitude of a specific parameter recorded at a coastal station and the concurrently recorded value of the parameter at the reference offshore station, relative to the annual mean value at the reference offshore station.

The two-stream model expresses the vertical attenuation coefficient K and the irradiance ratio R as functions of the absorption coefficient a, the backward scattering coefficient bb, the downward and upward average cosines μ ¯ d and μ ¯ u, and the normalized reflectance coefficients of downward and upward scalar irradiance, rd and ru. While K/a and R are almost linear functions of bb/a when bb/a is small, they will approach asymptotic values, which only depend on rd, ru, μ ¯ d, and μ ¯ u when bb/a becomes large. The results agree well with oceanic observations of K and R. They also agree with theoretical results derived by other methods. Still proper testing of the model in turbid waters remains.

The average cosine of the underwater light field (i) is a simple quantity that describes the angular distribution of radiance at a given point. A model of the rate of vertical change of ji in the ocean was developed in order to examine the influences of light absorption and scattering. We made calculations of radiative transfer based on invariant imbedding theory assuming an optically homogeneous ocean with a typical scattering phase function and the simple boundary conditions of the sun overhead in a black sky and a flat ocean surface. Under such conditions, the decrease of ji throughout the water column is well approximated by a single exponential function. The dependence of the parameter P7, which describes the rate of change of ji with optical depth, on the single-scattering albedo wo, is well approximated by a quadratic function. By applying a linearization technique to the P, vs. w. relationship, we identified the contributions of absorption and scattering to P,. Our results indicate that scattering is the more important process, contributing >50% to P, for typical situations when w. > 0.1. Absorption dominates P, when w. < 0.1, which occurs only in very clear oceanic water at long wavelengths (> 6 50 nm). Our analysis of the effect of scattering phase function shows that the scattering into the middle angles, approximately between 20" and 45", largely determines the magnitude of P,. Using spectral bio-optical models with several Chl concentrations, we also examined the rate of change in ji with geometric depth P, for various water types with realistic values of the absorption and scattering coefficients. This analysis shows large variations in both the magnitude and the spectral behavior of P, with varying Chl concentration. The average cosine of the light field (fi) is a simple and convenient quantity that describes the angular distribu- tion of the underwater radiance at a given point. This quantity is defined as