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Mesophotic coral reefs, generally defined as deep reefs between 30 and 150 m, are found worldwide and are largely structured by changes in the underwater light field. Additionally, it is increasingly understood that reef-to-reef variability in topography, combined with quantitative and qualitative changes in the underwater light field with increasing depth, significantly influence the observed changes in coral distribution and abundance. Here, we take a modeling approach to examine the effects of the inherent optical properties of the water column on the irradiance that corals are exposed to along a shallow to mesophotic depth gradient. In particular, the roles of reef topography including horizontal, sloping and vertical substrates are quantified, as well as the differences between mounding, plating and branching colony morphologies. Downwelling irradiance and reef topography interact such that for a water mass of similar optical properties, the irradiance reaching the benthos varies significantly with topography (i.e. substrate angle). Coral morphology, however, is also a factor; model results show that isolated hemispherical colonies consistently ‘see’ greater incident irradiances across depths, and throughout the day, compared to plating and branching morphologies. These modeled geometric-based differences in the incident irradiances on different coral morphologies are not, however, consistent with actual depth-dependent distributions of these coral morphotypes, where plating morphologies dominate as you go deeper. Other factors, such as the cost of calcification, arguably contribute to these differences, but irradiance-driven patterns are a strong proximate cause for the observed differences in mesophotic communities on sloping versus vertical reef substrates.

Mesophotic coral reefs, currently defined as deep reefs between 30 and 150 m, are linked physically and biologically to their shallow water counterparts, have the potential to be refuges for shallow coral reef taxa such as coral and sponges, and might be a source of larvae that could contribute to the resiliency of shallow water reefs. Mesophotic coral reefs are found worldwide, but most are undescribed and understudied. Here, we review our current knowledge of mesophotic coral reefs and their functional ecology as it relates to their geomorphology, changes in the abiotic environment along depth gradients, trophic ecology, their reproduction, and their connectivity to shallow depths. Understanding the ecology of mesophotic coral reefs, and the connectivity between them and their shallow water counterparts, is now a primary focus for many reef studies as the worldwide degradation of shallow coral reefs, and the ecosystem services they provide, continues unabated.

Background/purpose The purpose of this paper is to estimate the contribution to our erythemal exposure at the coast of solar ultraviolet (UV) both reflected from, and transmitted into, the ocean. Methods The reflection of solar UV radiation from, and transmitted into, seawater was calculated using a numerical model under a number of atmospheric conditions to estimate erythemal exposure on the skin of supine/prone and ambulant people. Results The results were expressed as UV Indices. Even under the most extreme insolation with the sun directly overhead, where the ambient UV Index may be around 14, reflected UV from the ocean contributes an erythemal exposure to the skin equivalent to a UV Index of about 0.7. For typical ocean waters, with the sun high in the sky, the UV index within the water is about 7 at a depth of 2 m. Conclusion Whilst our eyes often sense a high level of reflected sunlight from the ocean, especially when the sun is low in the sky, our skin does not share that experience. The reason people get sunburnt at the seaside has more to do with the absence of shade than with reflectance by the water surface or even beach sand.

Atmospheric and oceanic radiative transfer models were used to compute spectral radiances between 285 and 400 nm onto horizontal and vertical plane surfaces over water. The calculations kept track of the contributions by the sun's direct beam, by diffuse-sky radiance, by radiance reflected from the sea surface and by water-leaving radiance. Clear, hazy and cloudy sky conditions were simulated for a range of solar zenith angles, wind speeds and atmospheric ozone concentrations. The radiances were used to estimate erythemal exposures due to the sun and sky, as well as from radiation reflected by the sea surface and backscattered from the water column. Diffuse-sky irradiance is usually greater than direct-sun irradiance at wavelengths below 330 nm, and reflected and water-leaving irradiance accounts for20% of the UV exposure on a vertical surface. Total exposure depends strongly on solar zenith angle and azimuth angle relative to the sun. Sea surface roughness affects the UV exposures by only a few percent. For very clear waters and the sun high in the sky, the UV index within the water can be10 at depths down to two meters and6 down to 5 m.

This paper introduces a framework for examining connections between the flow field, the texture of the air-water interface, and the reflectance of the water surface and thus evaluating the potential to infer hydraulic information from remotely sensed observations of surface reflectance. We used a spatial correlation model describing water surface topography to illustrate the application of our framework. Nondimensional relations between model parameters and flow intensity were established based on a prior flume study. Expressing the model in the spatial frequency domain allowed us to use an efficient Fourier transform-based algorithm for simulating water surfaces. Realizations for both flume and field settings had water surface slope distributions positively correlated with velocity and water surface roughness. However, most surface facets were gently sloped and thus unlikely to yield strong specular reflections; the model exaggerated the extent of water surface features, leading to underestimation of facet slopes. A ray tracing algorithm indicated that reflectance was greatest when solar and view zenith angles were equal and the sensor scanned toward the Sun to capture specular reflections of the solar beam. Reflected energy was concentrated in a small portion of the sky, but rougher water surfaces reflected rays into a broader range of directions. Our framework facilitates flight planning to avoid surface-reflected radiance while mapping other river attributes, or to maximize this component to exploit relationships between hydraulics and surface reflectance. This initial analysis also highlighted the need for improved models of water surface topography in natural rivers.

This chapter develops invariant imbedding theory as needed to solve the time-independent vector (polarized) radiative transfer equation (VRTE) for a plane-parallel water body bounded by a wind-blown sea surface and a reflective bottom.

Ocean ecosystem models require accurate calculations of both hydrodynamics and biology; those calculations in turn require accurate calculation of in-water irradiance. Ecosystem models now achieve great accuracy in their hydrodynamical predictions, and the biological modules are becoming correspondingly sophisticated. The optical calculations are however often oversimplified, to the possible detriment of the physical and biological predictions. We used a recently developed, extremely fast radiative transfer code, EcoLight-S, to study differences in ecosystem and thermal development in an idealized upwelling-downwelling system when simple versus accurate irradiance calculations are used. The use of accurate irradiances gave up to 57% differences in chlorophyll concentrations after two weeks of simulated time, compared to predictions based on irradiances obtained using a simple exponential attenuation formula. Accurate irradiance calculations increased sea surface temperatures and decreased temperatures at depth, leading to increased stratification. Use of EcoLight-S couples the physical and biological calculations so that biology feeds back to physics, and vice versa. EcoLight-S outputs ancillary quantities such as remote sensing reflectance and in-water spectral irradiance, which can be used to validate ecosystem predictions using remotely sensed ocean color imagery or optical measurements from buoys or gliders, without the need to convert such measurements to chlorophyll values. After optimization, the ecosystem model total run times with EcoLight-S were less than 20% more than for the analytical irradiance models. We also found that the use of 24 h average irradiances gave factor-of-two differences in chlorophyll concentrations compared to the use of a diel irradiance pattern with the same 24 h average value.

The evolution of terrestrial vertebrates, starting around 385 million years ago, is an iconic moment in evolution that brings to mind images of fish transforming into four-legged animals. Here, we show that this radical change in body shape was preceded by an equally dramatic change in sensory abilities akin to transitioning from seeing over short distances in a dense fog to seeing over long distances on a clear day. Measurements of eye sockets and simulations of their evolution show that eyes nearly tripled in size just before vertebrates began living on land. Computational simulations of these animal’s visual ecology show that for viewing objects through water, the increase in eye size provided a negligible increase in performance. However, when viewing objects through air, the increase in eye size provided a large increase in performance. The jump in eye size was, therefore, unlikely to have arisen for seeing through water and instead points to an unexpected hybrid of seeing through air while still primarily inhabiting water. Our results and several anatomical innovations arising at the same time suggest lifestyle similarity to crocodiles. The consequent combination of the increase in eye size and vision through air would have conferred a 1 million-fold increase in the amount of space within which objects could be seen. The “buena vista” hypothesis that our data suggest is that seeing opportunities from afar played a role in the subsequent evolution of fully terrestrial limbs as well as the emergence of elaborated action sequences through planning circuits in the nervous system.

Many pelagic species, particularly teleost fish, have silvered lateral surfaces that are thought to primarily serve as a form of camouflage. The underlying argument is that the underwater light field is cylindrically symmetrical around the vertical axis; thus a vertical mirror reflects a region of the water column that matches the region directly behind the mirror. However, the degree of symmetry of the underwater light field itself has not been assessed. Modeled underwater radiances from the surface to a depth of 100 m using measured profiles of inherent optical properties and HydroLight radiative transfer software showed that the horizontal light field under sunny conditions was asymmetrical over a wide range of solar elevations. In addition, the maximum asymmetry at 100 m occurred not when the sun was near the horizon, but when it was 45u above it. We validated these modeled results in Hawaiian waters using a modification of a commercial radiometer. Both modeled and measured radiances showed that the inherent contrast of silvery fish was typically higher at longer wavelengths. However, models of the sighting distances of these surfaces showed that sighting distance was greatest at the peak wavelength of the downwelling irradiance (,480 nm). The modeled and measured asymmetry of the horizontal light field implies that mirror camouflage is not always as successful as originally thought and suggests that there may be further refinements for this form of crypsis that have not been previously considered.

The complexity and heterogeneity of shallow coastal waters over small spatial scales provides a challenging environment for mapping and monitoring benthic habitats using remote sensing imagery. Additionally, changes in coral reef community structure are occurring on unprecedented temporal scales that require large-scale synoptic coverage and monitoring of coral reefs. A variety of sensors and analyses have been employed for monitoring coral reefs: this study applied a spectrum-matching and look-up-table methodology to the analysis of hyperspectral imagery of a shallow coral reef in the Bahamas. In unconstrained retrievals the retrieved bathymetry was on average within 5% of that measured acoustically, and 92% of pixels had retrieved depths within 25% of the acoustic depth. Retrieved absorption coefficients had less than 20% errors observed at blue wavelengths. The reef scale benthic classification derived by analysis of the imagery was consistent with the percent cover of specific coral reef habitat classes obtained by conventional line transects over the reef, and the inversions were robust as the results were similar when the benthic classification retrieval was constrained by measurements of bathymetry or water column optical properties. These results support the use of calibrated hyperspectral imagery for the rapid determination of bathymetry, water optical properties, and the classification of important habitat classes common to coral reefs.

The diffuse attenuation coefficient Kd(λ) was first expressed in terms of the inherent optical properties (IOPs) of water according to well-established empirical bio-optical models. Boltzmann simulated annealing was then used to find the best sets of IOPs to fit Kd(λ) spectra to the reference spectra Kd0(λ) that define the Jerlov water types. Absorption a(λ) and scattering b(λ) coefficients were thus obtained for all Jerlov water types over the wavelength range 300-700 nm. The chlorophyll concentrations corresponding to the Jerlov water types were also obtained via bio-optical models. The result is a self-consistent set of spectral IOPs, chlorophyll concentrations, and Jerlov water types useful for a variety of underwater optical communications and remote sensing applications.

Many deep-sea species, particularly crusta- ceans, cephalopods, and fish, use photophores to illuminate their ventral surfaces and thus disguise their silhouettes from predators viewing them from below. This strategy has several potential limitations, two of which are examined here. First, a predator with acute vision may be able to detect the individual photophores on the ventral surface. Second, a predator may be able to detect any mismatch between the spectrum of the bioluminescence and that of the background light. The first limitation was examined by modeling the perceived images of the counterillumination of the squid Abralia veranyi and the myctophid fish Cera- toscopelus maderensis as a function of the distance and visual acuity of the viewer. The second limitation was addressed by measuring downwelling irradiance under moonlight and starlight and then modeling underwater spec- tra. Four water types were examined: coastal water at a depth of 5 m and oceanic water at 5, 210, and 800 m. The appearance of the counterillumination was more affected by the visual acuity of the viewer than by the clarity of the water, even at relatively large distances. Species with high visual acuity (0.11° resolution) were able to distinguish the individual photophores of some counterilluminating signals at distances of several meters, thus breaking the camouflage. Depth and the presence or absence of moonlight strongly affected the spectrum of the background light, particularly near the surface. The increased variability near the surface was partially offset by the higher contrast attenuation at shallow depths, which reduced the sighting distance of mismatches. This research has implications for the study of spatial resolution, contrast sensitivity, and color discrimina- tion in deep-sea visual systems.

This is the publisher’s final pdf. The published article is copyrighted by Oceanography Society and can be found at: http://www.tos.org/.

If the benthic boundary in optically shallow waters is spatially inhomogeneous or sloping, the underwater light field is inherently three-dimensional (3D). Numerical simulations of 3D underwater radiances were made for environmental conditions observed in shallow Bahamian waters. The simulations show that if the pattern of bottom reflectance for an inhomogeneous but level bottom has a spatial scale much smaller than the bottom area seen by a radiometer, the inhomogeneous bottom can be replaced by a homogeneous bottom whose reflectance is the areaweighted average of the actual bottom reflectances. For large-scale patterns of bottom reflectance, the 3D light fields near the edges of bottom patches of different reflectances can be predicted from analytical models incorporating the sensor geometry and one-dimensional (1D) light fields computed for homogeneous bottoms, with errors of order 10% when compared to the exact 3D solutions. The same holds true for uniformly sloping bottoms, whose 3D light fields can be modeled in terms of the 1D light fields computed for level bottoms, with errors of less than 10% for bottom slopes of 20° or less.

water is nearly opaque to infrared energy (Figure 1),the study of ocean optics has been primarily concernedwith propagation of visible energy, i.e. light. This is alsoa natural starting point for the study of ocean ecologyas photosynthesis is driven (with a few exceptions) byenergy within the visible light spectrum, which has suf-ficient energy per photon to induce photochemistry. Asphytoplankton accumulations also impact the colorand clarity of the water column, there is a direct linkbetween the studies of ocean optics and ocean ecology(Yentsch and Phinney, 1989).

Radiative transfer calculations are used to quantify the effects of physical and biological processes on variations in the transmission of solar radiation through the upper ocean. Results indicate that net irradiance at 10 cm and 5 m can vary by 23 and 34 W m−2, respectively, due to changes in the chlorophyll concentration, cloud amount, and solar zenith angle (when normalized to a climatological surface irradiance of 200 W m−2). Chlorophyll influences solar attenuation in the visible wavebands, and thus has little effect on transmission within the uppermost meter where the quantity of near-infrared energy is substantial. Beneath the top few meters, a chlorophyll increase from 0.03 to 0.3 mg m−3 can result in a solar flux decrease of more than 10 W m−2. Clouds alter the spectral composition of the incident irradiance by preferentially attenuating in the near-infrared region, and serve to increase solar transmission in the upper few meters as a greater portion of the irradiance exists in the deep-...

Numerical simulations of radiative transfer within the ocean surface mixed layer have been used to derive a set of simple equations for estimating the absorption, a, and backscattering, bb, coefficients in the blue-green spectral region from measurements of downwelling irradiance, Ed, upwelling irradiance, Eu, and upwelling nadir radiance, Lu. Two relationships are used in this derivation: (i) irradiance reflectance, R 5 Eu/Ed, is approximately proportional to bb/a and inversely proportional to the average cosine of the underwater light field, m; and (ii) radiance reflectance, RL 5 Lu/Ed, is proportional to bb/a but changes little with m. Accordingly, m is first estimated from Lu/Eu and then the absorption coefficient is obtained from Gershun’s equation. Having determined a, bb is estimated from the relation between RL and bb/a. We also show how the estimation of m, a, and bb is improved with additional data of the beam attenuation coefficient, c. The retrieval of a and bb from Ed, Eu, and Lu has been tested using field data collected in the Southern California Bight. The a values predicted by the model show good agreement with absorption determinations from the ac-9 instrument and on-board spectrophotometric method, and the modeled bb agrees well with the backscattering determinations from the Hydroscat-6 instrument. The algorithm has been derived for a broad range of the ocean inherent optical properties that do not necessarily covary with one another like in chlorophyll-based bio-optical models. However, the model should be used with caution if significant departure from the average Petzold particle scattering phase function is expected, for example in waters with high load of mineral particles. The inherent optical properties (IOPs) of seawater are solely the properties of the medium and are fundamental to the understanding of the marine optical environment. The development of instrumentation for measuring IOPs and models for deriving the IOPs from the apparent optical properties (AOPs) have been essential to the objective of achieving accurate determinations of oceanic IOPs. Historically, accurate radiometric measurements of underwater light field

Blooms of coccolithophores, particularly those of the species Emiliania huxleyi, cause light in the surface ocean to behave in an unusual fashion, producing distinctive bright “white waters,” apparent from ships and readily detected by remote sensing. The brightness is caused by scattering of light from calcium carbonate platelets (coccoliths). Here we present the results of a modeling study, giving precise calculations of how the coccolith light scattering changes the behavior of light in the water. The results from a Monte Carlo optical model are closely compared to data from the CD60 cruise for a coccolithophore bloom south of Iceland in 1991 [Holligan et al., 1993], and the model is then used to extrapolate from the observational data to predict diverse optical properties that were not measured. Model performance was also tested by comparison of results with those from other, more established optical models. The model results demonstrate clearly that coccoliths cause (1) an increase in the emergent flux (the water-leaving radiance), (2) brighter, more intensely heated water in the top few meters, and (3) darker, less intensely heated water deeper down. Implications of these effects for phytoplankton productivity and for climatology are discussed. Coccolith light scattering is estimated to contribute to global annually averaged planetary albedo by a maximum of ∼0.13%, equivalent to only a small globally averaged radiative forcing of ∼0.22 W m−2.

We have investigated the effect of Raman scattering on the average cosine of underwater irradiance, ,%, the diffuse attenuation coefficient of irradiance, K, and the Raman scattering source coefficient, P*, throughout the water column and into the asymptotic field. The Raman scattering source coefficient is the fractional gain in the scalar irradiance from local Raman scattering at a given depth, and it can be found from the Gershun equation with a Raman source term. In particular, by using calculations from a radiative transfer model (Hydrolight 3.0), we compare ,%, K, and P* from simulations that include and that omit Raman scattering. These simulations are performed at wavelengths between 355 and 665 nm in a vertically homogeneous ocean with inherent optical properties (IOPs) determined from case 1 bio-optical models for three different chlorophyll concentrations (0.05, 0.5, and 5 mg m-j). We also investigated several two-layered oceans that assumed different inherent optical properties in the surface and deep layers. Our calculations showed that when Raman scattering is present, there may exist strong vertical gradients in the average cosine and the diffuse attenuation coefficient, especially at long wavelengths for low chlorophyll concentrations. In addition, a quasi-asymptotic field may be a feature of the vertical profiles of the average cosine and the diffuse attenuation coefficient. In the asymptotic field, there is no effect of Raman scattering at shorter wavelengths, there is a strong effect of Raman scattering at longer wavelengths and between these two spectral regions, and there is a transition that increases from 500 to 590 nm as the concentration of chlorophyll increases from 0.05 to 5 mg m-2. Over a broad range of IOPs, the asymptotic parameters pm*, K,*, and P*, are related by a quadratic relationship. Neither the magnitude or angular distribution of surface light nor changes in the absorption and scattering coefficients in the surface layer of a two-layered ocean have auy effect on the values of ,%=*, K,*, and P*,; the values of these parameters depend only upon the IOPs in the deepest layer.

The beam spread function (BSF) of sea ice is of interest for several reasons. The BSF characterizes beam propagation through sea ice. Its equivalent, the point spread function, is essentially the optical impulse response of the medium, which has many useful connections to radiative transfer theory. In-ice measurements of the BSF over the full angular range 0–180°, using a novel method, were made of first- and multiyear ice off the shore of Barrow, Alaska. All of the measured sea ice BSFs were drastically different than the BSF of ocean water, and they strongly indicated that sea ice is a highly scattering medium, with a single scattering albedo generally >0.97 over the visible spectrum. At pathlengths >30 cm, the BSF was found to be nearly identical to the computed asymptotic radiance distribution. The rapid approach to the asymptotic state and the high single scattering albedo of sea ice suggest that photon diffusion theory should accurately describe radiative transfer in sea ice away from boundaries. Equating the results of diffusion theory with asymptotic radiative transfer theory yields a simple expression that relates the asymptotic attenuation coefficient K∞, to the inherent optical property coefficients and the asymmetry parameter g of the scattering phase function. It is shown that the necessary optical parameters for computing g can be obtained from the measured BSE Thus, all the information necessary for modeling optical propagation in sea ice can be obtained from the BSF measurements using the method described here.

Radiative transfer numerical modeling provides a powerful means of separating and understanding the effects of various types of microbial particles on oceanic light fields. We illustral:e the methodology for achieving this separation and provide various idealized examples. We begin with a database of the single-particle optical properties of marine microbial particles and then construct the total absorption and! scattering properties of natural waters for given concentrations of the various particle types. When used as input to the Hydrolight radiative transfer numerical model, these absorption and scattering properties generate underwater light fields. Because this modeling process rests upon the optical properties of the individual microbial components, rather than just on the total absorption and scattering properties of a water body, it is possible to analyze the e:ffects of the various particulate components on quantities such as diffuse attenuation coefficients and remote-sensing reflectances. We find that different microbial compositions in two water bodies can give considerably different optical properties, even though the chlorophyll concentration is the same in each of the water bodies. Our simulations show how variability in chlorophyll concentrations obtained from remotely sensed ocean color signals can be explained by the detailed composition of the water body. This approach suggests that it may be possible to distinguish between blooms of small picophytoplankton and larger nanophytoplankton by using remotely sensed signals. Stramski and Mobley (1997, hereafter referred to as SM) described a database of single-particle optical properties for five types of microbial particles. These particle types were marine viruses (VIR), heterotrophic bacteria (BAC), cyanobacteria (CYA), small nanophytoplanktonic diatoms (DIA), and nanophytoplanktonic chlorophytes (CHLO). In the present paper, the particular microbes found in the database are viewed as representatives of broader classes of particles. For example, the particular species of DIA in the database (Thalussiosiru pseudonana) has cells with diameters of -4 Frn, and the particular species of CHL0 (Dunaliella tertiolecta) has cells -8 p,m in size. We thus take DIA as representative of small nanophytoplankton of size 4 pm, and we take CHL0 as representative of nanophytoplankton of size 8 pm. The particular species involved are not important for the purposes of this paper. Moreover, it is sufficient for our present purposes to consider only five types of microbial particles, even though realistic simulations of actual water bodies might require more microbial types (such as prochlorophytes, larger bloom-forming species, or coccolithophores). We do include detritus (DET) and colored dissolved organic matter (CDOM) in some of our examples. The database includes, among other things, the single-particle absorption and scattering cross sections, o,(X) and a,(X), respectively, and the scattering phase functions p(0

We describe a database of the single-particle optical properties cd marine microbial particles. This database includes representatives from five classes of particles: viruses (VIR), heterotrophic bacteria (BAC), cyanobacteria (CYA), small nanoplanktonic diatoms (DIA), and nanoplanktonic chlorophytes (CHLO). The optical properties of VIR, whose mean size is 0.07 pm, were determined from Mie scattering calculations using reasonable approximations about the size distribution and refractive index of viral particles. The database for BAC, CYA, DIA, and CHL0 was created from laboratory measurements of microbial cultures and modeling of particle optics. BAC are represented by a mixed natural population of bacterial species (-0.55 pm in size), CYA by Synechococcus (clone WH 8103, - 1 pm), DIA by Thalassiosira pseudonana (-4 Fm), and CHL0 by Dunaliella tertiolecta (-7.5 pm). The database includes the single-particle optical properties that are useful in radiative transfer modeling: the absorption and scattering cross sections and scattering phase functions. Additionally, the database includes the attenuation cross sections, optical efficiency factors, single-scattering albedos, and backscattering properties. For phytoplankton species, chlorophyll- and carbon-specific optical coefficients are also available. The optical quantities are generally determined at I-nm intervals in the spectral region from 350 to 750 nm. The scattering phase function is determined at 5-nm intervals in wavelength and 1” intervals in scattering angle. The size distribution and refractive index of the particles are also included. This database, when combined with radiative transfer modeling, provides a powerful approach to advancing our understanding of oceanic optics. Achieving a detailed understanding of the roles played by various types of particles in oceanic radiative transfer is a prerequisite to advancing our knowledge of the marine optical environment and applying optical techniques to the study of the ocean. It is the fundamental processes of absorption and scattering of light by many individual particles and soluble materials present in seawater that determine the magnitudes and variability of the bulk optical properties and light field characteristics in the ocean. To achieve a comprehensive understanding of the marine optical environment and to construct reliable predictive and inverse optical models, we must first understand how each of these various water components absorbs and scatters light, and hence affects underwater radiative transfer. It is well known that there is great variability in the inherent optical properties (IOPs) of seawater in the world’s oceans. This variability induces a correspondingly large variability in oceanic apparent optical properties (AOPs), even after accounting for variability in the AOPs associated with the incident lighting and sea state. The optical properties of

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. 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 distribution of the underwater radiance at a given point. This quantity is defined as

Accurate calculation of underwater light is fundamental to predictions of upper-ocean heating, primary production, and photo-oxidation. However, most ocean models simulating these processes do not yet incorporate radiative transfer modules for their light calculations. Such models are often driven by above-surface, broadband, daily averaged irradiance or photosynthetically available radiation (PAR) values obtained from climatology or satellite observations, sometimes without correction for sea-surface reflectance, even though surface reflectance can reduce in-water values by more than 20%. We present factors computed by a radiative transfer code that can be used to convert above-surface values in either energy or quantum units to in-water net irradiance, as needed for calculations of water heating, and to in-water PAR, as needed for calculations of photosynthesis and photo-oxidation.

Ocean physical-biological-optical ecosystem models can require light calculations at thousands of grid points and time steps. Implicit inverse models that recover ocean absorption and scattering properties from measured light variables can require thousands of solutions of the radiative transfer equation. An extremely fast radiative transfer code, EcoLight-S(ubroutine), has been developed to address these needs. EcoLight-S requires less than one second on a moderately fast computer to compute spectral irradiances over near-ultraviolet to near-infrared wavelengths with errors in the photosyntheically available radiation (PAR) of no more than ten percent throughout the euphotic zone. It is thus possible to replace simple and often inaccurate analytical PAR or spectral irradiance models with more accurate radiative transfer calculations, with very little computational penalty. EcoLight-S is applicable to Case 2 and optically shallow waters for which no analytical light models exist. EcoLight-S also computes upwelling and downwelling plane irradiances, nadir and zenith radiances, and the remote-sensing reflectance. These quantities allow ecosystem predictions to be validated with optical measurements obtained from in-water instruments or remotely sensed imagery.

The goal of this effort was to incorporate extremely fast but accurate light calculations into coupled physical-biological-optical ocean ecosystem models as used for operational three-dimensional ecosystem predictions. Improvements in light calculations lead to improvements in predictions of chlorophyll concentrations and other water quality parameters (such as visibility), and of upper-ocean thermal structure, relevant to naval needs. In particular, we wanted to imbed the EcoLight-S radiative transfer model in a three-dimensional, time-dependent, coupled physical-biological-optical ecosystem model and then use that coupled model to quantify differences in ecosystem biological and thermal development when using approximate vs. accurate optics. The objective of this year s effort was therefore to further improve the previously developed EcoLight radiative transfer model and incorporate it into a three-dimensional, time-dependent, coupled physical-biological-optical ecosystem model. That coupled model was used to evaluate various strategies for updating the in-water spectral irradiance so as to obtain accurate light predictions while maintaining acceptably fast computation times in fully 3D ecosystem simulations. This year s work centered on the final development of EcoLight-S and imbedding it into the ROMS-CoSiNE code, and then doing studies of the differences in ecosystem predictions of chlorophyll, nutrients, and water heating for various environmental situations.

The goal of this work was to evaluate several existing algorithms for inverting remotely sensed hyperspectral reflectances to extract environmental information such as water-column optical properties, bathymetry, and bottom classification. A number of investigators worldwide have developed algorithms for recovery of bathymetry, bottom classification, and water-column optical properties (in particular, absorption and backscatter coefficients) from airborne hyperspectral imagery of optically shallow waters. Each of those algorithms has its own strengths and weaknesses, or environments for which it may provide better or poorer retrievals than other algorithms. It is therefore necessary to determine the performance characteristics of all available retrieval algorithms. This objective of the present small effort was to finish an on-going comparison of those algorithms via the preparation of a paper on the comparison results.

The overall goal of this work is to develop and validate a spectrum-matching and look-up-table (LUT) technique for rapidly and accurately inverting remotely sensed hyperspectral reflectances to extract environmental information such as bathymetry, and bottom classification, and water-column optical properties. My colleague W. P. Bissett and I have developed new techniques for the extraction of environmental information including shallow-water bathymetry, bottom classification, and water-column inherent optical properties (IOPs), from remotely-sensed hyperspectral ocean-color imagery. We have addressed the need for rapid, semi-automated interpretation of such imagery. My research centered on development and evaluation of the spectrum-matching algorithms, including the generation of confidence metrics for the retrieved information. My initial objectives during the current year were to wrap up the previous developments by (1) documenting the lessons learned about what works well and what does not; (2) clean up the computer codes; (3) create more extensive databases of remote-sensing reflectances Rrs so that the existing algorithms can be applied to a wider range of environments; (4) prepare a user s guide for the processes of creating new databases, processing images with the algorithms previous developed, and displaying the results; (5) transfer the code to NRL for beta testing. Additional on-going work centers on evaluating World View 2 satellite multi-spectral imagery for retrieval of bathymetry.

We present the derivation of an analytical model for the self-shading error of an oceanographic upwelling radiometer. The radiometer is assumed to be cylindrical and can either be a profiling instrument or include a wider cylindrical buoy for floating at the sea surface. The model treats both optically shallow and optically deep water conditions and can be applied any distance off the seafloor. We evaluate the model by comparing its results to those from Monte Carlo simulations. The analytical model performs well over a large range of environmental conditions and provides a significant improvement to previous analytical models. The model is intended for investigators who need to apply self-shading corrections to radiometer data but who do not have the ability to compute shading corrections with Monte Carlo simulations. The model also can provide guidance for instrument design and cruise planning.

Upwelling radiance measurements made with instruments designed to float at the sea surface are shaded both by the instrument housing and by the buoy that holds the instrument. The amount of shading is wavelength dependent and is affected by the local marine and atmospheric conditions. Radiance measurements made with such instruments should be corrected for this self-shading error before being applied to remote sensing calibrations or remote sensing algorithm validation. Here we use Monte Carlo simulations to compute the self-shading error of a commercially available buoyed radiometer so that measurements made with this instrument can be improved. This approach can be easily adapted to the dimensions of other instruments.

Modeling the plankton ecosystem requires a code for simulating the profile of irradiance from the chlorophyll profile at each time step of the integration. We have compared two existing codes with data from the Biogeochemical Ocean Flux Study: the Hydrolight radiative transfer model is accurate but too slow to use interactively in ecological models; Morel's [J. Geophys. Res. 93, 10, 749 (1988)] empirical model is much faster but produces substantial error. We have developed a streamlined version of the Hydrolight radiative transfer model that is 20 times faster than the full Hydrolight code, while limiting errors to less than 12% within the euphotic zone. This new code is both fast and accurate and is, therefore, suitable for use interactively in oceanic ecosystem models.

For analytical or semianalytical retrieval of shallow-water bathymetry andyor optical properties of the water column from remote sensing, the contribution to the remotely sensed signal from the water column has to be separated from that of the bottom. The mathematical separation involves three diffuse attenuation coefficients: one for the downwelling irradiance ~Kd!, one for the upwelling radiance of the water column ~Ku C !, and one for the upwelling radiance from bottom reflection ~Ku B !. Because of the differences in photon origination and path lengths, these three coefficients in general are not equal, although their equality has been assumed in many previous studies. By use of the Hydrolight radiativetransfer numerical model with a particle phase function typical of coastal waters, the remote-sensing reflectance above ~Rrs! and below ~rrs! the surface is calculated for various combinations of optical properties, bottom albedos, bottom depths, and solar zenith angles. A semianalytical ~SA! model for rrs of shallow waters is then developed, in which the diffuse attenuation coefficients are explicitly expressed as functions of in-water absorption ~a! and backscattering ~bb!. For remote-sensing inversion, parameters connecting Rrs and rrs are also derived. It is found that rrs values determined by the SA model agree well with the exact values computed by Hydrolight ~;3% error!, even for Hydrolight rrs values calculated with different particle phase functions. The Hydrolight calculations included bbya values as high as 1.5 to simulate high-turbidity situations that are occasionally found in coastal regions. © 1998 Optical Society of America OCIS codes: 010.0010, 280.0280.

Ten-year simulations were performed using a coupled physical-biological-optical ocean ecosystem model with both simple analytic and accurate EcoLight numerical computations of the in-water irradiances. The predicted chlorophyll concentrations differed by tens of percent over the course of 10-year simulations. The EcoLight code runs with less than a 30% increase in nm time, which providing several advantages than cannot he obtained with an analytic light model. These advantages are as follows. (1) EcoLight does a much better job of computing irradiances near 400 and beyond 600 nm, and at depth. These differences can have significant effects on how particular phytoplankton functional groups evolve in time and at depth. (2) EcoLight can model any water body, including Case 2 water and optically shallow waters for which bottom reflectance can substantially increase the irradiance available for photosynthesis and water heating. (3) EcoLight provides the outputs necessary for ecosystem validation using satellite-derived water-leaving radiances or remote-sensing reflectances, without the necessity of using a chlorophyll algorithm to convert satellite data into an ecosystem variable. (4) EcoLight provides a means for improved ecosystem model initialization and data assimilation directly in terms of the available data, again without an intermediate step involving a data-to-chlorophyll conversion algorithm.

[1] Nighttime water-leaving radiance is a function of the depth-dependent distribution of both the in situ bioluminescence emissions and the absorption and scattering properties of the water. The vertical distributions of these parameters were used as inputs for a modified one-dimensional radiative transfer model to solve for spectral bioluminescence water-leaving radiance from prescribed depths of the water column. Variation in the water-leaving radiance was consistent with local episodic physical forcing events, with tidal forcing, terrestrial runoff, particulate accumulation, and biological responses influencing the shorter timescale dynamics. There was a >90 nm shift in the peak water-leaving radiance from blue (∼474 nm) to green as light propagated to the surface. In addition to clues in ecosystem responses to physical forcing, the temporal dynamics in intensity and spectral quality of water-leaving radiance provide suitable ranges for assessing detection. This may provide the information needed to estimate the depth of internal light sources in the ocean, which is discussed in part 2 of this paper.

[1] Many bioluminescence observations are made from the ocean's surface. However, the depth of the bioluminescent source is difficult to estimate on the basis of surface observations alone, given the variable light attenuation of unknown concentrations of water column constituents such as phytoplankton, colored dissolved organic matter, and detritus. Part 1 of this paper showed that bioluminescent water-leaving radiance signals are detectable, even in extremely turbid and dynamic coastal waters. Here, in part 2 of this paper, we analyze the water-leaving radiance patterns of bioluminescence modeled by HydroLight 4.2 to determine if the depth of the bioluminescent source can be estimated from its spectral signature. We find that the depth of the bioluminescent source is contained within the spectral signal and can be elucidated by simple neural networks. These networks can predict the depth of a bioluminescent layer with great accuracy, solely on the basis of the spectral shape of bioluminescent water-leaving radiance in a variety of water column and bottom type conditions. In addition, we found that as little as three wavelengths from the spectrum of water-leaving radiance are sufficient for an accurate determination of the depth of the bioluminescent source.

The overall goal of this work is to refine and validate a spectrum-matching and look-up-table (LUT) technique for rapidly inverting remotely sensed hyperspectral reflectances to extract environmental information such as water-column optical properties, bathymetry, and bottom classification. My colleagues at the Florida Environmental Research Institute and I are developing and evaluating techniques for the extraction of environmental information including water-column inherent optical properties (IOPs) and shallow-water bathymetry and bottom classification from remotely-sensed hyperspectral ocean-color spectra. We address the need for rapid, automated interpretation of hyperspectral imagery. The research issues center on development and evaluation of spectrum-matching algorithms, including the generation of confidence metrics for the retrieved information. The present work, which is just starting, continues investigations that were previously funded under a different contract (see the associated report for previous results). The on-going work will continue the evaluation, refinement, and optimization of the LUT technique including, in particular, applications to turbid coastal waters, inhomogeneous water columns, and optically deep waters.

Long-term goals are to: Quantify and understand the inherent optical properties (IOP's) of natural particles from a standpoint of measuring size-distribution (ii) Understand how the properties of particles (composition, shape, and internal structure) affect their IOP. (iii) Incorporate these properties into radiative transfer models for prediction of downwelling and upwelling radiances.

Generation of random sea surfaces using wave variance spectra and Fourier transforms is formulated in a way that guarantees conservation of wave energy and fully resolves wave height and slope variances. Monte Carlo polarized ray tracing, which accounts for multiple scattering between light rays and wave facets, is used to compute effective Mueller matrices for reflection and transmission of air- or water-incident polarized radiance. Irradiance reflectances computed using a Rayleigh sky radiance distribution, sea surfaces generated with Cox-Munk statistics, and unpolarized ray tracing differ by 10%-18% compared with values computed using elevation- and slope-resolving surfaces and polarized ray tracing. Radiance reflectance factors, as used to estimate water-leaving radiance from measured upwelling and sky radiances, are shown to depend on sky polarization, and improved values are given.

The overall goal of this work, now completed, was to combine hyperspectral imagery (HSI) with LIDAR bathymetry to improve retrievals of bottom classification and water-column inherent optical properties including, if possible, the retrieval of the vertical structure of water-column and benthic-boundary scattering layers from airborne platforms.

A spectrum-matching and look-up-table (LUT) methodology has been developed and evaluated to extract environmental information from remotely sensed hyperspectral imagery. The LUT methodology works as follows. First, a database of remote-sensing reflectance (Rrs) spectra corresponding to various water depths, bottom reflectance spectra, and water-column inherent optical properties (IOPs) is constructed using a special version of the HydroLight radiative transfer numerical model. Second, the measured Rrs spectrum for a particular image pixel is compared with each spectrum in the database, and the closest match to the image spectrum is found using a least-squares minimization. The environmental conditions in nature are then assumed to be the same as the input conditions that generated the closest matching HydroLight-generated database spectrum. The LUT methodology has been evaluated by application to an Ocean Portable Hyperspectral Imaging Low-Light Spectrometer image acquired near Lee Stocking Island, Bahamas, on 17 May 2000. The LUT-retrieved bottom depths were on average within 5% and 0.5 m of independently obtained acoustic depths. The LUT-retrieved bottom classification was in qualitative agreement with diver and video spot classification of bottom types, and the LUT-retrieved IOPs were consistent with IOPs measured at nearby times and locations.

HyperSpectral Imagery (HSI) of the coastal zone often focuses on the estimation of bathymetry. However, the estimation of bathymetry requires knowledge, or the simultaneous solution, of water column Inherent Optical Properties (IOPs) and bottom reflectance. The numerical solution to the simultaneous set of equations for bathymetry, IOPs, and bottom reflectance places high demands on the spectral quality, calibration, atmospheric correction, and Signal-to-Noise (SNR) of the HSI data stream. In October of 2002, a joint FERI/NRL/NAVO/USACE HSI/LIDAR experiment was conducted off of Looe Key, FL. This experiment yielded high quality HSI data at a 2 m resolution and bathymetric LIDAR data at a 4 m resolution. The joint data set allowed for the advancement and validation of a previously generated Look-Up-Table (LUT) approach to the simultaneous retrieval of bathymetry, IOPs, and bottom type. Bathymetric differences between the two techniques were normally distributed around a 0 mean, with the exception of two peaks. One peak related to a mechanical problem in the LIDAR detector mirrors that causes errors on the edges of the LIDAR flight lines. The other significant difference occurred in a single geographic area (Hawk Channel) suggesting an incomplete IOP or bottom reflectance description in the LUT data base. In addition, benthic habitat data from NOAA’s National Ocean Service (NOS) and the Florida Wildlife Research Institute (FWRI) provided validation data for the estimation of bottom type. Preliminary analyses of the bottom type estimation suggest that the best retrievals are for seagrass bottoms. One source of the potential difficulties may be that the LUT database was generated from a more pristine location (Lee Stocking Island, Bahamas). It is expected that fusing the HSI/LIDAR data streams should reduce the errors in bottom typing and IOP estimation.

This report provides a methodology and the equations needed to generate Monte Carlo computer simulations for many common ocean optics applications. These applications include the modeling of natural ocean-atmosphere environments and analyses of laboratory and in-situ optical instrumentation. We attempt to provide enough practical detail to make it straightforward for the reader to write his/her own computer code for his/ her own application. This document also serves as documentation of the methods the authors have used in several specific research projects.

A spectrum-matching and look-up-table (LUT) methodology has been developed and evaluated for extracting environmental information from remotely sensed hyperspectral imagery. The LUT methodology works as follows. First, a database of remote-sensing reflectance (R(sub rs) spectra corresponding to various water depths, bottom reflectance spectra, and water-column inherent optical properties (IOPs) is constructed using a special version of the Hydrolight radiative transfer numerical model. Second, the R(sub rs) spectrum for a particular image pixel is compared with each spectrum in the database and the closest match to the image spectrum is found using a least-squares minimization. The environmental conditions in nature are then assumed to be the same as the input conditions that generated the closest-matching Hydrolight-generated spectrum in the database. The LUT methodology has been evaluated by application to an Ocean PHILLS (Portable Hyperspectral Imaging Low-Light Spectrometer) image acquired near Lee Stocking Island, Bahamas, on 17 May 2000. The LUT-retrieved bottom depths were on average within 5% and 0.5 m of independently obtained acoustic depths. The LUT-retrieved bottom classification was in qualitative agreement with diver and video spot classification of bottom types, and the LUT-retrieved IOPs were consistent with IOPs measured at nearby times and locations.