Satellite retrieval of inherent optical properties by inversion of an oceanic radiance model: a preliminary algorithm

A previously published radiance model inversion theory has been field tested by using airborne water-leaving radiances to retrieve the chromophoric dissolved organic matter (CDOM) and detritus absorption coefficient, the phytoplankton absorption coefficient, and the total backscattering coefficient. The radiance model inversion theory was tested for potential satellite use by comparing two of the retrieved inherent optical properties with concurrent airborne laser-derived truth data. It was found that (1) matrix inversion of water-leaving radiances is well conditioned even in the presence of instrument-induced noise, (2) retrieved CDOM and detritus and phytoplankton absorption coefficients are both in reasonable agreement with absorption coefficients derived from airborne laser-induced fluorescence spectral emissions, (3) the total backscattering retrieval magnitude and variability are consistent with expected values for the Middle Atlantic Bight, and (4) the algorithm performs reasonably well in Sargasso Sea, Gulf Stream, slope, and shelf waters but is less consistent in coastal waters.     

Chlorophyll biomass in the global oceans: satellite retrieval using inherent optical properties

In the upper layer of the global ocean, 2082 in situ chlorophyll biomass values (Chl) are retrieved by concurrent satellite-derived inherent optical properties (IOP). It is found that (1) the phytoplankton absorption coefficient IOP alone does not provide satisfactory (Chl) retrieval; (2) the chromophoric dissolved organic matter (CDOM) absorption coefficient IOP must also be used to obtain satisfactory retrieval through (Chl) alpha a ph + pa CDOM where p is a constant and a ph and aCDOM are, respectively, the phytoplankton and CDOM absorption coefficients; (3) the IOP-based (Chl) retrieval performance is comparable to standard satellite reflectance ratio retrievals (that have CDOM absorption intrinsically embedded within them); (4) inclusion of the total backscattering coefficient IOP does not contribute significantly to (Chl) retrieval; and (5) the new IOP-based algorithm may provide the possibility for future research to establish the actual role of extracellular CDOM from all sources in the intracellular production of chlorophyll biomass.     

Spectral parameters of inherent optical property models: method for satellite retrieval by matrix inversion of an oceanic radiance model

Inherent optical property (IOP) spectral models for the phytoplankton absorption coefficient, chromophoric dissolved organic matter (CDOM) absorption coefficient, and total constituent backscattering (TCB) coefficient are linear in the reference wavelength IOP and nonlinear in the spectral parameters. For example, the CDOM absorption coefficient IOP a(CDOM)(lambda(i)) = a(CDOM)(lambda(ref))exp[-S(lambda(i)- lambda(ref))] is linear in a(CDOM)(lambda(ref)) and nonlinear in S. Upon linearization by Taylor's series expansion, it is shown that spectral model parameters, such as S, can be concurrently accommodated within the same conventional linear matrix formalism used to retrieve the reference wavelength IOP's. Iteration is used to adjust for errors caused by truncation of the Taylor's series expansion. Employing an iterative linear matrix inversion of a water-leaving radiance model, computer simulations using synthetic data suggest that (a) no instabilities or singularities are introduced by the linearization and subsequent matrix inversion procedures, (b) convergence to the correct value can be expected only if starting values for a model parameter are within certain specific ranges, (c) accurate retrievals of the CDOM slope S (or the phytoplankton Gaussian width g) are generally reached in 3-20 iterations, (d) iterative retrieval of the exponent n of the TCB wavelength ratio spectral model is not recommended because the starting values must be within approximately +/-5% of the correct value to achieve accurate convergence, and (e) concurrent retrieval of S and g (simultaneously with the phytoplankton, CDOM, and TCB coefficient IOP's) can be accomplished in a 5 x 5 iterative matrix inversion if the starting values for S and g are carefully chosen to be slightly higher than the expected final retrieved values.     

Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters

For open ocean and coastal waters, a multiband quasi-analytical algorithm is developed to retrieve absorption and backscattering coefficients, as well as absorption coefficients of phytoplankton pigments and gelbstoff. This algorithm is based on remote-sensing reflectance models derived from the radiative transfer equation, and values of total absorption and backscattering coefficients are analytically calculated from values of remote-sensing reflectance. In the calculation of total absorption coefficient, no spectral models for pigment and gelbstoff absorption coefficients are used. Actually those absorption coefficients are spectrally decomposed from the derived total absorption coefficient in a separate calculation. The algorithm is easy to understand and simple to implement. It can be applied to data from past and current satellite sensors, as well as to data from hyperspectral sensors. There are only limited empirical relationships involved in the algorithm, and they are for less important properties, which implies that the concept and details of the algorithm could be applied to many data for oceanic observations. The algorithm is applied to simulated data and field data, both non-case1, to test its performance, and the results are quite promising. More independent tests with field-measured data are desired to validate and improve this algorithm.     

Radiance-irradiance inversion algorithm for estimating the absorption and backscattering coefficients of natural waters: vertically stratified water bodies

A full multiple-scattering algorithm for inverting profiles of the upwelling and downwelling irradiances to yield profiles of the absorption and backscattering coefficients in a vertically stratified water body is described and tested with simulated data. The algorithm does not require knowledge of the scattering phase function of the medium. The results are better the closer the phase function assumed in the retrievals is to the true phase function, although excellent retrievals of the absorption coefficient can still be obtained with an inaccurate phase function. Simulations show that the algorithm is capable of determining the vertical structure of a stratified water body and usually provides the absorption coefficient profile with an error ?2% and the backscattering coefficient profile with an error ?10%, as long as the spacing between pseudodata samples is sufficiently small that the necessary derivatives of the irradiances can be accurately computed. The performance is only slightly degraded when the upwelling radiance (nadir viewing) is substituted for the upwelling irradiance.     

Effects of noise on lidar data inversion with the backward algorithm

The lidar data-inversion algorithm widely known as the Klett method (and its more elaborate variants) has long been used to invert elastic-lidar data obtained from atmospheric sounding systems. The Klett backward algorithm has also been shown to be robust in the face of uncertainties concerning the boundary condition. Nevertheless electrical noise at the photoreceiver output unavoidably has an impact on the data-inversion process, and describing in an explicit way how it affects retrieval of the atmospheric optical coefficients can contribute to improvement in inversion quality. We examine formally the way noise disturbs backscatter-coefficient retrievals done with the Klett backward algorithm, derive a mathematical expression for the retrieved backscatter coefficient in the presence of noise affecting the signal, and assess the noise impact and suggest ways to limit it.     

Optical remote sensing of marine constituents in coastal waters: a feasibility study

Optical remote sensing of ocean color is a well-established technique for inferring ocean properties. However, most retrieval algorithms are based on the assumption that the radiance received by satellite instruments is affected only by the phytoplankton pigment concentration and correlated substances. This assumption works well for open ocean water but becomes questionable for coastal waters. To reduce uncertainties associated with this assumption, we developed a new algorithm for the retrieval of marine constituents in a coastal environment. We assumed that ocean color can be adequately described by a three-component model made up of chlorophyll a, suspended matter, and yellow substance. The simultaneous retrieval of these three marine constituents and of the atmospheric aerosol content was accomplished through an inverse-modeling scheme in which the difference between simulated radiances exiting the atmosphere and radiances measured with a satellite sensor was minimized. Simulated radiances were generated with a comprehensive radiative transfer model that is applicable to the coupled atmosphere-ocean system. The method of simulated annealing was used to minimize the difference between measured and simulated radiances. To evaluate the retrieval algorithm, we used simulated (instead of measured) satellite-received radiances that were generated for specified concentrations of aerosols and marine constituents, and we tested the ability of the algorithm to retrieve assumed concentrations. Our results require experimental validation but show that the retrieval of marine constituents in coastal waters is possible.     

Apparent and inherent optical properties of turbid estuarine waters: measurements, empirical quantification relationships, and modeling

Spectral measurements of remote-sensing reflectance (Rrs) and absorption coefficients carried out in three European estuaries (Gironde and Loire in France, Tamar in the UK) are presented and analyzed. Typical Rrs and absorption spectra are compared with typical values measured in coastal waters. The respective contributions of the water constituents, i.e., suspended sediments, colored dissolved organic matter, and phytoplankton (characterized by chlorophyll-a), are determined. The Rrs spectra are then reproduced with an optical model from the measured absorption coefficients and fitted backscattering coefficients. From Rrs ratios, empirical quantification relationships are established, reproduced, and explained from theoretical calculations. These quantification relationships were established from numerous field measurements and a reflectance model integrating the mean values of the water constituents' inherent optical properties. The model's sensitivity to the biogeochemical constituents and to their nature and composition is assessed.     

Effect of the particle-size distribution on the backscattering ratio in seawater

Mie theory is used to model the backscattering ratio (the ratio of the backscattering coefficient to the total scattering coefficient) of marine particles with the assumption that they follow a Junge-type size distribution. Results show that the backscattering ratio is very sensitive to the presence of submicrometer particles and depends strongly on the shape of the size distribution. However, it is not affected significantly by absorption and does not vary with wavelength over the visible range. The implications for modeling of backscattering and ocean color in terms of phytoplankton pigment concentration are discussed.     

Evaluation of a compact sensor for backscattering and absorption

Seawater inherent optical properties (IOPs) are key parameters in a wide range of applications in environmental studies and oceanographic research. In particular, the absorption coefficient (a) is the typical IOP used to obtain the concentration of chlorophyll-a in the water-a critical parameter in biological oceanography studies and the backscattering coefficient (b(b)) is used as a measure of turbidity. In this study, we test a novel instrument concept designed to obtain both the absorption and backscattering coefficients. The instrument would emit a collimated monochromatic light beam into the water retrieving the backscattered light intensity as a function of distance from the center of illumination. We use Monte Carlo modeling of light propagation to create an inversion algorithm that translates the signal from such an instrument into values of a and b(b). Our results, based on simulations spanning the bulk of natural values of seawater IOP combinations, indicate that a 6.2 cm diameter instrument with a radial resolution of 1 cm would be capable of predicting b(b) within less than 13.4% relative difference and a within less than 57% relative difference (for 90% of the inverted a values, the relative errors fall below 29.7%). Additionally, these errors could be further reduced by constraining the inversion algorithm with information from concurrent measurements of other IOPs. Such a compact and relatively simple device could have multiple applications for in situ optical measurements, including a and b(b) retrievals from instrumentation mounted on autonomous underwater vehicles. Furthermore, the same methodology could possibly be used for an out-of-water sensor.     

Accurate and self-consistent ocean color algorithm: simultaneous retrieval of aerosol optical properties and chlorophyll concentrations

A new algorithm has been developed for simultaneous retrieval of aerosol optical properties and chlorophyll concentrations in case I waters. This algorithm is based on an improved complete model for the inherent optical properties and accurate simulations of the radiative transfer process in the coupled atmosphere-ocean system. It has been tested against synthetic radiances generated for the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) channels and has been shown to be robust and accurate. A unique feature of this algorithm is that it uses the measured radiances in both near-IR and visible channels to find that combination of chlorophyll concentration and aerosol optical properties that minimizes the error across the spectrum. Thus the error in the retrieved quantities can be quantified.     

Validation of satellite-retrieved oceanic inherent optical properties: proposed two-color elastic backscatter lidar and retrieval theory

Recent radiative transfer models show that: (1) regardless of elastic lidar receiver field of view (FOV), at vanishing lidar depth the lidar-derived attenuation coefficient klidar --> a, where a is the total absorption coefficient per meter of depth; and (2) for a wide FOV as the lidar sensing depth approaches some large value (depending on water type), klidar --> Kd, where Kd is the diffuse attenuation for downwelling irradiance. As a result, it is shown that a time-resolved, dual-wavelength-laser, elastic-backscattering lidar can retrieve the three principal oceanic optical properties: (1) the absorption coefficient of phytoplankton aph, (2) the absorption coefficient of chromophoric dissolved organic matter (CDOM) aCDOM, and (3) the nonwater total constituent backscattering coefficient bbt. The lidar-retrieved aph, aCDOM, and bbt inherent optical properties can be used to validate corresponding satellite-derived products such as those from terra moderate-resolution imaging spectroradiometer (MODIS), Aqua MODIS, Sea-viewing Wide Field-of-view Sensor, (SeaWiFS), and other ocean color sensors.     

Chlorophyll biomass in the global oceans: airborne lidar retrieval using fluorescence of both chlorophyll and chromophoric dissolved organic matter

For three decades airborne laser-induced fluorescence has demonstrated value for chlorophyll biomass retrieval in wide-area oceanic field experiments, satellite validation, and algorithm development. A new chlorophyll biomass retrieval theory is developed using laser-induced and water Raman normalized fluorescence of both (a) chlorophyll and (b) chromophoric dissolved organic matter (CDOM). This airborne lidar retrieval theory is then independently confirmed by chlorophyll biomass obtained from concurrent (1) ship-cruise retrievals, (2) satellite inherent optical property (IOP) biomass retrievals, and (3) satellite standard band-ratio chlorophyll biomass retrievals. The new airborne lidar chlorophyll and CDOM fluorescence-based chlorophyll biomass retrieval is found to be more robust than prior lidar methods that used chlorophyll fluorescence only. Future research is recommended to further explain the underlying influence of CDOM on chlorophyll production.     

Optical modeling and measurements of a coccolithophore bloom

Blooms of the phytoplankton coccolithophorid Emiliania huxleyi can cause significant changes to both the inherent and the apparent optical properties within an oceanic column. Measurements made within such a bloom off the southwestern coast of England during July 1999 are reported. The multiple scattering properties of the bloom prevented accurate retrieval of absorption (a) and attenuation (c) coefficients with a WETLabs ac-9. Upwelling radiance measurements were similarly affected by the bloom, which caused the sensors to saturate. An optical model has been developed that gives close agreement with the in situ optics when it is used as input to the Hydrolight radiative-transfer model.     

Optical assessment of particle size and composition in the Santa Barbara Channel, California

The suspended particle assemblage in complex coastal waters is a mixture of living phytoplankton, other autochthonous matter, and materials of terrestrial origin. The characterization of suspended particles is important for understanding regional primary productivity and rates of carbon sequestration, the fate of anthropogenic materials released to the coastal environment, as well as its effects on bulk optical properties, which influence the passive optical remote sensing of the coastal ocean. Here, the extensive bio-optical Plumes and Blooms data set is used to characterize the surface particle assemblage in the Santa Barbara Channel, California, a highly productive, upwelling-dominated, coastal site affected by episodic sediment inputs. Available variables sensitive to characteristics of the particle assemblage include particle beam attenuation and backscattering coefficients, High Performance Liquid Chromatography (HPLC) pigment concentration observations, chlorophyll and particulate organic carbon concentration, particulate and phytoplankton absorption coefficients, and Laser In-situ Scattering and Transmissometry (LISST) 100-X particle sizer observations. Comparisons among these particle assemblage proxy variables indicate good agreement and internal consistency among the data set. Correlations among chlorophyll concentration, particulate organic carbon concentration (POC), HPLC pigments, and proxies sensitive to the entire particle assemblage such as backscattering and LISST data strongly indicate that in spite of its coastal character, variability in the particle assemblage in the Santa Barbara Channel is dominated by its marine biogenic component. Relatively high estimates of the bulk real index of refraction and its positive correlation with chlorophyll and lithogenic silica concentration tentatively indicate that there is minerogenic particle influence in the Santa Barbara Channel that tends to covary with the phytoplankton blooms. Limitations of each particle assemblage proxy and remote-sensing applications are discussed.     

Improved retrievals of the optical properties of cirrus clouds by a combination of lidar methods

We focus on improvement of the retrieval of optical properties of cirrus clouds by combining two lidar methods. We retrieve the cloud's optical depth by using independently the molecular backscattering profile below and above the cloud [molecular integration (MI) method] and the backscattering profile inside the cloud with an a priori effective lidar ratio [particle integration (PI) method]. When the MI method is reliable, the combined MI-PI method allows us to retrieve the optimal effective lidar ratio. We compare these results with Raman lidar retrievals. We then use the derived optimal effective lidar ratio for retrieval with the PI method for situations in which the MI method cannot be applied.     

Particle extinction measured at ambient conditions with differential optical absorption spectroscopy. 2. Closure study

Spectral particle extinction coefficients of atmospheric aerosols were measured with, to the best of our knowledge, a newly designed differential optical absorption spectroscopy (DOAS) instrument. A closure study was carried out on the basis of optical and microphysical aerosol properties obtained from nephelometer, particle soot/absorption photometer, hygroscopic tandem differential mobility analyzer, twin differential mobility particle sizer, aerodynamic particle sizer, and Berner impactors. The data were collected at the urban site of Leipzig during a period of 10 days in March 2000. The performance test also includes a comparison of the optical properties measured with DOAS to particle optical properties calculated with a Mie-scattering code. The computations take into account dry and ambient particle conditions. Under dry particle conditions the linear regression and the correlation coefficient for particle extinction are 0.95 and 0.90, respectively. At ambient conditions these parameters are 0.89 and 0.97, respectively. An inversion algorithm was used to retrieve microphysical particle properties from the extinction coefficients measured with DOAS. We found excellent agreement within the retrieval uncertainties.     

Multiparameter retrieval of water optical properties from above-water remote-sensing reflectance using the simulated annealing algorithm

Water-leaving radiance, measured just above the ocean surface, contains important information about near-surface or subsurface processes that occur on or below the deep ocean and coastal water. As such, retrieving seawater inherent optical properties (IOPs) is an important step to determining water type, subsurface light field, turbidity, pigment concentration, and sediment loading. However, the retrieval (or inversion) of seawater IOPs from just above water radiance measurements is a multiparameter nonlinear problem that is difficult to solve by conventional optimization methods. The applicability of the simulated annealing algorithm (SA) is explored as a nonlinear global optimizer to solve this multiparameter retrieval problem. The SA algorithm is combined with widely known semianalytical relations for seawater's IOPs to parameter invert these properties from simulated and measured water-leaving reflectance spectra. Furthermore, given the versatility of the SA algorithm, the scheme is extended to retrieve water depth from input reflectance data. Extensive tests and comparisons with in situ and simulated data sets compiled by the International Ocean-Color Coordinating Group are presented. Field data include reflectance spectra acquired with a handheld GER 1500 spectroradiometer and absorption measurements, performed with the AC-9 instrument on waters around Singapore's nearby islands.     

Semianalytical model for the derivation of ocean color inherent optical properties: description, implementation, and performance assessment

A semianalytical approach to the problem of determining inherent optical properties from satellite and in situ ocean color data is presented. The model uses empirically derived spectral slopes between neighboring wavebands in combination with radiative transfer modeling to determine the spectral absorption (alpha) and backscatter (b(b)); these values are then further decomposed into absorption due to phytoplankton, detrital, and colored dissolved organic matter components. When compared with over 400 in situ data points the model makes good retrievals of the total absorption and backscatter across the entire spectrum, with regression slopes close to unity, little or no bias, high percentage of variance explained, and low rms errors.     

Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from space

Existing atmospheric correction algorithms for multichannel remote sensing of ocean color from space were designed for retrieving water-leaving radiances in the visible over clear deep ocean areas and cannot easily be modified for retrievals over turbid coastal waters. We have developed an atmospheric correction algorithm for hyperspectral remote sensing of ocean color with the near-future Coastal Ocean Imaging Spectrometer. The algorithm uses lookup tables generated with a vector radiative transfer code. Aerosol parameters are determined by a spectrum-matching technique that uses channels located at wavelengths longer than 0.86 mum. The aerosol information is extracted back to the visible based on aerosol models during the retrieval of water-leaving radiances. Quite reasonable water-leaving radiances have been obtained when our algorithm was applied to process hyperspectral imaging data acquired with an airborne imaging spectrometer.