Optical remote sensing of waters with vertical structure

Optical remote sensing of ocean color is a well-established technique that is used to produce maps of marine constituents on a routine basis. Retrieval algorithms used to infer pigment concentrations from measurements of ocean color are usually based on the assumption that the upper ocean column is vertically homogeneous. However, stable stratification of the water column is often encountered in coastal waters and in fjords. This stratification is decisive for the initiation, maintainance, and species composition of phytoplankton blooms. Here we present an optical remote-sensing algorithm with the ability to resolve such a vertical structure of oceanic waters. The vertical structure is assumed to consist of two homogeneous layers with different concentrations of chlorophyll a. The algorithm is designed to determine the chlorophyll-a concentrations of the two layers as well as the thickness of the upper layer. These three parameters influence the ocean color and are simultaneously retrieved through an inverse-modeling technique. This technique consists of using radiative-transfer computations for a coupled atmosphere-ocean system to simulate radiances received in various bands of the satellite sensor and to compare these simulated results with measured radiances. The sum of absolute values of differences between simulated and measured radiances is minimized by use of an optimization algorithm, and the retrieved parameters are those that yield the minimum sum of differences between measured and simulated data. The optimization algorithm that we used in our study is the simulated annealing method, which is an extension of the downhill simplex algorithm. In this study the algorithm was tested on synthetic data generated by the forward model. The results indicate that it should be possible to retrieve vertical variations in the pigment concentration. The synthetic data were generated for spectral bands that coincide with those of the Medium Resolution Imaging Spectrometer sensor, which will be a part of the instrument package of the upcoming Environmental Satellite.     

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.     

Assessment of a bidirectional reflectance distribution correction of above-water and satellite water-leaving radiance in coastal waters

Water-leaving radiances, retrieved from in situ or satellite measurements, need to be corrected for the bidirectional properties of the measured light in order to standardize the data and make them comparable with each other. The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. However, versions of bidirectional reflectance correction algorithms specifically tuned for typical coastal waters and other case 2 conditions are particularly needed to improve the overall quality of those data. In order to analyze the bidirectional reflectance distribution function (BRDF) of case 2 waters, a dataset of typical remote sensing reflectances was generated through radiative transfer simulations for a large range of viewing and illumination geometries. Based on this simulated dataset, a case 2 water focused remote sensing reflectance model is proposed to correct above-water and satellite water-leaving radiance data for bidirectional effects. The proposed model is first validated with a one year time series of in situ above-water measurements acquired by collocated multispectral and hyperspectral radiometers, which have different viewing geometries installed at the Long Island Sound Coastal Observatory (LISCO). Match-ups and intercomparisons performed on these concurrent measurements show that the proposed algorithm outperforms the algorithm currently in use at all wavelengths, with average improvement of 2.4% over the spectral range. LISCO's time series data have also been used to evaluate improvements in match-up comparisons of Moderate Resolution Imaging Spectroradiometer satellite data when the proposed BRDF correction is used in lieu of the current algorithm. It is shown that the discrepancies between coincident in-situ sea-based and satellite data decreased by 3.15% with the use of the proposed algorithm. This confirms the advantages of the proposed model over the current one, demonstrating the need for a specific case 2 water BRDF correction algorithm as well as the feasibility of enhancing performance of current and future satellite ocean color remote sensing missions for monitoring of typical coastal waters.     

On-orbit vicarious calibration of ocean color sensors using an ocean surface reflectance model

Recent advances in global biogeochemical research demonstrate a critical need for long-term ocean color satellite data records of consistent high quality. To achieve that quality, spaceborne instruments require on-orbit vicarious calibration, where the integrated instrument and atmospheric correction system is adjusted using in situ normalized water-leaving radiances, such as those collected by the marine optical buoy (MOBY). Unfortunately, well-characterized time-series of in situ data are scarce for many historical satellite missions, in particular, the NASA coastal zone color scanner (CZCS) and the ocean color and temperature scanner (OCTS). Ocean surface reflectance models (ORMs) accurately reproduce spectra observed in clear marine waters, using only chlorophyll a (C(a)) as input, a measurement for which long-term in situ time series exist. Before recalibrating CZCS and OCTS using modeled radiances, however, we evaluate the approach with the Sea-viewing Wide-Field-of-view Sensor (SeaWiFS). Using annual C(a) climatologies as input into an ORM, we derive SeaWiFS vicarious gains that differ from the operational MOBY gains by less than +/-0.9% spectrally. In the context of generating decadal C(a) climate data records, we quantify the downstream effects of using these modeled gains by generating satellite-to-in situ data product validation statistics for comparison with the operational SeaWiFS results. Finally, we apply these methods to the CZCS and OCTS ocean color time series.     

Remote sensing of ocean color and aerosol properties: resolving the issue of aerosol absorption

Current atmospheric correction and aerosol retrieval algorithms for ocean color sensors use measurements of the top-of-the-atmosphere reflectance in the near infrared, where the contribution from the ocean is known for case 1 waters, to assess the aerosol optical properties. Such measurements are incapable of distinguishing between weakly and strongly absorbing aerosols, and the atmospheric correction and aerosol retrieval algorithms fail if the incorrect absorption properties of the aerosol are assumed. We present an algorithm that appears promising for the retrieval of in-water biophysical properties and aerosol optical properties in atmospheres containing both weakly and strongly absorbing aerosols. By using the entire spectrum available to most ocean color instruments (412-865 nm), we simultaneously recover the ocean's bio-optical properties and a set of aerosol models that best describes the aerosol optical properties. The algorithm is applied to simulated situations that are likely to occur off the U.S. East Coast in summer when the aerosols could be of the locally generated weakly absorbing Maritime type or of the pollution-generated strongly absorbing urban-type transported over the ocean by the winds. The simulations show that the algorithm behaves well in an atmosphere with either weakly or strongly absorbing aerosol. The algorithm successfully identifies absorbing aerosols and provides close values for the aerosol optical thickness. It also provides excellent retrievals of the ocean bio-optical properties. The algorithm uses a bio-optical model of case 1 waters and a set of aerosol models for its operation. The relevant parameters of both the ocean and atmosphere are systematically varied to find the best (in a rms sense) fit to the measured top-of-the-atmosphere spectral reflectance. Examples are provided that show the algorithm's performance in the presence of errors, e.g., error in the contribution from whitecaps and error in radiometric calibration.     

Adaptive semianalytical inversion of ocean color radiometry in optically complex waters

To address the challenges of the parameterization of ocean color inversion algorithms in optically complex waters, we present an adaptive implementation of the linear matrix inversion method (LMI) [J. Geophys. Res.101, 16631 (1996)], which iterates over a limited number of model parameter sets to account for naturally occurring spatial or temporal variability in inherent optical properties (IOPs) and concentration specific IOPs (SIOPs). LMI was applied to a simulated reflectance dataset for spectral bands representing measured water properties of a macrotidal embayment characterized by a large variability in the shape and amplitude factors controlling the IOP spectra. We compare the inversion results for the single-model parameter implementation to the adaptive parameterization of LMI for the retrieval of bulk IOPs, the IOPs apportioned to the optically active constituents, and the concentrations of the optically active constituents. We found that ocean color inversion with LMI is significantly sensitive to the a priori selection of the empirical parameters g0 and g1 of the equations relating the above-surface remote-sensing reflectance to the IOPs in the water column [J. Geophys. Res.93, 10909 (1988)]. When assuming the values proposed for open-ocean applications for g0 and g1 [J. Geophys. Res.93, 10909 (1988)], the accuracy of the retrieved IOPs, and concentrations was substantially lower than that retrieved with the parameterization developed for coastal waters [Appl. Opt.38, 3831 (1999)] because the optically complex waters analyzed in this study were dominated by particulate and dissolved matter. The adaptive parameterization of LMI yielded consistently more accurate inversion results than the single fixed SIOP model parameterizations of LMI. The adaptive implementation of LMI led to an improvement in the accuracy of apportioned IOPs and concentrations, particularly for the phytoplankton-related quantities. The adaptive parameterization encompassing wider IOP ranges were more accurate for the retrieval of bulk IOPs, apportioned IOPs, and concentration of optically active constituents.     

Factor analysis of multispectral radiances over coastal and open ocean water based on radiative transfer calculations

Factor analysis is applied to multispectral (seventeen wavelengths) radiances simulated by a radiative transfer model (matrix-operator method) in and above coastal and open ocean waters. The calculated radiances were compared with measured radiances before applying factor analysis. They agree well for different sun elevations and even for turbid coastal waters. The factor analysis technique allows us to extract the characteristic signatures of phytoplankton, suspended matter, and yellow substance. The fluorescence of chlorophyll at lambda = 685 nm is found to be a clear signal for phytoplankton, also in the presence of other suspensions and yellow substance. A comparison of different algorithms for the extraction of the fluorescence peak favors the addition of chlorophyll absorption at lambda = 670 nm. The blue-green ratio is found to be useless for chlorophyll detection in coastal waters. Suspended matter and yellow substance can also clearly be seen in the factor loading for all multispectral radiances analyzed. However, suspended matter is reflected more strongly than yellow substance.     

Atmospheric correction over case 2 waters with an iterative fitting algorithm: relative humidity effects

In algorithms for the atmospheric correction of visible and near-IR satellite observations of the Earth's surface, it is generally assumed that the spectral variation of aerosol optical depth is characterized by an Angstr?m power law or similar dependence. In an iterative fitting algorithm for atmospheric correction of ocean color imagery over case 2 waters, this assumption leads to an inability to retrieve the aerosol type and to the attribution to aerosol spectral variations of spectral effects actually caused by the water contents. An improvement to this algorithm is described in which the spectral variation of optical depth is calculated as a function of aerosol type and relative humidity, and an attempt is made to retrieve the relative humidity in addition to aerosol type. The aerosol is treated as a mixture of aerosol components (e.g., soot), rather than of aerosol types (e.g., urban). We demonstrate the improvement over the previous method by using simulated case 1 and case 2 sea-viewing wide field-of-view sensor data, although the retrieval of relative humidity was not successful.     

Remote sensing of the ocean contributions from ultraviolet to near-infrared using the shortwave infrared bands: simulations

In the remote sensing of the ocean near-surface properties, it is essential to derive accurate water-leaving radiance spectra through the process of the atmospheric correction. The atmospheric correction algorithm for Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) uses two near-infrared (NIR) bands at 765 and 865 nm (748 and 869 nm for MODIS) for retrieval of aerosol properties with assumption of the black ocean at the NIR wavelengths. Modifications are implemented to account for some of the NIR ocean contributions for the productive but not very turbid waters. For turbid waters in the coastal regions, however, the ocean could have significant contributions in the NIR, leading to significant errors in the satellite-derived ocean water-leaving radiances. For the shortwave infrared (SWIR) wavelengths (approximately > 1000 nm), water has significantly larger absorption than those for the NIR bands. Thus the black ocean assumption at the SWIR bands is generally valid for turbid waters. In addition, for future sensors, it is also useful to include the UV bands to better quantify the ocean organic and inorganic materials, as well as for help in atmospheric correction. Simulations are carried out to evaluate the performance of atmospheric correction for nonabsorbing and weakly absorbing aerosols using the NIR bands and various combinations of the SWIR bands for deriving the water-leaving radiances at the UV (340 nm) and visible wavelengths. Simulations show that atmospheric correction using the SWIR bands can generally produce results comparable to atmospheric correction using the NIR bands. In particular, the water-leaving radiance at the UV band (340 nm) can also be derived accurately. The results from a sensitivity study for the required sensor noise equivalent reflectance, (NE Delta rho), [or the signal-to-noise ratio (SNR)] for the NIR and SWIR bands are provided and discussed.     

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.     

An inherent-optical-property-centered approach to correct the angular effects in water-leaving radiance

Remote-sensing reflectance (R(rs)), which is defined as the ratio of water-leaving radiance (L(w)) to downwelling irradiance just above the surface (E(d)(0?)), varies with both water constituents (including bottom properties of optically-shallow waters) and angular geometry. L(w) is commonly measured in the field or by satellite sensors at convenient angles, while E(d)(0?) can be measured in the field or estimated based on atmospheric properties. To isolate the variations of R(rs) (or L(w)) resulting from a change of water constituents, the angular effects of R(rs) (or L(w)) need to be removed. This is also a necessity for the calibration and validation of satellite ocean color measurements. To reach this objective, for optically-deep waters where bottom contribution is negligible, we present a system centered on water's inherent optical properties (IOPs). It can be used to derive IOPs from angular R_rs and offers an alternative to the system centered on the concentration of chlorophyll. This system is applicable to oceanic and coastal waters as well as to multiband and hyperspectral sensors. This IOP-centered system is applied to both numerically simulated data and in situ measurements to test and evaluate its performance. The good results obtained suggest that the system can be applied to angular R(rs) to retrieve IOPs and to remove the angular variation of R(rs).     

Atmospheric correction of satellite ocean color imagery: the black pixel assumption

The assumption that values of water-leaving radiance in the near-infrared (NIR) are negligible enable aerosol radiative properties to be easily determined in the correction of satellite ocean color imagery. This is referred to as the black pixel assumption. We examine the implications of the black pixel assumption using a simple bio-optical model for the NIR water-leaving reflectance [rho(w)(lambda(NIR))](N). In productive waters [chlorophyll (Chl) concentration >2 mg m(-3)], estimates of [rho(w)(lambda(NIR))](N) are several orders of magnitude larger than those expected for pure seawater. These large values of [rho(w)(lambda(NIR))](N) result in an overcorrection of atmospheric effects for retrievals of water-leaving reflectance that are most pronounced in the violet and blue spectral region. The overcorrection increases dramatically with Chl, reducing the true water-leaving radiance by roughly 75% when Chl is equal to 5 mg m(-3). Relaxing the black pixel assumption in the correction of Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) satellite ocean color imagery provides significant improvements in Chl and water-leaving reflectance retrievals when Chl values are greater than 2 mg m(-3). Improvements in the present modeling of [rho(w)(lambda(NIR))](N) are considered, particularly for turbid coastal waters. However, this research shows that the effects of nonzero NIR reflectance must be included in the correction of satellite ocean color imagery.     

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.     

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.     

Sensor-independent approach to the vicarious calibration of satellite ocean color radiometry

The retrieval of ocean color radiometry from space-based sensors requires on-orbit vicarious calibration to achieve the level of accuracy desired for quantitative oceanographic applications. The approach developed by the NASA Ocean Biology Processing Group (OBPG) adjusts the integrated instrument and atmospheric correction system to retrieve normalized water-leaving radiances that are in agreement with ground truth measurements. The method is independent of the satellite sensor or the source of the ground truth data, but it is specific to the atmospheric correction algorithm. The OBPG vicarious calibration approach is described in detail, and results are presented for the operational calibration of SeaWiFS using data from the Marine Optical Buoy (MOBY) and observations of clear-water sites in the South Pacific and southern Indian Ocean. It is shown that the vicarious calibration allows SeaWiFS to reproduce the MOBY radiances and achieve good agreement with radiometric and chlorophyll a measurements from independent in situ sources. We also find that the derived vicarious gains show no significant temporal or geometric dependencies, and that the mission-average calibration reaches stability after approximately 20-40 high-quality calibration samples. Finally, we demonstrate that the performance of the vicariously calibrated retrieval system is relatively insensitive to the assumptions inherent in our approach.     

Atmospheric correction of ocean color imagery: use of the junge power-law aerosol size distribution with variable refractive index to handle aerosol absorption

When strongly absorbing aerosols are present in the atmosphere, the usual two-step procedure of processing ocean color data-(1) atmospheric correction to provide the water-leaving reflectance (rho(w)), followed by (2) relating rho(w) to the water constituents-fails and simultaneous estimation of the ocean and aerosol optical properties is necessary. We explore the efficacy of using a simple model of the aerosol-a Junge power-law size distribution consisting of homogeneous spheres with arbitrary refractive index-in a nonlinear optimization procedure for estimating the relevant oceanic and atmospheric parameters for case 1 waters. Using simulated test data generated from more realistic aerosol size distributions (sums of log-normally distributed components with different compositions), we show that the ocean's pigment concentration (C) can be retrieved with good accuracy in the presence of weakly or strongly absorbing aerosols. However, because of significant differences in the scattering phase functions for the test and power-law distributions, large error is possible in the estimate of the aerosol optical thickness. The positive result for C suggests that the detailed shape of the aerosol-scattering phase function is not relevant to the atmospheric correction of ocean color sensors. The relevant parameters are the aerosol single-scattering albedo and the spectral variation of the aerosol optical depth. We argue that the assumption of aerosol sphericity should not restrict the validity of the algorithm and suggest an avenue for including colored aerosols, e.g., wind-blown dust, in the procedure. A significant advantage of the new approach is that realistic multicomponent aerosol models are not required for the retrieval of C.     

Contribution of water-leaving radiances to multiangle, multispectral polarimetric observations over the open ocean: bio-optical model results for case 1 waters

Multiangle, multispectral photopolarimetry of atmosphere-ocean systems provides the fullest set of remote sensing information possible on the scattering properties of aerosols and on the color of the ocean. Recent studies have shown that inverting such data allows for the potential of separating the retrieval of aerosol properties from ocean color monitoring in the visible part of the spectrum. However, the data in these studies were limited to those principal plane observations where the polarization of water-leaving radiances could be ignored. Examining similar potentials for off-principal plane observations requires the ability to assess realistic variations in both the reflectance for and bidirectionality of polarized water-leaving radiances for such viewing geometries. We provide hydrosol models for use in underwater light scattering computations to study such variations. The model consists of two components whose refractive indices resemble those of detritus-minerallike and planktonlike particles, whose size distributions are constrained by underwater light linear polarization signatures, and whose mixing ratios change as a function of particulate backscattering efficiency. Multiple scattering computations show that these models are capable of reproducing realistic underwater light albedos for wavelengths ranging from 400 to 600 nm, and for chlorophyll a concentrations ranging from 0.03 to 3.0 mg/m(3). Numerical results for spaceborne observations of the reflectance for total and polarized water-leaving radiances are provided as a function of polar angles, and the change in these reflectances with wavelength, chlorophyll a concentration, and hydrosol model are discussed in detail for case 1 (open ocean) waters.     

Evaluation of a reflectance model used in the SeaWiFS ocean color algorithm: implications for chlorophyll concentration retrievals

For the atmospheric correction of ocean-color imagery obtained over Case I waters with the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) instrument the method currently used to relax the black-pixel assumption in the near infrared (NIR) relies on (1) an approximate model for the nadir NIR remote-sensing reflectance and (2) an assumption that the water-leaving radiance is isotropic over the upward hemisphere. Radiance simulations based on a comprehensive radiative-transfer model for the coupled atmosphere-ocean system and measurements of the nadir remote-sensing reflectance at 670 nm compiled in the SeaWiFS Bio-optical Algorithm Mini-Workshop (SeaBAM) database are used to assess the validity of this method. The results show that (1) it is important to improve the flexibility of the reflectance model to provide more realistic predictions of the nadir NIR water-leaving reflectance for different ocean regions and (2) the isotropic assumption should be avoided in the retrieval of ocean color, if the chlorophyll concentration is larger than approximately 6, 10, and 40 mg m(-3) when the aerosol optical depth is approximately 0.05, 0.1, and 0.3, respectively. Finally, we extend our scope to Case II ocean waters to gain insight and enhance our understanding of the NIR aspects of ocean color. The results show that the isotropic assumption is invalid in a wider range than in Case I waters owing to the enhanced water-leaving reflectance resulting from oceanic sediments in the NIR wavelengths.     

Field observations of the relation between satellite and sea radiances in coastal waters

Estimates of the different contributions to the satellite radiance above the outer Oslofjord are presented. The contribution from the sea is of the order of 10% of the total signal, and the part due to reflection from the sea surface constitutes 10-20%. The presence of land may increase the satellite radiance up to 4-9%, but such effects, which are probably reduced to 1/e at a distance of 1 km from the coast, cannot be detected in the present measurements. In situ observations of the marine radiance are corrected for shadings by ship and instrument and for varying solar altitude. The average correction for the self-shading effect of the marine instrument becomes 30-50% in these waters. The linear relations between satellite and sea radiances are determined with correlation coefficients of better than 0.95. The observed minimum value of the satellite radiance (or darkest pixel) is not a satisfactory approximation for the atmospheric correction. It is concluded that, in coastal waters and at the present stage, satellite observations have to be combined with field measurements to obtain reliable results.     

Improving atmospheric correction for highly productive coastal waters using the short wave infrared retrieval algorithm with water-leaving reflectance constraints at 412 nm

The recently developed short wave infrared (SWIR) atmospheric correction algorithm for ocean color retrieval uses long wavelength channels to retrieve atmospheric parameters to avoid bright pixel contamination. However, this retrieval is highly sensitive to errors in the aerosol model, which is magnified by the higher variability of aerosols observed over urban coastal areas. While adding extra regional aerosol models into the retrieval lookup tables would tend to increase retrieval error since these models are hard to distinguish in the IR, we explore the possibility that for highly productive waters with high colored dissolved organic matter, an estimate of the 412 nm channel water-leaving reflectance can be used to constrain the aerosol model retrieval and improve the water-leaving reflectance retrieval. Simulations show that this constraint is particularly useful where aerosol diversity is significant. To assess this algorithm we compare our retrievals with the operational SeaWiFS Data Analysis System (SeaDAS) SWIR and near infrared retrievals using in situ validation data in the Chesapeake Bay and show that, especially for absorbing aerosols, significant improvement is obtained. Further insight is also obtained by the intercomparison of retrieved remote sensing reflectance images at 443 and 551 nm, which demonstrates the removal of anomalous artifacts in the operational SeaDAS retrieval.