Advection of Karenia brevis blooms from the Florida Panhandle towards Mississippi coastal waters.

Harmful Algal Blooms (HABs) of Karenia brevis have been documented along coastal waters of every state bordering the Gulf of Mexico (GoM). Some Gulf Coast locations, such as Florida and Texas, suffer from recurrent intense and spatially large blooms, while others such as Mississippi seem to rarely observe them. The main objective of this work is to understand the dynamics that led to the K. brevis bloom in Mississippi coastal waters in fall 2015. Blooms of K. brevis from the Florida Panhandle region are often advected westward towards the Mississippi-Alabama coast; however there is interannual variability in their presence and intensity in Mississippi coastal waters. The 2015 K. brevis bloom was compared to the 2007 Florida Panhandle K. brevis bloom, which showed a westward advection pattern, but did not intensify along the Mississippi coast. Cell counts and flow cytometry were obtained from the Mississippi Department of Marine Resources, Alabama Department of Public Health, Florida Fish and Wildlife Conservation Commission and The University of Southern Mississippi. Ocean color satellite imagery from the Moderate Resolution Imaging Spectroradiometer onboard the Aqua satellite was used to detect and delineate the blooms in 2007 and 2015. Two different regional applications of NCOM-Navy Coastal Ocean Model (1-km resolution NCOM-GoM/Gulf of Mexico and 6-km resolution NCOM-IASNFS/Intra Americas Sea Nowcast Forecast System) were used to understand the circulation and transport pathways. A Lagrangian particle tracking software was used to track the passive movement of particles released at different locations for both bloom events. Ancillary data (e.g., nutrients, wind, salinity, river discharge) from local buoys, monitoring stations and coincident oceanographic cruises were also included in the analysis. The blooms of K. brevis reached the Mississippi coast both years; however, the bloom in 2007 lasted only a few days and there is no evidence that it entered the Mississippi Sound. Two major differences were observed between both years. First, circulation patterns in 2015 resulting from an intense westward-northwestward that persisted until December allowed for continuous advection, whereas this pattern was not evident in 2007. Second, local river discharge was elevated throughout late fall 2015 while 2007 was below the average. Thus, elevated discharge may have provided sufficient nutrients for bloom intensification. These results illustrate the complex, but important interactions in coastal zones. Further, they emphasize the importance in establishing comprehensive HAB monitoring programs, which facilitate our understanding of nutrient and phytoplankton dynamics, and stress the importance for multi-agency cooperation across state boundaries.

Determining the optimal spectral sampling frequency and uncertainty thresholds for hyperspectral remote sensing of ocean color.

Using a modified geostatistical technique, empirical variograms were constructed from the first derivative of several diverse Remote Sensing Reflectance and Phytoplankton Absorbance spectra to describe how data points are correlated with "distance" across the spectra. The maximum rate of information gain is measured as a function of the kurtosis associated with the Gaussian structure of the output, and is determined for discrete segments of spectra obtained from a variety of water types (turbid river filaments, coastal waters, shelf waters, a dense Microcystis bloom, and oligotrophic waters), as well as individual and mixed phytoplankton functional types (PFTs; diatoms, eustigmatophytes, cyanobacteria, coccolithophores). Results show that a continuous spectrum of 5 to 7 nm spectral resolution is optimal to resolve the variability across mixed reflectance and absorbance spectra. In addition, the impact of uncertainty on subsequent derivative analysis is assessed, showing that a 3% Gaussian noise (SNR ~66) addition compromises data quality without smoothing the spectrum, and a 13% noise (SNR ~15) addition compromises data with smoothing.

Radiometric calibration of ocean color satellite sensors using AERONET-OC data.

Radiometric vicarious calibration of ocean color (OC) satellite sensors is carried out through the full sunlight path radiative transfer (RT) simulations of the coupled ocean-atmosphere system based on the aerosol and water-leaving radiance data from AERONET-OC sites for the visible and near-infrared (NIR) bands. Quantitative evaluation of the potential of such approach for achieving the radiometric accuracies of OC satellite sensors is made by means of direct comparisons between simulated and satellite measured top of atmosphere (TOA) radiances. Very high correlations (R ≥ 0.96 for all visible channels) are achieved for the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor when this approach is applied with the data from the LISCO and WaveCIS AERONET-OC sites. Vicarious calibration gain factors derived with this approach are highly consistent, with comparisons between the two sites exhibiting around 0.5% discrepancy in the blue and green parts of the spectrum, while their average temporal variability is also within 0.28% - 1.23% permitting the approach to be used, at this stage, for verification of sensor calibration performance.

Polarization impacts on the water-leaving radiance retrieval from above-water radiometric measurements.

Above-water measurements of water-leaving radiance are widely used for water-quality monitoring and ocean-color satellite data validation. Reflected skylight in above-water radiometry needs to be accurately estimated prior to derivation of water-leaving radiance. Up-to-date methods to estimate reflection of diffuse skylight on rough sea surfaces are based on radiative transfer simulations and sky radiance measurements. But these methods neglect the polarization state of the incident skylight, which is generally highly polarized. In this paper, the effects of polarization on the sea surface reflectance and the subsequent water-leaving radiance estimation are investigated. We show that knowledge of the polarization field of the diffuse skylight significantly improves above-water radiometry estimates, in particular in the blue part of the spectrum where the reflected skylight is dominant. A newly developed algorithm based on radiative transfer simulations including polarization is described. Its application to the standard Aerosol Robotic Network-Ocean Color and hyperspectral radiometric measurements of the 1.5-year dataset acquired at the Long Island Sound site demonstrates the noticeable importance of considering polarization for water-leaving radiance estimation. In particular it is shown, based on time series of collocated data acquired in coastal waters, that the azimuth range of measurements leading to good-quality data is significantly increased, and that these estimates are improved by more than 12% at 413 nm. Full consideration of polarization effects is expected to significantly improve the quality of the field data utilized for satellite data validation or potential vicarious calibration purposes.

Impact of sub-pixel variations on ocean color remote sensing products.

Passive remote sensing of the Earth system has used spatial resolutions ranging from meters to kilometers. It is thus necessary to understand how data products with different spatial resolutions can be compared with each other, and how sub-pixel variations may affect data comparison. This is particularly important for ocean color remote sensing where the measured signal (water-leaving radiance or remote sensing reflectance) is a non-linear function of sub-surface constituents. As a result, products at low resolution are not necessarily arithmetic or geometric means of those at higher resolution. Here, we developed analytical expressions to link ocean color properties derived from high- and low-resolution data, and the proof-of-concept is further demonstrated with both simple examples and measurements of MERIS full-resolution (FR) and reduced resolution (RR). These results suggest that current global chlorophyll concentration is likely underestimated due to the coarse spatial resolutions. Application of the expressions will facilitate cross-sensor comparisons and may also reduce uncertainties.

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.

Long Island Sound Coastal Observatory: assessment of above-water radiometric measurement uncertainties using collocated multi and hyperspectral systems.

The Long Island Sound Coastal Observational platform (LISCO) near Northport, New York, has been recently established to support validation of ocean color radiometry (OCR) satellite data. LISCO is equipped with collocated multispectral, SeaPRISM, and hyperspectral, HyperSAS, above-water systems for OCR measurements. This combination offers the potential for improving validation activities of current and future OCR satellite missions, as well as for satellite intercomparisons and spectral characterization of coastal waters. Results of measurements made by both the multi and hyperspectral instruments, in operation since October 2009, are presented, evaluated and their associated uncertainties quantified based on observations for a period of over a year. Multi- and hyperspectral data processing as well as the data quality analysis are described and their uncertainties evaluated. The quantified intrinsic uncertainties of HyperSAS data exhibit satisfactory values, less than 5% over a large spectral range, from 340 to 740 nm, and over a large range of diurnal daylight conditions, depending on the maximum sun elevation at the solar noon. Intercomparisons between HyperSAS and SeaPRISM data revealed that an overcorrection of the sun glint effect in the current SeaPRISM processing induces errors, which are amplified through the whole data processing, especially at the shorter wavelengths. The spectral-averaged uncertainties can be decomposed as follows: (i) sun glint removal generates 2% uncertainty, (ii) sky glint removal generates strong uncertainties of the order of 15% mainly induced by sun glint overcorrection, (iii) viewing angle dependence corrections improve the data intercomparison by reducing the dispersion by 2%, (iv) normalization of atmospheric effects generates approximately 4% uncertainty. Based on this study, improvements of the sun glint correction are expected to significantly reduce the uncertainty associated with the data processing down to the level of 1%. On the other hand, strong correlations between both datasets (R(2)>0.96) demonstrate the efficacy of the above-water retrieval concept and confirm that the collocated instrumentation constitutes an important aid to above-water data quality analysis, which makes LISCO a key element of the AERONET-OC network.

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 Rrs 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).

Relationships between water attenuation coefficients derived from active and passive remote sensing: a case study from two coastal environments.

Relationships between the satellite-derived diffuse attenuation coefficient of downwelling irradiance (K(d)) and airborne-based vertical attenuation of lidar volume backscattering (α) were examined in two coastal environments. At 1.1 km resolution and a wavelength of 532 nm, we found a greater connection between α and K(d) when α was computed below 2 m depth (Spearman rank correlation coefficient up to 0.96), and a larger contribution of K(d) to α with respect to the beam attenuation coefficient as estimated from lidar measurements and K(d) models. Our results suggest that concurrent passive and active optical measurements can be used to estimate total scattering coefficient and backscattering efficiency in waters without optical vertical structure.

Removal of surface-reflected light for the measurement of remote-sensing reflectance from an above-surface platform.

Using hyperspectral measurements made in the field, we show that the effective sea-surface reflectance ρ (defined as the ratio of the surface-reflected radiance at the specular direction corresponding to the downwelling sky radiance from one direction) varies not only for different measurement scans, but also can differ by a factor of 8 between 400 nm and 800 nm for the same scan. This means that the derived water-leaving radiance (or remote-sensing reflectance) can be highly inaccurate if a spectrally constant ρ value is applied (although errors can be reduced by carefully filtering measured raw data). To remove surface-reflected light in field measurements of remote sensing reflectance, a spectral optimization approach was applied, with results compared with those from remote-sensing models and from direct measurements. The agreement from different determinations suggests that reasonable results for remote sensing reflectance of clear blue water to turbid brown water are obtainable from above-surface measurements, even under conditions of high waves.

Uncertainties of optical parameters and their propagations in an analytical ocean color inversion algorithm.

Following the theory of error propagation, we developed analytical functions to illustrate and evaluate the uncertainties of inherent optical properties (IOPs) derived by the quasi-analytical algorithm (QAA). In particular, we evaluated the effects of uncertainties of these optical parameters on the inverted IOPs: the absorption coefficient at the reference wavelength, the extrapolation of particle backscattering coefficient, and the spectral ratios of absorption coefficients of phytoplankton and detritus/gelbstoff, respectively. With a systematically simulated data set (46,200 points), we found that the relative uncertainty of QAA-derived total absorption coefficients in the blue-green wavelengths is generally within +/-10% for oceanic waters. The results of this study not only establish theoretical bases to evaluate and understand the effects of the various variables on IOPs derived from remote-sensing reflectance, but also lay the groundwork to analytically estimate uncertainties of these IOPs for each pixel. These are required and important steps for the generation of quality maps of IOP products derived from satellite ocean color remote sensing.

Polarized light in coastal waters: hyperspectral and multiangular analysis.

Measurements of the underwater polarized light field were performed at different stations, atmospheric conditions and water compositions using a newly developed hyperspectral and multiangular polarimeter during a recent cruise in the coastal areas of New York Harbor - Sandy Hook, NJ region (USA). Results are presented for waters with chlorophyll concentrations 1.3-4.8 microg/l and minerals concentrations 2.0- 3.9 mg/l. Angular and spectral variations of the degree of polarization are found to be consistent with theory. Maximum values of the degree of polarization do not exceed 0.4 and the position of the maximum is close to 100 masculine scattering angle. Normalized radiances and degrees of polarization are compared with simulated ones obtained with a Monte Carlo radiative transfer code for the atmosphere-ocean system and show satisfactory agreement.

Comparison and validation of point spread models for imaging in natural waters.

It is known that scattering by particulates within natural waters is the main cause of the blur in underwater images. Underwater images can be better restored or enhanced with knowledge of the point spread function (PSF) of the water. This will extend the performance range as well as the information retrieval from underwater electro-optical systems, which is critical in many civilian and military applications, including target and especially mine detection, search and rescue, and diver visibility. A better understanding of the physical process involved also helps to predict system performance and simulate it accurately on demand. The presented effort first reviews several PSF models, including the introduction of a semi-analytical PSF given optical properties of the medium, including scattering albedo, mean scattering angles and the optical range. The models under comparison include the empirical model of Duntley, a modified PSF model by Dolin et al, as well as the numerical integration of analytical forms from Wells, as a benchmark of theoretical results. For experimental results, in addition to that of Duntley, we validate the above models with measured point spread functions by applying field measured scattering properties with Monte Carlo simulations. Results from these comparisons suggest it is sufficient but necessary to have the three parameters listed above to model PSFs. The simplified approach introduced also provides adequate accuracy and flexibility for imaging applications, as shown by examples of restored underwater images.

Optical scattering and backscattering by organic and inorganic particulates in U.S. coastal waters.

We present the results of a study of optical scattering and backscattering of particulates for three coastal sites that represent a wide range of optical properties that are found in U.S. near-shore waters. The 6000 scattering and backscattering spectra collected for this study can be well approximated by a power-law function of wavelength. The power-law exponent for particulate scattering changes dramatically from site to site (and within each site) compared with particulate backscattering where all the spectra, except possibly the very clearest waters, cluster around a single wavelength power-law exponent of -0.94. The particulate backscattering-to-scattering ratio (the backscattering ratio) displays a wide range in wavelength dependence. This result is not consistent with scattering models that describe the bulk composition of water as a uniform mix of homogeneous spherical particles with a Junge-like power-law distribution over all particle sizes. Simultaneous particulate organic matter (POM) and particulate inorganic matter (PIM) measurements are available for some of our optical measurements, and site-averaged POM and PIM mass-specific cross sections for scattering and backscattering can be derived. Cross sections for organic and inorganic material differ at each site, and the relative contribution of organic and inorganic material to scattering and backscattering depends differently at each site on the relative amount of material that is present.

Determination of Primary Spectral Bands for Remote Sensing of Aquatic Environments.

About 30 years ago, NASA launched the first ocean-color observing satellite:the Coastal Zone Color Scanner. CZCS had 5 bands in the visible-infrared domain with anobjective to detect changes of phytoplankton (measured by concentration of chlorophyll) inthe oceans. Twenty years later, for the same objective but with advanced technology, theSea-viewing Wide Field-of-view Sensor (SeaWiFS, 7 bands), the Moderate-ResolutionImaging Spectrometer (MODIS, 8 bands), and the Medium Resolution ImagingSpectrometer (MERIS, 12 bands) were launched. The selection of the number of bands andtheir positions was based on experimental and theoretical results achieved before thedesign of these satellite sensors. Recently, Lee and Carder (2002) demonstrated that foradequate derivation of major properties (phytoplankton biomass, colored dissolved organicmatter, suspended sediments, and bottom properties) in both oceanic and coastalenvironments from observation of water color, it is better for a sensor to have ~15 bands inthe 400 - 800 nm range. In that study, however, it did not provide detailed analysesregarding the spectral locations of the 15 bands. Here, from nearly 400 hyperspectral (~ 3-nm resolution) measurements of remote-sensing reflectance (a measure of water color)taken in both coastal and oceanic waters covering both optically deep and optically shallowwaters, first- and second-order derivatives were calculated after interpolating themeasurements to 1-nm resolution. From these derivatives, the frequency of zero values foreach wavelength was accounted for, and the distribution spectrum of such frequencies wasobtained. Furthermore, the wavelengths that have the highest appearance of zeros wereidentified. Because these spectral locations indicate extrema (a local maximum orminimum) of the reflectance spectrum or inflections of the spectral curvature, placing the bands of a sensor at these wavelengths maximizes the potential of capturing (and then restoring) the spectral curve, and thus maximizes the potential of accurately deriving properties of the water column and/or bottom of various aquatic environments with a multi-band sensor.

Uniqueness in remote sensing of the inherent optical properties of ocean water.

We examine the problem of uniqueness in the relationship between the remote-sensing reflectance (Rrs) and the inherent optical properties (IOPs) of ocean water. The results point to the fact that diffuse reflectance of plane irradiance from ocean water is inherently ambiguous. Furthermore, in the 400 < lambda < 750 nm region of the spectrum, Rrs(lambda) also suffers from ambiguity caused by the similarity in wavelength dependence of the coefficients of absorption by particulate matter and of absorption by colored dissolved organic matter. The absorption coefficients have overlapping exponential responses, which lead to the fact that more than one combination of IOPs can produce nearly the same Rrs spectrum. This ambiguity in absorption parameters demands that we identify the regions of the Rrs spectrum where we can isolate the effects that are due only to scattering by particulates and to absorption by pure water. The results indicate that the spectral shape of the absorption coefficient of phytoplankton, a(ph)(lambda), cannot be derived from a multiparameter fit to Rrs(lambda). However, the magnitude and the spectral dependence of the absorption coefficient can be estimated from the difference between the measured Rrs(lambda) and the best fit to Rrs(lambda) in terms of IOPs that exclude a(ph)(lambda).

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.