Generalized ocean color inversion model for retrieving marine inherent optical properties

Spectral attenuation and backscattering as indicators of average particle size

Measurements of the particulate beam attenuation coefficient at multiple wavelengths in the ocean typically exhibit a power law dependence on wavelength, and the slope of that power law has been related to the slope of the particle size distribution (PSD), when assumed to be a power law function of particle size. Recently, spectral backscattering coefficient measurements have been made using sensors deployed at moored observatories, on autonomous underwater vehicles, and even retrieved from space-based measurements of remote sensing reflectance. It has been suggested that these backscattering measurements may also be used to obtain information about the shape of the PSD. In this work, we directly compared field-measured PSD with multispectral beam attenuation and backscattering coefficients in a coastal bottom boundary later. The results of this comparison demonstrated that (1) the beam attenuation spectral slope correlates with the average particle size as suggested by theory for idealized particles and PSD; and (2) measurements of spectral backscattering also contain information reflective of the average particle size in spite of large deviations of the PSD from a spectral power law shape.

Inversion of spectral absorption coefficients to infer phytoplankton size classes, chlorophyll concentration, and detrital matter

Measured spectral absorption coefficients were inverted to infer phytoplankton concentration in three size classes (picoplankton, nanoplankton, and microplankton), chlorophyll concentration [Chl], and both magnitude and spectral shape of absorption by colored detrital matter (CDM). Our algorithm allowed us to solve for the nonlinear factor of CDM absorption slope separately from the other linear factors, thus fully utilizing the additive characteristic inherent in absorption coefficients. We validated the inversion with three datasets: two spatially distributed global datasets, the Laboratoire d'Océanographie de Villefranche dataset and the NASA bio-Optical Marine Algorithm Dataset, and a time series coastal dataset, the Martha's Vineyard Coastal Observatory dataset. Comparison with high performance liquid chromatography analyses showed that the phytoplankton size classes can be retrieved with correlation coefficients (r)>0.7, root mean square errors of 0.2, and median relative errors of 20% in oceanic waters and with similar performance in coastal waters. Much improved agreement was found for the entire phytoplankton population, with r>0.90 for [Chl] and absorption coefficients (a_ph) for all three datasets. The inferred a_CDM(400) and CDM spectral slope agree within ±4% of measurements in both oceanic and coastal waters. The results indicate that the chlorophyll-a specific absorption spectra used as an inversion kernel represent well the global mean states for each of the three phytoplankton size classes. The method can be applied to either bulk or particulate absorption data and is spectrally flexible.

Band shifting for ocean color multi-spectral reflectance data

An approach to perform band shifting applied to multi-spectral ocean remote sensing reflectance RRS values in the visible spectral range is presented. The band-shifting scheme aims at expressing RRS at a wavelength not originally part of the spectrum from data at neighboring bands. The scheme relies on the determination of inherent optical properties (IOPs) by a bio-optical model, the calculation of the IOPs at the target wavelength using the spectral shapes assumed for each IOP, and the operation of the bio-optical model in forward mode to express RRS at the target wavelength. The performance of the band-shifting scheme applied to bands typical of satellite missions is assessed with hyper-spectral data sets obtained from radiative transfer simulations or from field measurements. The relative error ε on the conversion factors from 488 to 490 nm is mostly within 1%. Analogous results are obtained for conversions in the red spectral domain (665, 667 and 670 nm) only for synthetic data sets. The range of ε for conversions between green bands (547, 555 and 560 nm) is within 2% to 5% depending on the data set considered. Similar results are obtained when RRS values are computed at 510 nm from data at 488 and 531 nm. In the case of the assessment with simulated data, all band-shifting operations are characterized by an ε range within 2% for all conversions when the concentration of chlorophyll-a is lower than 1 mg m(-3). Applied to satellite data, the band-shifting scheme noticeably improves the agreement between RRS data from different missions.

On the non-closure of particle backscattering coefficient in oligotrophic oceans

Many studies have consistently found that the particle backscattering coefficient (bbp) in oligotrophic oceans estimated from remote-sensing reflectance (Rrs) using semi-analytical algorithms is higher than that from in situ measurements. This overestimation can be as high as ~300% for some oligotrophic ocean regions. Various sources potentially responsible for this discrepancy are examined. Further, after applying an empirical algorithm to correct the impact from Raman scattering, it is found that bbp from analytical inversion of Rrs is in good agreement with that from in situ measurements, and that a closure is achieved.

Discrimination of phytoplankton functional groups using an ocean reflectance inversion model

Ocean reflectance inversion models (ORMs) provide a mechanism for inverting the color of the water observed by a satellite into marine inherent optical properties (IOPs), which can then be used to study phytoplankton community structure. Most ORMs effectively separate the total signal of the collective phytoplankton community from other water column constituents; however, few have been shown to effectively identify individual contributions by multiple phytoplankton groups over a large range of environmental conditions. We evaluated the ability of an ORM to discriminate between Noctiluca miliaris and diatoms under conditions typical of the northern Arabian Sea. We: (1) synthesized profiles of IOPs that represent bio-optical conditions for the Arabian Sea; (2) generated remote-sensing reflectances from these profiles using Hydrolight; and (3) applied the ORM to the synthesized reflectances to estimate the relative concentrations of diatoms and N. miliaris. By comparing the estimates from the inversion model with those from synthesized vertical profiles, we identified those conditions under which the ORM performs both well and poorly. Even under perfectly controlled conditions, the absolute accuracy of ORM retrievals degraded when further deconstructing the derived total phytoplankton signal into subcomponents. Although the absolute magnitudes maintained biases, the ORM successfully detected whether or not Noctiluca miliaris appeared in the simulated water column. This quantitatively calls for caution when interpreting the absolute magnitudes of the retrievals, but qualitatively suggests that the ORM provides a robust mechanism for identifying the presence or absence of species.

Retrieving marine inherent optical properties from satellites using temperature and salinity-dependent backscattering by seawater

Time-series of marine inherent optical properties (IOPs) from ocean color satellite instruments provide valuable data records for studying long-term time changes in ocean ecosystems. Semi-analytical algorithms (SAAs) provide a common method for estimating IOPs from radiometric measurements of the marine light field. Most SAAs assign constant spectral values for seawater absorption and backscattering, assume spectral shape functions of the remaining constituent absorption and scattering components (e.g., phytoplankton, non-algal particles, and colored dissolved organic matter), and retrieve the magnitudes of each remaining constituent required to match the spectral distribution of measured radiances. Here, we explore the use of temperature- and salinity-dependent values for seawater backscattering in lieu of the constant spectrum currently employed by most SAAs. Our results suggest that use of temperature- and salinity-dependent seawater spectra elevate the SAA-derived particle backscattering, reduce the non-algal particles plus colored dissolved organic matter absorption, and leave the derived absorption by phytoplankton unchanged.