Shipborne ocean color remote sensing

In this paper, modernized shipborne procedures are presented to collect and process above-water radiometry for remote sensing applications. A setup of five radiometers and a bidirectional camera system, which provides panoramic sea surface and sky images, is proposed for the collection of high-resolution radiometric quantities. Images from the camera system can be used to determine sky state and potential glint, whitecaps, or foam contamination. A peak in the observed remote sensing reflectance RRS spectra between 750-780 nm was typically found in spectra with relatively high surface reflected glint (SRG), which suggests this waveband could be a useful SRG indicator. Simplified steps for computing uncertainties in SRG corrected RRS are proposed and discussed. The potential of utilizing "unweighted multimodel averaging," which is the average of four or more common SRG correction models, is examined to determine the best approximation RRS. This best approximation RRS provides an estimate of RRS based on various SRG correction models established using radiative transfer simulations and field investigations. Applying the average RRS provides a measure of the inherent uncertainties or biases that result from a user subjectively choosing any one SRG correction model. Comparisons between inherent and apparent optical property derived observations were used to assess the robustness of the SRG multimodel averaging ap- proach. Correlations among the standard SRG models were completed to determine the degree of association or similarities between the SRG models. Results suggest that the choice of glint models strongly affects derived RRS values and can also influence the blue to green band ratios used for modeling biogeochemical parameters such as for chlorophyll a. The objective here is to present a uniform and traceable methodology for determining ship- borne RRS measurements and its associated errors due to glint correction and to ensure the direct comparability of these measurements in future investigations. We encourage the ocean color community to publish radiometric field measurements with matching and complete metadata in open access repositories.

Particle camera and settling chamber measurements at site PC (GeoB11834-3) and SC (GeoB12914-4) off Cape Blanc/Mauritania

Particles sinking out of the euphotic zone are important vehicles of carbon export from the surface ocean. Most of the particles produce heavier aggregates by coagulating with each other before they sink. We implemented an aggregation model into the biogeochemical model of Regional Oceanic Modelling System (ROMS) to simulate the distribution of particles in the water column and their downward transport in the Northwest African upwelling region. Accompanying settling chamber, sediment trap and particle camera measurements provide data for model validation. In situ aggregate settling velocities measured by the settling chamber were around 55 m d**-1. Aggregate sizes recorded by the particle camera hardly exceeded 1 mm. The model is based on a continuous size spectrum of aggregates, characterised by the prognostic aggregate mass and aggregate number concentration. Phytoplankton and detritus make up the aggregation pool, which has an averaged, prognostic and size dependent sinking. Model experiments were performed with dense and porous approximations of aggregates with varying maximum aggregate size and stickiness as well as with the inclusion of a disaggregation term. Similar surface productivity in all experiments has been generated in order to find the best combination of parameters that produce measured deep water fluxes. Although the experiments failed to represent surface particle number spectra, in the deep water some of them gave very similar slope and spectrum range as the particle camera observations. Particle fluxes at the mesotrophic sediment trap site off Cape Blanc (CB) have been successfully reproduced by the porous experiment with disaggregation term when particle remineralisation rate was 0.2 d**-1. The aggregation-disaggregation model improves the prediction capability of the original biogeochemical model significantly by giving much better estimates of fluxes for both upper and lower trap. The results also point to the need for more studies to enhance our knowledge on particle decay and its variation and to the role that stickiness play in the distribution of vertical fluxes.