Abstract. We have examined several approaches for estimating the surface concentration of particulate organic carbon, POC, from optical measurements of spectral remotesensing reflectance, R rs (λ), using field data collected in tropical and subtropical waters of the eastern South Pacific and eastern Atlantic Oceans. These approaches include a direct empirical relationship between POC and the blue-to-green band ratio of reflectance, R rs (λ B )/R rs (555), and two-step algorithms that consist of relationships linking reflectance to an inherent optical property IOP (beam attenuation or backscattering coefficient) and POC to the IOP. We considered two-step empirical algorithms that exclusively include pairs of empirical relationships and two-step hybrid algorithms that consist of semianalytical models and empirical relationships. The surface POC in our data set ranges from about 10 mg m −3 within the South Pacific Subtropical Gyre to 270 mg m −3 in the Chilean upwelling area, and ancillary data suggest a considerable variation in the characteristics of particulate assemblages in the investigated waters. The POC algorithm based on the direct relationship between POC and R rs (λ B )/R rs (555) promises reasonably good performance in the vast areas of the open ocean covering different provincesCorrespondence to: D. Stramski (dstramski@ucsd.edu) from hyperoligotrophic and oligotrophic waters within subtropical gyres to eutrophic coastal upwelling regimes characteristic of eastern ocean boundaries. The best error statistics were found for power function fits to the data of POC vs. R rs (443)/R rs (555) and POC vs. R rs (490)/R rs (555). For our data set that includes over 50 data pairs, these relationships are characterized by the mean normalized bias of about 2% and the normalized root mean square error of about 20%. We recommend that these algorithms be implemented for routine processing of ocean color satellite data to produce maps of surface POC with the status of an evaluation data product for continued work on algorithm development and refinements. The two-step algorithms also deserve further attention because they can utilize various models for estimating IOPs from reflectance, offer advantages for developing an understanding of bio-optical variability underlying the algorithms, and provide flexibility for regional or seasonal parameterizations of the algorithms.

[1] Digital photographs of the sea surface were analyzed for the fraction of aerial coverage by whitecaps (stage A and B) in the north polar region of the Atlantic. Photography was accompanied by measurements of wind velocity, air temperature and humidity, sea surface temperature, and observations of significant wave height. Whitecap coverage increased significantly with an increase in wind speed (or wind friction velocity). Our data exhibit lower values of the average whitecap coverage at low and moderate wind speeds than previous estimates from literature. In addition, our results indicate that the prediction of whitecap coverage can be improved if the state of the development of surface waves is taken into account. Changes in sea surface temperature (2 to 13°C) and near-water air stability showed no discernible effect on whitecap coverage at any given wind speed within our data set.

[1] Up to now, relatively few bio-optical measurements have been made in the high northern latitude waters, which allow sound relationships for ocean color remote sensing to be determined. We collected optical and chlorophyll a concentration, Chl, data in the north polar region of the Atlantic in summer season. The investigated region includes subarctic and arctic waters between 70°N and 80°N within the meridional zone between 1°E and 20°E. Our measurements show that the current NASA global algorithms, OC2, OC4, and chlor-MODIS, generally overpredict Chl in the investigated waters by a factor of about 2 at low pigment concentrations (<0.2 mg m À3 ) and underpredict Chl at higher concentrations (20-50% at 2-3 mg m À3 ). For our data set, the best two-band algorithm for Chl involves the ratio of remote-sensing reflectance, R rs (442)/R rs (555), at 442-nm and 555-nm light wavebands. We found that the general trend of variation in the blue-to-green reflectance ratio, R rs (442)/R rs (555) or R rs (490)/R rs (555), with Chl was driven primarily by Chldependent change in the green-to-blue ratio of absorption by pure seawater and particles. The effect of the blue-to-green backscattering ratio was of secondary importance. We observed a characteristic optical differentiation of waters within the investigated region. The majority of waters, which are here hypothesized to be dominated by diatoms, exhibited a relatively high blue-to-green reflectance ratio. The waters at several other stations, presumably dominated by dinoflagellates and/or prymnesiophytes, showed much lower reflectance ratio. Our data also show that the seemingly random variations in particulate absorption and backscattering coefficients at any given Chl are significant (more than a factor of 2) in the investigated waters.

[1] We examined optical variability of seawater in relation to particle concentration, composition, and size distribution in the nearshore marine environment at Imperial Beach, California, over a period of 1.5 years. Measurements included the hyperspectral inherent optical properties (IOPs) of seawater (particulate beam attenuation, particulate and CDOM absorption coefficients within the spectral range 300-850 nm), particle size distribution (PSD) within the diameter range 2-60 mm, and the mass concentrations of suspended particulate matter (SPM), particulate organic carbon (POC), and chlorophyll a (Chl). The particulate assemblage spanned a wide range of concentrations and composition, from the dominance of mineral particles (POC/SPM < 0.06) with relatively steep PSDs to the high significance or dominance of organic particles (POC/SPM > 0.25) with considerably greater contribution of larger-sized particles. Large variability in the particulate characteristics produced correspondingly large variability in the IOPs; up to 100-fold variation in particulate absorption and scattering coefficients and several-fold variation in the SPM-specific and POC-specific coefficients. Analysis of these data demonstrates that knowledge of general characteristics about the particulate composition and size distribution leads to improved interpretations of the observed optical variability. We illustrate a multistep empirical approach for estimating proxies of particle concentration (SPM and POC), composition (POC/SPM), and size distribution (median diameter) from the measured IOPs in a complex coastal environment. The initial step provides information about a proxy for particle composition; other particulate characteristics are subsequently derived from relationships specific to different categories of particulate composition. Cieplak (2010), Optical variability of seawater in relation to particle concentration, composition, and size distribution in the nearshore marine environment at

[1] We use satellite data from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) to investigate distributions of particulate organic carbon (POC) concentration in surface waters of the north polar Atlantic Ocean during the spring-summer season (April through August) over a 6-year period from 1998 through 2003. By use of field data collected at sea, we developed regional relationships for the purpose of estimating POC from remote-sensing observations of ocean color. Analysis of several approaches used in the POC algorithm development and match-up analysis of coincident in situ-derived and satellite-derived estimates of POC resulted in selection of an algorithm that is based on the blue-to-green ratio of remote-sensing reflectance R rs (or normalized water-leaving radiance L wn ). The application of the selected algorithm to a 6-year record of SeaWiFS monthly composite data of L wn revealed patterns of seasonal and interannual variability of POC in the study region. For example, the results show a clear increase of POC throughout the season. The lowest values, generally less than 200 mg m À3 , and at some locations often less than 50 mg m À3 , were observed in April. In May and June, POC can exceed 300 or even 400 mg m À3 in some parts of the study region. Patterns of interannual variability are intricate, as they depend on the geographic location within the study region and particular time of year (month) considered. By comparing the results averaged over the entire study region and the entire season (April through August) for each year separately, we found that the lowest POC occurred in 2001 and the highest POC occurred in 2002 and 1999.