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.

Fertilization of the ocean by adding iron compounds has induced diatom-dominated phytoplankton blooms accompanied by considerable carbon dioxide drawdown in the ocean surface layer. However, because the fate of bloom biomass could not be adequately resolved in these experiments, the timescales of carbon sequestration from the atmosphere are uncertain. Here we report the results of a five-week experiment carried out in the closed core of a vertically coherent, mesoscale eddy of the Antarctic Circumpolar Current, during which we tracked sinking particles from the surface to the deep-sea floor. A large diatom bloom peaked in the fourth week after fertilization. This was followed by mass mortality of several diatom species that formed rapidly sinking, mucilaginous aggregates of entangled cells and chains. Taken together, multiple lines of evidence-although each with important uncertainties-lead us to conclude that at least half the bloom biomass sank far below a depth of 1,000 metres and that a substantial portion is likely to have reached the sea floor. Thus, iron-fertilized diatom blooms may sequester carbon for timescales of centuries in ocean bottom water and for longer in the sediments.

Diatoms of the iron-replete continental margins and North Atlantic are key exporters of organic carbon. In contrast, diatoms of the iron-limited Antarctic Circumpolar Current sequester silicon, but comparatively little carbon, in the underlying deep ocean and sediments. Because the Southern Ocean is the major hub of oceanic nutrient distribution, selective silicon sequestration there limits diatom blooms elsewhere and consequently the biotic carbon sequestration potential of the entire ocean. We investigated this paradox in an in situ iron fertilization experiment by comparing accumulation and sinking of diatom populations inside and outside the iron-fertilized patch over 5 wk. A bloom comprising various thin-and thick-shelled diatom species developed inside the patch despite the presence of large grazer populations. After the third week, most of the thinner-shelled diatom species underwent mass mortality, formed large, mucous aggregates, and sank out en masse (carbon sinkers). In contrast, thicker-shelled species, in particular Fragilariopsis kerguelensis, persisted in the surface layers, sank mainly empty shells continuously, and reduced silicate concentrations to similar levels both inside and outside the patch (silica sinkers). These patterns imply that thick-shelled, hence grazer-protected, diatom species evolved in response to heavy copepod grazing pressure in the presence of an abundant silicate supply. The ecology of these silica-sinking species decouples silicon and carbon cycles in the iron-limited Southern Ocean, whereas carbon-sinking species, when stimulated by iron fertilization, export more carbon per silicon. Our results suggest that large-scale iron fertilization of the silicate-rich Southern Ocean will not change silicon sequestration but will add carbon to the sinking silica flux.evolutionary arms race | top-down control | geo-engineering

Abstract. The climate active trace-gas carbonyl sulfide (OCS) is the most abundant sulfur gas in the atmosphere. A missing source in its atmospheric budget is currently suggested, resulting from an upward revision of the vegetation sink. Tropical oceanic emissions have been proposed to close the resulting gap in the atmospheric budget. We present a bottom-up approach including (i) new observations of OCS in surface waters of the tropical Atlantic, Pacific and Indian oceans and (ii) a further improved global box model to show that direct OCS emissions are unlikely to account for the missing source. The box model suggests an undersaturation of the surface water with respect to OCS integrated over the entire tropical ocean area and, further, global annual direct emissions of OCS well below that suggested by top-down estimates. In addition, we discuss the potential of indirect emission from CS 2 and dimethylsulfide (DMS) to account for the gap in the atmospheric budget. This bottom-up estimate of oceanic emissions has implications for using OCS as a proxy for global terrestrial CO 2 uptake, which is currently impeded by the inadequate quantification of atmospheric OCS sources and sinks.

Abstract. In this study the technique of Differential OpticalAbsorption Spectroscopy (DOAS) has been adapted for the retrieval of the absorption and biomass of two major phytoplankton groups (PhytoDOAS) from data of the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite sensor. SCIAMACHY measures back scattered solar radiation in the UV-Vis-NIR spectral regions with a high spectral resolution (0.2 to 1.5 nm). In order to identify phytoplankton absorption characteristics in the SCIAMACHY data in the range of 430 to 500 nm, phytoplankton absorption spectra measured in-situ during two different RV "Polarstern" expeditions were used. The two spectra have been measured in different ocean regions where different phytoplankton groups (cyanobacteria and diatoms) dominated the phytoplankton composition. Results clearly show distinct absorption characteristics of the two phytoplankton groups in the SCIAMACHY spectra. Using these results in addition to calculations of the light penetration depth derived from DOAS retrievals of the inelastic scattering (developed by Vountas et al., 2007), globally distributed pigment concentrations for these characteristic phytoplankton groups for two monthly periods (FebruaryMarch 2004 and October-November 2005) were determined. This satellite information on cyanobacteria and diatoms distribution clearly matches the concentrations based on high pressure liquid chromatography (HPLC) pigment analysis of collocated water samples and concentrations derived from a Correspondence to: A. Bracher (astrid.bracher@awi.de) global model analysis with the NASA Ocean Biogeochemical Model (Gregg et al., 2003;Gregg and Casey 2007). The quantitative assessment of the distribution of key phytoplankton groups from space enables various biogeochemical regions to be distinguished and will be of great importance for the global modeling of marine ecosystems and biogeochemical cycles which enables the impact of climate change in the oceanic biosphere to be estimated.