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.

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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.

To improve our understanding of the role of phytoplankton for marine ecosystems and global biogeochemical cycles, information on the global distribution of major phytoplankton groups is essential. Although algorithms have been developed to assess phytoplankton diversity from space for over two decades, so far the application of these data sets has been limited. This scientific roadmap identifies user needs, summarizes the current state of the art, and pinpoints major gaps in long-term objectives to deliver space-derived phytoplankton diversity data that meets the user requirements. These major gaps in using ocean color to estimate phytoplankton community structure were identified as: (a) the mismatch between satellite, in situ and model data on phytoplankton composition, (b) the lack of quantitative uncertainty estimates provided with satellite data, (c) the spectral limitation of current sensors to enable the full exploitation of backscattered sunlight, and (d) the very limited applicability of satellite algorithms determining phytoplankton composition for regional, especially coastal or inland, waters. Recommendation for actions include but are not limited to: (i) an increased communication and round-robin exercises among and within the related expert groups, (ii) the launching of higher spectrally and spatially resolved sensors, (iii) the development of algorithms that exploit

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Postprint (published version

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Abstract. This paper presents extensive bias determination analyses of ozone observations from the Atmospheric Chemistry Experiment (ACE) satellite instruments: the ACE Fourier Transform Spectrometer (ACE-FTS) and the Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (ACE-MAESTRO) instrument. Here we compare the latest ozone data products from ACE-FTS and ACE-MAESTRO with coincident observations from nearly 20 satellite-borne, airborne, balloonborne and ground-based instruments, by analysing volume mixing ratio profiles and partial column densities. The ACE-FTS version 2.2 Ozone Update product reports more ozone than most correlative measurements from the upper troposphere to the lower mesosphere. At altitude levels from 16 to 44 km, the average values of the mean relative differences are nearly all within +1 to +8%. At higher altitudes (45-60 km), the ACE-FTS ozone amounts are significantly larger than those of the comparison instruments, with mean relative differences of up to +40% (about +20% on average). For the ACE-MAESTRO version 1.2 ozone data product, mean relative differences are within ±10% (average values within ±6%) between 18 and 40 km for both the sunrise and sunset measurements. At higher altitudes (∼35-55 km), systematic biases of opposite sign are found between the ACE-MAESTRO sunrise and sunset observations. While ozone amounts derived from the ACE-MAESTRO sunrise occultation data are often smaller than the coincident observations (with mean relative differences down to −10%), the sunset occultation profiles for ACE-MAESTRO show results that are qualitatively similar to ACE-FTS, indicating a large positive bias (mean relative differences within +10 to +30%) in the 45-55 km altitude range. In contrast, there is no significant systematic difference in bias found for the ACE-FTS sunrise and sunset measurements.