Beschreibung: Data consist of global monthly-averaged maps of Hue angle, Forel-Ule index and Secchi disk depth at ~ 4 km spatial resolution at the equator. Data extend from 1997 and 2018 and were generated from the ESA-OC-CCI v4.0 multi-sensor merged remote-sensing reflectances. Two downsized subproducts are also provided: - The global dataset, reduced at 1 degree spatial resolution - A North Atlantic dataset, reduced at 0.25 degree spatial resolution

Beschreibung: We derive the chlorophyll a concentration (Chla)for three main phytoplankton functional types (PFTs)-- diatoms, coccolithophores and cyanobacteria- by combining satellite multispectral-based information, being of a high spatial and temporal resolution, with retrievals based on high resolution of PFT absorption properties derived from hyperspectral measurements. The multispectral-based PFT Chla retrievals are based on a revised version of the empirical OC-PFT algorithm (Hirata et al. 2011) applied to the Ocean Colour Climate Change Initiative (OC-CCI) total Chla product. The PhytoDOAS analytical algorithm (Bracher et al. 2009, Sadeghi et al. 2012) is used with some modifications to derive PFT Chla from SCIAMACHY hyperspectral measurements. To combine synergistically these two PFT products (OC-PFT and PhytoDOAS), an optimal interpolation is performed for each PFT in every OC-PFT sub-pixel within a PhytoDOAS pixel, given its Chla and its a priori error statistics. The synergistic product (SynSenPFT) is presented for the period of August 2002 ? March 2012 and evaluated against in situ HPLC pigment data and satellite information on phytoplankton size classes (PSC) (Brewin et al. 2010, Brewin et al. 2015) and the size fraction (Sf) by Ciotti and Bricaud (2006. The most challenging aspects of the SynSenPFT algorithm implementation are discussed. Perspectives on SynSenPFT product improvements and prolongation of the time series over the next decades by adaptation to Sentinel multi- and hyperspectral instruments are highlighted.

Beschreibung: The Copernicus Marine Environment Monitoring Service (CMEMS) Ocean State Report (OSR) provides an annual report of the state of the global ocean and European regional seas for policy and decision-makers with the additional aim of increasing general public awareness about the status of, and changes in, the marine environment. The CMEMS OSR draws on expert analysis and provides a 3-D view (through reanalysis systems), a view from above (through remote-sensing data) and a direct view of the interior (through in situ measurements) of the global ocean and the European regional seas. The report is based on the unique CMEMS monitoring capabilities of the blue (hydrography, currents), white (sea ice) and green (e.g. Chlorophyll) marine environment. This first issue of the CMEMS OSR provides guidance on Essential Variables, large-scale changes and specific events related to the physical ocean state over the period 1993–2015. Principal findings of this first CMEMS OSR show a significant increase in global and regional sea levels, thermosteric expansion, ocean heat content, sea surface temperature and Antarctic sea ice extent and conversely a decrease in Arctic sea ice extent during the 1993–2015 period. During the year 2015 exceptionally strong large-scale changes were monitored such as, for example, a strong El Niño Southern Oscillation, a high frequency of extreme storms and sea level events in specific regions in addition to areas of high sea level and harmful algae blooms. At the same time, some areas in the Arctic Ocean experienced exceptionally low sea ice extent and temperatures below average were observed in the North Atlantic Ocean.

Beschreibung: Published

Beschreibung: s235–s320

Beschreibung: 4A. Oceanografia e clima

Beschreibung: JCR Journal

Beschreibung: Phytoplankton are composed of diverse taxonomical groups, which are manifested as distinct morphology, size, and pigment composition. These characteristics, modulated by their physiological state, impact their light absorption and scattering, allowing them to be detected with ocean color satellite radiometry. There is a growing volume of literature describing satellite algorithms to retrieve information on phytoplankton composition in the ocean. This synthesis provides a review of current methods and a simplified comparison of approaches. The aim is to provide an easily comprehensible resource for non-algorithm developers, who desire to use these products, thereby raising the level of awareness and use of these products and reducing the boundary of expert knowledge needed to make a pragmatic selection of output products with confidence. The satellite input and output products, their associated validation metrics, as well as assumptions, strengths, and limitations of the various algorithm types are described, providing a framework for algorithm organization to assist users and inspire new aspects of algorithm development capable of exploiting the higher spectral, spatial and temporal resolutions from the next generation of ocean color satellites.

Beschreibung: 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 hyperspectral information, and of (iv) techniques to merge and synergistically use the various streams of continuous information on phytoplankton diversity from various satellite sensors' and in situ data to ensure long-term monitoring of phytoplankton composition.

Beschreibung: Ocean color remote sensing of chlorophyll concentration has revolutionized our understanding of the biology of the oceans. However, a comprehensive understanding of the structure and function of oceanic ecosystems requires the characterization of the spatio-temporal variability of various phytoplankton functional types (PFTs), which have differing biogeochemical roles. Thus, recent bio-optical algorithm developments have focused on retrieval of various PFTs. It is important to validate and inter-compare the existing PFT algorithms; however direct comparison of retrieved variables is non-trivial because in those algorithms PFTs are defined differently. Thus, it is more plausible and potentially more informative to focus on emergent properties of PFTs, such as phenology. Furthermore, ocean color satellite PFT data sets can play a pivotal role in informing and/or validating the biogeochemical routines of Earth System Models. Here, the phenological characteristics of 10 PFT satellite algorithms and 7 latest-generation climate models from the Coupled Model Inter-comparison Project (CMIP5) are intercompared as part of the International Satellite PFT Algorithm Inter-comparison Project. The comparison is based on monthly satellite data (mostly SeaWiFS) for the 2003–2007 period. The phenological analysis is based on the fraction of microplankton or a similar variable for the satellite algorithms and on the carbon biomass due to diatoms for the climate models. The seasonal cycle is estimated on a per-pixel basis as a sumof sinusoidal harmonics, derived from the Discrete Fourier Transform of the variable time series. Peak analysis is then applied to the estimated seasonal signal and the following phenological parameters are quantified for each satellite algorithm and climate model: seasonal amplitude, percent seasonal variance, month of maximum, and bloom duration. Secondary/double blooms occur in many areas and are also quantified. The algorithms and the models are quantitatively compared based on these emergent phenological parameters. Results indicate that while algorithms agree to a first order on a global scale, large differences among themexist; differences are analyzed in detail for two Longhurst regions in the North Atlantic: North Atlantic Drift Region (NADR) and North Atlantic Subtropical Gyre West (NASW). Seasonal cycles explain the most variance in zonal bands in the seasonally-stratified subtropics at about 30° latitude in the satellite PFT data. The CMIP5 models do not reproduce this pattern, exhibiting higher seasonality in mid and high-latitudes and generally much more spatially homogeneous patterns in phenological indices compared to satellite data. Satellite data indicate a complex structure of double blooms in the Equatorial region and mid-latitudes, and single blooms on the poleward edges of the subtropical gyres. In contrast, the CMIP5 models showsingle annual blooms over most of the ocean except for the Equatorial band and Arabian Sea.

Beschreibung: We derive the chlorophyll a concentration (Chla) for three main phytoplankton functional types (PFTs) – diatoms, coccolithophores and cyanobacteria – by combining satellite multispectral-based information, being of a high spatial and temporal resolution, with retrievals based on high resolution of PFT absorption properties derived from hyperspectral satellite measurements. The multispectral-based PFT Chla retrievals are based on a revised version of the empirical OC-PFT algorithm applied to the Ocean Color Climate Change Initiative (OC-CCI) total Chla product. The PhytoDOAS analytical algorithm is used with some modifications to derive PFT Chla from SCIAMACHY hyperspectral measurements. To combine synergistically these two PFT products (OC-PFT and PhytoDOAS), an optimal interpolation is performed for each PFT in every OC-PFT sub-pixel within a PhytoDOAS pixel, given its Chla and its a priori error statistics. The synergistic product (SynSenPFT) is presented for the period of August 2002 March 2012 and evaluated against PFT Chla data obtained from in situ marker pigment data and the NASA Ocean Biogeochemical Model simulations and satellite information on phytoplankton size. The most challenging aspects of the SynSenPFT algorithm implementation are discussed. Perspectives on SynSenPFT product improvements and prolongation of the time series over the next decades by adaptation to Sentinel multi- and hyperspectral instruments are highlighted.

Beschreibung: The IOCCG-supported workshop “Phytoplankton Composition from Space: towards a validation strategy for satellite algorithms” was organized as a follow-up to the Phytoplankton Functional Types from Space splinter session, held at the International Ocean Colour Science Meeting (Germany, 2013). The specific goals of the workshop were to: 1.Provide a summary of the status of activities from relevant IOCCG working groups, the 2nd PFT intercomparison working group, PFT validation data sets and other research developments. 2.Provide a PFT validation strategy that considers the different applications of PFT products: and seeks community consensus on datasets and analysis protocols. 3.Discuss possibilities for sustaining ongoing PFT algorithm validation and intercomparison activities. The workshop included 15 talks, breakout sessions and plenary discussions. Talks covered community algorithm intercomparison activity updates, review of established and novel methods for PFT validation, validation activities for specific applications and space-agency requirements for PFT products and validation. These were followed by general discussions on (a) major recommendations for global intercomparison initiative in respect to validation, intercomparison and user’s guide; (b) developing a community consensus on which data sets for validation are optimal and which measurement and analysis protocols should be followed to support sustained validation of PFT products considering different applications; (c) the status of different validation data bases and measurement protocols for different PFT applications, and (d) engagement of the various user communities for PFT algorithms in developing PFT product specifications. From these discussions, two breakout groups provided in depth discussion and recommendations on (1) validation of current algorithms and (2) work plan to prepare for validation of future missions. Breakout group 1 provided an action list for progressing the current international community validation and intercomparison activity. Breakout group 2 provided the following recommendations towards developing a future validation strategy for satellite PFT products: 1. Establish a number of validation sites that maintain measurements of a key set of variables. 2. This set of variables should include: •Phytoplankton pigments from HPLC, phycobilins from spectrofluorometry •Phytoplankton cell counts and ID, volume / carbon estimation and imaging (e.g. from flow cytometry, FlowCam, FlowCytobot type technologies) •Inherent optical properties (e.g. absorption, backscattering, VSF) •Hyperspectral radiometry (both above and in-water) •Particle size distribution •Size-fractionated measurements of pigments and absorption •Genetic / -omics data 3. Undertake an intercomparison of methods / instruments over several years at a few sites to understand our capabilities to fully characterize the phytoplankton community. 4. Organise workshops to address the following topics: •Techniques for particle analysis, characterization and classification •Engagement with modellers and understanding end-user requirements •Data storage and management, standards for data contributors, data challenges In conclusion, the workshop was assessed to have fulfilled its goals. A follow-on meeting will be organized during the International Ocean Colour Science Meeting 2015 in San Francisco. Specific follow-on actions are listed at the end of the report.

Beschreibung: A corrigendum on Synergistic Exploitation of Hyper- and Multi-Spectral Precursor Sentinel Measurements to Determine Phytoplankton Functional Types (SynSenPFT) by Losa, S. N., Soppa, M. A., Dinter, T., Wolanin, A., Brewin, R. J. W., Bricaud, A., et al. (2017). Front. Mar. Sci. 4:203. doi: 10.3389/fmars.2017.00203. In the original article, we neglected, but would like to acknowledge the North-German Supercomputing Alliance (HLRN) for providing HPC resources that have contributed to the research results reported in this paper. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way.

Beschreibung: To overcome the short-comings of current multi- spectral PFT products (supplying either knowledge on dominant groups or size fractions only, data products with strong linkage to a-priori-information) and PhytoDOAS data products (with only low temporal and spatial coverage), this ESA SEOM project's objective is a substantial improvement of retrieving phytoplankton groups with defined accuracy and good spatial and temporal coverage. This shall be done by developing a synergistic product which contains the Chl-a (biomass) of several PFT by using complementary information from multi- and hyper-spectral satellite ocean colour data. The algorithm can be later applied to produce a synergistic PFT product from TROPOMI (on Sentinel- 5-Precursor, Sentinel-4, Sentinel-5) and OLCI (on Sentinel-3). The project started in December 2014. Here we present the main aspects of the project, including development and validation of the synergistic product.