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- Sathyendranath, Shubha, et al.
(author)
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An Ocean-Colour Time Series for Use in Climate Studies : The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI)
- 2019
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In: Sensors. - : MDPI AG. - 1424-8220. ; 19:19
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Journal article (peer-reviewed)abstract
- Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean-colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea-viewing Wide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel.
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- Porter, Richard T. J., et al.
(author)
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Techno-economic assessment of CO2 quality effect on its storage and transport : CO(2)QUEST An overview of aims, objectives and main findings
- 2016
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In: International Journal of Greenhouse Gas Control. - : Elsevier BV. - 1750-5836 .- 1878-0148. ; 54, s. 662-681
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Journal article (peer-reviewed)abstract
- This paper provides an overview of the aims, objectives and the main findings of the CO(2)QUEST FP7 collaborative project, funded by the European Commission and designed to address the fundamentally important and urgent issues regarding the impact of the typical impurities in CO2 streams captured from fossil fuel power plants and other CO2 intensive industries on their safe and economic pipeline transportation and storage. The main features and results recorded from some of the unique test facilities constructed as part of the project are presented. These include an extensively instrumented realistic-scale test pipeline for conducting pipeline rupture and dispersion tests in China, an injection test facility in France to study the mobility of trace metallic elements contained in a CO2 stream following injection near a shallow-water qualifier and fluid/rock interactions and well integrity experiments conducted using a fully instrumented deep-well CO2/impurities injection test facility in Israel. The above, along with the various unique mathematical models developed, provide the fundamentally important tools needed to define impurity tolerance levels, mixing protocols and control measures for pipeline networks and storage infrastructure, thus contributing to the development of relevant standards for the safe design and economic operation of CCS.
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