Hooker
Stanford B.
Hooker
Stanford B.
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Working PaperSatellite images of warm core ring 82-B sea surface temperature and a chronological record of major physical events affecting ring structure(Woods Hole Oceanographic Institution, 1984-01) Evans, Robert H. ; Baker, Karen S. ; Brown, O. ; Smith, Raymond C. ; Hooker, Stanford B. ; Olson, Donald B. ; Warm Core Rings Program Service OfficeA chronology constructed from satellite-derived thermal imagery is presented to describe the formation and life history of warm-core ring 82-B. A comparison is made with warm-core ring 81-F in order to illustrate similarities that may be common to warm-core rings that traverse the region of the Slope Water occupied by 82-B. Particular attention is paid to discrete events identified from analysis of changes in the surface thermal field. Significant events include interactions between the ring and the Gulf Stream, warm (Gulf Stream) and cold (shelf) streamers and interaction with other vortices. The events are documented by following changes in ring size, shape, translation, and surface thermal structure. Observations determined from the infrared satellite imagery are supported by hydrography, acoustic velocity profiling and drifter trajectories.
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Technical ReportDrifter studies in warm core rings(Woods Hole Oceanographic Institution, 1984-04) Tynan, Cynthia T. ; Hooker, Stanford B.The results of multiple deployments of surface drifters in warm core rings of the Gulf Stream are presented. Four satellite drifters (tracked by the Argos system) were deployed on nine separate occasions and two LORAN-C drifters (operated by the University of Miami) were deployed three times. Drifter studies were conducted during four cruises aboard the R/V Endeavor in 1982 in conjunction with the Warm Core Rings Experiment and one cruise of the USNS Bartlett in January 1983 which was sponsored by the Office of Naval Research. Translational velocities and periods of rotation are provided for two rings: 82B and 82H.
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ArticleAn ocean-colour time series for use in climate studies: The experience of the ocean-colour climate change initiative (OC-CCI)(MDPI, 2019-10-03) Sathyendranath, Shubha ; Brewin, Robert J. W. ; Brockmann, Carsten ; Brotas, Vanda ; Calton, Ben ; Chuprin, Andrei ; Cipollini, Paolo ; Couto, André B. ; Dingle, James ; Doerffer, Roland ; Donlon, Craig ; Dowell, Mark ; Farman, Alex ; Grant, Michael ; Groom, Steven ; Horseman, Andrew ; Jackson, Thomas ; Krasemann, Hajo ; Lavender, Samantha ; Martinez-Vicente, Victor ; Mazeran, Constant ; Melin, Frederic ; Moore, Timothy S. ; Müller, Dagmar ; Regner, Peter ; Roy, Shovonlal ; Steele, Chris J. ; Steinmetz, François ; Swinton, John ; Taberner, Malcolm ; Thompson, Adam ; Valente, André ; Zühlke, Marco ; Brando, Vittorio ; Feng, Hui ; Feldman, Gene ; Franz, Bryan A. ; Frouin, Robert ; Gould, Richard ; Hooker, Stanford B. ; Kahru, Mati ; Kratzer, Susanne ; Mitchell, B. Greg ; Muller-Karger, Frank E. ; Sosik, Heidi M. ; Voss, Kenneth ; Werdell, Jeremy ; Platt, TrevorOcean 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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ArticleA compilation of global bio-optical in situ data for ocean-colour satellite applications - version two(Copernicus Publications, 2019-07-15) Valente, André ; Sathyendranath, Shubha ; Brotas, Vanda ; Groom, Steven ; Grant, Michael ; Taberner, Malcolm ; Antoine, David ; Arnone, Robert ; Balch, William M. ; Barker, Kathryn ; Barlow, Ray ; Belanger, Simon ; Berthon, Jean-François ; Besiktepe, Sukru ; Borsheim, Yngve ; Bracher, Astrid ; Brando, Vittorio ; Canuti, Elisabetta ; Chavez, Francisco P. ; Cianca, Andrés ; Claustre, Hervé ; Clementson, Lesley ; Crout, Richard ; Frouin, Robert ; García-Soto, Carlos ; Gibb, Stuart W. ; Gould, Richard ; Hooker, Stanford B. ; Kahru, Mati ; Kampel, Milton ; Klein, Holger ; Kratzer, Susanne ; Kudela, Raphael M. ; Ledesma, Jesus ; Loisel, Hubert ; Matrai, Patricia A. ; McKee, David ; Mitchell, Brian G. ; Moisan, Tiffany ; Muller-Karger, Frank E. ; O'Dowd, Leonie ; Ondrusek, Michael ; Platt, Trevor ; Poulton, Alex J. ; Repecaud, Michel ; Schroeder, Thomas ; Smyth, Timothy ; Smythe-Wright, Denise ; Sosik, Heidi M. ; Twardowski, Michael ; Vellucci, Vincenzo ; Voss, Kenneth ; Werdell, Jeremy ; Wernand, Marcel ; Wright, Simon ; Zibordi, GiuseppeA global compilation of in situ data is useful to evaluate the quality of ocean-colour satellite data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (including, inter alia, MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT and GeP&CO) and span the period from 1997 to 2018. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties, spectral diffuse attenuation coefficients and total suspended matter. The data were from multi-project archives acquired via open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenization, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) was propagated throughout the work and made available in the final table. By making the metadata available, provenance is better documented, and it is also possible to analyse each set of data separately. This paper also describes the changes that were made to the compilation in relation to the previous version (Valente et al., 2016). The compiled data are available at https://doi.org/10.1594/PANGAEA.898188 (Valente et al., 2019).
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ArticleA compilation of global bio-optical in situ data for ocean-colour satellite applications(Copernicus Publications on behalf of the European Geosciences Union, 2016-06-03) Valente, André ; Sathyendranath, Shubha ; Brotas, Vanda ; Groom, Steven ; Grant, Michael ; Taberner, Malcolm ; Antoine, David ; Arnone, Robert ; Balch, William M. ; Barker, Kathryn ; Barlow, Ray ; Belanger, Simon ; Berthon, Jean-François ; Besiktepe, Sukru ; Brando, Vittorio ; Canuti, Elisabetta ; Chavez, Francisco P. ; Claustre, Hervé ; Crout, Richard ; Frouin, Robert ; García-Soto, Carlos ; Gibb, Stuart W. ; Gould, Richard ; Hooker, Stanford B. ; Kahru, Mati ; Klein, Holger ; Kratzer, Susanne ; Loisel, Hubert ; McKee, David ; Mitchell, Brian G. ; Moisan, Tiffany ; Muller-Karger, Frank E. ; O'Dowd, Leonie ; Ondrusek, Michael ; Poulton, Alex J. ; Repecaud, Michel ; Smyth, Timothy ; Sosik, Heidi M. ; Twardowski, Michael ; Voss, Kenneth ; Werdell, Jeremy ; Wernand, Marcel ; Zibordi, GiuseppeA compiled set of in situ data is important to evaluate the quality of ocean-colour satellite-data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GeP&CO), span between 1997 and 2012, and have a global distribution. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties and spectral diffuse attenuation coefficients. The data were from multi-project archives acquired via the open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were preserved throughout the work and made available in the final table. Using all the data in a validation exercise increases the number of matchups and enhances the representativeness of different marine regimes. By making available the metadata, it is also possible to analyse each set of data separately. The compiled data are available at doi:10.1594/PANGAEA.854832 (Valente et al., 2015).
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ArticleExtending aquatic spectral information with the first radiometric IR-B field observations(National Academy of Sciences, 2023-10-14) Houskeeper, Henry F. ; Hooker, Stanford B.Planetary radiometric observations enable remote sensing of biogeochemical parameters to describe spatiotemporal variability in aquatic ecosystems. For approximately the last half century, the science of aquatic radiometry has established a knowledge base using primarily, but not exclusively, visible wavelengths. Scientific subdisciplines supporting aquatic radiometry have evolved hardware, software, and procedures to maximize competency for exploiting visible wavelength information. This perspective culminates with the science requirement that visible spectral resolution must be continually increased to extract more information. Other sources of information, meanwhile, remain underexploited, particularly information from nonvisible wavelengths. Herein, absolute radiometry is used to evaluate spectral limits for deriving and exploiting aquatic data products, specifically the normalized water-leaving radiance, Γ(λ), and its derivative products. Radiometric observations presented herein are quality assured for individual wavebands, and spectral verification is conducted by analyzing celestial radiometric results, comparing agreement of above- and in-water observations at applicable wavelengths, and evaluating consistency with bio-optical models and optical theory. The results presented include the first absolute radiometric field observations of Γ(λ) within the IR-B spectral domain (i.e. spanning 1400–3000 nm), which indicate that IR-B signals confer greater and more variable flux than formerly ascribed. Black-pixel processing, a routine correction in satellite and in situ aquatic radiometry wherein a spectrum is offset corrected relative to a nonvisible waveband (often IR-B or a shorter legacy waveband) set to a null value, is shown to degrade aquatic spectra and derived biogeochemical parameters.
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ArticleExpanded signal to noise ratio estimates for validating next-generation satellite sensors in oceanic, coastal, and inland waters(MDPI, 2024-03-31) Kudela, Raphael M. ; Hooker, Stanford B. ; Guild, Liane S. ; Houskeeper, Henry F. ; Taylor, NikyThe launch of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) and the Surface Biology and Geology (SBG) satellite sensors will provide increased spectral resolution compared to existing platforms. These new sensors will require robust calibration and validation datasets, but existing field-based instrumentation is limited in its availability and potential for geographic coverage, particularly for coastal and inland waters, where optical complexity is substantially greater than in the open ocean. The minimum signal-to-noise ratio (SNR) is an important metric for assessing the reliability of derived biogeochemical products and their subsequent use as proxies, such as for biomass, in aquatic systems. The SNR can provide insight into whether legacy sensors can be used for algorithm development as well as calibration and validation activities for next-generation platforms. We extend our previous evaluation of SNR and associated uncertainties for representative coastal and inland targets to include the imaging sensors PRISM and AVIRIS-NG, the airborne-deployed C-AIR radiometers, and the shipboard HydroRad and HyperSAS radiometers, which were not included in the original analysis. Nearly all the assessed hyperspectral sensors fail to meet proposed criteria for SNR or uncertainty in remote sensing reflectance (Rrs) for some part of the spectrum, with the most common failures (>20% uncertainty) below 400 nm, but all the sensors were below the proposed 17.5% uncertainty for derived chlorophyll-a. Instrument suites for both in-water and airborne platforms that are capable of exceeding all the proposed thresholds for SNR and Rrs uncertainty are commercially available. Thus, there is a straightforward path to obtaining calibration and validation data for current and next-generation sensors, but the availability of suitable high spectral resolution sensors is limited.