1. An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic regions across the globe
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Joji Ishizaka, Robert Armstrong, Walker O. Smith, Michele Scardi, John Marra, Kimberly J. W. Hyde, Shilin Tang, Vincent S. Saba, Takahiko Kameda, André Morel, John E. O'Reilly, Ichio Asanuma, Toby K. Westberry, Kirk Waters, David Antoine, Mark Dowell, Michael J. Behrenfeld, Frédéric Mélin, Julia Uitz, Timothy J Smyth, Áurea Maria Ciotti, Marjorie A. M. Friedrichs, Nicolas Hoepffner, Laboratoire d'océanographie de Villefranche (LOV), Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Department of Botany and Plant Pathology, Cordley Hall 2082, JOINT RESEARCH CENTER ITA, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Paulista University, JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre [Ispra] (JRC), Virginia Institute of Marine Science (VIMS), Scripps Institution of Oceanography (SIO - UC San Diego), University of California [San Diego] (UC San Diego), University of California (UC)-University of California (UC), Oregon State University (OSU), Hydrobiologie (UR HYAX), Centre national du machinisme agricole, du génie rural, des eaux et forêts (CEMAGREF), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Virginia Inst Marine Sci, CNRS, Univ Paris 06, SUNY Stony Brook, Tokyo Univ Informat Sci, Oregon State Univ, Universidade Estadual Paulista (Unesp), European Commiss, NOAA, Nagoya Univ, Seikai Natl Fisheries Res Inst, CUNY, Univ Roma Tor Vergata, Plymouth Marine Lab, Fisheries & Oceans Canada, and Univ Calif San Diego
- Subjects
0106 biological sciences ,Fixed carbon ,Settore BIO/07 ,010504 meteorology & atmospheric sciences ,010604 marine biology & hydrobiology ,lcsh:QE1-996.5 ,lcsh:Life ,Primary production ,Pelagic zone ,01 natural sciences ,Pacific ocean ,lcsh:Geology ,lcsh:QH501-531 ,Oceanography ,Ocean color ,lcsh:QH540-549.5 ,Environmental science ,Sargasso sea ,lcsh:Ecology ,14. Life underwater ,Ecology, Evolution, Behavior and Systematics ,Primary productivity ,[SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography ,0105 earth and related environmental sciences ,Earth-Surface Processes - Abstract
Made available in DSpace on 2013-08-28T14:13:50Z (GMT). No. of bitstreams: 1 WOS000287796800018.pdf: 4189122 bytes, checksum: 57872b9405eca4911ea4efd9756f160c (MD5) Made available in DSpace on 2013-09-30T19:22:54Z (GMT). No. of bitstreams: 2 WOS000287796800018.pdf: 4189122 bytes, checksum: 57872b9405eca4911ea4efd9756f160c (MD5) WOS000287796800018.pdf.txt: 74870 bytes, checksum: b4ae21f33d5d23b3ff5f0482dfbc34ee (MD5) Previous issue date: 2011-01-01 Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-20T15:34:00Z No. of bitstreams: 2 WOS000287796800018.pdf: 4189122 bytes, checksum: 57872b9405eca4911ea4efd9756f160c (MD5) WOS000287796800018.pdf.txt: 74870 bytes, checksum: b4ae21f33d5d23b3ff5f0482dfbc34ee (MD5) Made available in DSpace on 2014-05-20T15:34:00Z (GMT). No. of bitstreams: 2 WOS000287796800018.pdf: 4189122 bytes, checksum: 57872b9405eca4911ea4efd9756f160c (MD5) WOS000287796800018.pdf.txt: 74870 bytes, checksum: b4ae21f33d5d23b3ff5f0482dfbc34ee (MD5) Previous issue date: 2011-01-01 National Aeronautics and Space Agency Nearly half of the earth's photosynthetically fixed carbon derives from the oceans. To determine global and region specific rates, we rely on models that estimate marine net primary productivity (NPP) thus it is essential that these models are evaluated to determine their accuracy. Here we assessed the skill of 21 ocean color models by comparing their estimates of depth-integrated NPP to 1156 in situ C-14 measurements encompassing ten marine regions including the Sargasso Sea, pelagic North Atlantic, coastal Northeast Atlantic, Black Sea, Mediterranean Sea, Arabian Sea, subtropical North Pacific, Ross Sea, West Antarctic Peninsula, and the Antarctic Polar Frontal Zone. Average model skill, as determined by root-mean square difference calculations, was lowest in the Black and Mediterranean Seas, highest in the pelagic North Atlantic and the Antarctic Polar Frontal Zone, and intermediate in the other six regions. The maximum fraction of model skill that may be attributable to uncertainties in both the input variables and in situ NPP measurements was nearly 72%. on average, the simplest depth/wavelength integrated models performed no worse than the more complex depth/wavelength resolved models. Ocean color models were not highly challenged in extreme conditions of surface chlorophyll-a and sea surface temperature, nor in high-nitrate low-chlorophyll waters. Water column depth was the primary influence on ocean color model performance such that average skill was significantly higher at depths greater than 250 m, suggesting that ocean color models are more challenged in Case-2 waters (coastal) than in Case-1 (pelagic) waters. Given that in situ chlorophyll-a data was used as input data, algorithm improvement is required to eliminate the poor performance of ocean color NPP models in Case-2 waters that are close to coastlines. Finally, ocean color chlorophyll-a algorithms are challenged by optically complex Case-2 waters, thus using satellite-derived chlorophyll-a to estimate NPP in coastal areas would likely further reduce the skill of ocean color models. Virginia Inst Marine Sci, Coll William & Mary, Gloucester Point, VA 23062 USA CNRS, LOV, Villefranche Sur Mer, France Univ Paris 06, UMR 7093, Villefranche Sur Mer, France SUNY Stony Brook, Sch Marine & Atmospher Sci, Stony Brook, NY 11794 USA Tokyo Univ Informat Sci, Chiba 2658501, Japan Oregon State Univ, Dept Bot & Plant Pathol, Corvallis, OR 97331 USA Univ Estadual Paulista, BR-11330900 São Paulo, Brazil European Commiss, Joint Res Ctr, I-21027 Ispra, Italy NOAA, NMFS, Narragansett Lab, Narragansett, RI 02882 USA Nagoya Univ, Hydrospher Atmospher Res Ctr, Nagoya, Aichi 4648601, Japan Seikai Natl Fisheries Res Inst, Ishigaki Trop Stn, Okinawa 9070451, Japan CUNY, Brooklyn Coll, Dept Geol, Brooklyn, NY 11210 USA Univ Roma Tor Vergata, Dept Biol, I-00173 Rome, Italy Plymouth Marine Lab, Plymouth PL1 3DH, Devon, England Fisheries & Oceans Canada, Inst Freshwater, Winnipeg, MB R3T 2N6, Canada Univ Calif San Diego, Scripps Inst Oceanog, La Jolla, CA 92093 USA NOAA, Coastal Serv Ctr, Charleston, SC 29405 USA Univ Estadual Paulista, BR-11330900 São Paulo, Brazil NASA: NNG06GA03G
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- 2011
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