Assessing the uncertainties of model estimates of primary productivity in the tropical Pacific Ocean

被引:188
作者
Friedrichs, Marjorie A. M. [1 ]
Carr, Mary-Elena [2 ]
Barber, Richard T. [3 ]
Scardi, Michele [4 ]
Antoine, David [5 ,6 ]
Armstrong, Robert A. [7 ]
Asanuma, Ichio [8 ]
Behrenfeld, Michael J. [9 ]
Buitenhuis, Erik T. [10 ]
Chai, Fei [11 ]
Christian, James R. [12 ]
Ciotti, Aurea M. [13 ]
Doney, Scott C. [14 ]
Dowell, Mark [15 ]
Dunne, John [16 ]
Gentili, Bernard [5 ,6 ]
Gregg, Watson [17 ]
Hoepffner, Nicolas [15 ]
Ishizaka, Joji [18 ]
Kameda, Takahiko [19 ]
Lima, Ivan [14 ]
Marra, John [20 ]
Melin, Frederic [15 ]
Moore, J. Keith [21 ]
Morel, Andre [5 ,6 ]
O'Malley, Robert T. [9 ]
O'Reilly, Jay [22 ]
Saba, Vincent S. [1 ]
Schmeltz, Marjorie [2 ]
Smyth, Tim J. [23 ]
Tjiputra, Jerry [24 ]
Waters, Kirk [25 ]
Westberry, Toby K. [9 ]
Winguth, Arne [26 ]
机构
[1] Virginia Inst Marine Sci, Coll William & Mary, Gloucester Point, VA 23062 USA
[2] CALTECH, Jet Prop Lab, Pasadena, CA 91101 USA
[3] Duke Univ, Marine Lab, Beaufort, NC 28516 USA
[4] Univ Roma Tor Vergata, Dept Biol, I-00133 Rome, Italy
[5] Univ Paris 06, Paris 6, France
[6] CNRS, Lab Oceanog Villefranche, Paris, France
[7] SUNY Stony Brook, Sch Marine & Atmospher Sci, Stony Brook, NY 11794 USA
[8] Tokyo Univ Informat Sci, Wakaba Ku, Chiba 2658501, Japan
[9] Oregon State Univ, Dept Bot & Plant Pathol, Corvallis, OR 97331 USA
[10] Univ E Anglia, Lab Global Marine & Atmospher Chem, Sch Environm Sci, Norwich NR4 7TJ, Norfolk, England
[11] Univ Maine, Sch Marine Sci, Orono, ME 04469 USA
[12] Fisheries & Oceans Canada, Sidney, BC V8L 4B2, Canada
[13] Univ Estadual Paulista, BR-11330900 Sao Paulo, Brazil
[14] Woods Hole Oceanog Inst, Dept Marine Chem & Geochem, Woods Hole, MA 02543 USA
[15] Commiss European Communities, Joint Res Ctr, I-21020 Ispra, Italy
[16] Geophys Fluid Dynam Lab, Princeton, NJ 08540 USA
[17] NASA, Goddard Space Flight Ctr, Global Modeling & Assimilat Off, Greenbelt, MD 20771 USA
[18] Nagasaki Univ, Fac Fisheries, Nagasaki 8528521, Japan
[19] Natl Res Inst Far Seas Fisheries, Grp Oceanog, Shizuoka 4248633, Japan
[20] CUNY Brooklyn Coll, Dept Geol, Brooklyn, NY 11210 USA
[21] Univ Calif Irvine, Dept Earth Syst Sci, Irvine, CA 92697 USA
[22] NOAA NMFS Narragansett Lab, Narragansett, RI 02887 USA
[23] Plymouth Marine Lab, Plymouth PL1 3DH, Devon, England
[24] Bjerknes Ctr Climate Res, N-5007 Bergen, Norway
[25] NOAA Coastal Serv Ctr, Charleston, SC 29405 USA
[26] Univ Texas Arlington, Dept Earth & Environm Sci, Arlington, TX 76019 USA
关键词
Primary production; Modeling; Remote sensing; Satellite ocean color; Statistical analysis; Tropical Pacific Ocean (15 degrees N to 15 degrees S and 125 degrees E; to 95 degrees W); MARINE ECOSYSTEM MODEL; EQUATORIAL PACIFIC; SATELLITE CHLOROPHYLL; METAL CONTAMINATION; SKILL ASSESSMENT; ARABIAN SEA; LIGHT; PHOTOSYNTHESIS; ASSIMILATION; ACCLIMATION;
D O I
10.1016/j.jmarsys.2008.05.010
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Depth-integrated primary productivity (PP) estimates obtained from satellite ocean color-based models (SatPPMs) and those generated from biogeochemical ocean general circulation models (BCGCMs) represent a key resource for biogeochemical and ecological studies at global as well as regional scales. Calibration and validation of these PP models are not straightforward, however, and comparative studies show large differences between model estimates. The goal of this paper is to compare PP estimates obtained from 30 different models (21 SatPPMs and 9 BOGCMs) to a tropical Pacific PP database consisting of similar to 1000 C-14 measurements spanning more than a decade (1983-1996). Primary findings include: skill varied significantly between models, but performance was not a function of model complexity or type (i.e. SatPPM vs. BOGCM); nearly all models underestimated the observed variance of PR specifically yielding too few low PP (< 0.2 g Cm-2 d(-1)) values; more than half of the total root-mean-squared model-data differences associated with the satellite-based PP models might be accounted for by uncertainties in the input variables and/or the PP data; and the tropical Pacific database captures a broad scale shift from low biomassnormalized productivity in the 1980s to higher biomass-normalized productivity in the 1990s, which was not successfully captured by any of the models. This latter result suggests that interdecadal and global changes will be a significant challenge for both SatPPMs and BOGCMs. Finally, average root-mean-squared differences between in situ PP data on the equator at 140 degrees W and PP estimates from the satellite-based productivity models were 58% lower than analogous values computed in a previous PP model comparison 6 years ago. The success of these types of comparison exercises is illustrated by the continual modification and improvement of the participating models and the resulting increase in model skill. (C) 2008 Elsevier BY. All rights reserved.
引用
收藏
页码:113 / 133
页数:21
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