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Modeling and Data Assimilation

  • John R. Moisan
  • Arthur J. Miller
  • Emanuele Di Lorenzo
  • John Wilkin
Part of the Remote Sensing and Digital Image Processing book series (RDIP, volume 7)

Keywords

Data Assimilation Coastal Ocean Colored Dissolve Organic Matter Ocean Color Biogeochemical Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Abbott, M. R. and D. B. Chelton. 1991. Advances in passive remote sensing of the ocean, Review of Geophysics, Supplement:571-589.Google Scholar
  2. Abbott, M. R., P. J. Richerson, and T. M. Powell. 1982. In situ response of phytoplankton fluorescence to rapid variations in light, Limnology and Oceanography, 27:218-225.Google Scholar
  3. Abbott, M. R. and R. M. Letelier. 1998. Decorrelation scales of chlorophyll as observed from bio-optical drifters in the California Current, Deep-Sea Research, 45:1639-1668.Google Scholar
  4. Anderson, L. A., A. R. Robinson, and C. J. Lozano. 2000. Physical and biological modeling in the Gulf Stream region: I. Data assimilation methodology, Deep-Sea Research I, 47:1787-1827.Google Scholar
  5. Anderson, L. A. and A. R. Robinson. 2001. Physical and biological modeling in the Gulf Stream region Part II. Physical and biological processes, Deep-Sea Research I, 48:1139-1168.Google Scholar
  6. Anderson, T. R. and P. J. le B. Williams. 1998. Modelling the seasonal cycle of dissolved organic carbon at Station E1 in the English Channel, Estuarine, Coastal and Shelf Science, 46:93-109.Google Scholar
  7. Antoine, D. and A. Morel. 1995. Modelling the seasonal course of the upper ocean pCO2 (2) Validation of the model and sensitivity studies, Tellus, 47B:103-121.Google Scholar
  8. Balch, W. M., R. W. Eppley, and M. R. Abbott. 1989a. Remote sensing of primary production—I. A comparison of empirical and semi-analytical algorithms, Deep-Sea Research, 36:281-295.Google Scholar
  9. Balch, W. M., R. W. Eppley, and M. R. Abbott. 1989b. Remote sensing of primary production—II. A semianalytic algorithm based on pigments, temperature and light, Deep-Sea Research, 36:1201-1217.Google Scholar
  10. Balch, W., R. Evans, J. Brown, G. Feldman, C. McClain, and W. Esaias. 1992. The remote sensing of ocean primary productivity: Use of new data compilation to test satellite algorithms, Journal of Geophysical Research, 97:2279-2293.Google Scholar
  11. Balch, W. M. and C. F. Byrne. 1994. Factors affecting the estimate of primary production from space, Journal of Geophysical Research, 99:7555-7570.Google Scholar
  12. Balzer, W., W. Helder, E. Epping, L. Lohse, and S. Otto. 1998. Benthic denitrification and nitrogen cycling at the slope and rise of the N. W. European Continental Margin (Goban Spur), Progress in Oceanography, 42:111-126.Google Scholar
  13. Behrenfeld, M. J. and P. G. Falkowski. 1997a. A consumer’s guide to phytoplankton primary productivity models, Limnology and Oceanography, 42:1479-1491.CrossRefGoogle Scholar
  14. Behrenfeld, M. J. and P. G. Falkowski. 1997b. Photosynthetic rates derived from satellite-based chlorophyll concentration, Limnology and Oceanography, 42:1-20.Google Scholar
  15. Bennett, A. F., 1992: Inverse Methods in Physical Oceanography. Monographs on Mechanics and Applied Mathematics. Cambridge University Press, 346 pp., reprinted 1999, 2003.Google Scholar
  16. Bennett, A. F., 2002. Inverse Modeling of the Ocean and Atmosphere. Cambridge University Press, 234 pp.Google Scholar
  17. Bernstein, R. L., L. Breaker, and R. Whritner. 1997. California current eddy formation: Ship, air, and satellite results, Science, 195:353-359.Google Scholar
  18. Bissett, W. P., J. J. Walsh, D. A. Dieterle, and K. L. Carder. 1999a. Carbon cycling in the upper waters of the Sargasso Sea: I. Numerical simulation of differential carbon and nitrogen fluxes, Deep-Sea Research I, 46:205-269.Google Scholar
  19. Bissett, W. P., K. L. Carder, J. J. Walsh, and D. A. Dieterle. 1999b. Carbon cycling in the upper waters of the Sargasso Sea: II. Numerical simulation of differential carbon and nitrogen fluxes, Deep-Sea Research I, 46:271-317.Google Scholar
  20. Bissett, W. P., H. Arango, R. Arnone, R. Chant, S. Glenn, C. Mobley, M. A. Moline, O. M. Schofield, R. Steward, and J. Wilkin. 2004. The prediction of hyperspectral inherent optical properties in the New Jersey Bight, In Prep.Google Scholar
  21. Broecker, W. S. and T.–H. Peng. 1982. Tracers in the Sea, Lamont-Doherty Geological Observatory, Columbia University, 690 pp.Google Scholar
  22. Brown, O. B., R. H. Evans, J. W. Brown, H. R. Gordon, R. C. Smith, and K. S. Baker. 1985. Phytoplankton blooming off the U.S. East Coast: A satellite description, Science, 229:163-167.Google Scholar
  23. Carlson, C. A., H. W. Ducklow, and T. D. Sleeter. 1996. Stocks and dynamics of bacterioplankton in the northwestern Sargasso Sea, Deep-Sea Research II, 43:491-515.Google Scholar
  24. Campbell, J., D. Antoine, R. Armstrong, K. Arrigo, W. Balch, R. Barber, M. Behrenfeld, R. Bidigare, J. Bishop, M.-E. Carr, W. Esaias, P. Falkowski, N. Hoepffner, R. Iverson, D. Kiefer, S. Lorenz, J. Marra, A. Morel, J. Ryan, V. Vedernikov, K. Waters, C. Yentch, and J. Yoder. 2002. Comparison of algorithms for estimating ocean primary production from surface chlorophyll, temperature, and irradiance, Global Biogeochemical Cycles, 16(3), 10.1029/2001GB001444.Google Scholar
  25. Carder, K. L., F. R. Chen, Z. P. Lee, S. K. Hawes, and D. Kamykowski. 1999. Semianalytic moderateresolution algorithms for chlorophyll a and absorption with bio-optical domains based on nitrate-depletion temperatures, Journal of Geophysical Research, 104:5403-5421.Google Scholar
  26. Chelton, D. B., P. A. Bernal, and J. A. McGowan. 1982. Large-scale interannual physical and biological interaction in the California Current, Journal of Marine Research, 40:1095-1125.Google Scholar
  27. Christian, J. R., M. A. Verschell, R. Murtugudde, A. J. Busalacchi, and C. R. McClain. 2002a. Biogeochemical modelling of the tropical Pacific Ocean. I: Seasonal and interannual variability, Deep-Sea Research II, 49:509-543.Google Scholar
  28. Christian, J. R., M. A. Verschell, R. Murtugudde, A. J. Busalacchi, and C. R. McClain. 2002b. Biogeochemical modelling of the tropical Pacific Ocean. II: Iron biogeochemistry, Deep-Sea Research II, 49:545-565.Google Scholar
  29. Di Lorenzo, E., A. J. Miller, D. J. Neilson, B. D. Cornuelle, and J. R. Moisan. 2004. Modeling observed California Current mesoscale eddies and the ecosystem response, International Journal of Remote Sensing, 25:1307-1312.Google Scholar
  30. Doerffer, R. and J. Fischer. 1994. Concentrations of chlorophyll, suspended matter, and gelbstoff in case II waters derived from satellite coastal zone color scanner data with inverse modeling methods, Journal of Geophysical Research, 99:7457-7466.Google Scholar
  31. Doney, S. C., D. M. Glover, and R. J. Najjar. 1996. A new coupled, one-dimensional biological-physical model for the upper ocean: Applications to the JGOFS Bermuda Atlantic Time-series Station (BATS) site, Deep-Sea Research II, 43:591-624.Google Scholar
  32. Eppley, R. W., E. Stewart, M. R. Abbott, and U. Heyman. 1985. Estimating primary production from satellite chlorophyll. Introduction to regional differences and statistics for the Southern California Bight, Journal of Plankton Research, 7:57-70.Google Scholar
  33. Falkowski, P. G., M. J. Behrenfeld, W. E. Esaias, W. Balch, J. W. Campbell, R. L. Iverson, D. A. Kiefer, A. Morel, and J. A. Yoder. 1998. Satellite primary productivity data and algorithm development: A science plan for Mission to Planet Earth, SeaWiFS Tech. Rep. Ser., Vol. 42, S. F. Hooker (ed.). NASA/TM-1998- 1045566, pp. 36.Google Scholar
  34. Fasham, M. J. R., H. W. Ducklow, and S. W. McKelvie. 1990. A nitrogen-based model of plankton dynamics in the ocean mixed layer, Journal of Marine Research, 48:591-639.Google Scholar
  35. Fasham, M. J. R. 1995. Variations in the seasonal cycle of biological production in subarctic ocean: A model sensitivity analysis, Deep-Sea Research I, 42:1111-1149.Google Scholar
  36. Fasham, M. J. R. and G. T. Evans. 1995. The use of optimization techniques to model marine ecosystem dynamics at the JGOFS station at 47° N 20° W, Philosophical Transaction of the Royal Society of London B, 348:203-209.Google Scholar
  37. Fasham, M. J. R., P. W. Boyd, and G. Savidge. 1999. Modeling the relative contributions of autotrophs and heterotrophs to carbon flow at a Lagrangian JGOFS station in the Northeast Atlantic: The importance of DOC, Limnology and Oceanography, 44:80-94.CrossRefGoogle Scholar
  38. Franks, P. J. S. 1995. Coupled physical-biological models in oceanography, Reviews in Geophysics, Supplement:1177-1187.Google Scholar
  39. Friedrichs, M. A. M. 2001. A data assimilative marine ecosystem model of the central equatorial Pacific: Numerical twin experiments. Journal of Marine Research, 59:859-894.Google Scholar
  40. Fox, D. N., W. J. Teague, C. N. Barron, M. R. Carnes, and C. M. Lee. 2001. The Modular Ocean Data Assimilation System (MODAS), Journal of Atmospheric and Oceanic Technology, 19:240-252.Google Scholar
  41. Gallaway, J. N., R. W. Howarth, A. F. Michaels, S. W. Nixon, J. M. Prospero, and F. J. Dentener. 1996. Nitrogen and phosphorus budgets of the North Atlantic Ocean and its watershed, Biogeochemistry, 35:3- 25.Google Scholar
  42. Garver, S. A. and D. A. Siegel. 1997. Inherent optical property inversion of ocean color spectra and its biogeochemical interpretation. 1. Time series from the Sargasso Sea, Journal of Geophysical Research, 102:18,607-18,625.Google Scholar
  43. Geider, R. J. 1987. Light and temperature dependence of the carbon to chlorophyll ratio in microalgae and cyanobacteria: implications for physiology and growth of phytoplankton. New Phytology, 106:1-34.Google Scholar
  44. Gill, A. E. and P. P. Niiler. 1973. The theory of seasonal variability in the ocean, Deep-Sea Research, 20:141- 177.Google Scholar
  45. Gordon, H. R. and D. K. Clark. 1980. Clear water radiances for atmospheric correction of coastal zone color scanner imagery, Applied Optics, 20:4175-4180.Google Scholar
  46. Gordon, H. R., O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker, and D. K. Clark. 1988. A semi-analytical radiance model of ocean color, Journal of Geophysical Research, 93:10,909-10,924.Google Scholar
  47. Gordon, D. C., P. R. Boudreaum K. H. Mann, J. –E. Ong, W. L. Silvert, S. V. Smith, G. Wattayakorn, F. Wulff, and T. Yanagi. 1996. LOICZ Biogeochemical Modeling Guidelines, LOICZ/R&S/95-5, VI +96 pp. LOICZ, Texel, Netherlands.Google Scholar
  48. Gregg, W. W. and J. J. Walsh. 1992. Simulation of the 1979 spring bloom in the Mid-Atlantic Bight: A coupled physical/biological/optical model, Journal of Geophysical Research, 97:5723-5743.Google Scholar
  49. Gross, L., S. Thiria, R. Frouin, and B. G. Mitchell. 2000. Artificial neural networks for modeling the transfer function between marine reflectance and phytoplankton pigments concentration, Journal of Geophysical Research, 105:3483-3495.Google Scholar
  50. Haidvogel, D. B. and A. Beckmann. 1999. Numerical Ocean Circulation Modeling, Imperial College Press, London, 320 pp.Google Scholar
  51. Harmon, R. and P. Challenor. 1997. A Markov chain Monte Carlo method for estimation and assimilation into models, Ecological Modeling, 101:41-59.Google Scholar
  52. Hecky, R. E. and P. Kilman. 1984. Nutrient limitation of phytoplankton in freshwater and marine environments: A review of recent evidence on the effects of enrichment, Limnology and Oceanography, 33:796-822.CrossRefGoogle Scholar
  53. Hickey, B.M. 1993. Physical oceanography. In: Marine Ecology of the Southern California Bight, Hood, D. (ed.) Pergamon Press.Google Scholar
  54. Hickey, B.M. 1998. Coastal Oceanography of Western North America from the tip of Baja California to Vancouver Is., In: Volume 11, Chapter 12, The Sea, K.H. Brink and A.R. Robinson (eds.), pp. 345-393, Wiley and Sons, Inc.Google Scholar
  55. Hofmann, E. E. and J. W. Ambler. 1988. Plankton dynamics on the outer southeastern U. S. continental shelf. Part II: A time-dependent biological model, Journal of Marine Research, 46:883-917.Google Scholar
  56. Hofmann, E. E. and C. M. Lascara. 1998. Overview of interdisciplinary modeling for marine ecosystems, in The Sea, Vol. 10, K. H. Brink and A. R. Robinson (eds.), John Wiley and Sons Ltd., pp 507-540.Google Scholar
  57. Hoge, F. E., C. W. Wright, P. E. Lyon, R. N. Swift, and J. K. Yungel. 1999. Satellite retrieval of inherent optical properties by inversion of an oceanic radiance model: a preliminary algorithm, Applied Optics, 38: 495-540.Google Scholar
  58. Hoge, F. E., C. W. Wright, P. E. Lyon, R. N. Swift, and J. K. Yungel. 2001. Inherent optical properties imagery of the western North Atlantic Ocean: Horizontal spatial variability of the upper mixed layer, Journal of Geophysical Research, 106:31,129-31,140.Google Scholar
  59. Howard, K. L., and J. A. Yoder. 1997. Contribution of the subtropical ocean to global primary production, In Space Remote Sensing of the Subtropical Oceans, C. T-. Liu (Ed.), Pergamon Press, New York, 157-168.Google Scholar
  60. Hurtt, G. C. and R. T. Armstrong. 1996. A pelagic ecosystem model calibrated with BATS data, Deep-Sea Research II, 43:653-683.Google Scholar
  61. Hurtt, G. C. and R. T. Armstrong. 1999. A pelagic ecosystem model calibrated with BATS and OWSI data, Deep-Sea Research II, 46:27-61.Google Scholar
  62. 254.
    254 Moisan, Miller, Di Lorenzo and Wilkin Iverson, R. L., W. E. Esaias, and K. R. Turpie. 2000. Ocean annual phytoplankton carbons and new production, and annual export production estimated with empirical equations and CZCS data, Global Change Biology, 6:57-72.Google Scholar
  63. Kiefer, D. A. and B. G. Mitchell. 1983. A simple steady-state description of phytoplankton growth based on absorption cross-section and quantum efficiency, Limnology and Oceanography, 28:770-776.CrossRefGoogle Scholar
  64. King, M. D., J. Closs, S. Spangler, and R. Greenstone (eds.). 2003. EOS Data Products Handbook, Vol. 1, NASA Goddard Space Flight Center, pp. 225.Google Scholar
  65. Kwiatowska, E. J. and G. S. Fargion. 2003. Merger of ocean color data from multiple satellite missions within the SIMBIOS project, In: Ocean Remote Sensing and Applications, Frouin R. J., Y. Yuan, and H. Kawamura (eds.), Proceedings of the Society of Photo-Optical Engineering (SPIE), 4892:168-182.Google Scholar
  66. Lawson, L. M., Y. H. Spitz, E. E. Hofmann, and R. B. Long. 1995. A data assimilation technique applied to a predator-prey model, Bulletin of Mathematical Biology, 57:593-617.Google Scholar
  67. Lawson, L. M., E. E. Hofmann, and Y. H. Spitz. 1996. Time series sampling and data assimilation in a simple marine ecosystem model, Deep-Sea Research II, 43:625-651.Google Scholar
  68. LeBaron, P., P. Servais, H. Agogué, C. Courties, and F. Joux. 2001. Does the high nucleic acid content of individual bacterial cells allow us to discriminate between active cells and inactive cells in aquatic systems? Applied Environmental Microbiology 67:1775-1782.Google Scholar
  69. Lermusiaux, P. F. J. and A. R. Robinson. 1999. Data assimilation via error subspace statistical estimation. Part I: Theory and schemes, Monthly Weather Review, 127:1385-1407.Google Scholar
  70. Lewis, E. and D. W. R. Wallace. 1998. Program Developed for CO2 System Calculations. ORNL/CDIAC- 105. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee.Google Scholar
  71. Liu, K.-K., S. –Y. Chao, P. –T. Shaw, G. C. Gong, C. C. Chen, and T. Y. Tang. 2002. Monsoon forced chlorophyll distribution and primary productivity in the South China Sea: observations and a numerical study. Deep-Sea Research Part I, 49:1387-1412.Google Scholar
  72. Lorenzen, C. J. 1970. Surface chlorophyll as an index of the depth, chlorophyll content and primary productivity of the euphotic layer, Limnology and Oceanography, 15:479-480.CrossRefGoogle Scholar
  73. Lozano, C. J., A. R. Robinson, H. G. Arango, A. Gangopadhyay, Q. Sloan, P. J. Haley, L. Anderson, and W. Leslie. 1996. An interdisciplinary ocean prediction system: Assimilation strategies and structured data sets, In: Modern Approached to Data Assimilation in Ocean Modeling, P. Malanotte-Rizzoli (ed.), pg. 413-452, Elsevier Science, B. V.Google Scholar
  74. Lynch, D. R., J. T. C. Ip, C. E., Naimie, and F. E. Werner. 1996. Comprehensive circulation model with application to the Gulf of Maine, Continental Shelf Research, 16:875-906.Google Scholar
  75. Mantua, N, D. Haidvogel, Y. Kushnir, and N. Bond. 2002. Making the climate connections: Bridging scales of space and time in the U. S. GLOBEC Program, Oceanography, 15(2):75-87.Google Scholar
  76. Marchesiello, P., J. C. McWilliams, and A. Shchepetkin. 2001. Open boundary conditions for long-term integration of regional oceanic models, Ocean Modelling, 3:1-20.Google Scholar
  77. Marchesiello, P., J. C. McWilliams, and A. Shchepetkin. 2002. Equilibrium structure and dynamics of the California Current System, Journal of Physical Oceanography, 33, Sub judice.Google Scholar
  78. Maritorena, S., D. A. Siegel, and A. R. Peterson. 2002. Optimization of a semianalytical ocean color model for global-scale applications, Applied Optics, 41(15): 2705-2714.Google Scholar
  79. Matear, R. J. 1995. Parameter optimization and analysis of ecosystem models using simulated annealing: A case study at Station P, Journal of Marine Research, 53:571-607.Google Scholar
  80. Matear, R. J. and G. Holloway. 1995. Modeling the inorganic phosphorus cycle of the North Pacific using an adjoint data assimilation model to assess the role of dissolved organic phosphorus, Global Biogeochemical Cycles, 9:101-119.Google Scholar
  81. McClain, C. R., K. Arrigo, K.-S. Tai, and D. Turk. 1996. Observations and simulations of physical and biological processes at ocean weather station P, 1951-1980, Journal of Geophysical Research, 101:3697- 3713.Google Scholar
  82. McGillicuddy, D. J., J. J. McCarthy, and A. R. Robinson. 1995. Coupled physical and biological modeling of the spring bloom in the North Atlantic (I): model formulation and one-dimensional bloom processes, Deep-Sea Research Part I, 42:1313-1357.Google Scholar
  83. McGillicuddy, D. J., D. R. Lynch, A. M. Moore, W. C. Gentelman, C. S. Davis, and C. J. Meise. 1998. An adjoint data assimilation approach to diagnosis of physical and biological controls of Pseudocalanus spp.Google Scholar
  84. in the Gulf of Maine—Georges Bank region, Fisheries Oceanography, 7:205-218.Google Scholar
  85. McGowan, J. A., S. J. Bograd, R. J. Lynn, and A. J. Miller. 2003. The biological response to the 1977 regime shift in the California Current, Deep-Sea Research II, Sub judice.Google Scholar
  86. Miller, A. J. and B. D. Cornuelle. 1999. Forecasts from fits of frontal fluctuations, Dynamics of Atmospheres and Oceans, 29:305-333.Google Scholar
  87. Miller, A. J., E. Di Lorenzo, D. J. Neilson, B. D. Cornuelle and J. R. Moisan. 2000. Modeling CalCOFI observations during El Nino: Fitting physics and biology. California Cooperative Oceanic Fisheries Investigations Reports, 41:87-97.Google Scholar
  88. Modeling and Data Assimilation 255 Moisan, J. R. 1993. Modeling nutrient and plankton processes in the California Coastal Transition Zone. Ph.D. thesis, Old Dominion University, Norfolk, VA., 214 pp.Google Scholar
  89. Moisan, J. R. and E. E. Hofmann. 1996. Modeling nutrient and plankton processes in the California Coastal Transition Zone. 1. A time- and depth-dependent model, Journal of Geophysical Research, 101:22,647- 22,676.Google Scholar
  90. Moisan, J. R., E. E. Hofmann, and D. B. Haidvogel. 1996. Modeling nutrient and plankton processes in the California Coastal Transition Zone. 2. A three-dimensional physical-bio-optical model, Journal of Geophysical Research, 101:22,677-22,691.Google Scholar
  91. Moisan, J. R. and P. P. Niiler. 1998. The seasonal heat budget of the North Pacific: Net heat flux and heat storage rates (1950-1990), Journal of Physical Oceanography, 28:401-421.Google Scholar
  92. Moisan, J. R., T. K. Moisan, and M. R. Abbott. 2002. Modeling the effect of temperature on the maximum growth rates of phytoplankton populations, Ecological Modeling, 153:197-215.Google Scholar
  93. Moisan, J. R., A. Shchepetkin, E. Di Lorenzo, P. Marchesiello, K. Stolzenbach, A. J. Miller, and J. C. McWilliams. 2004. Modeling the biogeochemical processes in the coastal ocean along the U.S. Continental Margin: Calibrations using one dimensional simulations, Journal of Geophysical Research, In Prep.Google Scholar
  94. Moisan, T. A. and B. G. Mitchell. 1999. Photophysiological acclimation of Phaeocystis antarctica Karsten under light limitation, Limnology and Oceanography, 44:247-258.CrossRefGoogle Scholar
  95. Moloney, C. L., J. G. Field, and M. I. Lucas. 1991. The size-based dynamics of plankton food webs. II. Simulation of three contrasting southern Benguela food webs, Journal of Plankton Research, 13:1039- 1092.Google Scholar
  96. Moore, A. M., H. G. Arango, E. Di Lorenzo, B. D. Cornuelle, A. J. Miller, and D. J. Nelson. 2004. A comprehensive ocean prediction and analysis system based on the tangent linear and adjoint components of a regional ocean model, Ocean Modeling, 7:227-258.Google Scholar
  97. Mullon, C., P. Cury, and P. Penven. 2002. Evolutionary individual-based model for the recruitment of anchovy (Engraulis capensis) in the southern Bengula, Canadian Journal Fisheries and Aquatic Science, 59:910-922.Google Scholar
  98. Nixon, S. W., J. W. Ammerman, L. P. Atkinson, V. M. Berounsky, G. Billen, W. C. Boicourt, W. R. Boynton, T. M. Church, D. M. Ditoro, R. Elmgren, J. H. Garber, A. E. Giblin, R. A. Jahnke, N. J. P. Owens, M. E. Q. Pilson, and S. P. Seitzinger. 1996. The fate of nitrogen and phosphorus at the land-sea margin of the North Atlantic Ocean. Biogeochemistry, 35:141-180.Google Scholar
  99. Ocean.US. 2002. An Integrated and Sustained Ocean Observing System (IOOS) for the United States: Design and Implementation, Ocean.US, Arlington, VA, 21 pp.Google Scholar
  100. Oguz, T., P. Malanotte-Rizzoli, and D. Aubrey. 1995. Wind and thermohaline circulation of the Black Sea driven by yearly mean climatological forcing, Journal of Geophysical Research, 100:6845-6863, 1995.Google Scholar
  101. Oguz, T., H. W. Ducklow, and P. Malanotte-Rizzoli. 2000. Modeling distinct vertical biogechemical structure of the Black Sea: Dynamical coupling of the oxic, suboxic, and anoxic layers, Global Biogeochemical Cycles, 14:1331-1352.Google Scholar
  102. Oguz, T., P. Malanotte-Rizzoli, H. W. Ducklow, and J. W. Murray. 2002. Interdisciplinary studies integrating the Black Sea biogeochemistry and circulation dynamics, Oceanography, 15:4-11.Google Scholar
  103. Olivieri, R. A. and F. P. Chavez. 2000. A model of plankton dynamics for the coastal upwelling system of Monterey Bay, California, Deep-Sea Research II, 47:1077-1106.Google Scholar
  104. O’Reilly, J. E., S. Maritorena, B. G. Mitchell, D. A. Siegel, K. L. Carder, S. A. Garver, M. Kahru, and C. McClain. 1998. Ocean color chlorophyll algorithms for SeaWiFS, Journal of Geophysical Research, 103:24,937-24,953.Google Scholar
  105. O’Reilly, J. E., and 21 co-authors. 2000. Ocean color chlorophyll a algorithms for SeaWiFS, OC2, and OC4: Version 4. Chapter 2 in SeaWiFS Post-launch Calibration and Validation Analyses, Part 3, SeaWiFS Postlaunch Technical Memorandum Series, Vol. 11, NASA.Google Scholar
  106. Orr, J. C. 1999. Ocean Carbon-Cycle Model Intercomparison Project (OCMIP): Pase 1 (1995-1997), GAIM Report 7, IGBP/GAIM Office, EOS, Univ. of New Hampshire, Durham, NH.Google Scholar
  107. Penven, P., C. Roy, G. B. Brundrit, A. Colin de Verdiere, P. Freon, A. S. Johnson, J. R. E. Lutjeharms, and F. A. Shillington. 2001. A regional hydrodynamic model of upwelling in the Southern Benguela, South African Journal of Science, 97:1-4.Google Scholar
  108. Pickard, G. L., and W. J. Emery. 1990. Descriptive Physical Oceanography, An Introduction, Butterwork Heinmann, Oxford, 320 pp.Google Scholar
  109. Platt, T. 1986. Primary production of the ocean water column as a function of surface light intensity: algorithms for remote sensing, Deep-Sea Research, 33:149-163.Google Scholar
  110. Pontius, R. G. 2002. Statistical methods to partition effects of quantity and location during comparison of categorical maps at multiple resolution, Photogrammetric Engineering and Remote Sensing, 68:1041- 1049.Google Scholar
  111. Prospero, J. M., K. Barrett, T. Church, F. Dentener, R. A. Duce, J. N. Galloway, H. Levy II, J. Moody, and P. Quinn. 1996. Atmospheric deposition of nutrients to the North Atlantic Basin, Biogeochemistry, 35:27- 73.Google Scholar
  112. Prunet, P., J.-F. Minster, D. Ruiz-Pino, and I. Dadou. 1996a. Assimilation of surface data into a onedimensional physical-biogeochemical model of the surface ocean. 1. Method and preliminary results, Global Biogeochemical Cycles, 10:111-138.Google Scholar
  113. Prunet, P., J.-F. Minster, V. Echevin, and I. Dabou. 1996b. Assimilation of surface data into a one-dimensional physical-biogeochemical model of the surface ocean. 2. Adjusting a simple trophic model to chlorophyll, temperature, nitrate and pCO2 data, Global Biogeochemical Cycles, 10:139-158.Google Scholar
  114. Robinson, A. R. 1996. Physical processes, field estimation and an approach to interdisciplinary ocean modeling, Earth-Science Reviews, 40:3-54.Google Scholar
  115. Robinson, A. R., H. Arango, A. Warn-Varnas, W. G. Leslie, A. J. Miller, P. J. Haley, and C. J. Lozano. 1996.Google Scholar
  116. Real-time regional forecasting, In: Modern Approached to Data Assimilation in Ocean Modeling, P. Malanotte-Rizzoli (ed.), pg. 377-410, Elsevier Science, B. V. Robinson, A. R., and P. F. J. Lermusiaux (eds.). 2000. Workshop on the assimilation of biological data in coupled physical/ecosystem models, GLOBEC Special Contribution 3, 152 pp.Google Scholar
  117. Roemmich, D. 1992. Ocean warming and sea level rise along the southwest U.S. coast, Nature, 257:373-375.Google Scholar
  118. Roemmich, D. and J. McGowan. 1995. Climate warming and the decline of zooplankton in the California Current, Science, 267:1324-1326.Google Scholar
  119. Ryther, J. H. and C. S. Yentsch. 1957. The estimation of phytoplankton production in the ocean from chlorophyll and light data, Limnology and Oceanography, 2:281-286.Google Scholar
  120. Seitzinger, S. P. and A. E. Giblin. 1996. Estimating denitrification in North Atlantic continental shelf sediments, Biogeochemistry, 35:235-260.Google Scholar
  121. Semovski, S. V., B. Wozniak, and V. N. Pelevin. 1995. Multispectral ocean color data assimilation in a model of plankton dynamics, Studia I Materialy Oceanologia, Marine Physics, 68:125-147.Google Scholar
  122. Semovski, S. V., and B. Wozniak. 1995. Model of the annual phytoplankton cycle in the marine ecosystem— assimilation of monthly satellite chlorophyll data for the North Atlantic and Baltic, Oceanologia, 37:3-31.Google Scholar
  123. Shchepetkin, A. F., and J. C. McWilliams. 2003. The Regional Ocean Modeling System: A split-explicit, freesurface, topography following coordinates ocean model, unpublished manuscript.Google Scholar
  124. Siegel, D. A., Maritorena, S., Nelson, N. B., Hansell, D. A., and Lorenzi-Kayser, M. 2003. Global distribution and dynamics of colored dissolved and detrital organic materials. Journal of Geophysical Research, 107(12):10.1029/2001JC000965.Google Scholar
  125. Sieracki, M. E., E. M. Haugen, and T. L. Cucci. 1995. Overestimation of heterotrophic bacteria in the Sargasso Sea: direct evidence by flow and imaging cytometry, Deep-Sea Research I, 42:1399-1409.Google Scholar
  126. Signorini, S. R., C. R. McClain, J. R. Christian, and C. S. Wong. 2001. Seasonal and interannual variability of phytoplankton, nutrients, TCO2, pCO2, and O2 in the eastern subarctic Pacific (ocean weather station Papa), Journal of Geophysical Research, 106:31,197-31,215.Google Scholar
  127. Smith, R. C. and K. S. Baker. 1978. The bio-optical state of ocean waters and remote sensing, Limnology and Oceanography, 23:247-259.CrossRefGoogle Scholar
  128. Smith, R. C. 1981. Remote sensing and depth distribution of ocean chlorophyll, Marine Ecology Progress Series, 5:359-361.Google Scholar
  129. Smith, R. C., R. W. Eppley and K. S. Baker. 1982. Correlation of primary production as measured aboard ship in Southern California coastal waters and as estimated from satellite chlorophyll images, Marine Biology, 66:281-288.Google Scholar
  130. Soetaert, K., J. J. Middelburg, P. M. J. Herman, and K. Buis. 2000. On the coupling of benthic and pelagic biogeochemical models, Earth-Science Reviews, 51:173-210.Google Scholar
  131. Soetaert, K., P. M. J. Herman, J. J. Middelburg, C. Heip, C. L. Smith, P. Tett, and K. Wild-Allen. 2001. Numerical modelling of the shelf break ecosystem: reproducing benthic and pelagic measurements, Deep- Sea Research II, 48:3141-3177.Google Scholar
  132. Spitz, Y. H., J. R. Moisan, M. R. Abbott, and J. G. Richman. 1998. Data assimilation and a pelagic ecosystem model: Parameterization using time series observations, Journal of Marine Systems, 16:51-68.Google Scholar
  133. Spitz, Y. H., J. R. Moisan, M. R. Abbott, and J. G. Richman. 2001. Using data assimilation to configure a biogeochemical model of the Bermuda-Atlantic Time Series (BATS), Deep-Sea Research II, 48:1733- 1768.Google Scholar
  134. Stolzenbach, K. D., J. R. Moisan, H. Frenzel, N. Gruber, P. Marchesiello, J. C. McWilliams and J. Oram. 2004. Simulation of the plankton ecosystem in the California Current System, In Prep.Google Scholar
  135. Strub, P. T., C. James, A. C. Thomas, and M. R. Abbott. 1990. Seasonal and nonseasonal variability of satellite-derived surface pigment concentration in the California Current, Journal of Geophysical Research, 95:11,501-11,530.Google Scholar
  136. Strub, P. T. and C. James. 2000. Altimeter-derived variability of surface velocities in the California Current System: 2. Seasonal circulation and eddy statistics, Deep-Sea Research II, 47:831-870.Google Scholar
  137. Swenson, M. S. and P. P. Niiler. 1996. Statistical analysis of the surface circulation of the California Current. Journal of Geophyical Research, 22:631-645.Google Scholar
  138. Takahashi, T., R. E. Feely, R. F. Weiss, R. H. Wanninkhof, D. W. Chipman, S. C. Sutherland, and T. T. Takahashi. 1997. Global air-sea flux of CO2: An estimate based on measurements of sea-air pCO2 difference, Proceedings of the National Academy of Science, 94:8292-8299.Google Scholar
  139. Talling, J. F. 1957a. Photosynthetic characteristics of some freshwater plankton in relation to underwater radiation, New Phytologist, 56:29-50.Google Scholar
  140. Talling, J. F. 1957b. The phytoplankton population as a compound photosynthetic system. New Phytologist, 56:133-149.Google Scholar
  141. Tanaka, A., M. Kishino, T. Oishi, R. Doerffer, and H. Schiller. 2000. Application of neural network to case II water, In: Remote Sensing of the Ocean and Sea Ice, Bostater, C. R., and R. Santoleri (eds.), Proceedings of the Society of Photo-Optical Engineering (SPIE), 4172:144-152.Google Scholar
  142. Thomas, A. C. and P. T. Strub. 1989. Interannual variability in phytoplankton pigment distribution during the spring transition along the west coast of North America, Journal of Geophysical Research, 94:18,095- 18,117.Google Scholar
  143. Thomas, A. C. and P. T. Strub. 1990. Seasonal and interannual variability of pigment concentrations across a California Current frontal zone, Journal of Geophysical Research, 95:13,023-13,042.Google Scholar
  144. Vallino, J. J. 2000. Improving marine ecosystem models: use of data assimilation and mesocosm experiments, Journal of Marine Research, 58:117-164.Google Scholar
  145. Vichi, M. 2002. Predictability studies of coastal marine ecosystem behavior, Ph. D. Thesis, University of Oldenburg, Oldenburg, Germany.Google Scholar
  146. Vichi, M., P. Oddo, M. Zavatarelli, A. Coluccelli, G. Coppini, M. Celio, S. Fonda Umani, and N. Pinardi. 2003. Calibration and validation of a one-dimensional complex marine biogeochemical flux model in different areas of the northern Adriatic shelf, Annales Geophysicae, 21:1-24.CrossRefGoogle Scholar
  147. Weingartner, T. J., K. Coyle, B. Finney, R. Hopcroft, T. Whitledge, R. Brodeur, M. Dagg, E. Farley, D. Haidvogel, L. Haldorson, A. Hermann, S. Hinckley, J. Napp, P. Stabeno, T. Kline, C. Lee, E. Lessard, T. Royer, S. Strom. 2002. The Northeast Pacific GLOBEC Program: Coastal Gulf of Alaska, Oceanography, 15(2):48-63.Google Scholar
  148. Wilkin, J. L., H. G. Arango, D. B. Haidvogel, C. S. Lichtenwalner, S. M. Glenn, and K. S. Hedstrom. 2004. A regional ocean modeling system for the long-term ecosystem observatory, Journal of Geophysical Research, Sub judice.Google Scholar
  149. Wunsch, C. 1996. The Ocean Circulation Inverse Problem. Cambridge University Press, 442 pp.Google Scholar
  150. Zhang, T. L., F. Fell, Z. S. Liu, R. Preusker, J. Fischer, and M. X. He. 2003. Evaluating the performance of artificial neural network techniques for pigment retrieval from ocean color in Case I waters, Journal Geophysical Research, 108(C9):3286, 10.1029/2002JC001638.Google Scholar

Copyright information

© Springer 2007

Authors and Affiliations

  • John R. Moisan
    • 1
  • Arthur J. Miller
    • 2
  • Emanuele Di Lorenzo
    • 3
  • John Wilkin
    • 4
  1. 1.National Aeronautics and Space AdministrationGoddard Space Flight Center, Wallops Flight FacilityWallops IslandUSA
  2. 2.Scripps Institution of OceanographyUniversity of CaliforniaSan DiegoUSA
  3. 3.Scripps Institution of OceanographyUniversity of CaliforniaSan DiegoUSA
  4. 4.Rutgers University, Douglas CampusInstitute of Marine and Coastal SciencesNew BrunswickUSA

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