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Modeling the dynamics of continental shelf carbon
Hofmann, E.E.; Cahill, B.; Fennel, K.; Friedrichs, M.A.M.; Hyde, K.; Lee, C.; Mannino, A.; Najjar, R.G.; O'Reilly, J.E.; Wilkin, J.; Xue, J. (2011). Modeling the dynamics of continental shelf carbon, in: Carlson, C.A. et al. Ann. Rev. Mar. Sci. 3. Annual Review of Marine Science, 3: pp. 93-122. https://dx.doi.org/10.1146/annurev-marine-120709-142740
In: Carlson, C.A.; Giovannoni, S.J. (2011). Ann. Rev. Mar. Sci. 3. Annual Review of Marine Science, 3. Annual Reviews: Palo Alto. ISBN 978-0-8243-4503-7. 599 pp., more
In: Annual Review of Marine Science. Annual Reviews: Palo Alto, Calif. ISSN 1941-1405; e-ISSN 1941-0611, more
Peer reviewed article  

Available in  Authors 

Keyword
    Marine/Coastal
Author keywords
    carbon cycling; continental shelf; coupled circulation-biogeochemical models; model-data comparisons; data assimilation; biogeochemical model initialization

Authors  Top 
  • Hofmann, E.E.
  • Cahill, B.
  • Fennel, K.
  • Friedrichs, M.A.M.
  • Hyde, K.
  • Lee, C.
  • Mannino, A.
  • Najjar, R.G.
  • O'Reilly, J.E.
  • Wilkin, J.
  • Xue, J.

Abstract
    Continental margin systems are important contributors to global nutrient and carbon budgets. Effort is needed to quantify this contribution and how it will be modified under changing patterns of climate and land use. Coupled models will be used to provide projections of future states of continental margin systems. Thus, it is appropriate to consider the limitations that impede the development of realistic models. Here, we provide an overview of the current state of modeling carbon cycling on continental margins as well as the processes and issues that provide the next challenges to such models. Our overview is done within the context of a coupled circulation-biogeochemical model developed for the northeastern North American continental shelf region. Particular choices of forcing and initial fields and process parameterizations are used to illustrate the consequences for simulated distributions, as revealed by comparisons to observations using quantitative statistical metrics.

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