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Title: Complex functionality with minimal computation. Promise and pitfalls of reduced-tracer ocean biogeochemistry models

Earth System Models increasingly include ocean biogeochemistry models in order to predict changes in ocean carbon storage, hypoxia, and biological productivity under climate change. However, state-of-the-art ocean biogeochemical models include many advected tracers, that significantly increase the computational resources required, forcing a trade-off with spatial resolution. Here, we compare a state-of the art model with 30 prognostic tracers (TOPAZ) with two reduced-tracer models, one with 6 tracers (BLING), and the other with 3 tracers (miniBLING). The reduced-tracer models employ parameterized, implicit biological functions, which nonetheless capture many of the most important processes resolved by TOPAZ. All three are embedded in the same coupled climate model. Despite the large difference in tracer number, the absence of tracers for living organic matter is shown to have a minimal impact on the transport of nutrient elements, and the three models produce similar mean annual preindustrial distributions of macronutrients, oxygen, and carbon. Significant differences do exist among the models, in particular the seasonal cycle of biomass and export production, but it does not appear that these are necessary consequences of the reduced tracer number. With increasing CO2, changes in dissolved oxygen and anthropogenic carbon uptake are very similar across the different models. Thus, whilemore » the reduced-tracer models do not explicitly resolve the diversity and internal dynamics of marine ecosystems, we demonstrate that such models are applicable to a broad suite of major biogeochemical concerns, including anthropogenic change. Lastly, these results are very promising for the further development and application of reduced-tracer biogeochemical models that incorporate ‘‘sub-ecosystem-scale’’ parameterizations.« less
 [1] ;  [2] ;  [3] ;  [4] ;  [4] ;  [4] ;  [4] ;  [5] ;  [6] ;  [4] ;  [7]
  1. Univ. Autonoma de Barcelona, Barcelona (Spain); McGill Univ., Montreal, QC (Canada)
  2. NOAA Geophysical Fluid Dynamics Lab., Princeton, NJ (United States)
  3. Johns Hopkins Univ., Baltimore, MD (United States)
  4. Princeton Univ., Princeton, NJ (United States)
  5. McGill Univ., Montreal, QC (Canada); Univ. of California, Los Angeles, CA (United States)
  6. McGill Univ., Montreal, QC (Canada)
  7. Johns Hopkins Univ., Baltimore, MD (United States); Islamic Azad Univ., Tehran (Iran)
Publication Date:
Grant/Contract Number:
Published Article
Journal Name:
Journal of Advances in Modeling Earth Systems
Additional Journal Information:
Journal Volume: 7; Journal Issue: 4; Journal ID: ISSN 1942-2466
American Geophysical Union (AGU)
Research Org:
Princeton Univ., NJ (United States)
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
United States
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1243072