The CESM Ocean Ecosystem Scientific Description
National Center for Atmospheric Research
- Summary Description
The Biogeochemical Elemental Cycling (BEC) model is an
ecosystem/biogeochemistry model that runs within the ocean circulation
component of CESM (Moore et al., 2004). The ecosystem includes multiple
phytoplankton functional groups (diatoms, diazotrophs, small phytoplankton,
and coccolithophores) and multiple potentially growth limiting nutrients
(nitrate, ammonium, phosphate, silicate, and iron) (Moore et al.,
2002, 2004). There is one zooplankton group, dissolved organic material
(semi-labile), sinking particulate pools and explicit simulation of the
biogeochemical cycling of key elements (C, N, P, Fe, Si, O, plus alkalinity)
(Moore et al., 2004). The ecosystem component is coupled with a carbonate
chemistry module based on the Ocean Carbon Model Intercomparison Project
(OCMIP) (Doney et al., 2009) allowing dynamic computation of surface ocean
pCO2 and air-sea CO2 flux. The model allows for water column denitrication,
whereby nitrate is consumed during remineralization in place of O2 once
ambient O2 concentrations fall below 4 micro-molar (Moore and Doney,
2007). Photoadaptation is calculated as a variable phytoplankton ratio of
chlorophyll to nitrogen based on Geider et al. (1998). The model allows
for variable Fe/C and Si/C ratios with an optimum and minimum value
prescribed. As ambient Fe (or Si for diatoms) concentrations decline the
phytoplankton lower their cellular quotas. Phytoplankton N/P ratios are
fixed at the Redfield value of 16, but the diazotroph group has a higher
N/P atomic ratio of 50 (see detailed description of the model in Moore et
al. (2002, 2004)). Thus, community N/P uptake varies with the phytoplankton
community composition. The ecosystem model results have been compared
extensively against in situ data (e.g., JGOFS time series stations) and
SeaWiFS satellite ocean color observations in a global mixed layer only
variant and coupled with a full-depth, global 3-D general circulation
model (Moore et al., 2002; 2004; Doney et al., 2009). In both cases,
the simulated output is in generally good agreement with bulk ecosystem
observations (e.g., total biomass, productivity, nutrients, export) across
diverse ecosystems that include both macro-nutrient and iron-limited regimes
as well as very different physical environments from high latitude sites
to the mid-ocean gyres. The model also incorporates the work of Moore
and Braucher (2008), who incorporated an improved sedimentary iron source
and scavenging parameterization, greatly improving simulated iron fields
relative to observations, and the work of Krishnamurthy et al. (2007),
who describe the impact of atmospheric deposition of nitrogen.
Doney, S.C., I. Lima, J.K. Moore, K. Lindsay, M.J. Behrenfeld, T.K. Westberry, N. Mahowald, D.M. Glover, and T. Takahashi, 2009b: Skill metrics for confronting global upper ocean ecosystem-biogeochemistry models against field and remote sensing data, J. Mar. Systems, 76, 95--112.
Geider, R., H. MacIntyre, and T. Kana, A dynamic regulatory model of phytoplankton acclimation to light, nutrients, and temperature, Limnology and Oceanography, 43, 679694, 1998.
Krishnamurthy, A., J. K. Moore, C. S. Zender, and C. Luo, The effects of atmospheric inorganic nitrogen deposition on ocean biogeochemistry, J. Geophys. Res., 112, 2007.
Moore, J. K., S. Doney, J. Kleypas, D. Glover, and I. Fung, An intermediate complexity marine ecosystem model for the global domain, Deep-Sea Res. II, 49, 403--462, 2002.
Moore, J. K., S. C. Doney, and K. Lindsay, Upper ocean ecosystem dynamics and iron cycling in a global three-dimensional model, Global Biogeochem. Cycles, 18, 2004.
Moore, J. K., and S. C. Doney, Iron availability limits the ocean nitrogen inventory stabilizing feedbacks between marine denitrification and nitrogen fixation, Global Biogeochem. Cycles, 21, 2007.
Moore, J. K., and O. Braucher, Sedimentary and mineral dust sources of dissolved iron to the world ocean, Biogeosciences, 5, 631--656, 2008.