Constraining global marine iron source and scavenging fluxes with GEOTRACES dissolved iron measurements in an ocean biogeochemical model

2021 ◽  
Author(s):  
Christopher J. Somes ◽  
Andrew W. Dale ◽  
Klaus Wallmann ◽  
Florian Scholz ◽  
Wanxuan Yao ◽  
...  
2021 ◽  
Author(s):  
Christopher J. Somes ◽  
Andrew W. Dale ◽  
Klaus Wallmann ◽  
Florian Scholz ◽  
Wanxuan Yao ◽  
...  

2021 ◽  
Author(s):  
Christopher Somes ◽  
Andew Dale ◽  
Klaus Wallmann ◽  
Florian Scholz ◽  
Wanxuan Yao ◽  
...  

2020 ◽  
Author(s):  
Samantha Carter ◽  
◽  
Elizabeth M. Griffith ◽  
Arne Winguth ◽  
Teresa Beaty

2014 ◽  
Vol 11 (21) ◽  
pp. 6107-6117 ◽  
Author(s):  
N. C. Swart ◽  
J. C. Fyfe ◽  
O. A. Saenko ◽  
M. Eby

Abstract. We estimate changes in the historical ocean carbon sink and their uncertainty using an ocean biogeochemical model driven with wind forcing from six different reanalyses and using two different eddy parameterization schemes. First, we quantify wind-induced changes over the extended period from 1871 to 2010 using the 20th Century Reanalysis winds. Consistent with previous shorter-term studies, we find that the wind changes act to reduce the ocean carbon sink, but the wind-induced trends are subject to large uncertainties. One major source of uncertainty is the parameterization of mesoscale eddies in our coarse resolution simulations. Trends in the Southern Ocean residual meridional overturning circulation and the globally integrated surface carbon flux over 1950 to 2010 are about 2.5 times smaller when using a variable eddy transfer coefficient than when using a constant coefficient in this parameterization. A second major source of uncertainty arises from disagreement on historical wind trends. By comparing six reanalyses over 1980 to 2010, we show that there are statistically significant differences in estimated historical wind trends, which vary in both sign and magnitude amongst the products. Through simulations forced with these reanalysis winds, we show that the influence of historical wind changes on ocean carbon uptake is highly uncertain, and the resulting trends depend on the choice of surface wind product.


2019 ◽  
Vol 124 (9) ◽  
pp. 2728-2750 ◽  
Author(s):  
L. Castro de la Guardia ◽  
Y. Garcia‐Quintana ◽  
M. Claret ◽  
X. Hu ◽  
E. D. Galbraith ◽  
...  

2015 ◽  
Vol 8 (2) ◽  
pp. 1375-1509 ◽  
Author(s):  
O. Aumont ◽  
C. Ethé ◽  
A. Tagliabue ◽  
L. Bopp ◽  
M. Gehlen

Abstract. PISCES-v2 is a biogeochemical model which simulates the lower trophic levels of marine ecosystem (phytoplankton, microzooplankton and mesozooplankton) and the biogeochemical cycles of carbon and of the main nutrients (P, N, Fe, and Si). The model is intended to be used for both regional and global configurations at high or low spatial resolutions as well as for short-term (seasonal, interannual) and long-term (climate change, paleoceanography) analyses. There are twenty-four prognostic variables (tracers) including two phytoplankton compartments (diatoms and nanophytoplankton), two zooplankton size-classes (microzooplankton and mesozooplankton) and a description of the carbonate chemistry. Formulations in PISCES-v2 are based on a mixed Monod–Quota formalism: on one hand, stoichiometry of C/N/P is fixed and growth rate of phytoplankton is limited by the external availability in N, P and Si. On the other hand, the iron and silicium quotas are variable and growth rate of phytoplankton is limited by the internal availability in Fe. Various parameterizations can be activated in PISCES-v2, setting for instance the complexity of iron chemistry or the description of particulate organic materials. So far, PISCES-v2 has been coupled to the NEMO and ROMS systems. A full description of PISCES-v2 and of its optional functionalities is provided here. The results of a quasi-steady state simulation are presented and evaluated against diverse observational and satellite-derived data. Finally, some of the new functionalities of PISCES-v2 are tested in a series of sensitivity experiments.


2003 ◽  
Vol 50 (22-26) ◽  
pp. 3143-3169 ◽  
Author(s):  
Watson W. Gregg ◽  
Paul Ginoux ◽  
Paul S. Schopf ◽  
Nancy W. Casey

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