Inverse-model estimates of the ocean's coupled phosphorus, silicon, and iron cycles

Abstract

Abstract. The ocean's nutrient cycles are important for the carbon balance of the climate system and for shaping the ocean's distribution of dissolved elements. Dissolved iron (dFe) is a key limiting micronutrient, but iron scavenging is observationally poorly constrained, leading to large uncertainties in the external sources of iron and hence in the state of the marine iron cycle.Here we build a steady-state model of the ocean's coupled phosphorus, silicon, and iron cycles embedded in a dataassimilated steady-state global ocean circulation. The model includes the redissolution of scavenged iron, parameterization of subgrid topography, and small, large, and diatom phytoplankton functional classes. Phytoplankton concentrations are implicitly represented in the parameterization of biological nutrient utilization through an equilibrium logistic model. Our formulation thus has only three coupled nutrient tracers, the three-dimensional distributions of which are found using a Newton solver. The very efficient numerics allow us to use the model in inverse mode to objectively constrain many biogeochemical parameters by minimizing the mismatch between modeled and observed nutrient and phytoplankton concentrations. Iron source and sink parameters cannot jointly be optimized because of local compensation between regeneration, recycling, and scavenging. We therefore consider a family of possible state estimates corresponding to a wide range of external iron source strengths. All state estimates have a similar mismatch with the observed nutrient concentrations and very similar large-scale dFe distributions. However, the relative contributions of aeolian, sedimentary, and hydrothermal iron to the total dFe concentration differ widely depending on the sources.Both the magnitude and pattern of the phosphorus and opal exports are well constrained, with global values of 8.1 ± 0.3 Tmol P yr −1 (or, in carbon units, 10.3 ± 0.4 Pg C yr −1 ) and 171. ± 3. Tmol Si yr −1 . We diagnose the phosphorus and opal exports supported by aeolian, sedimentary, and hydrothermal iron. The geographic patterns of the export supported by each iron type are well constrained across the family of state estimates. Sedimentary-iron-supported export is important in shelf and large-scale upwelling regions, while hydrothermal iron contributes to export mostly in the Southern Ocean. The fraction of the global export supported by a given iron type varies systematically with its fractional contribution to the total iron source. Aeolian iron is most efficient in supporting export in the sense that its fractional contribution to export exceeds its fractional contribution to the total source. Per source-injected molecule, aeolian iron supports 3.1 ± 0.8 times more phosphorus export and 2.0 ± 0.5 times more opal export than the other iron types. Conversely, per injected molecule, sedimentary and hydrothermal iron support 2.3 ± 0.6 and 4. ± 2. times less phosphorus export, and 1.9 ± 0.5 and 2. ± 1. times less opal export than the other iron types.

Iron fertilization efficiency and the number of past and future regenerations of iron in the ocean

“…We emphasize that Figure 4 does not show the response of the iron cycle to changes in σ tot , but instead shows the fraction of the unused DFe inventory for distinct equilibrium states, each of which was optimized against observations under a different prescribed iron source scenario (Pasquier and Holzer, 2017). Because the total iron inventory is well constrained across the family, the bulk iron lifetime τ , given by the ratio of inventory to source (see also Table 1), is inversely proportional to σ tot , and hence the mean iron age also scales with (σ tot ) −1 .…”

“…Our analysis uses the 287 optimized state estimates of Pasquier and Holzer (2017), which were obtained from a steady-state 15 inverse model of the ocean's coupled iron, phosphorus, and silicon cycles, embedded in the data-assimilated steady global ocean circulation of Primeau et al (2013). The members of our family of state estimates correspond to different iron source strengths, given that the actual values for the real ocean are still highly uncertain (e.g., Tagliabue et al, 2016).…”

“…Following Pasquier and Holzer (2017), we write the nonlinear tracer equation for DFe concentration χ as of a Martin power-law POP flux profile (Martin et al, 1987).) Similarly, the redissolution rate of scavenged DFe is modelled by S j J j where the source operator S j represents the instantaneous transport to depth of iron scavenged by particles of type j.…”

“…The detailed model formulation of the coupled iron-phosphorus-silicon cycles, including the construction of the operators S c and S j , has been published by Pasquier and Holzer (2017).…”

“…from the optimized phosphorus uptake U P c (r) of the underlying model (Pasquier and Holzer, 2017). The mean number of phosphorus molecules, n P k (r), globally exported and remineralized in the past, per DFe molecule that is currently at r, obeys…”