Stoichiometries of remineralisation and denitrification in global biogeochemical ocean models

Since the seminal paper of Redfield (1934), constant stoichiometric elemental ratios linking biotic carbon and nutrient fluxes are often assumed in marine biogeochemistry, and especially in coupled biogeochemical circulation models, to couple the global oxygen, carbon and nutrient cycles. However, when looking in more detail, some deviations from the classical Redfield stoichiometry have been reported, in particular with respect to remineralization of organic matter changing with depth or with ambient oxygen levels. We here compare the assumptions about the stoichiometry of organic matter and its remineralization that are used explicitly and implicitly in common biogeochemical ocean models. We find that the implicit assumptions made about the hydrogen content of organic matter can lead to inconsistencies in the modeled remineralization and denitrification stoichiometries. It is suggested that future marine biogeochemical models explicitly state the chemical composition assumed for the organic matter, including its oxygen and hydrogen content

Swept under the carpet: organic matter burial decreases global ocean biogeochemical model sensitivity to remineralization length scale

Although of substantial importance for marine tracer distributions and eventually global carbon, oxygen, and nitrogen fluxes, the interaction between sinking and remineralization of organic matter, benthic fluxes and burial is not always represented consistently in global biogeochemical models. We here aim to investigate the relationships between these processes with a suite of global biogeochemical models, each simulated over millennia, and compared against observed distributions of pelagic tracers and benthic and pelagic fluxes. We concentrate on the representation of sediment–water interactions in common numerical models, and investigate their potential impact on simulated global sediment–water fluxes and nutrient and oxygen distributions. We find that model configurations with benthic burial simulate global oxygen well over a wide range of possible sinking flux parameterizations, making the model more robust with regard to uncertainties about the remineralization length scale. On a global scale, burial mostly affects oxygen in the meso- to bathypelagic zone. While all model types show an almost identical fit to observed pelagic particle flux, and the same sensitivity to particle sinking speed, comparison to observational estimates of benthic fluxes reveals a more complex pattern, but definite interpretation is not straightforward because of heterogeneous data distribution and methodology. Still, evaluating model results against observed pelagic and benthic fluxes of organic matter can complement model assessments based on more traditional tracers such as nutrients or oxygen. Based on a combined metric of dissolved tracers and biogeochemical fluxes, we here identify two model descriptions of burial as suitable candidates for further experiments and eventual model refinements

Cs-137 off Fukushima Dai-ichi, Japan - model based estimates of dilution and fate

In the aftermath of an earthquake and tsunami on 11 March 2011 radioactive 137Cs was discharged from a damaged nuclear power plant to the sea off Fukushima Dai-ichi, Japan. Here we explore its dilution and fate with a state-of-the-art global ocean general circulation model, which is eddy-resolving in the region of interest. We find apparent consistency between our simulated circulation, estimates of 137Cs discharged ranging from 0.94 p Bq (Japanese Government, 2011) to 3.5 ± 0.7 p Bq (Tsumune et al., 2012), and measurements by Japanese authorities and the power plant operator. In contrast, our simulations are apparently inconsistent with the high 27 ± 15 p Bq discharge estimate of Bailly du Bois et al. (2012). Expressed in terms of a diffusivity we diagnose, from our simulations, an initial dilution on the shelf of 60 to 100 m2 s−1. The cross-shelf diffusivity is at 500 ± 300 m2 s−1 significantly higher and variable in time as indicated by its uncertainty. Expressed as an effective residence time of surface water on the shelf, the latter estimate transfers to 43 ± 16 days. As regards the fate of 137Cs, our simulations suggest that activities up to 4 mBq l−1 prevail in the Kuroshio-Oyashio Interfrontal Zone one year after the accident. This allows for low but detectable 0.1 to 0.3 m Bq l−1 entering the North Pacific Intermediate Water before the 137Cs signal is flushed away. The latter estimates concern the direct release to the sea only

MOPS-1.0: modelling the regulation of the global oceanic nitrogen budget by marine biogeochemical processes

Global models of the oceanic nitrogen cycle are subject to many uncertainties, among them type and form of biogeochemical processes involved in the fixed nitrogen cycle, and the spatial and temporal scales, on which the global nitrogen budget is regulated. We investigate these aspects using a global model of ocean biogeochemistry, that explicitly considers phosphorus and nitrogen, including pelagic denitrification and nitrogen fixation as sink and source terms of fixed nitrogen, respectively. The model explores different parameterizations of organic matter sinking speed, oxidant affinity of oxic and suboxic remineralization, and regulation of nitrogen fixation by temperature and different stoichiometric ratios. Examination of the initial transient behaviour of different model setups initialized from observed tracer distributions reveal changes in simulated nitrogen inventories and fluxes particularly during the first centuries. Millennial timescales have to be resolved in order to bring all biogeochemical and physical processes into a dynamically consistent steady state, for which global patterns of biogeochemical tracers and fluxes are reproduced quite well. Analysis of global properties suggests that particularly particle sinking speed, but also the parameterization of denitrification determines the extent of oxygen minimum zones, global nitrogen fluxes, and hence the oceanic nitrogen inventory. However, the ways and directions, in which different parameterizations of particle sinking, nitrogen fixation and denitrification affect the global diagnostics, are different, suggesting that these may, in principle, be constrained independently from each other. Analysis of the model misfit suggests a particle flux profile close to the one suggested by Martin et al. (1987). Simulated pelagic denitrification best agrees with the lower values between 59 and 84 Tg N yr−1 recently estimated by other authors

Modelling the effect of cell-size-dependent nutrient uptake and exudation on phytoplankton size spectra

The effect of phytoplankton cell size on the variation of nutrient uptake and exudation rates is examined: we first present an overview of the relationship between the variation of the growth and loss parameters and cell size. We then investigate the effect of cell-size-dependent parameters on the development of an entire phytoplankton community by means of a numerical, vertically resolved nutrient phytoplankton model. The model represents phytoplankton size distributions in three different ways, namely one configuration with explicit representation of 14 size classes, one configuration with constant-slope power-law spectral representation, and one configuration with variable-slope power-law spectral representation. The size-dependent configurations are further compared to a size-independent configuration. Consistent with theory, the explicit and variable-slope spectral model simulations predict increased importance of larger cells, or "flat" size distribution under conditions of low light and high nutrients, while smaller cells ("steep" size distributions) may dominate in oligotrophic, well-lit regimes. In some situations the variable-slope spectral model seems to be sufficient to reflect the phytoplankton size distribution; however, especially in the deep phytoplankton maximum a unimodal rather than power-law spectral description might be more appropriate to reproduce results of the explicit 14-size-class model. The assumption of a fixed spectral slope, according to which larger size classes gain importance especially during bloom periods, is not consistent with the underlying theory, and does not agree with the results of the size-discrete model. The comparison of model predictions with variations of phytoplankton size distribution observed in the field is hampered by the sparsity of data, especially for the winter season. A half-saturation constant that represents the nutrient uptake of the entire phytoplankton community (K*) compares well to published values. (C) 2007 Elsevier Ltd. All rights reserved

On the treatment of particulate organic matter sinking in large-scale models of marine biogeochemical cycles

Various functions have been suggested and applied to represent the sedimentation and remineralisation of particulate organic matter (POM) in numerical ocean models. Here we investigate some representations commonly used in large-scale biogeochemical models: a constant sinking speed, a sinking speed increasing with depth, a spectrum of particles with different size and different size-dependent sinking velocities, and a model that assumes a power law particle size distribution everywhere in the water column. The analysis is carried out for an idealised one-dimensional water column, under stationary boundary conditions for surface POM. It focuses on the intrinsic assumptions of the respective sedimentation function and their effect on POM mass, mass flux, and remineralisation profiles. A constant and uniform sinking speed does not appear appropriate for simulations exceeding a few decades, as the sedimentation profile is not consistent with observed profiles. A spectrum of size classes, together with size-dependent sinking and constant remineralisation, causes the sinking speed of total POM to increase with depth. This increase is not strictly linear with depth. Its particular form will further depend on the size distribution of the POM ensemble at the surface. Assuming a power law particle size spectrum at the surface, this model results in unimodal size distributions in the ocean interior. For the size-dependent sinking model, we present an analytic integral over depth and size that can explain regional variations of remineralisation length scales in response to regional patterns in trophodynamic state

A derivative-free optimisation method for global ocean biogeochemical models

The skill of global ocean biogeochemical models, and the earth system models in which they are embedded, can be improved by systematic calibration of the parameter values against observations. However, such tuning is seldom undertaken as these models are computationally very expensive. Here we investigate the performance of DFO-LS, a local, derivative-free optimisation algorithm which has been designed for computationally expensive models with irregular model–data misfit landscapes typical of biogeochemical models. We use DFO-LS to calibrate six parameters of a relatively complex global ocean biogeochemical model (MOPS) against synthetic dissolved oxygen, phosphate and nitrate “observations” from a reference run of the same model with a known parameter configuration. The performance of DFO-LS is compared with that of CMA-ES, another derivative-free algorithm that was applied in a previous study to the same model in one of the first successful attempts at calibrating a global model of this complexity. We find that DFO-LS successfully recovers five of the six parameters in approximately 40 evaluations of the misfit function (each one requiring a 3000-year run of MOPS to equilibrium), while CMA-ES needs over 1200 evaluations. Moreover, DFO-LS reached a “baseline” misfit, defined by observational noise, in just 11–14 evaluations, whereas CMA-ES required approximately 340 evaluations. We also find that the performance of DFO-LS is not significantly affected by observational sparsity, however fewer parameters were successfully optimised in the presence of observational uncertainty. The results presented here suggest that DFO-LS is sufficiently inexpensive and robust to apply to the calibration of complex, global ocean biogeochemical models