Description: This study presents results from 46 sensitivity experiments carried out with three structurally simple (2, 3, and 6 biogeochemical state variables, respectively) models of production, export and remineralization of organic phosphorus, coupled to a global ocean circulation model and integrated for 3000 years each. The models’ skill is assessed via different misfit functions with respect to the observed global distributions of phosphate and oxygen. Across the different models, the global root-mean square misfit with respect to observed phosphate and oxygen distributions is found to be particularly sensitive to changes in the remineralization length scale, and also to changes in simulated primary production. For this metric, changes in the production and decay of dissolved organic phosphorus as well as in zooplankton parameters are of lesser importance. For a misfit function accounting for the misfit of upper-ocean tracers, however, production parameters and organic phosphorus dynamics play a larger role. Regional misfit patterns are investigated as indicators of potential model deficiencies, such as missing iron limitation, or deficiencies in the sinking and remineralization length scales. In particular, the gradient between phosphate concentrations in the northern North Pacific and the northern North Atlantic is controlled predominantly by the biogeochemical model parameters related to particle flux. For the combined 46 sensitivity experiments performed here, the global misfit to observed oxygen and phosphate distributions shows no clear relation to either simulated global primary or export production for either misfit metric employed. However, a relatively tight relationship that is very similar for the different model of different structural complexity is found between the model-data misfit in oxygen and phosphate distributions to simulated meso- and bathypelagic particle flux. Best agreement with the observed tracer distributions is obtained for simulated particle fluxes that agree most closely with sediment trap data for a nominal depth of about 1000 m, or deeper.

Description: Global biogeochemical ocean models rely on many parameters, which govern the interaction between individual components, and their response to the physical environment. They are often assessed/calibrated against quasi-synoptic data sets of dissolved inorganic tracers. However, a good fit to one observation might not necessarily imply a good match to another. We investigate whether two different metrics—the root-mean-square error to nutrients and oxygen and a metric measuring the overlap between simulated and observed oxygen minimum zones (OMZs)—help to constrain a global biogeochemical model in different aspects of performance. Three global model optimizations are carried out. Two single-objective optimizations target the root-mean-square metric and a sum of both metrics, respectively. We then present and explore multiobjective optimization, which results in a set of compromise solutions. Our results suggest that optimal parameters for denitrification and nitrogen fixation differ when applying different metrics. Optimization against observed OMZs leads to parameters that enhance fixed nitrogen cycling; this causes too low nitrate concentrations and a too high global pelagic denitrification rate. Optimization against nutrient and oxygen concentrations leads to different parameters and a lower global fixed nitrogen turnover; this results in a worse fit to OMZs. Multiobjective optimization resolves this antagonistic effect and provides an ensemble of parameter sets, which help to address different research questions. We finally discuss how systematic model calibration can help to improve models used for projecting climate change and its effect on fisheries and climate gas emissions.

Description: Southern Ocean (SO) physical and biological processes are known to have a large impact on global biogeochemistry. However, the role that SO biology plays in determining ocean oxygen concentrations is not completely understood. These dynamics are investigated here by shutting off SO biology in two marine biogeochemical models. The results suggest that SO biological processes reduce the ocean's oxygen content, mainly in the deep ocean, by 14 to 19%. However, since these processes also trap nutrients that would otherwise be transported northward to fuel productivity and subsequent organic matter export, consumption, and the accompanying oxygen consumption in midlatitude to low-latitude waters, SO biology helps to maintain higher oxygen concentrations in these subsurface waters. Thereby, SO biology can influence the size of the tropical oxygen minimum zones. As a result of ocean circulation the link between SO biological processes and remote oxygen changes operates on decadal to centennial time scales.

Description: For modeled sediment cores of the open ocean, a method for predicting simultaneously the ages of four different solid sediment compounds with respect to their depositional year onto the sediment surface is presented. The simulation of time-dependent age distribution in the sediment mixed layer and the eventually accumulating sediment is a prerequisite of a proper data assimilation of marine sediment core data into predictive climate models. Through such a data assimilation, marine paleoclimate data could then be efficiently used in order to optimally determine adjustable model parameters. The age simulation is based on a passive tracer transport method taking into account varying vertical advection rates within the sediment top layers, chemical pore water reactions, and bioturbation. It turns out that different weight fractions of the modeled sediment have different ages in one horizontal geometric depth-in-core level depending on the particle rain onto the sediment and the reactivity of the material within the sediment pore waters. For simultaneous consideration of paleoclimatic tracers associated within one and the same weight fraction, e.g., for calcium carbonate, tracers such as foraminiferal δ13C, and calcium carbonate weight percentages, this may not be critical. However, for simultaneous consideration of calcium carbonate and opal weight percentages, the age difference in the observed weight fractions may have to be corrected. The age offset between CaCO3 and opal depends critically on the sediment accumulation rate. Low-accumulation sites are more strongly affected than high-accumulation sites.

Description: In geoscience and other fields, researchers use models as a simplified representation of reality. The models include processes that often rely on uncertain parameters that reduce model performance in reflecting real-world processes. The problem is commonly addressed by adapting parameter values to reach a good match between model simulations and corresponding observations. Different optimization tools have been successfully applied to address this task of model calibration. However, seeking one best value for every single model parameter might not always be optimal. For example, if model equations integrate over multiple real-world processes which cannot be fully resolved, it might be preferable to consider associated model parameters as random parameters. In this paper, a random parameter is drawn from a wide probability distribution for every singe model simulation. We developed an optimization approach that allows us to declare certain parameters random while optimizing those that are assumed to take fixed values. We designed a corresponding variant of the well known Covariance Matrix Adaption Evolution Strategy (CMA-ES). The new algorithm was applied to a global biogeochemical circulation model to quantify the impact of zooplankton mortality on the underlying biogeochemistry. Compared to the deterministic CMA-ES, our new method converges to a solution that better suits the credible range of the corresponding random parameter with less computational effort.

Description: Quantifying changes in oceanic aerobic respiration is essential for understanding marine deoxygenation. Here we use an Earth system model to investigate if and to what extent oxygen utilization rate (OUR) can be used to track the temporal change of true respiration (Rtrue). Rtrue results from the degradation of particulate and dissolved organic matter in the model ocean, acting as ground truth to evaluate the accuracy of OUR. Results show that in thermocline and intermediate waters of the North Atlantic Subtropical Gyre (200–1,000 m), vertically integrated OUR and Rtrue both decrease by 0.2 molO2/m2/yr from 1850 to 2100 under global warming. However, in the mesopelagic Tropical South Atlantic, integrated OUR increases by 0.2 molO2/m2/yr, while the Rtrue integral decreases by 0.3 molO2/m2/yr. A possible reason for the diverging OUR and Rtrue is ocean mixing, which affects water mass composition and maps remote respiration changes to the study region. Key Points: - Our model study confirms earlier findings that oxygen utilization rate (OUR) underestimates true respiration (Rtrue) in mesopelagic ocean - Despite OUR underestimate Rtrue, OUR can adequately estimate long-term changes in Rtrue in the mesopelagic North Atlantic subtropical gyre - OUR cannot adequately estimate climate-driven changes in Rtrue in the mesopelagic tropical South Atlantic where different water masses mix