ALBERT

Description: Global biogeochemical ocean models are often tuned to match the observed distributions and fluxes of inorganic and organic quantities. This tuning is typically carried out “by hand”. However, this rather subjective approach might not yield the best fit to observations, is closely linked to the circulation employed and is thus influenced by its specific features and even its faults. We here investigate the effect of model tuning, via objective optimisation, of one biogeochemical model of intermediate complexity when simulated in five different offline circulations. For each circulation, three of six model parameters have been adjusted to characteristic features of the respective circulation. The values of these three parameters – namely, the oxygen utilisation of remineralisation, the particle flux parameter and potential nitrogen fixation rate – correlate significantly with deep mixing and ideal age of North Atlantic Deep Water (NADW) and the outcrop area of Antarctic Intermediate Waters (AAIW) and Subantarctic Mode Water (SAMW) in the Southern Ocean. The clear relationship between these parameters and circulation characteristics, which can be easily diagnosed from global models, can provide guidance when tuning global biogeochemistry within any new circulation model. The results from 20 global cross-validation experiments show that parameter sets optimised for a specific circulation can be transferred between similar circulations without losing too much of the model's fit to observed quantities. When compared to model intercomparisons of subjectively tuned, global coupled biogeochemistry–circulation models, each with different circulation and/or biogeochemistry, our results show a much lower range of oxygen inventory, oxygen minimum zone (OMZ) volume and global biogeochemical fluxes. Export production depends to a large extent on the circulation applied, while deep particle flux is mostly determined by the particle flux parameter. Oxygen inventory, OMZ volume, primary production and fixed-nitrogen turnover depend more or less equally on both factors, with OMZ volume showing the highest sensitivity, and residual variability. These results show a beneficial effect of optimisation, even when a biogeochemical model is first optimised in a relatively coarse circulation and then transferred to a different finer-resolution circulation model.

Description: Controlled manipulation of environmental conditions within large enclosures in the ocean, so-called pelagic mesocosms, has become a standard method to explore potential responses of marine plankton communities to anthropogenic change. Among the challenges of interpreting mesocosm data is the often uncertain role of vertical mixing, which usually is not observed directly. To account for mixing nonetheless, two pragmatic assumptions are common: either that the water column is homogeneously mixed or that it is divided into two water bodies with a horizontal barrier inhibiting turbulent exchange. In this study, we present a model-based reanalysis of vertical turbulent diffusion in the mesocosm experiments PeECE III and KOSMOS 2013. Our diffusivity estimates indicate intermittent mixing events along with stagnating periods and yield simulated temperature and salinity profiles that are consistent with the observations. Here, we provide the respective diffusivities as a comprehensive data product in the Network Common Data Format (NetCDF). This data product will help to guide forthcoming model studies that aim at deepening our understanding of biogeochemical processes in the PeECE III and KOSMOS 2013 mesocosms, such as the CO2-related changes in marine carbon export. In addition, we make our model code available, providing an adjustable tool to simulate vertical mixing in any other pelagic mesocosm. The data product and the model code are available at https://doi.org/10.1594/PANGAEA.905311 (Mathesius et al., 2019).

Description: The University of Victoria Earth System Climate Model (UVic ESCM) of intermediate complexity has been a useful tool in recent assessments of long-term climate changes, including both paleo-climate modelling and uncertainty assessments of future warming. Since the last official release of the UVic ESCM 2.9 and the two official updates during the last decade, considerable model development has taken place among multiple research groups. The new version 2.10 of the University of Victoria Earth System Climate Model presented here will be part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). More precisely it will be used in the intercomparison of Earth system models of intermediate complexity (EMIC), such as the C4MIP, the Carbon Dioxide Removal and Zero Emissions Commitment model intercomparison projects (CDR-MIP and ZECMIP, respectively). It now brings together and combines multiple model developments and new components that have come about since the last official release of the model. The main additions to the base model are (i) an improved biogeochemistry module for the ocean, (ii) a vertically resolved soil model including dynamic hydrology and soil carbon processes, and (iii) a representation of permafrost carbon. To set the foundation of its use, we here describe the UVic ESCM 2.10 and evaluate results from transient historical simulations against observational data. We find that the UVic ESCM 2.10 is capable of reproducing changes in historical temperature and carbon fluxes well. The spatial distribution of many ocean tracers, including temperature, salinity, phosphate and nitrate, also agree well with observed tracer profiles. The good performance in the ocean tracers is connected to an improved representation of ocean physical properties. For the moment, the main biases that remain are a vegetation carbon density that is too high in the tropics, a higher than observed change in the ocean heat content (OHC) and an oxygen utilization in the Southern Ocean that is too low. All of these biases will be addressed in the next updates to the model.

Description: Ocean eddies can both trigger mixing (during their formation and decay) and effectively shield water encompassed from being exchanged with ambient water (throughout their lifetimes). These antagonistic effects of eddies complicate the interpretation of synoptic snapshots typically obtained by ship-based oceanographic measurement campaigns. Here we use a coupled physical–biogeochemical model to explore biogeochemical dynamics within anticyclonic eddies in the eastern tropical South Pacific Ocean. The goal is to understand the diverse biogeochemical patterns that have been observed at the subsurface layers of the anticyclonic eddies in this region. Our model results suggest that the diverse subsurface nutrient patterns within eddies are associated with the presence of water masses of different origins at different depths.

Description: To describe the underlying processes involved in oceanic plankton dynamics is crucial for the determination of energy and mass flux through an ecosystem and for the estimation of biogeochemical element cycling. Many planktonic ecosystem models were developed to resolve major processes so that flux estimates can be derived from numerical simulations. These results depend on the type and number of parameterizations incorporated as model equations. Furthermore, the values assigned to respective parameters specify a model's solution. Representative model results are those that can explain data; therefore, data assimilation methods are utilized to yield optimal estimates of parameter values while fitting model results to match data. Central difficulties are (1) planktonic ecosystem models are imperfect and (2) data are often too sparse to constrain all model parameters. In this review we explore how problems in parameter identification are approached in marine planktonic ecosystem modelling. We provide background information about model uncertainties and estimation methods, and how these are considered for assessing misfits between observations and model results. We explain differences in evaluating uncertainties in parameter estimation, thereby also discussing issues of parameter identifiability. Aspects of model complexity are addressed and we describe how results from cross-validation studies provide much insight in this respect. Moreover, approaches are discussed that consider time- and space-dependent parameter values. We further discuss the use of dynamical/statistical emulator approaches, and we elucidate issues of parameter identification in global biogeochemical models. Our review discloses many facets of parameter identification, as we found many commonalities between the objectives of different approaches, but scientific insight differed between studies. To learn more from results of planktonic ecosystem models we recommend finding a good balance in the level of sophistication between mechanistic modelling and statistical data assimilation treatment for parameter estimation.

Description: Observations indicate an expansion of oxygen minimum zones (OMZs) over the past 50 years, likely related to ongoing deoxygenation caused by reduced oxygen solubility, changes in stratification and circulation, and a potential acceleration of organic matter turnover in a warming climate. The overall area of ocean sediments that are in direct contact with low-oxygen bottom waters also increases with expanding OMZs. This leads to a release of phosphorus from ocean sediments. If anthropogenic carbon dioxide emissions continue unabated, higher temperatures will cause enhanced weathering on land, which, in turn, will increase the phosphorus and alkalinity fluxes into the ocean and therefore raise the ocean's phosphorus inventory even further. A higher availability of phosphorus enhances biological production, remineralisation and oxygen consumption, and might therefore lead to further expansions of OMZs, representing a positive feedback. A negative feedback arises from the enhanced productivity-induced drawdown of carbon and also increased uptake of CO2 due to weathering-induced alkalinity input. This feedback leads to a decrease in atmospheric CO2 and weathering rates. Here, we quantify these two competing feedbacks on millennial timescales for a high CO2 emission scenario. Using the University of Victoria (UVic) Earth System Climate Model of intermediate complexity, our model results suggest that the positive benthic phosphorus release feedback has only a minor impact on the size of OMZs in the next 1000 years. The increase in the marine phosphorus inventory under assumed business-as-usual global warming conditions originates, on millennial timescales, almost exclusively (〉 80 %) from the input via terrestrial weathering and causes a 4- to 5-fold expansion of the suboxic water volume in the model.

Description: The fate of the organic matter (OM) produced by marine life controls the major biogeochemical cycles of the Earth's system. The OM produced through photosynthesis is either preserved, exported towards sediments or degraded through remineralisation in the water column. The productive eastern boundary upwelling systems (EBUSs) associated with oxygen minimum zones (OMZs) would be expected to foster OM preservation due to low O2 conditions. But their intense and diverse microbial activity should enhance OM degradation. To investigate this contradiction, sediment traps were deployed near the oxycline and in the OMZ core on an instrumented moored line off Peru. Data provided high-temporal-resolution O2 series characterising two seasonal steady states at the upper trap: suboxic ([O2]

Description: This study introduces the Systematic Correlation Matrix Evaluation (SCoMaE) method, a bottom-up approach which combines expert judgment and statistical information to systematically select transparent, non redundant indicators for a com- prehensive assessment of the state of the Earth system. The methods consists of three basic steps: 1) Calculation of a correlation matrix among variables relevant for a given research question, 2) Systematic evaluation of the matrix, to identify clusters of variables with similar behavior and respective mutually independent indicators, and 3) Interpretation of the identified clusters, enabling a learning effect from the selection of indicators. Optional further analysis steps include: 4) Testing the robustness of identified clusters with respect to changes in forcing or boundary conditions, 5) Enabling a comparative assessment of varying scenarios by constructing and evaluating a common correlation matrix, or 6) Inclusion of expert judgment such as to prescribe indicators, to allow for considerations other than statistical consistency. The exemplary application of the SCoMaE method to Earth system model output forced by different CO2 emission scenarios reveals the necessity of re-evaluating indicators identified in a historical scenario simulation for an accurate assessment of an intermediate-high, as well as a business-as-usual, climate change scenario simulation, which arises from changes in prevailing correlations in the Earth system under varying climate forcing. For a comparative assessment of the three climate change scenarios, we construct and evaluate a common correlation matrix, in which we identify robust correlations between variables across the three considered scenarios.

Description: We investigate the climate mitigation potential and collateral effects of direct injections of captured CO2 into the deep ocean as a possible means to close the gap between an intermediate CO2 emissions scenario and a specific temperature target, such as the 1.5 ∘C target aimed for by the Paris Agreement. For that purpose, a suite of approaches for controlling the amount of direct CO2 injections at 3000 m water depth are implemented in an Earth system model of intermediate complexity. Following the representative concentration pathway RCP4.5, which is a medium mitigation CO2 emissions scenario, cumulative CO2 injections required to meet the 1.5 ∘C climate goal are found to be 390 Gt C by the year 2100 and 1562 Gt C at the end of simulations, by the year 3020. The latter includes a cumulative leakage of 602 Gt C that needs to be reinjected in order to sustain the targeted global mean temperature. CaCO3 sediment and weathering feedbacks reduce the required CO2 injections that comply with the 1.5 ∘C target by about 13 % in 2100 and by about 11 % at the end of the simulation. With respect to the injection-related impacts we find that average pH values in the surface ocean are increased by about 0.13 to 0.18 units, when compared to the control run. In the model, this results in significant increases in potential coral reef habitats, i.e., the volume of the global upper ocean (0 to 130 m depth) with omega aragonite 〉 3.4 and ocean temperatures between 21 and 28 ∘C, compared to the control run. The potential benefits in the upper ocean come at the expense of strongly acidified water masses at depth, with maximum pH reductions of about −2.37 units, relative to preindustrial levels, in the vicinity of the injection sites. Overall, this study demonstrates that massive amounts of CO2 would need to be injected into the deep ocean in order to reach and maintain the 1.5 ∘C climate target in a medium mitigation scenario on a millennium timescale, and that there is a trade-off between injection-related reductions in atmospheric CO2 levels accompanied by reduced upper-ocean acidification and adverse effects on deep-ocean chemistry, particularly near the injection sites.

Description: Uncertainties in projections of marine biogeochemistry from Earth system models (ESMs) are associated to a large degree with the imperfect representation of the marine plankton ecosystem, in particular the physiology of primary and secondary producers. Here, we describe the implementation of an optimality-based plankton–ecosystem model (OPEM) version 1.1 with variable carbon : nitrogen : phosphorus (C:N:P) stoichiometry in the University of Victoria ESM (UVic; Eby et al., 2009; Weaver et al., 2001) and the behaviour of two calibrated reference configurations, which differ in the assumed temperature dependence of diazotrophs. Predicted tracer distributions of oxygen and dissolved inorganic nutrients are similar to those of an earlier fixed-stoichiometry formulation in UVic (Nickelsen et al., 2015). Compared to the classic fixed-stoichiometry UVic model, OPEM is closer to recent satellite-based estimates of net community production (NCP), despite overestimating net primary production (NPP), can better reproduce deep-ocean gradients in the NO3-:PO43- ratio and partially explains observed patterns of particulate C:N:P in the surface ocean. Allowing diazotrophs to grow (but not necessarily fix N2) at similar temperatures as other phytoplankton results in a better representation of surface Chl and NPP in the Arctic and Antarctic oceans. Deficiencies of our calibrated OPEM configurations may serve as a magnifying glass for shortcomings in global biogeochemical models and hence guide future model development. The overestimation of NPP at low latitudes indicates the need for improved representations of temperature effects on biotic processes, as well as phytoplankton community composition, which may be represented by locally varying parameters based on suitable trade-offs. The similarity in the overestimation of NPP and surface autotrophic particulate organic carbon (POC) could indicate deficiencies in the representation of top-down control or nutrient supply to the surface ocean. Discrepancies between observed and predicted vertical gradients in particulate C:N:P ratios suggest the need to include preferential P remineralisation, which could also benefit the representation of N2 fixation. While OPEM yields a much improved distribution of surface N* (NO3--16⋅PO43-+2.9 mmol m−3), it still fails to reproduce observed N* in the Arctic, possibly related to a misrepresentation of the phytoplankton community there and the lack of benthic denitrification in the model. Coexisting ordinary and diazotrophic phytoplankton can exert strong control on N* in our simulations, which questions the interpretation of N* as reflecting the balance of N2 fixation and denitrification.