Description: The effects of climate change (CC) on contaminants and their potential consequences to marine ecosystem services and human wellbeing are of paramount importance, as they pose overlapping risks. Here, we discuss how the interaction between CC and contaminants leads to poorly constrained impacts that affects the sensitivity of organisms to contamination leading to impaired ecosystem function, services and risk assessment evaluations. Climate drivers, such as ocean warming, ocean deoxygenation, changes in circulation, ocean acidification, and extreme events interact with trace metals, organic pollutants, excess nutrients, and radionuclides in a complex manner. Overall, the holistic consideration of the pollutants-climate change nexus has significant knowledge gaps, but will be important in understanding the fate, transport, speciation, bioavailability, toxicity, and inventories of contaminants. Greater focus on these uncertainties would facilitate improved predictions of future changes in the global biogeochemical cycling of contaminants and both human health and marine ecosystems.

Description: Diatoms play an essential role in marine biogeochemical cycles by their large contribution to primary production and particle export. Under nutrient limitation, diatom biomass often exhibits large deviations from the Redfield ratio. Here a biogeochemical ocean general circulation model is applied to investigate the influence of variations in diatom stoichiometry. The ecosystem model allows for variable Chl:C:N:Si stoichiometry in phytoplankton biomass regulated by light and availability of macronutrients (nitrate, silicic acid) and iron. Two size classes of phytoplankton are considered with the larger representing diatoms. After 5 years of simulation, the surface distributions of both phytoplankton groups are in a reasonable cyclostationary state. Compared to the ‘steady’ state, a sensitivity simulation with fixed diatom stoichiometry for Si:N of 1.2:1 showed a slight shift from small phytoplankton to diatoms leading to a shift in primary production between two groups. Total primary and export production were conservative, indicating a tendency for compensation. In the Southern Ocean, less opal production and decreased particle export ratio of Si:N resulted in raising silicic acid to the south of Subantarctic Front elucidating the importance of decoupling of different elemental cycles.

Description: In coupled biogeochmical–ocean models, the choice of numerical schemes in the ocean circulation component can have a large influence on the distribution of the biological tracers. Biogeochemical models are traditionally coupled to ocean general circulation models (OGCMs), which are based on dynamical cores employing quasi-regular meshes, and therefore utilize limited spatial resolution in a global setting. An alternative approach is to use an unstructured-mesh ocean model, which allows variable mesh resolution. Here, we present initial results of a coupling between the Finite Element Sea Ice–Ocean Model (FESOM) and the biogeochemical model REcoM2 (Regulated Ecosystem Model 2), with special focus on the Southern Ocean. Surface fields of nutrients, chlorophyll a and net primary production (NPP) were compared to available data sets with a focus on spatial distribution and seasonal cycle. The model produces realistic spatial distributions, especially regarding NPP and chlorophyll a, whereas the iron concentration becomes too low in the Pacific Ocean. The modelled NPP is 32.5 Pg C yr−1 and the export production 6.1 Pg C yr−1, which is lower than satellite-based estimates, mainly due to excessive iron limitation in the Pacific along with too little coastal production. The model performs well in the Southern Ocean, though the assessment here is hindered by the lower availability of observations. The modelled NPP is 3.1 Pg C yr−1 in the Southern Ocean and the export production 1.1 Pg C yr−1. All in all, the combination of a circulation model on an unstructured grid with a biogeochemical–ocean model shows similar performance to other models at non-eddy-permitting resolution. It is well suited for studies of the Southern Ocean, but on the global scale deficiencies in the Pacific Ocean would have to be taken into account.

Description: Over the Last Glacial Maximum (LGM, about 21ka BP) and subsequent deglaciation, the presence of vast Northern Hemisphere ice sheets caused abrupt changes in surface topography and background climatic state. While the ice-sheet extent is well known, several conflicting ice-sheet topography reconstructions suggest that there is an existence of uncertainty in this boundary condition. Simulations with a water isotope-enabled fully coupled Earth system model (COSMOS) and five different Laurentide Ice Sheet (LIS) reconstructions of different elevation are used to assess the range of sensitivity of climate modes in response to the uncertainty in this LIS topography. This study reveals that a change in ice sheet height can alter the coupled oceanic and atmospheric climate system during the LGM. A warming anomaly can be found over the region of lower ice sheet height, i.e. North America and lead to a slightly enhanced P-E over the North Atlantic, which also contributes to a weaker ocean circulation in the northern North Atlantic. The continental and sea surface temperature (SST) of the LGM as simulated by climate models have been compared with the subfossil pollen and plant macrofossil based reconstruction and reconstructed from marine temperature proxies. The continental reconstruction shows a similar pattern and in a good agreement with model data. The SST proxy dataset comprises a global compilation of planktonic foraminifera, diatom, radiolarian, dinocyst, alkenones and planktonic foraminifera Mg/Ca-derived SST estimates. Significant mismatches between modeled and reconstructed SST have been observed. Among the five LIS reconstructions, Tarasov LIS reconstructions show the highest correlation with reconstructed SAT and SST. In the case of Radiolarian, Mg/Ca, diatoms and foraminifera show a positive correlation where dinocyst and alkenones show very low and negative correlation with the model. Dinocyst-based SST records are much warmer than reconstructed by other proxies as well than PI temperature. However, large deviations with respect to model temperatures recorded by different proxies remain. Therefore, it has been speculated that considering different habitats depth and growing seasons of the planktonic organisms used for SST reconstruction could provide a better agreement of proxy data with model results on a regional scale and can reduce model–data misfits is determined. It is found that shifting in the habitat depth and living season can remove parts of the observed model–data mismatches in SST anomalies. The findings of this study give a clear reference for PMIP communities to use an appropriate ice sheet reconstructions with a more reliable ocean state as well as indicate that modelled and reconstructed temperature anomalies are to a large degree only qualitatively comparable, thus providing a challenge for the interpretation of proxy data as well as the model sensitivity to orbital forcing.

Description: The effects of climate change (CC) on contaminants and their potential consequences to marine ecosystem services and human wellbeing are of paramount importance, as they pose overlapping risks. Here, we discuss how the interaction between CC and contaminants leads to poorly constrained impacts that affects the sensitivity of organisms to contamination leading to impaired ecosystem function, services and risk assessment evaluations. Climate drivers, such as ocean warming, ocean deoxygenation, changes in circulation, ocean acidification, and extreme events interact with trace metals, organic pollutants, excess nutrients, and radionuclides in a complex manner. Overall, the holistic consideration of the pollutants-climate change nexus has significant knowledge gaps, but will be important in understanding the fate, transport, speciation, bioavailability, toxicity, and inventories of contaminants. Greater focus on these uncertainties would facilitate improved predictions of future changes in the global biogeochemical cycling of contaminants and both human health and marine ecosystems.