Impact of marine mercury cycling on coastal atmospheric mercury concentrations in the North- and Baltic Sea region

The cycling of mercury between ocean and atmosphere is an important part of the global Hg cycle. Here we study the regional contribution of the air-sea exchange in the North- and Baltic Sea region. We use a newly developed coupled regional chemistry transport modeling (CTM) system to determine the flux between atmosphere and ocean based on the meteorological model COSMO-CLM, the ocean-ecosystem model ECOSMO, the atmospheric CTM CMAQ and a newly developed module for mercury partitioning and speciation in the ocean (MECOSMO). The model was evaluated using atmospheric observations of gaseous elemental mercury (GEM), surface concentrations of dissolved gaseous mercury (DGM), and air-sea flux (ASF) calculations based on observations made on seven cruises in the western and central Baltic Sea and three cruises in the North Sea performed between 1991 and 2006. It was shown that the model is in good agreement with observations: DGM (Normalized Mean Bias NMB=-0.27 N=413), ASF (NMB=-0.32, N=413), GEM (NMB=0.07, N=2359). Generally, the model was able to reproduce the seasonal DGM cycle with the best agreement during winter and autumn (NMBWinter=-0.26, NMBSpring=-0.41, NMBSummer=-0.29, NMBAutumn=-0.03). The modelled mercury evasion from the Baltic Sea ranged from 3400 to 4000 kg/a for the simulation period 1994–2007 which is on the lower end of previous estimates. Modelled atmospheric deposition, river inflow and air-sea exchange lead to an annual net Hg accumulation in the Baltic Sea of 500 to 1000 kg/a. For the North Sea the model calculates an annual mercury flux into the atmosphere between 5700 and 6000 kg/a. The mercury flux from the ocean influenced coastal atmospheric mercury concentrations. Running CMAQ coupled with the ocean model lead to better agreement with GEM observations. Directly at the coast GEM concentrations could be increased by up to 10% on annual average and observed peaks could be reproduced much better. At stations 100km downwind the impact was still observable but reduced to 1–3%

Long-term retrospective analysis of mackerel spawning in the North Sea: a new time series and modeling approach to CPR data

We present a unique view of mackerel (Scomber scombrus) in the North Sea based on a new time series of larvae caught by the Continuous Plankton Recorder (CPR) survey from 1948-2005, covering the period both before and after the collapse of the North Sea stock. Hydrographic backtrack modelling suggested that the effect of advection is very limited between spawning and larvae capture in the CPR survey. Using a statistical technique not previously applied to CPR data, we then generated a larval index that accounts for both catchability as well as spatial and temporal autocorrelation. The resulting time series documents the significant decrease of spawning from before 1970 to recent depleted levels. Spatial distributions of the larvae, and thus the spawning area, showed a shift from early to recent decades, suggesting that the central North Sea is no longer as important as the areas further west and south. These results provide a consistent and unique perspective on the dynamics of mackerel in this region and can potentially resolve many of the unresolved questions about this stock.lved questions about this stoc

Can environmental conditions at North Atlantic deep-sea habitats be predicted several years ahead? - Taking sponge habitats as an example

Predicting the ambient environmental conditions in the coming several years to one decade is of key relevance for elucidating how deep-sea habitats, like for example sponge habitats, in the North Atlantic will evolve under near-future climate change. However, it is still not well known to what extent the deep-sea environmental properties can be predicted in advance. A regional downscaling prediction system is developed to assess the potential predictability of the North Atlantic deep-sea environmental factors. The large-scale climate variability predicted with the coupled Max Planck Institute Earth System Model with low-resolution configuration (MPI-ESM-LR) is dynamically downscaled to the North Atlantic by providing surface and lateral boundary conditions to the regional coupled physical-ecosystem model HYCOM-ECOSMO. Model results of two physical fields (temperature and salinity) and two biogeochemical fields (concentrations of silicate and oxygen) over 21 sponge habitats are taken as an example to assess the ability of the downscaling system to predict the interannual to decadal variations of the environmental properties based on ensembles of retrospective predictions over the period from 1985 to 2014. The ensemble simulations reveal skillful predictions of the environmental conditions several years in advance with distinct regional differences. In areas closely tied to large-scale climate variability and ice dynamics, both the physical and biogeochemical fields can be skillfully predicted more than 4 years ahead, while in areas under strong influence of upper oceans or open boundaries, the predictive skill for both fields is limited to a maximum of 2 years. The simulations suggest higher predictability for the biogeochemical fields than for the physical fields, which can be partly attributed to the longer persistence of the former fields. Predictability is improved by initialization in areas away from the influence of Mediterranean outflow and areas with weak coupling between the upper and deep oceans. Our study highlights the ability of the downscaling regional system to predict the environmental variations at deep-sea benthic habitats on time scales of management relevance. The downscaling system therefore will be an important part of an integrated approach towards the preservation and sustainable exploitation of the North Atlantic benthic habitats

Towards end-to-end (E2E) modelling in a consistent NPZD-F modelling framework (ECOSMO E2E_v1.0): application to the North Sea and Baltic Sea

Publisher's version (útgefin grein)Coupled physical-biological models usually resolve only parts of the trophic food chain; hence, they run the risk of neglecting relevant ecosystem processes. Additionally, this imposes a closure term problem at the respective "ends" of the trophic levels considered. In this study, we aim to understand how the implementation of higher trophic levels in a nutrient-phytoplankton-zooplankton-detritus (NPZD) model affects the simulated response of the ecosystem using a consistent NPZD-fish modelling approach (ECOSMO E2E) in the combined North Sea-Baltic Sea system. Utilising this approach, we addressed the above-mentioned closure term problem in lower trophic ecosystem modelling at a very low computational cost; thus, we provide an efficient method that requires very little data to obtain spatially and temporally dynamic zooplankton mortality. On the basis of the ECOSMO II coupled ecosystem model we implemented one functional group that represented fish and one group that represented macrobenthos in the 3-D model formulation. Both groups were linked to the lower trophic levels and to each other via predator-prey relationships, which allowed for the investigation of both bottom-up processes and top-down mechanisms in the trophic chain of the North Sea-Baltic Sea ecosystem. Model results for a 10-year-long simulation period (1980-1989) were analysed and discussed with respect to the observed patterns. To understand the impact of the newly implemented functional groups for the simulated ecosystem response, we compared the performance of the ECOSMO E2E to that of a respective truncated NPZD model (ECOSMO II) applied to the same time period. Additionally, we performed scenario tests to analyse the new role of the zooplankton mortality closure term in the truncated NPZD and the fish mortality term in the end-to-end model, which summarises the pressure imposed on the system by fisheries and mortality imposed by apex predators. We found that the model-simulated macrobenthos and fish spatial and seasonal patterns agree well with current system understanding. Considering a dynamic fish component in the ecosystem model resulted in slightly improved model performance with respect to the representation of spatial and temporal variations in nutrients, changes in modelled plankton seasonality, and nutrient profiles. Model sensitivity scenarios showed that changes in the zooplankton mortality parameter are transferred up and down the trophic chain with little attenuation of the signal, whereas major changes in fish mortality and fish biomass cascade down the food chain.This work is a contribution to the FP7 SEAS-ERA SEAMAN collaborative project financed by the Norwegian Research Council (grant no. NRC-227779/E40). We would like to thank Marie Maar for her constructive comments on an earlier version of the paper. Furthermore, we are grateful to an anonymous reviewer and Hagen Radtke, whose thoughtful comments helped to improve the paper.Peer Reviewe

Effects of wave-induced processes in a coupled wave-ocean model on particle transport simulations

This study investigates the effects of wind–wave processes in a coupled wave–ocean circulation model on Lagrangian transport simulations. Drifters deployed in the southern North Sea from May to June 2015 are used. The Eulerian currents are obtained by simulation from the coupled circulation model (NEMO) and the wave model (WAM), as well as a stand-alone NEMO circulation model. The wave–current interaction processes are the momentum and energy sea state dependent fluxes, wave-induced mixing and Stokes–Coriolis forcing. The Lagrangian transport model sensitivity to these wave-induced processes in NEMO is quantified using a particle drift model. Wind waves act as a reservoir for energy and momentum. In the coupled wave–ocean circulation model, the momentum that is transferred into the ocean model is considered as a fraction of the total flux that goes directly to the currents plus the momentum lost from wave dissipation. Additional sensitivity studies are performed to assess the potential contribution of windage on the Lagrangian model performance. Wave-induced drift is found to significantly affect the particle transport in the upper ocean. The skill of particle transport simulations depends on wave–ocean circulation interaction processes. The model simulations were assessed using drifter and high-frequency (HF) radar observations. The analysis of the model reveals that Eulerian currents produced by introducing wave-induced parameterization into the ocean model are essential for improving particle transport simulations. The results show that coupled wave–circulation models may improve transport simulations of marine litter, oil spills, larval drift or transport of biological materials.publishedVersio

Environmental Change at Deep-Sea Sponge Habitats Over the Last Half Century: A Model Hindcast Study for the Age of Anthropogenic Climate Change

Deep-sea sponges inhabit multiple areas of the deep North Atlantic at depths below 250 m. Living in the deep ocean, where environmental properties below the permanent thermocline generally change slowly, they may not easily acclimatize to abrupt changes in the environment. Until now consistent monitoring timeseries of the environment at deep sea sponge habitats are missing. Therefore, long-term simulation with coupled bio-physical models can shed light on the changes in environmental conditions sponges are exposed to. To investigate the variability of North Atlantic sponge habitats for the past half century, the deep-sea conditions have been simulated with a 67-year model hindcast from 1948 to 2014. The hindcast was generated using the ocean general circulation model HYCOM, coupled to the biogeochemical model ECOSMO. The model was validated at known sponge habitats with available observations of hydrography and nutrients from the deep ocean to evaluate the biases, errors, and drift in the model. Knowing the biases and uncertainties we proceed to study the longer-term (monthly to multi-decadal) environmental variability at selected sponge habitats in the North Atlantic and Arctic Ocean. On these timescales, these deep sponge habitats generally exhibit small variability in the water-mass properties. Three of the sponge habitats, the Flemish Cap, East Greenland Shelf and North Norwegian Shelf, had fluctuations of temperature and salinity in 4–6 year periods that indicate the dominance of different water masses during these periods. The fourth sponge habitat, the Reykjanes Ridge, showed a gradual warming of about 0.4°C over the simulation period. The flux of organic matter to the sea floor had a large interannual variability, that, compared to the 67-year mean, was larger than the variability of primary production in the surface waters. Lateral circulation is therefore likely an important control mechanism for the influx of organic material to the sponge habitats. Simulated oxygen varies interannually by less than 1.5 ml/l and none of the sponge habitats studied had oxygen concentrations below hypoxic levels. The present study establishes a baseline for the recent past deep conditions that future changes in deep sea conditions from observations and climate models can be evaluated against.publishedVersio

Quantify the monthly to decadal variability of climate effects on the lower trophic levelse of shelf sea ecosystems

ECOOP WP10, Deliverable no: D10.1.2.1This report describes three studies using multi-decadal simulations of regional coupled hydrodynamics ecosystem models. These models are used to investigate the relationship between lower trophic level marine ecosystems and biogeochemistry, and the physical environment. The models considered here: POLCOMS-ERSEM Atlantic Margin Model run from 1960 to 2003 (NERC and PML) NORWECOM North Sea Model run from 1985-2006 (IMR) ECOSMO (UiB-GFI) North sea and Baltic Sea run 1980-2004 (UiB-GFI) The POLCOMS-ERSEM model is validated using in-situ data from the world ocean data centre and analysed to investigate the potential long term changes in primary production across the period 1960-2004, in the context of model open boundary conditions and drift. The model experiments demonstrate a strong sensitivity of the on-shelf primary production to the oceanic nutrient boundary conditions, suggesting cross-shelf edge nutrient fluxes provide a significant source of variability. The relationship between the model results and the North Atlantic Oscillation are also considered, demonstrating a r~0.65 correlation with on-shelf nutrients and the NAO The NORWECOM model is validated here using time series data from the Dutch coast. Correlations between model variables in a selection of ICES boxes are compared with a number of driving factors. River loads are shown to dominate coastal boxes. The relationships in open-shelf boxes are more ambiguous, although the southerly inflow is demonstrated to have an important role. The validation of the POLCOMS-ERSEM and NORWECOM models both conclude that the simulations have better skill for nutrients than chlorophyll and in open-shelf seas away from the coast. The validation of ECOSMO presented here focuses on zooplankton and comparison with data from the continuous plankton recorder, investigating six different approaches to matching CPR records with model data. Across the North Sea the mean annual cycle shows good agreement between model and CPR. There is also good correlation with along-track variability. EOF and correlation analysis is used to relate the primary production in the North Sea to atmospheric forcing parameters. The EOF patterns tend to match the distribution of summer time stratification, while the wind speed is shows the highest correlation, particularly during the onset and breakdown of stratification. This indicates the strength of cross-thermocline mixing is an important control on primary production variability. The ECOSMO model has been further developed for use in the Baltic by inclusion of nitrogen fixing cyanobacteria. These studies each demonstrate significant control of the inter-annual variability of shelf sea ecosystems through a range of external forcing vectors: oceanic through cross-shelf edge nutrient flux, terrestrial through variations in river nutrient loading, and atmospheric via the wind control of vertical mixing. Each of these vectors potentially mediates climatic variability and climate change

Skilful prediction of cod stocks in the North and Barents Sea a decade in advance

Reliable information about the future state of the ocean and fish stocks is necessary for informed decision-making by fisheries scientists, managers and the industry. However, decadal regional ocean climate and fish stock predictions have until now had low forecast skill. Here, we provide skilful forecasts of the biomass of cod stocks in the North and Barents Seas a decade in advance. We develop a unified dynamical-statistical prediction system wherein statistical models link future stock biomass to dynamical predictions of sea surface temperature, while also considering different fishing mortalities. Our retrospective forecasts provide estimates of past performance of our models and they suggest differences in the source of prediction skill between the two cod stocks. We forecast the continuation of unfavorable oceanic conditions for the North Sea cod in the coming decade, which would inhibit its recovery at present fishing levels, and a decrease in Northeast Arctic cod stock compared to the recent high levels. North Sea cod stock may not recover in the decade 2020-2030 while Northeast Arctic cod biomass is also predicted to decline but will be better able to recover, according to an integration of statistical fisheries models and climate predictionspublishedVersio

Seasonal Prediction of Arabian Sea Marine Heatwaves

Marine heatwaves are known to have a detrimental impact on marine ecosystems, yet predicting when and where they will occur remains a challenge. Here, using a large ensemble of initialized predictions from an Earth System Model, we demonstrate skill in predictions of summer marine heatwaves over large marine ecosystems in the Arabian Sea seven months ahead. Retrospective forecasts of summer (June to August) marine heatwaves initialized in the preceding winter (November) outperform predictions based on observed frequencies. These predictions benefit from initialization during winters of medium to strong El Niño conditions, which have an impact on marine heatwave characteristics in the Arabian Sea. Our probabilistic predictions target spatial characteristics of marine heatwaves that are specifically useful for fisheries management, as we demonstrate using an example of Indian oil sardine (Sardinella longiceps)

Modelling the effects of changes in sea-ice extent on Arctic marine food webs

Diminishing extent of sea-ice cover in the Arctic over recent decades is well documented, and linked to global warming. The ecological effects have been profound especially in areas which have transformed from extensive seasonal ice-cover, to marginal sea-ice or year-round open water. The effects include an increase in Arctic primary production and changes in habitat and food availability for iconic marine mammals. Fishing nations anticipate increased harvesting opportunities in the Arctic as ice cover retreats further, but in November 2017 an international agreement was reached to prevent fisheries development in the Central Arctic Ocean for at least the next 16 years, to give time for development of scientific understanding. The scope for changes primary production due to diminishing sea-ice to propagate through the food web and affect higher trophic levels and charismatic megafauna such as whales, seals and polar bears, is extremely uncertain and hard to predict. The classical hypothesis would be that warming climate will result in a bottom-up trophic cascade from a) increased primary production, to b) increased zooplankton production, to c) increased fish production and harvesting potential, through to d) increased populations of charismatic marine megafauna. However, this assumes that primary production is retained in the upper layers of the water column – the outcome could be quite different if changes in vertical mixing and animal behavior associated with loss of ice cover lead instead to a greater proportion of primary production being directed to the benthos. Here we report on results from a configuration of the StrathE2E marine food web model to represent the Barents Sea. First, we show a baseline model representing sea-ice and temperature conditions during the 1980s-1990s, and then compare this with results from simulation of a warmer, year-round ice-free scenario. The results show that the increase in primary production in the ice-free scenario is amplified as it cascades up the food web. The effects preferentially benefit benthos and demersal fish, but this result is sensitive assumptions about prey preferences and vertical mixing. We also show how the food web responds to harvesting of fish, under both contemporary ice-cover and future ice-free situations. The results presented here are a starting point for a much more extensive new project under the NERC Charging Arctic Ocean Programme (Microbes to Megafauna Modelling of Arctic Seas (MiMeMo)) which we briefly introduce