ALBERT

Description: A new climate model has been developed that employs a multi-resolution dynamical core for the sea ice-ocean component. In principle, the multi-resolution approach allows one to use enhanced horizontal resolution in dynamically active regions while keeping a coarse-resolution setup otherwise. The coupled model consists of the atmospheric model ECHAM6 and the finite element sea ice-ocean model (FESOM). In this study only moderate refinement of the unstructured ocean grid is applied and the resolution varies from about 25 km in the northern North Atlantic and in the tropics to about 150 km in parts of the open ocean; the results serve as a benchmark upon which future versions that exploit the potential of variable resolution can be built. Details of the formulation of the model are given and its performance in simulating observed aspects of the mean climate is described. Overall, it is found that ECHAM6–FESOM realistically simulates many aspects of the observed climate. More specifically it is found that ECHAM6–FESOM performs at least as well as some of the most sophisticated climate models participating in the fifth phase of the Coupled Model Intercomparison Project. ECHAM6–FESOM shares substantial shortcomings with other climate models when it comes to simulating the North Atlantic circulation.

Description: Recent work has shown that glaciers are a globally significant source of the micronutrient Fe to the ocean. Polar regions are particularly susceptible to climate change and have been subject to pronounced warming in the past few decades. In response to this warming, the volume of glacial meltwater runoff from Greenland has increased. This meltwater has a relatively high particulate and dissolved Fe content. Seasonal Fe limitation of marine ecosystems has been found in parts of the North Atlantic, so it has been proposed that increasing fluxes of Fe rich meltwater from Greenland to the North Atlantic could alleviate this Fe limitation and thereby increase marine primary production. However, here we use a synthesis of biogeochemical and physical oceanography studies to suggest that the physical circulation around Greenland does not favour direct export of dissolved or particulate Fe from inshore to offshore waters. The Fe budget in surface waters of the North Atlantic may therefore be insensitive to increasing meltwater fluxes from Greenland.

Description: Hydrothermal vents on mid-oceanic ridges are patchily distributed and host many taxa endemic to deep-sea chemosynthetic environments, whose dispersal may be constrained by geographical barriers. The aim of this study was to investigate the connectivity of three populations of the ‘scaly-foot gastropod’ (Chrysomallon squamiferum Chen et al., 2015), a species endemic to hydrothermal vents in the Indian Ocean, amongst two vent fields on the Central Indian Ridge (CIR) and Longqi field, the first sampled vent field on the Southwest Indian Ridge (SWIR). Connectivity and population structure across the two mid-oceanic ridges were investigated using a 489-bp fragment of the cytochrome oxidase c subunit I (COI) gene. Phylogeographical approaches used include measures of genetic differentiation (FST), reconstruction of parsimony haplotype network, mismatch analyses and neutrality tests. Relative migrants per generation were estimated between the fields. Significant differentiation (FST = 0.28–0.29, P 〈 0.001) was revealed between the vent field in SWIR and the two in CIR. Signatures were detected indicating recent bottleneck events followed by demographic expansion in all populations. Estimates of relative number of migrants were relatively low between the SWIR and CIR, compared with values between the CIR vent fields. The present study is the first to investigate connectivity between hydrothermal vents across two mid-ocean ridges in the Indian Ocean. The phylogeography revealed for C. squamiferum indicates low connectivity between SWIR and CIR vent populations, with implications for the future management of environmental impacts for seafloor mining at hydrothermal vents in the region, as proposed for Longqi.

Description: Stable carbon isotopes of dissolved inorganic carbon (δ13CDIC) in the ocean are generally not well understood as they are governed by a complex interplay of biological processes and air–sea exchange. In the Arctic Ocean, δ13CDIC values are prone to change in the near future with rapidly changing climate conditions. This study provides a baseline to assess the δ13CDIC of the Arctic Ocean with a focus on upper to intermediate waters (to ~500 m). Measured δ13CDIC values in the Arctic Ocean range from ~−0.6 to +2.2 ‰. In the Eurasian Basin, the δ13CDIC values lie between ~1 and 1.5 ‰ and exhibit little variation within the upper layers. In the Canada Basin, δ13CDIC values reach 2 ‰ in the surface layer, with lowest values of ~−0.6 ‰ found at ~200 m water depth. At greater depth, δ13CDIC values range from ~1 to 1.5 ‰ within both basins. In the Canada Basin, nutrient levels are higher than in the Eurasian Basin and associated variations in δ13CDIC are clearly related to biological processes. However, low δ13CDIC values in the Canada Basin are also strongly influenced by non-equilibrium air–sea exchange processes. The different δ13CDIC patterns between the Canada Basin and the Eurasian Basin appear to be linked to differences in transport processes within the Arctic Ocean halocline. The upper layers in the Canada basins have direct contributions of waters from the Laptev, East Siberian and Chukchi shelves, which contain elevated fractions of river waters and sea-ice related brines, whereas their counterparts, in the Eurasian Basin, are mostly formed by halocline waters from the Barents and Kara seas. River waters have low δ13CDIC of ~−8 ‰ on average, but in the Arctic basins this signal is mostly lost and δ13CDIC values show only a weak correlation to river water fractions contained in the water mass. No relation between δ13CDIC and sea-ice related brine contribution is apparent.

Description: A seasonal forecast system is presented, based on the global coupled climate model MPI-ESM as used for CMIP5 simulations. We describe the initialisation of the system and analyse its predictive skill for surface temperature. The presented system is initialised in the atmospheric, oceanic, and sea ice component of the model from reanalysis/observations with full field nudging in all three components. For the initialisation of the ensemble, bred vectors with a vertically varying norm are implemented in the ocean component to generate initial perturbations. In a set of ensemble hindcast simulations, starting each May and November between 1982 and 2010, we analyse the predictive skill. Bias-corrected ensemble forecasts for each start date reproduce the observed surface temperature anomalies at 2–4 months lead time, particularly in the tropics. Niño3.4 sea surface temperature anomalies show a small root-mean-square error and predictive skill up to 6 months. Away from the tropics, predictive skill is mostly limited to the ocean, and to regions which are strongly influenced by ENSO teleconnections. In summary, the presented seasonal prediction system based on a coupled climate model shows predictive skill for surface temperature at seasonal time scales comparable to other seasonal prediction systems using different underlying models and initialisation strategies. As the same model underlying our seasonal prediction system—with a different initialisation—is presently also used for decadal predictions, this is an important step towards seamless seasonal-to-decadal climate predictions.

Description: Global-scale studies of marine food webs are rare, despite their necessity for examining and understanding ecosystem level effects of climate variability. Here we review the progress of an international collaboration that compiled regional diet datasets of multiple top predator fishes from the Indian, Pacific and Atlantic Oceans and developed new statistical methods that can be used to obtain a comprehensive ocean-scale understanding of food webs and climate impacts on marine top predators. We loosely define top predators not as species at the apex of the food web, but rather a guild of large predators near the top of the food web. Specifically, we present a framework for world-wide compilation and analysis of global stomach-contents and stable-isotope data of tunas and other large pelagic predatory fishes. To illustrate the utility of the statistical methods, we show an example using yellowfin tuna in a “test” area in the Pacific Ocean. Stomach-contents data were analyzed using a modified (bagged) classification tree approach, which is being prepared as an R statistical software package. Bulk δ15N values of yellowfin tuna muscle tissue were examined using a Generalized Additive Model, after adjusting for spatial differences in the δ15N values of the baseline primary producers predicted by a global coupled ocean circulation-biogeochemical-isotope model. Both techniques in tandem demonstrated the capacity of this approach to elucidate spatial patterns of variations in both forage species and predator trophic positions and have the potential to predict responses to climate change. We believe this methodology could be extended to all marine top predators. Our results emphasize the necessity for quantitative investigations of global-scale datasets when evaluating changes to the food webs underpinning top ocean predators under long-term climatic variability.