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The Arctic Mediterranean (AM) is the collective name for the Arctic Ocean, the Nordic Seas, and their adjacent shelf seas. Water enters into this region through the Bering Strait (Pacific inflow) and through the passages across the Greenland–Scotland Ridge (Atlantic inflow) and is modified within the AM. The modified waters leave the AM in several flow branches which are grouped into two different categories: (1) overflow of dense water through the deep passages across the Greenland–Scotland Ridge, and (2) outflow of light water – here termed surface outflow – on both sides of Greenland. These exchanges transport heat and salt into and out of the AM and are important for conditions in the AM. They are also part of the global ocean circulation and climate system. Attempts to quantify the transports by various methods have been made for many years, but only recently the observational coverage has become sufficiently complete to allow an integrated assessment of the AM exchanges based solely on observations. In this study, we focus on the transport of water and have collected data on volume transport for as many AM-exchange branches as possible between 1993 and 2015. The total AM import (oceanic inflows plus freshwater) is found to be 9.1 Sv (sverdrup, 1 Sv =106 m3 s−1) with an estimated uncertainty of 0.7 Sv and has the amplitude of the seasonal variation close to 1 Sv and maximum import in October. Roughly one-third of the imported water leaves the AM as surface outflow with the remaining two-thirds leaving as overflow. The overflow water is mainly produced from modified Atlantic inflow and around 70 % of the total Atlantic inflow is converted into overflow, indicating a strong coupling between these two exchanges. The surface outflow is fed from the Pacific inflow and freshwater (runoff and precipitation), but is still approximately two-thirds of modified Atlantic water. For the inflow branches and the two main overflow branches (Denmark Strait and Faroe Bank Channel), systematic monitoring of volume transport has been established since the mid-1990s, and this enables us to estimate trends for the AM exchanges as a whole. At the 95 % confidence level, only the inflow of Pacific water through the Bering Strait showed a statistically significant trend, which was positive. Both the total AM inflow and the combined transport of the two main overflow branches also showed trends consistent with strengthening, but they were not statistically significant. They do suggest, however, that any significant weakening of these flows during the last two decades is unlikely and the overall message is that the AM exchanges remained remarkably stable in the period from the mid-1990s to the mid-2010s. The overflows are the densest source water for the deep limb of the North Atlantic part of the meridional overturning circulation (AMOC), and this conclusion argues that the reported weakening of the AMOC was not due to overflow weakening or reduced overturning in the AM. Although the combined data set has made it possible to establish a consistent budget for the AM exchanges, the observational coverage for some of the branches is limited, which introduces considerable uncertainty. This lack of coverage is especially extreme for the surface outflow through the Denmark Strait, the overflow across the Iceland–Faroe Ridge, and the inflow over the Scottish shelf. We recommend that more effort is put into observing these flows as well as maintaining the monitoring systems established for the other exchange branches.

Recent Arctic studies suggest that sea ice decline and permafrost thawing will affect phytoplankton dynamics and stimulate heterotrophic communities. However, in what way the plankton composition will change as the warming proceeds remains elusive. Here we investigate the chemical signature of the plankton-dominated fraction of particulate organic matter (POM) collected along the Siberian Shelf. POM (> 10 µm) samples were analysed using molecular biomarkers (CuO oxidation and IP25) and dual-carbon isotopes (δ13C and Δ14C). In addition, surface water chemical properties were integrated with the POM (> 10 µm) dataset to understand the link between plankton composition and environmental conditions. δ13C and Δ14C exhibited a large variability in the POM (> 10 µm) distribution while the content of terrestrial biomarkers in the POM was negligible. In the Laptev Sea (LS), δ13C and Δ14C of POM (> 10 µm) suggested a heterotrophic environment in which dissolved organic carbon (DOC) from the Lena River was the primary source of metabolisable carbon. Within the Lena plume, terrestrial DOC probably became part of the food web via bacteria uptake and subsequently transferred to relatively other heterotrophic communities (e.g. dinoflagellates). Moving eastwards toward the sea-ice-dominated East Siberian Sea (ESS), the system became progressively more autotrophic. Comparison between δ13C of POM (> 10 µm) samples and CO2aq concentrations revealed that the carbon isotope fractionation increased moving towards the easternmost and most productive stations. In a warming scenario characterised by enhanced terrestrial DOC release (thawing permafrost) and progressive sea ice decline, heterotrophic conditions might persist in the LS while the nutrient-rich Pacific inflow will likely stimulate greater primary productivity in the ESS. The contrasting trophic conditions will result in a sharp gradient in δ13C between the LS and ESS, similar to what is documented in our semi-synoptic study.

Coastal time series of ocean carbonate chemistry are critical for understanding how global anthropogenic change manifests in near-shore ecosystems. Yet, they are few and have low temporal resolution. At the time series station Point B in the northwestern Mediterranean Sea, seawater was sampled weekly from 2007 through 2015, at 1 and 50 m, and analyzed for total dissolved inorganic carbon (CT) and total alkalinity (AT). Parameters of the carbonate system such as pH (pHT, total hydrogen ion scale) were calculated and a deconvolution analysis was performed to identify drivers of change. The rate of surface ocean acidification was −0.0028 ± 0.0003 units pHT yr−1. This rate is larger than previously identified open-ocean trends due to rapid warming that occurred over the study period (0.072 ± 0.022 °C yr−1). The total pHT change over the study period was of similar magnitude as the diel pHT variability at this site. The acidification trend can be attributed to atmospheric carbon dioxide (CO2) forcing (59 %, 2.08 ± 0.01 ppm CO2 yr−1) and warming (41 %). Similar trends were observed at 50 m but rates were generally slower. At 1 m depth, the increase in atmospheric CO2 accounted for approximately 40 % of the observed increase in CT (2.97 ± 0.20 µmol kg−1 yr−1). The remaining increase in CT may have been driven by the same unidentified process that caused an increase in AT (2.08 ± 0.19 µmol kg−1 yr−1). Based on the analysis of monthly trends, synchronous increases in CT and AT were fastest in the spring–summer transition. The driving process of the interannual increase in AT has a seasonal and shallow component, which may indicate riverine or groundwater influence. This study exemplifies the importance of understanding changes in coastal carbonate chemistry through the lens of biogeochemical cycling at the land–sea interface. This is the first coastal acidification time series providing multiyear data at high temporal resolution. The data confirm rapid warming in the Mediterranean Sea and demonstrate coastal acidification with a synchronous increase in total alkalinity.

Thanks to the abundant observation data, we are able to deploy the traditional point-to-point comparison and statistical measures in combination with a comprehensive model validation scheme to assess the skills of the biogeochemical model ERGOM in providing an operational service for the Baltic Sea. The model assessment concludes that the operational products can resolve the main observed seasonal features for phytoplankton biomass, dissolved inorganic nitrogen, dissolved inorganic phosphorus and dissolved oxygen in euphotic layers as well as their vertical profiles. This assessment reflects that the model errors of the operational system at the current stage are mainly caused by insufficient light penetration, excessive organic particle export downward, insufficient regional adaptation and some from improper initialization. This study highlights the importance of applying multiple schemes in order to assess model skills rigidly and identify main causes for major model errors.

As part of the GlobColour project, daily chlorophyll a observations, derived using remotely sensed ocean colour data from the MERIS, MODIS and SeaWiFS sensors, are produced. The ability of these products to be assimilated into a pre-operational global coupled physical-biogeochemical model has been tested, on both a hindcast and near-real-time basis, and the impact on the system assessed. The assimilation was found to immediately and considerably improve the bias, root mean square error and correlation of modelled surface chlorophyll concentration compared to the GlobColour observations, an improvement which was sustained throughout the year and in every ocean basin. Errors against independent in situ chlorophyll observations were also reduced, both at and beneath the ocean surface. However, the model fit to in situ observations was not consistently better than that of climatology, due to errors in the underlying model. The assimilation scheme used is multivariate, updating all biogeochemical model state variables at all depths. The other variables were not degraded by the assimilation, with annual mean surface fields of nutrients, alkalinity and carbon variables remaining of similar quality compared to climatology. There was evidence of improved representation of zooplankton concentration, and reduced errors were seen against in situ observations of nitrate and pCO2, but too few observations were available to conclude about global model skill. The near-real-time GlobColour products were found to be sufficiently reliable for operational purposes, and of benefit to both operational-style systems and reanalyses.