• European Marine Science
• Other research productsclose
• 2018-2022close
• Open Access close
• FR close
• IT close
• Ocean Science (OS) close

The paper investigates the wintertime dynamics of the coastal northeastern Adriatic Sea and is based on numerical modelling and in situ data collected through field campaigns executed during the winter and spring of 2015. The data were collected with a variety of instruments and platforms (acoustic Doppler current profilers, conductivity–temperature–depth probes, glider, profiling float) and are accompanied by the atmosphere–ocean ALADIN/ROMS modelling system. The research focused on the dense-water formation (DWF), thermal changes, circulation, and water exchange between the coastal and open Adriatic. According to both observations and modelling results, dense waters are formed in the northeastern coastal Adriatic during cold bora outbreaks. However, the dense water formed in this coastal region has lower densities than the dense water formed in the open Adriatic due to lower salinities. Since the coastal area is deeper than the open Adriatic, the observations indicate (i) balanced inward–outward exchange at the deep connecting channels of denser waters coming from the open Adriatic DWF site and less-dense waters coming from the coastal region and (ii) outward flow of less-dense waters dominating in the intermediate and surface layers. The latter phenomenon was confirmed by the model, even if it significantly underestimates the currents and transports in the connecting channels. The median residence time of the coastal area is estimated to be approximately 20 days, indicating that the coastal area may be renewed relatively quickly by the open Adriatic waters. The data that were obtained represent a comprehensive marine dataset that can be used to calibrate atmospheric and oceanic numerical models and point to several interesting phenomena to be investigated in the future.

Diel vertical migration (DVM) is a survival strategy adopted by zooplankton that we investigated in the Corsica Channel using acoustic Doppler current profiler (ADCP) data from April 2014 to November 2016. The principal aim of the study is to characterize migration patterns and biomass temporal evolution of zooplankton along the water column. The ADCP measured vertical velocity and echo intensity in the water column range between about 70 and 390 m (the bottom depth is 443 m). During the investigated period, zooplanktonic biomass had a well-defined daily and seasonal cycle, with peaks occurring in late winter to spring (2015 and 2016) when the stratification of the water column is weaker. Zooplanktonic biomass temporal distribution in the whole water column is well correlated with biomass of primary producers, estimated with satellite data. Zooplanktonic blooming and non-blooming periods have been identified and studied separately. During the non-blooming period zooplanktonic biomass was most abundant in the upper and the deep layers, while during the blooming period the upper-layer maximum in zooplanktonic biomass disappeared and the deep layer with high zooplanktonic biomass became thicker. These two layers are likely to correspond to two different zooplanktonic communities. The evolution of zooplanktonic biomass is well correlated with chlorophyll, with phytoplankton biomass peaks preceding the upper-layer secondary production by a lag of about 3.5 weeks. Nocturnal DVM appears to be the main pattern during both periods, but reverse and twilight migration are also detected. Nocturnal DVM was more evident at mid-water than in the deep and the upper layers. DVM occurred with different intensities during blooming and non-blooming periods. One of the main outcomes is that the principal drivers for DVM are light intensity and stratification, but other factors, like the moon cycle and primary production, are also taken in consideration.

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.

We develop and implement a new method to take into account the impact of waves into the 3-D circulation model SYMPHONIE (Marsaleix et al., 2008, 2009a) following the simplified equations of Bennis et al. (2011) which use glm2z-RANS theory (Ardhuin et al., 2008c). These adiabatic equations are completed by additional parameterizations of wave breaking, bottom friction and wave-enhanced vertical mixing, making the forcing valid from the surf zone through to the open ocean. The wave forcing is performed by wave generation and propagation models WAVEWATCH III® (Tolman, 2008, 2009; Ardhuin et al., 2010) and SWAN (Booij et al., 1999). The model is tested and compared with other models for a plane beach test case, previously tested by Haas and Warner (2009)and Uchiyama et al. (2010). A comparison is also made with the laboratory measurements of Haller et al. (2002) of a barred beach with channels. Results fit with previous simulations performed by other models and with available observational data. Finally, a realistic case is simulated with energetic waves travelling over a coast of the Gulf of Lion (in the northwest of the Mediterranean Sea) for which currents are available at different depths as well as an accurate bathymetric database of the 0–10 m depth range. A grid nesting approach is used to account for the different forcings acting at different spatial scales. The simulation coupling the effects of waves and currents is successful to reproduce the powerful northward littoral drift in the 0–15 m depth zone. More precisely, two distinct cases are identified: When waves have a normal angle of incidence with the coast, they are responsible for complex circulation cells and rip currents in the surf zone, and when they travel obliquely, they generate a northward littoral drift. These features are more complicated than in the test cases, due to the complex bathymetry and the consideration of wind and non-stationary processes. Wave impacts in the inner shelf are less visible since wind and regional circulation seem to be the predominant forcings. Besides, a discrepancy between model and observations is noted at that scale, possibly linked to an underestimation of the wind stress. This three-dimensional method allows a good representation of vertical current profiles and permits the calculation of the shear stress associated with waves and currents. Future work will focus on the combination with a sediment transport model.

Changes in both global and regional mean sea level, and changes in the magnitude of extreme flood heights, are the result of a combination of several distinct contributions most, but not all, of which are associated with climate change. These contributions include effects in the solid earth, gravity field, changes in ocean mass due to ice loss from ice sheets and glaciers, thermal expansion, alterations in ocean circulation driven by climate change and changing freshwater fluxes, and the intensity of storm surges. Due to the diverse range of models required to simulate these systems, the contributions to sea-level change have usually been discussed in isolation rather than in one self-consistent assessment. Focusing on the coastline of northwest Europe, we consider all the processes mentioned above and their relative impact on 21st century regional mean sea levels and the 50-year return flood height. As far as possible our projections of change are derived from process-based models forced by the A1B emissions scenario to provide a self-consistent comparison of the contributions. We address uncertainty by considering both a mid-range and an illustrative high-end combination of the different components. For our mid-range ice loss scenario we find that thermal expansion of seawater is the dominant contributor to change in northwest European sea level by 2100. However, the projected contribution to extreme sea level, due to changes in storminess alone, is in some places significant and comparable to the global mean contribution of thermal expansion. For example, under the A1B emissions scenario, by 2100, change in storminess contributes around 15 cm to the increase in projected height of the 50-year storm surge on the west coast of the Jutland Peninsula, compared with a contribution of around 22 cm due to thermal expansion and a total of 58 cm from all of the contributions we consider. An illustrative combination of our high-end projections suggests increases in the 50-year return level of 86 cm at Sheerness, 95 cm at Roscoff, 106 cm at Esbjerg, and 67cm at Bergen. The notable regional differences between these locations arise primarily from differences in the rates of vertical land movement and changes in storminess.

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.

A large number of SLA observations at a high along track horizontal resolution are an important ingredient of the data assimilation in the Mediterranean Forecasting System (MFS). Recently, new higher-frequency SLA products have become available, and the atmospheric pressure forcing has been implemented in the numerical model used in the MFS data assimilation system. In a set of numerical experiments, we show that, in order to obtain the most accurate analyses, the ocean model should include the atmospheric pressure forcing and the observations should contain the atmospheric pressure signal. When the model is not forced by the atmospheric pressure, the high-frequency filtering of SLA observations, however, improves the quality of the SLA analyses. It is further shown by comparing the power density spectra of the model fields and observations that the model is able to extract the correct information from noisy observations even without their filtering during the pre-processing.

Today, the routine assimilation of satellite data into operational models of ocean circulation is mature enough to enable the production of global reanalyses describing the ocean circulation variability during the past decades. The expansion of the "reanalysis" concept from ocean physics to biogeochemistry is a timely challenge that motivates the present study. The objective of this paper is to investigate the potential benefits of assimilating satellite-estimated chlorophyll data into a basin-scale three-dimensional coupled physical–biogeochemical model of the North Atlantic. The aim is on the one hand to improve forecasts of ocean biogeochemical properties and on the other hand to define a methodology for producing data-driven climatologies based on coupled physical–biogeochemical modeling. A simplified variant of the Kalman filter is used to assimilate ocean color data during a 9-year period. In this frame, two experiments are carried out, with and without anamorphic transformations of the state vector variables. Data assimilation efficiency is assessed with respect to the assimilated data set, nitrate of the World Ocean Atlas database and a derived climatology. Along the simulation period, the non-linear assimilation scheme clearly improves the surface analysis and forecast chlorophyll concentrations, especially in the North Atlantic bloom region. Nitrate concentration forecasts are also improved thanks to the assimilation of ocean color data while this improvement is limited to the upper layer of the water column, in agreement with recent related literature. This feature is explained by the weak correlation taken into account by the assimilation between surface phytoplankton and nitrate concentrations deeper than 50 meters. The assessment of the non-linear assimilation experiments indicates that the proposed methodology provides the skeleton of an assimilative system suitable for reanalyzing the ocean biogeochemistry based on ocean color data.

The MyOcean R&D project MESCLA (MEsoSCaLe dynamical Analysis through combined model, satellite and in situ data) was devoted to the high resolution 3-D retrieval of tracer and velocity fields in the oceans, based on the combination of in situ and satellite observations and quasi-geostrophic dynamical models. The retrieval techniques were also tested and compared with the output of a primitive equation model, with particular attention to the accuracy of the vertical velocity field as estimated through the Q vector formulation of the omega equation. The project focused on a test case, covering the region where the Gulf Stream separates from the US East Coast. This work demonstrated that innovative methods for the high resolution mapping of 3-D mesoscale dynamics from observations can be used to build the next generations of operational observation-based products.