Characterizing, modelling and understanding the climate variability of the deep water formation in the North-Western Mediterranean Sea

Observing, modelling and understanding the climate-scale variability of the deep water formation (DWF) in the North-Western Mediterranean Sea remains today very challenging. In this study, we first characterize the interannual variability of this phenomenon by a thorough reanalysis of observations in order to establish reference time series. These quantitative indicators include 31 observed years for the yearly maximum mixed layer depth over the period 1980–2013 and a detailed multi-indicator description of the period 2007–2013. Then a 1980–2013 hindcast simulation is performed with a fully-coupled regional climate system model including the high-resolution representation of the regional atmosphere, ocean, land-surface and rivers. The simulation reproduces quantitatively well the mean behaviour and the large interannual variability of the DWF phenomenon. The model shows convection deeper than 1000 m in 2/3 of the modelled winters, a mean DWF rate equal to 0.35 Sv with maximum values of 1.7 (resp. 1.6) Sv in 2013 (resp. 2005). Using the model results, the winter-integrated buoyancy loss over the Gulf of Lions is identified as the primary driving factor of the DWF interannual variability and explains, alone, around 50 % of its variance. It is itself explained by the occurrence of few stormy days during winter. At daily scale, the Atlantic ridge weather regime is identified as favourable to strong buoyancy losses and therefore DWF, whereas the positive phase of the North Atlantic oscillation is unfavourable. The driving role of the vertical stratification in autumn, a measure of the water column inhibition to mixing, has also been analyzed. Combining both driving factors allows to explain more than 70 % of the interannual variance of the phenomenon and in particular the occurrence of the five strongest convective years of the model (1981, 1999, 2005, 2009, 2013). The model simulates qualitatively well the trends in the deep waters (warming, saltening, increase in the dense water volume, increase in the bottom water density) despite an underestimation of the salinity and density trends. These deep trends come from a heat and salt accumulation during the 1980s and the 1990s in the surface and intermediate layers of the Gulf of Lions before being transferred stepwise towards the deep layers when very convective years occur in 1999 and later. The salinity increase in the near Atlantic Ocean surface layers seems to be the external forcing that finally leads to these deep trends. In the future, our results may allow to better understand the behaviour of the DWF phenomenon in Mediterranean Sea simulations in hindcast, forecast, reanalysis or future climate change scenario modes. The robustness of the obtained results must be however confirmed in multi-model studies

An acoustic view of ocean mixing

Knowledge of the parameter K (turbulent diffusivity/"mixing intensity") is a key to understand transport processes of matter and energy in the ocean. Especially the almost vertical component of K across the ocean stratification (diapycnal diffusivity) is vital for research on biogeochemical cycles or greenhouse gas budgets. Recent boost in precision of water velocity data that can be obtained from vessel-mounted acoustic instruments (vmADCP) allows identifying ocean regions of elevated diapycnal diffusivity during research cruises - in high horizontal resolution and without extra ship time needed. This contribution relates acoustic data from two cruises in the Tropical North East Atlantic Oxygen Minimum Zone to simultaneous field observations of diapycnal diffusivity: pointwise measurements by a microstructure profiler as well as one integrative value from a large scale Tracer Release Experiment

Biological processes and links to the physics

Analysis of the temporal and spatial variability of biological processes and identification of the main variables that drive the dynamic regime of marine ecosystems is complex. Correlation between physical variables and long-term changes in ecosystems has routinely been identified, but the specific mechanisms involved remain often unclear. Reasons for this could be various: the ecosystem can be very sensitive to the seasonal timing of the anomalous physical forcing; the ecosystem can be contemporaneously influenced by many physical variables and the ecosystem can generate intrinsic variability on climate time scales. Marine ecosystems are influenced by a variety of physical factors, e.g., light, temperature, transport, turbulence. Temperature has a fundamental forcing function in biology, with direct influences on rate processes of organisms and on the distribution of mobile species that have preferred temperature ranges. Light and transport also affect the physiology and distribution of marine organisms. Small-scale turbulence determines encounter between larval fish and their prey and additionally influences the probability of successful pursuit and ingestion. The impact of physical forcing variations on biological processes is studied through long-term observations, process studies, laboratory experiments, retrospective analysis of existing data sets and modelling. This manuscript reviews the diversity of physical influences on biological processes, marine organisms and ecosystems and their variety of responses to physical forcing with special emphasis on the dynamics of zooplankton and fish stocks

Evaluation of climate change scenarios based on aquatic food web modelling

In the years 2004 and 2005 we collected samples of phytoplankton, zooplankton and macroinvertebrates in an artificial small pond in Budapest. We set up a simulation model predicting the abundance of the cyclopoids, Eudiaptomus zachariasi and Ischnura pumilio by considering only temperature as it affects the abundance of population of the previous day. Phytoplankton abundance was simulated by considering not only temperature, but the abundance of the three mentioned groups. This discrete-deterministic model could generate similar patterns like the observed one and testing it on historical data was successful. However, because the model was overpredicting the abundances of Ischnura pumilio and Cyclopoida at the end of the year, these results were not considered. Running the model with the data series of climate change scenarios, we had an opportunity to predict the individual numbers for the period around 2050. If the model is run with the data series of the two scenarios UKHI and UKLO, which predict drastic global warming, then we can observe a decrease in abundance and shift in the date of the maximum abundance occurring (excluding Ischnura pumilio, where the maximum abundance increases and it occurs later), whereas under unchanged climatic conditions (BASE scenario) the change in abundance is negligible. According to the scenarios GFDL 2535, GFDL 5564 and UKTR, a transition could be noticed

Circumpolar connections between Antarctic krill (Euphausia superba Dana) populations: investigating the roles of ocean and sea ice transport

Antarctic krill, Euphausia superba Dana, has a heterogeneous circumpolar distribution in the Southern Ocean. Krill have a close association with sea ice which provides access to a critical food source and shelter, particularly in the early life stages. Advective modelling of transport pathways of krill have until now been on regional scales and have not taken explicit account of sea ice. Here we present Lagrangian modelling studies at the circumpolar scale that include interaction with sea ice. The advection scheme uses ocean velocity output from the Ocean Circulation and Climate Advanced Modelling (OCCAM) project model together with satellite-derived sea ice motion vectors to examine the potential roles of the ocean and sea ice in maintaining the observed circumpolar krill distribution. We show that the Antarctic Coastal Current is likely to be important in generating the large-scale distribution and that sea ice motion can substantially modify the ocean transport pathways, enhancing retention or dispersal depending upon location. Within the major krill region of the Scotia Sea, the effect of temporal variability in both the ocean and sea ice velocity fields is examined. Variability in sea ice motion increases variability of influx to South Georgia, at times concentrating the influx into pulses of arrival. This variability has implications for the ecosystem around the island. The inclusion of sea ice motion leads to the identification of source regions for the South Georgia krill populations additional to those identified when only ocean motion is considered. This study indicates that the circumpolar oceanic circulation and interaction with sea ice is important in determining the large-scale distribution of krill and its associated variability