This study examines the impact of different turbidity products on the Aegean Sea surface physical characteristics, by performing twin-experiment simulations using a high-resolution regional ocean model. The turbidity products used include an in-situ based diffuse attenuation coefficient dataset at 490 nm (kd490, in m− 1) and a satellite derived kd490 product. Satellite turbidity products are broadly used in ocean simulations due to their spatiotemporal coverage and algorithm universality. Their validation and empirical components are trained mainly in phytoplankton driven regions and this may cause systematic differences in oligotrophic areas of variable optical properties’ composition. In the Aegean Sea, the in-situ based turbidity product accounts for the contribution of suspended particles in the solar heating profile, having further implications in the surface characteristics. The Aegean Sea upper-ocean thermohaline characteristics and general circulation patterns, reveal distinct differences between the twin-experiment simulations, showcasing mesoscale to locally induced impact of the turbidity variations. The turbidity impact on the air-sea interaction fluxes affects both thermodynamic processes i.e., solar radiation penetration and absorption in the water column, as well as dynamic processes i.e., momentum fluxes due to changes of the sea surface temperature and subsequently to the momentum drag coefficient. The Aegean Sea surface characteristics in the in-situ based turbidity product simulation, show a stronger decoupling between the North and the South Aegean Sea, when compared with the satellite derived turbidity product simulation. These results highlight the importance of incorporating more realistic turbidity products in ocean models, especially for optically complex regions such as the Aegean Sea.

Ocean observing systems in coastal, shelf and marginal seas collect diverse oceanographic information supporting a wide range of socioeconomic needs, but observations are necessarily sparse in space and/or time due to practical limitations. Ocean analysis and forecast systems capitalize on such observations, producing data-constrained, four-dimensional oceanographic fields. Here we review efforts to quantify the impact of ocean observations, observing platforms, and networks of platforms on model products of the physical ocean state in coastal regions. Quantitative assessment must consider a variety of issues including observation operators that sample models, error of representativeness, and correlated uncertainty in observations. Observing System Experiments, Observing System Simulation Experiments, representer functions and array modes, observation impacts, and algorithms based on artificial intelligence all offer methods to evaluate data-based model performance improvements according to metrics that characterize oceanographic features of local interest. Applications from globally distributed coastal ocean modeling systems document broad adoption of quantitative methods, generally meaningful reductions in model-data discrepancies from observation assimilation, and support for assimilation of complementary data sets, including subsurface in situ observation platforms, across diverse coastal environments.

Accurate modelling of air-sea processes is essential for reliable forecasts of Mediterranean tropical-like cyclones (also known as “Medicanes”). Medicanes occasionally develop in the Mediterranean causing extreme weather conditions with catastrophic potential due to excessive precipitation, windstorms, and coastal flooding. In this work, we investigate how the complexity of ocean-wave-atmosphere coupling and model initialization affect the simulated track and intensity of the Medicane Ianos (2020). Results indicate that the model's initial conditions and the cyclone's development stage are the main drivers of track position errors, while ocean and wave feedback have a significant impact on the intensity and evolution of the cyclone. Compared with an atmosphere-only simulation, an atmosphere-ocean coupled system reproduces the cyclone's SST cooling effect (up to 3.7 °C), in agreement also with the satellite observations thus, reducing the cyclone intensity, as estimated by the minimum MSLP, the 10-m wind speed and the surface enthalpy flux. Adding a wave model to the coupled system, further increases the magnitude of ocean cooling (by about 1.2 °C), due to increased sea surface roughness leading to increased wind stress and enhanced upper ocean mixing. Overall, surface waves are shown to have competing effects on cyclone intensity i.e., negative feedback via increasing the surface momentum flux and positive feedback via increasing the enthalpy flux, the latter being more sensitive to surface roughness rather than to SST modifications brought by the wave coupled system. The turbulent air-sea fluxes under high winds, appear to be very sensitive to sea-state patterns resolved by the coupled models, highlighting the need to improve forecasting systems for extreme weather events in the Mediterranean.

The dynamics of fluid flows give rise to robust, persistent circulation features that underpin the flow and exert strong control over the advection of water masses, either enhancing it or suppressing it, collectively known as lagrangian coherent structures. Lagrangian approaches and metrics have been shown to be better suited than eulerian ones at locating and delineating such structures and capturing the effect they have on the formation and dispersion of water masses, particularly at the smaller scales. In this paper, we use the framework of lagrangian coherent structures to analyse the ocean velocity fields over a climatological year obtained from a high-resolution eddy-resolving model in order to investigate the lagrangian regimes that affect the motion, separation and mixing of water masses in the Mediterranean Sea. The lagrangian regimes that develop in each sub-basin over the course of the year are characterised and regions of persistent lagrangian activity and coherent structure formation and presence are identified. A quantitative picture of the seasonal variability of the lagrangian coherent structure-induced horizontal mixing and vortex formation is obtained.

The interannual variability of the Mediterranean overturning circulation is investigated using a high-resolution (1/36°) ocean model. As the overturning circulation regulates the replenishment and ventilation of the deep layers, we study the spatiotemporal scales of the maximum value of the overturning streamfunction over three main sub-basins of dense water formation (Aegean Sea, Adriatic, and the northwestern Mediterranean). The variability of the zonal overturning is also discussed. The spectrum analysis shows that the overturning variability has its largest signal on annual timescales in all sub-basins, explained by perpetual winter formation. On shorter frequencies (decadal) there are marked differences observed, due to regional processes of the overturning cells, led by buoyancy flux long-term variability in each sub-basin. The decomposition of the total overturning circulation into barotropic, geostrophic shear, and Ekman components revealed weakening and strengthening for the Aegean and Adriatic Sea total overturning, respectively, with opposite trends for the barotropic and geostrophic shear components. The simultaneous contribution of the Ekman and geostrophic component to the total overturning differentiates the variability of zonal overturning circulation from the local meridional overturning circulation of the three sub-basins. The cross spectra between the maximum overturning value and the buoyancy fluxes also revealed that the system keeps the “memory” of this forcing and shows annual variability.

In this Part 2 article of a two-part series, observations based on satellite missions were used to evaluate the empirical consistency of model ensembles generated via stochastic modelling of ocean physics and biogeochemistry. A high-resolution Bay of Biscay configuration was used as a case study to explore the model error subspace in both the open and coastal ocean. In Part 1 of this work, three experiments were carried out to generate model ensembles by perturbing only physics, only biogeochemistry, and both of them simultaneously. In Part 2 of this work, empirical consistency was checked, first by means of rank histograms projecting the data onto the model ensemble classes, and second, by pattern-selective consistency criteria in the space of “array modes” defined as eigenvectors of the representer matrix. Rank histograms showed large dependency on geographical region and on season for sea surface temperature (SST), sea-level anomaly (SLA), and phytoplankton functional types (PFT), shifting from consistent model-data configurations to large biases because of model ensemble underspread. Consistency for SST array modes was found to be verified at large, small and coastal scales soon after the ensemble spin-up. Array modes for the along-track sea-level showed useful consistent information at large scales and at the mesoscale; for the gridded SLA was verified only at large scale. Array modes showed that biogeochemical model uncertainties generated by stochastic physics, were effectively detected by PFT measurements at large scales, as well as at mesoscale and small-scale. By contrast, perturbing only biogeochemistry, with an identical physical forcing across the ensemble, limits the potential of PFT measurements at detecting and possibly correcting small-scale biogeochemical model errors. When an ensemble was found to be inconsistent with observations along a particular direction (here, an array mode), a plausible reason is that other error processes must have been active in the model, in addition to the ones at work across the ensemble.

In this article, Part 1 of a two-part series, we run and evaluate the skill of a regional physical–biogeochemical stochastic ocean model based on NEMO. The domain covers the Bay of Biscay at 1/36° resolution, as a case study for open-ocean and coastal shelf dynamics. We generate model ensembles based on assumptions about errors in the atmospheric forcing, the ocean model parameterizations and in the sources and sinks of the biogeochemical variables. The resulting errors are found to be mainly driven by the wind forcing uncertainties, with the rest of the perturbed forcing and parameters locally influencing the ensemble spread. Biogeochemical uncertainties arise from intrinsic ecosystem model errors and from errors in the physical state. Uncertainties in physical forcing and parameterization are found to have a larger impact on chlorophyll spread than uncertainties in ecosystem sources and sinks. The ensembles undergo quantitative verification with respect to observations, focusing on upper-ocean properties. Despite a tendency for ensembles to be generally under-dispersive, they appear to be reasonably consistent with respect to sea surface temperature data. The largest statistical sea-level biases are observed in coastal regions. These biases hint at the presence of high-frequency error sources currently unaccounted for, and suggest that the ensemble-based uncertainties are unfit to model error covariances for assimilation. Model ensembles for chlorophyll appear to be consistent with ocean colour data only at times. The stochastic model is qualitatively evaluated by analysing its ability at generating consistent multivariate incremental model corrections. Corrections to physical properties are associated with large-scale biases between model and data, with diverse characteristics in the open-ocean and the shelves. Mesoscale features imprint their signature on temperature and sea-level corrections, as well as on chlorophyll corrections due to the vertical velocities associated with vortices. Small scale local corrections are visible over the shelves. Chlorophyll information has measurable impact on physical variables.

Atmospheric-chemical coupled models usually parameterize sea-salt aerosol (SSA) emissions using whitecap fraction estimated considering only wind speed and ignoring sea state. This approach may introduce inaccuracies in SSA simulation. This study aims to assess the impact of sea state on SSA modeling, applying a new parameterization for whitecap fraction estimation based on wave age, calculated by the ratio between wave phase velocity and wind speed. To this end, the new parameterization was incorporated in the coupled Chemical Hydrological Atmospheric Ocean wave modeling System (CHAOS). CHAOS encompasses the wave model (WAM) two-way coupled through the OASIS3-MCT coupler with the Advanced Weather Research and Forecasting model coupled with Chemistry (WRF-ARW-Chem) and, thus, enabling the concurrent simulation of SSAs, wind speed and wave phase velocity. The simulation results were evaluated against in-situ and lidar measurements at 2 stations in Greece (Finokalia on 4 and 15 July 2014 and Antikythera-PANGEA on 15 September 2018). The results reveal significant differences between the parameterizations with the new one offering a more realistic representation of SSA levels in some layers of the lower atmosphere. This is attributed to the enhancement of the bubble-bursting mechanism representation with air-sea processes controlling whitecap fraction. Our findings also highlight the contribution of fresh wind-generated waves to SSA modeling.

The impact of tides on the Bay of Biscay dynamics is investigated by means of an ocean model twin-experiment, consisted of two simulations with and without tidal forcing. The study is based on a high-resolution (1/36∘) regional configuration of NEMO (Nucleus for European Modelling of the Ocean) performing one-year simulations. The results highlight the imprint of tides on the thermohaline properties and circulation patterns in three distinct dynamical areas in the model domain: the abyssal plain, the Armorican shelf and the English Channel. When tides are activated, the bottom stress is increased in the shelf areas by about two orders of magnitude with respect to the open ocean, subsequently enhancing vertical mixing and weakening stratification in the bottom boundary layer. The most prominent feature reproduced only when tides are modelled, is the Ushant front near the entrance of the English Channel. Tides appear also to constrain the freshwater transport of rivers from the continental shelf to the open ocean. The spectral analysis revealed that the tidal forcing contributes to the SSH variance at high frequencies near the semidiurnal band and to the open ocean mesoscale and small-scale features in the presence of summer stratification pattern.

Understanding the governing mechanisms of atmosphere–wave–ocean​ interactions is critical for unravelling the formation and evolution mechanisms of severe weather phenomena. This study aims at investigating the effects of atmosphere–wave–ocean​ feedbacks on a Mediterranean tropical-like cyclone (medicane), occurred on 27–30 September 2018 at the central-eastern Mediterranean Sea and characterized by severe environmental and socioeconomic impact. To unveil the interactions across the air–sea interface, the medicane was simulated by an integrated modelling system consisting of the Chemical Hydrological Atmospheric Ocean wave System (CHAOS), upgraded by embedding to it the Nucleus for European Modelling of the Ocean (NEMO) as ocean circulation component. Coupled simulations revealed that air–seaheat transfer and Ekman pumping, bringing sub-surface cold waters in upper ocean layers (upwelling), caused SST cooling (∼2–3 °C). SST cooling triggered a negative feedback loop procedure tending to balance between atmospheric and ocean processes. It also attenuated the cyclone and, subsequently, reduced the atmospheric energy embedded in ocean through the upper ocean vertical stratification weakening, thus, upper ocean vertical mixing, upwelling and SST cooling. The waves adjusted this feedback loop making the system more resistant in air–sea flux variations. Waves additionally weakened the cyclone not only due to the kinetic energy loss in the lower-atmosphere but also due to the enhancement of SST cooling which is attributed to the strengthening of Ekman pumping and vertical mixing, forced by wind stress increase. Nevertheless, waves partially balanced the air–wave–sea exchanges through the slight enthalpy flux gain under high wind conditions which is explained by considering the increase of enthalpy transfer coefficient in rougher sea areas.

The variability of the water mass exchange between the Arabian Gulf and the Indian Ocean is investigated using a high-resolution (1/36°) ocean model. We focus on the period from December 1996 to March 1998, having as reference in situ measurements at the Strait of Hormuz. Previous studies, based on models and observations, suggested a perpetual deep outflow, mainly in the southern part of the Strait, and a variable flow in the upper layers. In the present study, we confirm that there is a permanent core of a deep outflow in the Strait at depths greater than 40 m, characterised by high-salinity waters. In addition, we show that there is a seasonal signal in the upper layers net flow in the southern part of the Strait, altering from net inflow during winter/spring to net outflow during summer/fall. The mean annual inflow through the Strait is estimated at 0.22 ± 0.01 Sv and the deep outflow at 0.147 ± 0.01 Sv. The water mass exchange through the Strait is controlled by synoptic processes with high variability net transport fields. These processes characterise the structure and the intensity of the transport patterns, exhibiting 2- to 5-day period. On synoptic time scales, winds drive an immediate baroclinic flow at the Strait of Hormuz, affecting mostly the upper layers, and a quasi-barotropic flow that peaks approximately 2 days later.

The interannual variability and the mechanisms controlling the dissolved oxygen concentration in the Mediterranean Sea were investigated through generating gridded fields of dissolved oxygen, salinity and potential temperature. The Data-Interpolating Variational Analysis (DIVA) software was used to produce a gridded dataset for the time period 1960–2011. High oxygen concentrations for the upper and bottom layers, separated by an oxygen minimum zone at intermediate layers, are a typical structure of the dissolved oxygen in the Eastern and the Western Mediterranean sub-basins. Although an oxygen minimum zone is observed in both sub-basins, its vertical positions are different; in the Eastern Mediterranean at between 600 and 1200 m depth and in the Western Mediterranean at between 400 and 600 m. The vertical distribution of dissolved oxygen shows significant differences between the two sub-basins and their temporal evolution reveals large interannual to decadal variability. A negative correlation was observed between dissolved oxygen and surface potential temperature due to solubility changes over the whole period. However, the positive correlation between the dissolved oxygen and potential temperature in the Eastern Mediterranean deep layers is an indication that the dynamical processes are dominant and are involved in the dissolved oxygen interannual variability. The dissolved oxygen variability presents shifts with a multi-decadal signal, rather than trends as observed in the global ocean, associated with mixing processes and decadal oscillations that influence the dense water formation or biological activity.

We downscaled a free ensemble of a regional, parent model to a high-resolution coastal, child ensemble in the Bay of Biscay. The child ensemble was forced at the open boundaries by the parent ensemble, and locally by perturbing the winds. By comparing ensembles generated by each of these forcing perturbations separately and combined we were able to consider the ensemble from either of two paradigms: (1) characterising high-resolution, coastal model errors using local and non-local forcing perturbations, or (2) downscaling regional model errors into the coastal domain. We found that most of the spread in the child ensembles was generated from the ensemble of open boundary conditions, with the local wind perturbations on their own generating substantially less ensemble spread. Together, the two sources of error increased the ensemble spread by only a small amount over the non-local perturbations alone. In general, the spread in sea surface height was greater in the child ensembles than in the parent ensemble, probably due to the more refined dynamics, while the spread in sea surface temperature was lower, likely due to the way the open boundary conditions were averaged. Deep below the surface, though, the child ensemble featured a large spread even where the parent model’s spread was very weak. This enhanced error response is a promising result for an ensemble data assimilation system, as it could be exploited to correct the model deep below the surface.

A twin-experiment is carried out introducing elements of an Ensemble Kalman Filter (EnKF), to assess and correct ocean uncertainties in a high-resolution Bay of Biscay configuration. Initially, an ensemble of 102 members is performed by applying stochastic modeling of the wind forcing. The target of this step is to simulate the envelope of possible realizations and to explore the robustness of the method at building ensemble covariances. Our second step includes the integration of the ensemble-based error estimates into a data assimilative system adopting a 4D Ensemble Optimal Interpolation (4DEnOI) approach. In the twin-experiment context, synthetic observations are simulated from a perturbed member not used in the subsequent analyses, satisfying the condition of an unbiased probability distribution function against the ensemble by performing a rank histogram. We evaluate the assimilation performance on short-term predictability focusing on the ensemble size, the observational network, and the enrichment of the ensemble by inexpensive time-lagged techniques. The results show that variations in performance are linked to intrinsic oceanic processes, such as the spring shoaling of the thermocline, in combination with external forcing modulated by river runoffs and time-variable wind patterns, constantly reshaping the error regimes. Ensemble covariances are able to capture high-frequency processes associated with coastal density fronts, slope currents and upwelling events near the Armorican and Galician shelf break. Further improvement is gained when enriching model covariances by including pattern phase errors, with the help of time-neighbor states augmenting the ensemble spread.

The main objective of this study is to investigate the variability of the thermohaline characteristics of the deep-water masses in the Aegean Sea and the possible impact of the regional atmospheric forcing variability by analyzing the available oceanographic and atmospheric datasets for the period of 1960–2012. During this period the variability of the deep water characteristics of the Aegean sub-basins is found to be very large as well as the diversity of the deep water characteristics among the sub-basins. The Central Aegean seems to play the key role in the Aegean deep water formation processes. Due to its small size, the Aegean Sea surface responds rapidly to the meteorological changes and/or the variability of the lateral fluxes and this variability propagates in the thermohaline characteristics of the deep water masses of the basin through deep water formation processes. There are many episodes characterized by a tight coupling of the atmosphere and the ocean during the examined period, with the Eastern Mediterranean Transient (EMT) being the most prominent case. We suggest that deep water formation is triggered mostly by the combination of preconditioning during early winter and/or previous winters together with the number of subsequent extreme events during present winter and not only by the total amount of the extreme heat loss winter days.

This study is aimed at exploring the errors of a regional model of the Bay of Biscay, a regional zoom of the IBI configuration of the ocean model NEMO, with the ultimate objective of guiding the choice and implementation of a data assimilation system in that region. An ensemble experiment was carried out by randomly perturbing winds along a base of EOFs with the aim to mimic a potential source of error in the model forecasts. A characterisation was attempted with proxy forecast errors by using statistical moments of order 1 to 4. The temporal variability of model correction patterns in a hypothetical data assimilation system was also illustrated. Significant departures from linear/Gaussian response were found, as well as well-marked non-stationarities in the error patterns. Within the limits of the experimental protocol, this could be technically applicable to other coastal areas as the study illustrates the likely limits of stationary/Gaussian data assimilation approaches in the Bay of Biscay.

<p>Results from a high-resolution hindcast model experiment, supported by available observations, reveal an increasing salinity trend in the north Aegean during the Eastern Mediterranean Transient (EMT), largely controlled by increases in the flow rate and salinity of water masses of Levantine origin entering the domain through the Myconos-Ikaria strait as a response to an acceleration of the Aegean thermohaline cell. Changes in the Dardanelles inflow (increasing salinity) and in the surface freshwater flux (increasing Evaporation-Precipitation), although both contribute to a higher salt content of the basin during the EMT, play a minor role in the inter-annual/decadal variability of the freshwater budget. A long-term decreasing temperature trend is observed from the 1960s to the early 1990s. It is superimposed on the salinity-preconditioning phase over the 1980s and early 1990s. Both signals are, concomitantly, favouring conditions for intense Dense Water Formation (DWF) in the north Aegean Sea. In addition, the northward displacement of the Black Sea Water front over the EMT, leads to the expansion of convective cells towards the north and to higher formation rates associated with both colder and saltier surface waters.</p>

Saudi Aramco is the oil industry of the Kingdom of Saudi Arabia with several activities related to the environment. In order to optimize daily operations and minimize environmental risks a forecasting system has been employed and setup in operations. The objectives of the system include prevention and mitigation of environmental problems, as well as early warning of local conditions associated with extreme weather events. The management and operations part is related to early warning of weather and dust storms that affect operations of various facilities, whereas the environmental part is mainly focused on air quality and desert dust levels in the atmosphere.

Recent changes of the thermohaline circulation in the Eastern Mediterranean (i.e. the Eastern Mediterranean Transient) and older observations of the thermohaline structure of the Aegean-Levantine region (with events of dramatic changes of deep water characteristics) reveal the very sensitive character of the regional thermohaline circulation pattern. This and the long term variability of seawater characteristics in various Mediterranean basins show that the deep water mass formation processes in the region can be greatly affected by climate variability and the characteristics of the extreme atmospheric forcing events. Theoretical work and modeling experiments point out the effectiveness of extreme events and periods of abnormal atmospheric conditions to produce deep waters of different characteristics and different equilibrium depth. Studying the mechanisms involved in the air-sea interaction under extreme event conditions, with available observations and modeling techniques, and monitoring important sites of water mass formation becomes very important for understanding the regional dynamics of the water cycle and their effect on the climate of the whole Mediterranean Sea region.

A hindcast simulation in the Aegean–Levantine basins for the years 1960–2000 is performed, using an eddy resolving ocean model (1°/30). The model incorporates a 6-h atmospheric forcing provided by the ARPERA and captures the observed variability of the 40-years. The Eastern Mediterranean Transient (EMT) is the most prominent climatic event of the period. We investigate the impact of the atmospheric versus lateral forcing on the buoyancy content of the Aegean–Levantine basins. During the pre-EMT period, the basins’ buoyancy content is lowered by surface fluxes by about 1.5×10−8m2s−3 in the Aegean Sea, mostly related to surface heat loss, and lateral fluxes by about 0.9×10−8m2s−3, mostly related to salt flux, with the Levantine changes leading those of the Aegean. Furthermore, while long-term trends of surface and lateral inputs are preconditioning the changes in the Aegean stratification, it is the extreme heat loss pulses, related to the variability of the wind field that is controlling the formation processes by abruptly lowering the buoyancy content. Those events are possibly linked to an eastern Mediterranean bimodal atmospheric oscillation, with the anomalous surface heat fluxes shifting from the Levantine in the 1960s to the Aegean in the 1990s. The central Aegean due to its topography and thermohaline properties trigger events of excessive formation and producing the Aegean’s densest waters. During the EMT winters the central Aegean lower layers contain very dense waters, with σΘ larger than 29.3kgm−3. These waters form the core of the water mass outflowing in the Eastern Mediterranean, after being mixed with ambient waters along their southward flow. The outflowing layer is characterized by density of 29.21kgm−3. The deepest parts of the NW Levantine is initially filled with the new water mass, which later spreads to the SE parts of the basin, flowing over the Eastern Mediterranean Ridge.

Twenty-four years of AVHRR-derived sea surface temperature (SST) data (1985–2008) and 35 years of NOCS (V.2) in situ-based SST data (1973–2008) were used to investigate the decadal scale variability of this parameter in the Mediterranean Sea in relation to local air–sea interaction and large-scale atmospheric variability. Satellite and in situ-derived data indicate a strong eastward increasing sea surface warming trend from the early 1990s onwards. The satellite-derived mean annual warming rate is about 0.037°C year–1 for the whole basin, about 0.026°C year–1 for the western sub-basin and about 0.042°C year–1 for the eastern sub-basin over 1985–2008. NOCS-derived data indicate similar variability but with lower warming trends for both sub-basins over the same period. The long-term Mediterranean SST spatiotemporal variability is mainly associated with horizontal heat advection variations and an increasing warming of the Atlantic inflow. Analysis of SST and net heat flux inter-annual variations indicates a negative correlation, with the long-term SST increase, driving a net air–sea heat flux decrease in the Mediterranean Sea through a large increase in the latent heat loss. Empirical orthogonal function (EOF) analysis of the monthly average anomaly satellite-derived time series showed that the first EOF mode is associated with a long-term warming trend throughout the whole Mediterranean surface and it is highly correlated with both the Eastern Atlantic (EA) pattern and the Atlantic Multidecadal Oscillation (AMO) index. On the other hand, SST basin-average yearly anomaly and NAO variations show low and not statistically significant correlations of opposite sign for the eastern (negative correlation) and western (positive correlation) sub-basins. However, there seems to be a link between NAO and SST decadal-scale variations that is particularly evidenced in the second EOF mode of SST anomalies. NOCS SST time series show a significant SST rise in the western basin from 1973 to the late 1980s following a large warming of the inflowing surface Atlantic waters and a long-term increase of the NAO index, whereas SST slowly increased in the eastern basin. In the early 1990s, there is an abrupt change from a very high positive to a low NAO phase which coincides with a large change in the SST spatiotemporal variability pattern. This pronounced variability shift is followed by an acceleration of the warming rate in the Mediterranean Sea and a change in the direction (from westward to eastward) of its spatial increasing tendency.

The inter-annual/decadal scale variability of the Aegean Sea Surface Temperature (SST) is investigated by means of long-term series of satellite-derived and in situ data. Monthly mean declouded SST maps are constructed over the 1985?2008 period, based on a re-analysis of AVHRR Oceans Pathfinder optimally interpolated data over the Aegean Sea. Basin-average SST time series are also constructed using the ICOADS in situ data over 1950?2006. Results indicate a small SST decreasing trend until the early nineties, and then a rapid surface warming consistent with the acceleration of the SST rise observed on the global ocean scale. Decadal-scale SST anomalies were found to be negatively correlated with the winter North Atlantic Oscillation (NAO) index over the last 60 years suggesting that along with global warming effects on the regional scale, a part of the long-term SST variability in the Aegean Sea is driven by large scale atmospheric natural variability patterns. In particular, the acceleration of surface warming in the Aegean Sea began nearly simultaneously with the NAO index abrupt shift in the mid-nineties from strongly positive values to weakly positive/negative values.

Aiming at portraying the Aegean's water mass structure and identifying Dense Water Formation processes, two winter cruises were conducted in 2005?2006, across the plateaus and depressions of the Aegean Sea. The most prominent feature of the water mass distribution in the basin is a distinct ?X-shape? of the Θ-S characteristics, suggesting a complicated coupling of the major Aegean sub-basins. The surface and deep waters are relatively decoupled with diverse origin characteristics, while the intermediate layers act as connectors of the main thermohaline cells. The Central Aegean seems to play a key role due to formation processes of water masses with densities equal and/or higher than 29.2 kg/m3, that take place in the sub-basin and disperses in the North Aegean. On the other hand, the South Aegean appears greatly influenced by the Eastern Mediterranean circulation and water mass distribution, especially under the Eastern Mediterranean Transient status. The Transitional Mediterranean Water monitored in the post-EMT period and characterized by low temperature at 14.2°C, low salinity at 38.92 and low dissolved oxygen at 3.97 ml/l, with its core around 750 m and above the saline (39.06) Cretan Deep Water, altered significantly the South Aegean structure. The pre-EMT thermohaline pattern of the Central and South Aegean deep layers were similar, while the bottom density of the Central basin was higher than that in the South Aegean. Thus, it is possible that the deep waters of the Central Aegean acted as a dense water reserve supply for the deeper part of the Southern basin.