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Le changement climatique étant susceptible d’avoir des impacts majeurs sur les côtes basses, notre capacité à évaluer les conséquences des aléas littoraux dans le futur est un élément essentiel dans la prévention des risques littoraux. Cet article présente des exemples de l’application d’une méthode destinée à estimer la position future du trait de côte et à cartographier les zones à risque de submersion à l’horizon 2065, en prenant en compte l’élévation future du niveau marin, au niveau de deux communes du littoral du nord de la France où des habitations sont déjà menacées par l’érosion ou la submersion marine. Les résultats obtenus montrent que l’érosion représente le risque majeur sur un des deux sites étudiés où la majeure partie d’un lotissement pourrait disparaitre d’ici 2065 si rien n’est fait pour limiter l’érosion du littoral. Bien que la submersion marine constitue la principale menace sur le deuxième site d’étude, c’est l’érosion côtière qui augmentera, à terme, les risques de submersion des habitations en réduisant la largeur du cordon dunaire qui en assure la protection. La comparaison de nos résultats avec les cartes des aléas produites par les services de l’État fait apparaitre des différences sensibles qui s’expliquent par le fait que le risque d’érosion n’a pas été pris en compte dans les Plans de prévention des risques littoraux (PPRL) des deux communes considérées, ce qui pose la question de la validité de zones à risque définies sans prendre en compte l’évolution future probable du trait de côte., Because climate change will likely have major impacts in low-lying coastal areas, our ability for evaluating predictable consequences of coastal hazards in the future already represents a key issue in coastal risk reduction. This paper presents examples of the application of a method aimed at assessing the future position of the shoreline and at mapping areas that will be at risk of flooding by 2065 with future sea-level rise at two coastal localities of northern France where properties are already threatened by erosion or flooding. Our results show that erosion is the main coastal hazard at one of the two study sites where a large part of a housing estate may disappear by 2065 if no action is taken for limiting coastal erosion. Although marine flooding represents the primary risk at the second study site, coastal erosion will increase the risk of flooding of properties in the future due to the decrease in width of the protective coastal dunes. Comparison of our results with the coastal hazard maps published by the French government shows significant differences that can be explained by the fact that the risk of erosion was not considered in the Coastal Risk Protection Plans (PPRL) of the two municipalities considered in this study, which raises the question of the reliability of areas at risk defined without taking into account future shoreline evolution trends.

The discrete SIR (Susceptible–Infected–Recovered) model is used in many studies to model the evolution of epidemics. Here, we consider one of its dynamics—the exponential decrease in infected cases I(t). By considering only the I(t) dynamics, we extract three parameters: the exponent of the initial exponential increase \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\gamma $$\end{document}γ; the maximum value \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$I_{\max }$$\end{document}Imax; and the exponent of the final decrease \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varGamma $$\end{document}Γ. From these three parameters, we show mathematically how to extract all relevant parameters of the SIR model. We test this procedure on numerical data and then apply the methodology to real data received from the COVID-19 situation in France. We conclude that, based on the hospitalized data and the ICU (Intensive Care Unit) cases, two exponentials are found, for the initial increase and the decrease in I(t). The parameters found are larger than reported in the literature, and they are associated with a susceptible population which is limited to a sub-sample of the total population. This may be due to the fact that the SIR model cannot be applied to the covid-19 case, due to its strong hypotheses such as mixing of all the population, or also to the fact that the parameters have changed over time, due to the political initiatives such as social distanciation and lockdown.

International audience; The nocturnal low-level jet (LLJ) and orographic (gravity) waves play an important role in the generation of turbulence and pollutant dispersion and can affect the energy production by wind turbines. Additionally, gravity waves have an influence on the local mixing and turbulence within the surface layer and the vertical flux of mass into the lower atmosphere. On 25 September 2017, during a field campaign, a persistent easterly LLJ and gravity waves were observed simultaneously in a coastal area in the north of France. We explore the variability of the wind speed, turbulent eddies, and turbulence kinetic energy in the time–frequency and space domain using an ultrasonic anemometer and a scanning wind lidar. The results reveal a significant enhancement of the turbulence-kinetic-energy dissipation (by 50%) due to gravity waves in the LLJ shear layer (below the jet core) during the period of wave propagation. Large magnitudes of zonal and vertical components of the shear stress (approximately 0.4 and 1.5 m2 s−2, respectively) are found during that period. Large eddies (scales of 110 to 280 m) matching the high-wind-speed regime are found to propagate the momentum downwards, which enhances the mass transport from the LLJ shear layer to the roughness layer. Furthermore, these large-scale eddies are associated with the crests while comparatively small-scale eddies are associated with the troughs of the gravity wave

In aquatic ecosystems, anthropogenic activities disrupt nutrient fluxes, thereby promoting harmful algal blooms that could directly impact economies and human health. Within this framework, the forecasting of the proxy of chlorophyll a in coastal areas is the first step to managing these algal blooms. The primary goal was to analyze how phytoplankton bloom forecasts are impacted by different sampling frequencies, by using a machine learning model. The database used in this study was sourced from an automated system located in the English Channel. This device has a sampling frequency of 20 min. We considered 12 physicochemical parameters over a six-year period. Our forecast methodology is based on the random forest (RF) model and a sliding window strategy. The lag times for these sliding windows ranged from 12 h to 3 months with four different sampling times until 1 day. The results indicate that the optimal forecast was obtained for a 20 min time step, with an average R2 of 0.62. Moreover, the highest values of fluorescence were predicted when the water temperature was approximately 11.8 °C. Consequently, we demonstrated that the sampling frequency directly impacts the forecast performance of an RF model. Furthermore, this kind of model can recreate interactions that closely resemble biological processes. Our study suggests that the RF model can utilize the additional information contained in high-frequency datasets. The methodology presented here lays the foundation for the development of a numerical decision-making tool that could help mitigate the impact of these algal blooms.

The Bay of Biscay and the English Channel, in the North-eastern Atlantic, are considered as a natural laboratory to explore the coastal dynamics at different spatial and temporal scales. In those regions, the coastal circulation is constrained by a complex topography (e.g. varying width of the continental shelf, canyons), river runoffs, strong tides and a seasonally contrasted wind-driven circulation. Based on different numerical model experiments (from 400m to 4km spatial resolution, from 40 to 100 sigma vertical layers using 3D primitive equation ocean models), different features of the Bay of Biscay and English Channel circulation are assessed and explored. Both spatial (submesoscale and mesoscale) and temporal (from hourly to monthly) scales are considered. Modelled spatial scales, with a specific focus on the variability of fine scale features (e.g. fronts, filaments, eddies), are compared with remotely sensed observations (i.e. Sea Surface Temperature). Different methodologies as singularity and Lyapunov exponents allow describing fine scales features and are applied on both modelled and observed datasets. For temporal scales, in situ high frequency surface temperature measurements from coastal moorings (from COAST-HF observing network) provide a reference for the temporal variability to be modelled. Exploring differences in the temporal scales (from an Empirical Mode Decomposition) advises on the efficiency of our coastal modelling approach. This result overview in the Bay of Biscay and the English Channel aims illustrating the input of coastal modelling activities in understanding multi-scale interactions (spatial and temporal).

International audience; "Understanding public perception of climate change risks in coastal communities is a prerequisite for effective climate adaptation. This study aimed at evaluating the potential impacts of climate change on two coastal communities on the northern coast of France by producing prospective maps of the coastline by 2065 and at assessing the local inhabitants' risk perception and preferred strategies for facing future coastal risks through a survey of 285 households. The solutions inhabitants considered the more appropriate to preserve their living environment while adapting to the potential impacts of climate change were analyzed. A vast majority of the inhabitants is aware of coastal risks in their municipality, but their feeling of exposure is spatially-influenced depending on the distance to the hazard source. Conversely, no relationship was found between preferred strategies for facing future coastal risks and proximity to the shoreline. In the municipality where only soft defense structures are present, more inhabitants opt for the “hold the line” solution, while in the other municipality where a portion of the coast is protected by a seawall, a much larger proportion of the surveyed residents prefer the adaptation option." (source éditeur)

International audience; Automated pulse shape-recording flow cytometry was applied to address phytoplankton spatial distribution, at high frequency, in stratified and well mixed water masses in the Western and Central English Channel during the summer-fall transition. Cytometric pulse shapes derived from optical features of single cells allowed the characterization of eight phytoplankton groups. Abundance and total red fluorescence (chlorophyll a autofluorescence) per group were used to define six phytoplankton communities. Their distribution revealed high spatial heterogeneity. Abundance presented a longitudinal gradient for six over the eight groups and succession of brutal shifts along the cruise. Maximum values were often located near the Ushant front in the Western English Channel. A latitudinal gradient characterised the Central English Channel waters under the influence of the Seine estuary. Picophytoplankton (Synechococcus-like cells and picoeukaryotes) represented up to 96% of total abundance and half of the total red fluorescence of the communities near the main front and the Bay of Seine, whereas nanoeukaryotes and microphytoplankton, represented only 4% and less than 1% respectively of total abundance. Both nanoeukaryotes and microphytoplankton dominated the total red fluorescence of the communities of the Central English Channel. The study of traits within each group showed a high variability of traits between communities. The comparison between traits showed that they were independent from each other for some groups (size and red fluorescence per cell for PicoHighFLR and Coccolithophore-like cells; orange and red fluorescence for all the groups), whereas they were dependent for other groups (red fluorescence per cell was dependent of size for picophytoplankton, NanoLowFLR, NanoHighFLR, Cryptophyte-like cells and Microphytoplankton). Variance partitioning revealed that the environmental parameters (temperature, salinity and turbidity) accounted less than spatial descriptors (physical and biological processes) in shaping the communities. Hydrological structures (frontal structures, eddies and tidal streams) were responsible for patches of phytoplankton and defined the structure at the sub-mesoscale (1–10 km) in this area.

International audience; An experiment was performed to study the power production by a Darrieus type turbine of the Dutch company Water2Energy in a tidal estuary. Advanced instrumentation packages, including mechanical sensors, acoustic Doppler current profiler (ADCP), and velocimeter (ADV), were implemented to measure the tidal current velocities in the approaching flow, to estimate the turbine performance and to assess the effect of turbulence on power production. The optimal performance was found to be relatively high (Cp ∼ 0.4). Analysis of the power time history revealed a large increase in magnitude of power fluctuations caused by turbulence as the flow velocity increases between 1 and 1.2 m/s. Turbulence intensity does not alone capture quantitative changes in the turbulent regime of the real flow. The standard deviation of velocity fluctuations was preferred in assessing the effect of turbulence on power production. Assessing the scaling properties of the turbulence, such as dissipation rate, ε, the integral lengthscale, L, helped to understand how the turbulence is spatially organized with respect to turbine dimensions. The magnitude of power fluctuations was found to be proportional to L and the strongest impact of turbulence on power generation is achieved when the size of turbulent eddies matches the turbine size.

Sea breeze (SB) phenomena may strongly influence air quality and lead to important effects on human health. In order to study the impact of SB dynamics on the properties and toxicity of aerosols, an atmospheric mobile unit was deployed during a field campaign performed in an urbanized and industrialized coastal area in Northern France. This unit combines aerosol samplers, two scanning lidars (Doppler and elastic) and an air-liquid interface (ALI, Vitrocell®) in vitro cell exposure device. Our study highlights that after the passage of an SB front, the top of the atmospheric boundary layer collapses as the thermal internal boundary layer (TIBL) develops, which leads to high aerosol extinction coefficient values (>0.4 km−1) and an increase of PM2.5 and NOx concentrations in the SB current. The number-size distribution of particles indicates a high proportion of fine particles (with diameter below 500 nm), while the volume-size distribution shows a major mode of coarse particles centered on 2−3 µm. Individual particle analyses performed by cryo-transmission scanning electron microscopy (cryo-TSEM)-EDX highlights that submicronic particles contained a high fraction of secondary compounds, which may result from nucleation and/or condensation of condensable species (vapors or gaseous species after photo-oxidation). Secondary aerosol (SA) formation can be enhanced in some areas, by the interaction between the SB flow and the upper continental air mass, particularly due to the effect of both turbulence and temperature/humidity gradients between these two contrasting air masses. Potential areas of SA formation are located near the ground, during the SB front passage and in the vicinity of the SB current top. During the sea breeze event, an increase in the oxidative stress and inflammation processes in exposed lung cells, compared to the unexposed cells, can also be seen. In some instances, short singularity periods are observed during SB, corresponding to a double flow structure. It consists of two adjacent SB currents that induce an important increase of the TIBL top, improving the pollutants dispersion. This is associated with a substantial decrease of aerosol mass concentrations.

The intermittency of wind turbine power is an important issue limiting the massive development of this renewable energy. To address this issue, we consider the theoretical framework of multifractal energy cascades, which is a classical framework for describing and characterizing the fluctuations in the turbulent wind input. The multi-scaling statistics of the input turbulent wind are inherited by the wind power produced, and these multi-scaling statistics correspond to a memory in the process. There is memory coming from the fact that the Hurst scaling exponent is smaller than 1/2, and memory coming from the scale invariant cascade process generating intermittency. This memory can be exploited for prediction purposes. Here we test an approach based on an analogy of the power scaling properties with a fractional brownian motion. This is illustrated on real exploitation systems.

Surgeons performing laparoscopic surgery expe-rience distortion when perceiving the stiffness of a patient’s tis-sues. This is due to the lever effect induced by the introductionof instruments in their patient’s body through a fulcrum. Toaddress this problem, we propose to use the comanipulationparadigm. A robotic device is connected to the handle of theinstrument while simultaneously being held by the surgeon.This device applies a force on the handle that reflects the forcemeasured at the tool tip, with a gain that depends on the leverratio. The implementation of this method is presented on anexperimental setup and a preliminary assessment experimentis presented.

The temporal statistics of incompressible fluid velocity and passive scalar fields in developed turbulent conditions is investigated by means of direct numerical simulations along the trajectories of self-propelled point-like probes drifting in a flow. Such probes are characterised by a propulsion velocity which is fixed in intensity and direction; however, like vessels in a flow they are continuously deviated by their intended course as the result of local sweeping of the fluid flow. The recorded time-series by these moving probes represent the simplest realisation of transect measurements in a fluid flow environment. We investigate the non trivial combination of Lagrangian and Eulerian statistical properties displayed by the transect time-series. We show that, as a result of the homogeneity and isotropy of the flow, the single-point acceleration statistics of the probes follows a predictable trend at varying the propulsion speed, a feature that is also present in the scalar time-derivative fluctuations. Further, by focusing on two-time statistics we characterize how the Lagrangian-to-Eulerian transition occurs at increasing the propulsion velocity. The analysis of intermittency of temporal increments highlights in a striking way the opposite trends displayed by the fluid velocity and passive scalars., Comment: 12 pages, 7 figures + supplementary

International audience; The growing interest in soft robots comes from the new possibilities offered by these systems to cope with problems that cannot be addressed by robots built from rigid bodies. Many innovative solutions have been developed in recent years to design soft components and systems. They all demonstrate how soft robotics development is closely dependent on advanced manufacturing processes. This review aims at giving an insight on the current state of the art in soft robotics manufacturing. It first puts in light the elementary components that can be used to develop soft actuators, whether they use fluids, shape memory alloys, electro-active polymers or stimuli-responsive materials. Other types of elementary components, such as soft smart structures or soft-rigid hybrid systems, are then presented. The second part of this review deals with the manufacturing methods used to build complete soft structures. It includes molding, with possibly reinforcements and inclusions, additive manufacturing, thin-film manufacturing, shape deposition manufacturing, and bonding. The paper conclusions sums up the pros and cons of the presented techniques, and open to developing topics such as design methods for soft robotics and sensing technologies.

A key ecological parameter for planktonic copepods studies is their interspecies encounter rate which is driven by their behaviour and is strongly influenced by turbulence of the surrounding environment. A distinctive feature of copepods motility is their ability to perform quick displacements, often dubbed jumps, by means of powerful swimming strokes. Such a reaction has been associated to an escape behaviour from flow disturbances due to predators or other external dangers. In the present study, the encounter rate of copepods in a developed turbulent flow with intensity comparable to the one found in copepods' habitat is numerically investigated. This is done by means of a Lagrangian copepod (LC) model that mimics the jump escape reaction behaviour from localised high-shear rate fluctuations in the turbulent flows. Our analysis shows that the encounter rate for copepods of typical perception radius of ~ {\eta}, where {\eta} is the dissipative scale of turbulence, can be increased by a factor up to ~ 100 compared to the one experienced by passively transported fluid tracers. Furthermore, we address the effect of introducing in the LC model a minimal waiting time between consecutive jumps. It is shown that any encounter-rate enhancement is lost if such time goes beyond the dissipative time-scale of turbulence, {\tau}_{\eta}. Because typically in the ocean {\eta} ~ 0.001m and {\tau}_{\eta} ~ 1s, this provides stringent constraints on the turbulent-driven enhancement of encounter-rate due to a purely mechanical induced escape reaction., Comment: 11 pages, 10 figures

Colloque avec actes et comité de lecture. Internationale.; International audience; Les copépodes sont des crustacés zooplanctoniques très abondants dans les écosystèmes aquatiques. Ils sont un élément important de la chaîne alimentaire, reliant le phytoplancton et les larves de poisson. Les copépodes peuvent nager, et leur nage comporte entre autres des sauts puissants et localisés, souvent utilisés dans le milieu aquatique, pour échapper à leurs prédateurs. Ce comportement de nage, en relation en particulier avec les gradients locaux du champ de vitesse dans leur environnement proche, fait que les copépodes ne peuvent pas être considérés comme des traceurs passifs de l'écoulement. L'influence de ces sauts sur leur répartition spatiale est encore très mal connue. Les travaux présentés dans cette communication font partie d'un travail de thèse soutenue en octobre 2016. Il s'agit de placer des copépodes virtuels (un modèle lagrangien de copépodes) dans un écoulement de simulation numérique directe (DNS) de la turbulence, et de considérer numériquement l'influence du comportement de saut sur la répartition des copépodes dans l'écoulement. Les copépodes virtuels sont placés dans une turbulence homogène et isotrope de nombre de Reynolds (basé sur l'échelle de Taylor) de 80. Ils sont advectés comme des particules passives lagrangiennes, avec des sauts déterminés par la valeur du module du tenseur de déformation dans leur environnement immédiat. Plusieurs paramètres rentrent en compte: le seuil pour déclencher les sauts, la vitesse instantanée des sauts, l'orientation des sauts et le temps de latence entre deux sauts successifs. Différentes simulations sont réalisées, avec 256,000 particules. La répartition spatiale est étudiée via la dimension de corrélation des copépodes; on obtient, pour certaines valeurs des paramètres, une accumulation, ou concentration préférentielle (preferential concentration) assez marquée. L'effet de cette accumulation locale est potentiellement très important écologiquement: cela peut très fortement augmenter le taux de rencontre entre copépodes, et donc l'efficacité de la reproduction. Ces résultats, et leurs implications écologiques, seront discutés dans cette présentation.

International audience; The correlation between the flow turbulence and the performances of a ma- rine current turbine is studied. First, the incoming flow encountered in the flume tank is characterized in the framework of fully developed turbulent cascades in the inertial range. The Reynolds number, the Kolmogorov dissipation scale and the integral scale, are estimated from flow measurements. The intermittency of the turbulence is characterized in the lognormal multifractal framework, and the influence of the turbulent flow on the turbine power is assessed. The rotor speed control unit characteristics used for the turbine regulation induces non-negligible effects on the turbine behavior under fluctuations loads. Even if the power spectrum does not reveal any scale invariance, a multiscale analysis allows us to show the correlations between the turbulence time se- ries and the power produced. The classical Mean Square Coherency function shows that for scales larger than 10 seconds, the upstream velocity and power have large correlations. In the framework of the Empirical Mode Decomposition method, such correlations are studied using the time-dependence intrinsic corre- lation analysis method. This method allows to zoom into time-frequency scales where the flow perturbations induced some modifications in power production

International audience; The CASES-99 experimental data are used to analyze turbulence behaviour under a range of stable conditions using an adaptive method based on Hilbert spectral analysis. The characteristic scales of intrinsic mode functions vary between different stratifications. The second-order Hilbert marginal spectra display clear separation between fine-scale turbulence and large-scale motions. After removing the large-scale motions, the statistical characteristics of the reconstructed signals confirm the distinction of different stratifications in the fine-scale range. The correlation coefficient analyses reveal that the Hilbert spectral analysis method separates turbulence from large-scale motions in the stable boundary layer.

International audience; High-frequency temperature fluctuations recorded in the English Channel are compared using two long-term autonomous underwater monitoring stations at less than 20-min time resolution. Measurements were taken from 2005 to 2011 from two systems 460 km apart in the western and eastern parts of the English Channel. Spectral analysis reveals similar statistical behaviors, with approximate 5/3 spectra and several forcing frequencies in relation to tidal and daily cycles. A co-spectra study reveals a transition scale of 11 days. The influence of this scale is also visible though Time-Dependent Intrinsic Correlation analysis (TDIC)–a recently introduced cross-correlation analysis based on Empirical mode decomposition. This helps to spatialize high-frequency temporal records at a fixed location.

International audience; The Taylor power law (or temporal fluctuation scaling), is a scaling relationship of the form σ ~ (P)λ where !! is the standard deviation and hPi the mean value of a sample of a time series has been observed for power output data sampled at 5 min and 1 s and from five wind farms and a single wind turbine, located at different places. Furthermore, an analogy with the turbulence field is performed, consequently allowing the establishment of a scaling relationship between the turbulent production IP and the mean value (P)

International audience; In this paper, high frequency fluorescence fluctuations, recorded from 2004 to 2011 using an autonomous underwater monitoring system in the eastern English Channel, at 20-min time resolutions, are analyzed. Annual blooms are superposed to multiscale fluctuations. The probability density function (pdf) of the fluorescence time series obeys a power law with slope −2. The pdf for annual portions also obeys power laws, with slopes related to the annual average. Empirical mode decomposition (EMD) is used to study the dynamics and display the power spectrum, which is different from the temperature power spectrum. EMD is also used to extract a trend and isolate the blooms from the high frequency dynamics.

International audience; There is growing efforts for the development of wind energy. Yet, as for other renewable resources, a basic characteristic of wind energy is to deliver intermittent power. In this paper, we consider this topic by analyzing data provided by the wind industry. We discuss first the spectral properties of the data and the corresponding power curve. We estimate the scaling behavior in the inertial scale of wind input and the power output. We also study the rotor revolution scaling fluctuations. Finally the wind/power transfer function is studied, together with the wind/rotation and rotation/power intermediary transfer functions.

International audience; The temporal variability in phytoplankton photosynthetic activity was studied in the coastal waters of the Strait of Dover and related to environmental conditions. Phytoplankton photosynthetic activity data collected from October 2008 and August 2010 at different time scales (hourly to interannual) using a nested sampling design are presented. Photosynthetic parameters including the maximum quantum yield (Fv/Fm), maximal light utilization efficiency (α), maximum electron transport rate (ETRm) and light saturation coefficient (Ek) were measured using Pulse Amplitude Modulation (PAM) fluorometry. Information on the taxonomic composition of phytoplankton assemblages and physicochemical parameters were also collected. Marked changes in photosynthetic parameters were observed at the different time scales investigated. The variability of photosynthetic parameters at sub-seasonal scale (hourly to monthly) could be of the same order of magnitude as at seasonal scale. At short time scale (hour to week), there was no consistent pattern of diel periodicity in photosynthetic parameters. There was a decline of ETRm and α during the day as often as there was a peak at the maximum of irradiance. Light conditions were the main influencing factor on photosynthetic parameters at these time scales. The optimal use of incident irradiance seemed focused on between-day rather than within-day variability. At longer time scale (seasonal to interannual), close interplays between shifts in community taxonomic composition and changes in the physicochemical characteristics of the environment controlled the variability in photosynthetic parameters. Whatever the time scale and period of year considered, variability in photosynthetic parameters was ;Ek-independent;. In well-mixed macrotidal ecosystems, such as the Strait of Dover, a nested sampling design allowing to characterize the short- (intraday and daily) as well as long-term variability (within months, monthly, seasonal, annual and interannual) in photosynthetic parameters is required to get a suitable picture of phytoplankton photosynthesis and avoid potential problems of aliasing.

International audience; Satellite remote sensing observations allow the ocean surface to be sampled synopticallyover large spatio-temporal scales. The images provided from visible and thermal infraredsatellite observations are widely used in physical, biological, and ecological oceanography.The present work proposes a method to understand the multi-scaling properties of satelliteproducts such as the Chlorophyll-a (Chl-a), and the Sea Surface Temperature (SST), rarelystudied. The specific objectives of this study are to show how the small scale heterogeneitiesof satellite images can be characterised using tools borrowed from the fields of turbulence.For that purpose, we show how the structure function, which is classically used in theframe of scaling time series analysis, can be used also in 2D. The main advantage of thismethod is that it can be applied to process images which have missing data. Based on bothsimulated and real images, we demonstrate that coarse-graining (CG) of a gradient modulustransform of the original image does not provide correct scaling exponents. We show,using a fractional Brownian simulation in 2D, that the structure function (SF) can be usedwith randomly sampled couple of points, and verify that 1 million of couple of points providesenough statistics.

International audience; In this paper we propose for the rst time a multiplicative continuous model for generating multifractal elds with zero values, as a continuous generalization of the intermittent lognormal -model proposed by Over and Gupta (1996). It is built using in nitely multiplicative random variables, the multiplicative analog to in nitely divisible distributions for addition. The model also needs stochastic multiplicative measures and multiplicative stochastic integrals. It possesses as a special case a continuous generalization of the classical discrete -model. Applications are numerous in many elds of applied science, including small-scale rainfall and soil science.

In this work, the scaling statistics of the dissipation along Lagrangian trajectories are investigated by using fluid tracer particles obtained from a high resolution direct numerical simulation with $Re_{\lambda}=400$. Both the energy dissipation rate $\epsilon$ and the local time averaged $\epsilon_{\tau}$ agree rather well with the lognormal distribution hypothesis. Several statistics are then examined. It is found that the autocorrelation function $\rho(\tau)$ of $\ln(\epsilon(t))$ and variance $\sigma^2(\tau)$ of $\ln(\epsilon_{\tau}(t))$ obey a log-law with scaling exponent $\beta'=\beta=0.30$ compatible with the intermittency parameter $\mu=0.30$. The $q$th-order moment of $\epsilon_{\tau}$ has a clear power-law on the inertial range $10, Comment: 10 pages with 7 figures accepted for Journal of Fluid Mechanics as Rapids

International audience; The impact of tidal current, waves, and turbulence on particles re-suspension over the sea bottom is studied through eulerian high frequency measurements of velocity and particle size distribution (PSD) during 5 tidal cycles (65 hours) in a coastal environment of the eastern English Channel. High frequency variability of PSD is observed along with the velocity fluctuations. Power spectral analysis shows that turbulent velocity and PSD parameters have similarities in their spectral behaviour over the whole range of examined temporal scales. The low frequency variability of particles is controlled by turbulence (beta =-5/3) and the high frequency is partly driven by dynamical processes impacted by the sea bottom interactions with turbulence (wall turbulence). Stokes number (St), rarely measured in situ, exhibits very low values, emphasizing that these particles can be considered as passive tracers. The effect of tide and waves on turbidity and PSD is highlighted. During slack tide, when the current reaches its minimum value, we observe a higher proportion of small particles compared to larger ones. To a lower extent, high significant wave heights are also associated with a greater concentration of suspended sediments and the presence of larger particles (larger Sauter's diameter D_A, and lower PSD slope xi).

International audience; The objectives are to study and model the aggregate wind power fluctuations dynamics in the multifractal framework. We present here the analysis of aggregate power output sampled at 1 Hz during three years. We decompose the data into several Intrinsic Mode Functions (IMFs) using Empirical Mode Decomposition (EMD). We use a new approach, arbitrary order Hilbert spectral analysis, a combination of the EMD approach with Hilbert spectral analysis (or Hilbert-Huang Transform) and the classical structure-function analysis to extract the scaling exponents or multifractal spectrum ζ(q)ζ(q): this function provides a full characterization of a process at all intensities and all scales. The application of both methods, i.e. structure-function and arbitrary-order Hilbert spectral analyses, gives similar results indicating that the aggregate power output from a wind farm, possesses intermittent and multifractal properties. In order to check this result, we generate stochastic simulations of a Multifractal Random Walk (MRW) using a log-normal stochastic equation. We show that the simulation results are fully compatible with the experimental results

International audience; We have studied experimentally in the laboratory the behavioural responses of females and males of the calanoid copepodTemora longicornis and their encounter probability with the alga Rhodomonas. Both sexes of this calanoid copepod adapted their motion velocity and style of swimming in reaction to the presence of prey. Their mean velocity, as well as the probability of high velocity values, increased in the presence of the algae. Moreover, the time spent in swimming activity increased, reflecting a possible adaptation in order to facilitate encounter with prey. Females were more sensitive to the presence of food: mean velocities showed a 40 %increase for males, from control to food conditions, whereas for females the increase was 240 %. This result was confirmed using several indicators: net-to-gross displacement ratio, probability density functions, andsymbolic dynamics. This may indicate that female T. longicornis are more attracted by food than males.

International audience; In this paper, we have presented a spectral and a multifractal analysis performed on 412 time series of wind speed data each of duration of 350 s and sampled at 20 Hz. The average spectrum for the wind speed displays a scaling behavior, in the inertial range, over two decades, with b ¼ 1:68 close to the Kolmogorov value À 5/3. A multifractal analysis has been motivated by the presence of scaling invariance in data set. Then we have considered their scaling properties in the framework of fully developed turbulence and multifractal cascades. The results obtained for wind speed confirm that the exponent scaling function z V ðqÞ is nonlinear and concave. This exponent characterizes the scaling functions in the inertial range indicating that the wind speed is intermittent and multifractal. Moreover the theoretical quadratic relation for lognormal multifractals is well fitted. We investigate the consequence for wind energy production: we generate stochastic simulations of a multifractal random walk, and using a power curve derived from experimental data, we generate the associated power time series. We show that, due to the saturation of the power curve for large speed values, when the input time series (turbulent wind speed) is multifractal, the output can be almost monofractal.

International audience; Turbulence, unless reaching a threshold level, is generally assumed to enhance ingestion rates in larval fish by increasing encounters with prey. This hypothesis is mainly based on the assumption of a prey-limited environment. In some estuarine areas characterized by high turbulence levels, this hypothesis is rarely met. This study experimentally investigated the effects of flow turbulence (flow Reynolds number Re, ranging from 0 to 55 × 103) on prey ingestion in European sea bass (Dicentrarchus labrax) larvae exposed to prey densities comparable to what is found in a nursery area (i.e., Seine estuary, English Channel). This paper also estimated the prey ingestion rates in sea bass larvae exposed to three different flow conditions (Re = 0, 21.6 × 103, and 43.9 × 103) during various time periods. Contrary to predictions regarding limiting prey densities, the analysis of individual gut contents under different levels of turbulence revealed that increasing Reynolds number (Re) decreased prey ingestion. In addition, increased turbulence affected the feeding to satiation levels in sea bass larvae.

Time series of chlorophyll-a concentration (chl a), backscattering coefficient at 490 nm (bbp(490)) and spectral slope of bbp (γ) derived from satellite imagery of ocean color were used to study the aquatic ecosystem of the Southern Yellow Sea during the time period of 1997–2007. Our study indicated that chl a increased in offshore waters by 0.02 mg m−3 y −1 (p < 0.05), in contrast to a decline observed in the middle and low-latitude global waters. bbp(490), a proxy of total suspended particulate matter concentration did not have any significant trend, while γ, a proxy of the relative proportion of small-sized and larger particles in the surface ocean, decreased significantly. Annual spring phytoplankton blooms occurred in nearshore and offshore waters of the central Southern Yellow Sea; while autumn blooms only occurred in nearshore waters.

International audience; The present study investigated the effect of temperature on male and female swimming activity of the calanoid copepod Temora longicornis, sampled during winter (February) and summer (August) in the English Channel coastal ecosystem. Video recordings were conducted at 3 temperatures representative of those to which these organisms are normally exposed (13, 16 and 20 degrees C) and one extreme-event temperature (24 degrees C). Examinations of instantaneous velocity and symbolic analysis (i.e. dynamics of swimming states discretized from time series of instantaneous velocity) showed that T. longicornis changed its behaviour when confronted with environmental temperature variations. Swimming speed increased as temperature increased. In warmer water, this copepod displayed higher swimming activity, break periods were less frequent, and the frequency of jumps increased. This phenomenon was amplified when the environmental temperature was increased to 24 degrees C. These observations revealed a considerable tolerance to high temperatures and an ability to adjust to environmental temperature changes. The 'summer population' was less active in the low temperature range, but the swimming speed reached a higher value at higher temperatures than that shown by the 'winter population'. The results of the present study highlighted changes in the individual behaviour of this copepod in response to changing seasonal conditions in the form of swimming activity, and thus its ability to maintain biological processes throughout the year, even in a restrictive environment.

In this paper, we introduce a new way to estimate the scaling parameter of a self-similar process by considering the maximum probability density function (pdf) of tis increments. We prove this for $H$-self-similar processes in general and experimentally investigate it for turbulent velocity and temperature increments. We consider turbulent velocity database from an experimental homogeneous and nearly isotropic turbulent channel flow, and temperature data set obtained near the sidewall of a Rayleigh-B\'{e}nard convection cell, where the turbulent flow is driven by buoyancy. For the former database, it is found that the maximum value of increment pdf $p_{\max}(\tau)$ is in a good agreement with lognormal distribution. We also obtain a scaling exponent $\alpha\simeq 0.37$, which is consistent with the scaling exponent for the first-order structure function reported in other studies. For the latter one, we obtain a scaling exponent $\alpha_{\theta}\simeq0.33$. This index value is consistent with the Kolmogorov-Obukhov-Corrsin scaling for passive scalar turbulence, but different from the scaling exponent of the first-order structure function that is found to be $\zeta_{\theta}(1)\simeq 0.19$, which is in favor of Bolgiano-Obukhov scaling. A possible explanation for these results is also given., Comment: 25 pages with 10 figures

International audience; Copepod mating behavior can be broken down into several steps including search, encounter, pursuit, capture and copulation. Using optical systems, we examined the pre- and post-capture mating behavior for the little known subtropical species Pseudodiaptomusannandalei, living in the Danshuei estuary in northern Taiwan. During the mate-finding process, the male remotely located the female through water-born chemical signals released by the female. We found that, when placed into female-conditioned water, the displacement of males exhibited higher frequencies of swimming speeds over 20 mm s−1 and large displacements representing intensive search in restricted areas. Additionally, in presence of females, males responded to signals at a distance greater than 10 body lengths and raced up faithfully along diffusive chemical trails. P. annandalei males also used hydromechanical signals produced by females for close localization and final leap adjustment. The pursuits often resulted in encounters, but only a maximum of 50% of encounters led to copulation, due to rejection behavior by the females. To mate, males had to overcome intensely 'shaky' periods characterized by jumping alternating with strongly convoluted paths. Their chances to copulate increased with the time male maintained seizure of the female, which is helped by modified elements on both sides of the geniculation of their right antenna. Finally, copulation duration was estimated to last an average of 10 min. Rejection behavior by the female is another limitation in addition to the chance of an encounter in the success of the mating process. The possibility that females may perform rejection dance for matechoice is discussed.

International audience; This work revisits the analogy between Newtonian turbulence and non-Newtonian laminar flows. Several direct numerical simulations (DNS) data of a plane channel flow, for a large range of Reynolds numbers (180

International audience; Turbulent flows of Newtonian fluids have already been compared with non-Newtonian laminar flows. In this paper the analogy between these classes of flows is explored, and a new approach to derive a turbulent model based on a nonlinear constitutive equation is shown. In order to reach this aim, direct numerical simulation databases of turbulent channel flows are used and analyzed in the light of the classical parameters of non-Newtonian constitutive equations. The Reynolds stress tensor is expressed in terms of a set of basis tensors based on a projection of a nonlinear framework. The coefficients of the model are given as functions of the intensity of the mean strain tensor. The apparent turbulent viscosity, the first and second normal stress difference, are presented in function of the shear rate. A turbulent Weissenberg number, based on a characteristic turbulent time ratio of the first normal stress difference to the apparent viscosity is also presented. These material functions, exhibiting a shear-thinning behavior, are fitted with the power law (the Carreau-type) model. The range of the Reynolds number investigated was 180≤Reτ≤2000. One of the advantages of the new algebraic nonlinear power law constitutive equation derived in the paper is that its dependence is only on the mean velocity gradient and can be integrated up to the wall.

International audience; Polychaetes are a well-represented group in most marine and estuarine environments, both in terms of number of individuals and species; they typically constitute a significant percentage of the total macrofaunal diversity. The aim of our analyses was to characterise the biodiversity and regional distribution patterns of polychaete assemblages from the continental shelf (0-200 m) of the North Sea, English Channel and Irish Sea. Variations in depth and local distribution of sediment types, amongst other environmental factors, are the main factors affecting the pattern of distribution of benthic polychaetes. Here we applied and compared different approaches to draw the diversity pattern of this marine invertebrate group on a regional biogeographical scale, and to identify the main factors structuring these patterns.

International audience; In previous work [Huang et al., PRE 82, 26319, 2010], we found that the passive scalar turbulence field maybe less intermittent than what we believed before. Here we apply the same method, namely arbitrary-order Hilbert spectral analysis, to a passive scalar (temperature) time series with a Taylor's microscale Reynolds number Reλ 3000. We find that with increasing Reynolds number, the discrepancy of scaling exponents between Hilbert ξθ(q) and Kolmogorov-Obukhov-Corrsin (KOC) theory is increasing, and consequently the discrepancy between Hilbert and structure function could disappear at infinite Reynolds number

International audience; Turbulence models often involve Reynolds averaging, with a closure providing the Reynolds stress tensor as function of mean velocity gradients, through a turbulence constitutive equation. The main limitation of this linear closure is that it rests on an analogy with kinetic theory. For this analogy to be valid there has to be a scale separation between the mean velocity variations and the turbulent Lagrangian free path whose mean value is the turbulent mixing length. The aim of this work is to better understand this hypothesis from a microscopic point of view. Therefore, fluid elements are tracked in a turbulent channel flow. The flow is resolved by direct numerical simulation (DNS). Statistics on particle trajectories ending on a certain distance y0 from the wall are computed, leading to estimations of the turbulent mixing length scale and the Knudsen number. Comparing the computed values to the Knudsen number in the case of scale separation, we may know in which region of the flow and to what extent the turbulence constitutive equation is not verified. Finally, a new non-local formulation for predicting the Reynolds stress is proposed.

In fully developed turbulence, the velocity field possesses long-range correlations, denoted by a scaling power spectrum or structure functions. Here we consider the autocorrelation function of velocity increment $ {\Delta u_{\ell}(t)}$ at separation {time} $\ell$. Anselmet et al. [Anselmet et al. J. Fluid Mech. \textbf{140}, 63 (1984)] have found that the autocorrelation function of velocity increment has a minimum value, whose location is approximately equal to $\ell$. Taking statistical stationary assumption, we link the velocity increment and the autocorrelation function with the power spectrum of the original variable. We then propose an analytical model of the autocorrelation function. With this model, we prove that the location of the minimum autocorrelation function is exactly equal to the separation {time} $\ell$ when the scaling of the power spectrum of the original variable belongs to the range $0, Comment: 11 pages with 9 figures

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International audience; We consider here surf zone turbulence measurements, recorded in the Eastern English Channel using a sonic anemometer. In order to characterize the intermittent properties of their fluctuations at many time scales, we analyze the experimental time series using the Empirical Mode Decomposition (EMD) method. The series is decomposed into a sum of modes, each one narrow-banded, and we show that some modes are associated with the energy containing wave-breaking scales, and other modes are associated with small-scale intermittent fluctuations. We use the EMD approach in association with a newly developed method based on Hilbert spectral analysis, representing the probability density function in an amplitude-frequency space. We then characterize the fluctuations in a stochastic framework using a cumulant generating function for all scales, and compare the results obtained from direct and classical structure function analysis, to EMD-Hilbert spectral analysis results, showing that the former method saturates at large scales, whereas the latter method is more precise in its scale approach. These results show the strength of the new EMD-hilbert spectral analysis method for data presenting a strong forcing such as found in shallow water, wave dominated situations.

International audience; In this paper we presented the analysis of two long time series of daily river flow data, 32 years recorded in the Seine river (France), and 25 years recorded in the Wimereux river (Wimereux, France). We applied a scale based decomposition method, namely Empirical Mode Decomposition (EMD), on these time series. The data were decomposed into several Intrinsic Mode Functions (IMF). The mean frequency of each IMF mode indicated that the EMD method acts as a filter bank. Furthermore, the cross-correlation between these IMF modes from Seine river and Wimereux river demonstrated correlation among the large scale IMF modes, which indicates that both rivers are likely to be influenced by the same events maritime climate event of Northern France. As a confirmation we found that the large scale parts have the same evolution trend. We finally applied arbitrary order Hilbert spectral analysis, a new technique coming from turbulence studies and time series analysis, on the flow discharge of Seine river. This new method provides an amplitude-frequency representation of the original time series, giving a joint pdf $p(\omega,\mathcal{A})$. When marginal moments of the amplitude are computed, one obtains an intermittency study in the frequency space. Applied to river flow discharge data from the Seine river, this shows the scaling range and characterizes the intermittent fluctuations over the range of scales from 4.5 to 60 days, between synoptic and intraseasonal scales.

Hilbert-Huang transform is a method that has been introduced recently to decompose nonlinear, nonstationary time series into a sum of different modes, each one having a characteristic frequency. Here we show the first successful application of this approach to homogeneous turbulence time series. We associate each mode to dissipation, inertial range and integral scales. We then generalize this approach in order to characterize the scaling intermittency of turbulence in the inertial range, in an amplitude-frequency space. The new method is first validated using fractional Brownian motion simulations. We then obtain a 2D amplitude-frequency representation of the pdf of turbulent fluctuations with a scaling trend, and we show how multifractal exponents can be retrieved using this approach. We also find that the log-Poisson distribution fits the velocity amplitude pdf better than the lognormal distribution., Comment: 6 pages with 8 figures

International audience; We consider the nonlinear dynamics of a long-term copepod (small crustaceans) time series sampled weekly in the Mediterranean sea from 1967 to 1992. Such population dynamics display a high variability that we consider here in an interdisciplinary study, using tools borrowed from the field of statistical physics. We analyse the extreme events of male and female abundances, and of the total population, and show that they both have heavy tailed probability density functions (pdf). We provide hyperbolic fits of the form $p(x)\sim 1/x^{\mu+1}$, and estimate the value fo $\mu$ using Hill's estimator. We then study the ratio of male to female abundances, compared to the female abundances. Using conditional probability density functions and conditional averages, we show that this ratio is independent of the female density, when the latter is larger than a given threshold. This property is very useful for modelisation. We also consider the product of male to female abundances, which can be ecologically related to the encounters. We show that this product is extremely intermittent, and link its pdf to the female pdf.

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International audience; Turbulence has a strong influence on plankton contact rate, which is a crucial parameter for plankton ecology. In the field of particle-turbulence interactions, it is now well known that fully developed turbulence does not always homogenise particle distributions, but instead creates, in some well-defined conditions, preferential concentrations of heavy particles. Many studies have considered the influence of this type of preferential concentration on particle contact rate. We consider here the possible application of these results to copepods, assuming that some results obtained for heavy particles are still valid for light particles. Using parameter values representative of copepod species in coastal waters and open ocean, we numerically estimate the possible enhancement of copepod contact rates due to the preferential concentration by turbulence. The assessment is done by using data from a laboratory experiment: we find from the trajectory analysis of small neutrally buoyant particles, that the preferential concentration effect increases the contact rate up to $140\%$. We argue that this effect may be more pronounced for higher Reynolds numbers, and may have important ecological applications.

International audience; Boussinesq's hypothesis is at the heart of eddy viscosity models, which are used in many different fields to model turbulent flows. In its present time formulation, this hypothesis corresponds to an alignment between Reynolds stress and mean strain tensors. We begin with historical remarks on Boussinesq's results and recall that he introduced a local averaging twenty years before Reynolds, but using an approach that prevented him from discovering Reynolds' stress tensor. We then introduce an indicator that characterizes the validity of this hypothesis. For experimental and numerical databases, when the tensors are known, this can be used to directly estimate the validity of this hypothesis. We show, using several different databases, that this hypothesis is almost never verified. We address in conclusion the analogy with kinetic theory, and the reason why this analogy cannot be applied in general for turbulent flows.

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International audience; We reformulate various versions of infinitely divisible cascades proposed in the literature using stochastic equations. This approach sheds a new light on the differences and common points of several formulations that have been recently provided by several teams. In particular, we focus on the simplification occurring when the infinitely divisible noise at the heart of such model is stable: an independently scattered random measure becomes a stable stochastic integral. In the last section we discuss the $D$-dimensional generalization.