Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
Wind energy production is very sensitive to instantaneous wind speed fluctuations. Thus rapid variation of wind speed due to changes in the local meteorological conditions can lead to electrical power variations of the order of the nominal power output. The high variability of this renewable energy source can caused a disruptive effect on power quality and reliability, in non-interconnected island networks as in Guadeloupe (French West Indies). To palliate these difficulties, it is essential to identify and characterize the wind speed distribution over very short time intervals. This allows anticipating the eventuality of power shortage or power surge. Therefore, it is of interest to categorize wind speed fluctuations into distinct classes and to estimate the probability of a distribution to belong to a class. This paper presents a method for classifying wind speed distributions by estimating a finite mixture of Dirichlet distributions. The SAEM algorithm that we use provides a fine distinction between three wind speed distribution classes. It is a new nonparametric method for wind speed classification.
ISSN: 0960-1481

hal-01527881
https://hal.archives-ouvertes.fr/hal-01527881
DOI : 10.1016/j.renene.2011.03.024

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
Wind energy production is very sensitive to turbulent wind speed. Thus rapid variation of wind speed due to changes in the local meteorological conditions can lead to electrical power variations of the order of the nominal power output, in particular when wind power variations on very short time scales, range at few seconds to 1 h, are considered. In small grid as they exist on islands (Guadeloupean Archipelago: French West Indies) such fluctuations can cause instabilities in case of intermediate power shortages. The developed analysis in [14] reveals three main classes of time series for the wind speed fluctuations. In this work, Probability Density Functions (PDFs) are proposed to fit the wind speed fluctuations distributions in each class. After, to simulate wind speed fluctuations sequences, we use a stochastic differential equation, the Langevin equation considering Gaussian turbulence PDF (class I), Gram–Charlier PDF (class II) and a mixture of gaussian PDF (class III). The statistical and dynamical properties of simulated wind sequences are close to those of measured wind sequences, for each class
ISSN: 0306-2619

hal-01527885
https://hal.archives-ouvertes.fr/hal-01527885
DOI : 10.1016/j.apenergy.2012.05.007

Éditeur(s) : HAL CCSD MDPI
Résumé : 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)
ISSN: 2079-9276

hal-01528077
https://hal.archives-ouvertes.fr/hal-01528077
https://hal.archives-ouvertes.fr/hal-01528077/document
https://hal.archives-ouvertes.fr/hal-01528077/file/resources-04-00787.pdf
DOI : 10.3390/resources4040787

Éditeur(s) : HAL CCSD Springer
Résumé : International audience
Wind energy production is very sensitive to turbulent wind, in particular when wind power variations range from few seconds to 1 hour, are considered. Indeed rapid changes in the local meteorological condition as observed in tropical climate can provoke large variations of wind speed. Consequently the electric grid security can be jeopardized due to these fluctuations. This is particularly the case of island networks as in the Guadeloupean archipelago (French West Indies) where the installed 20 MW wind power already represents 11% of the electrical consumption. From 1 million wind sequences of duration 10 minutes, sampled at 1 Hz during the trade season, we proceed toward two objectives: i) the characterization of the wind speed sequences, ii) the dynamical simulation of the wind sequences using Langevin equation.
Progress in Turbulence and Wind Energy IV

ISBN : 978-3-642-28968-2.
hal-01527883
https://hal.archives-ouvertes.fr/hal-01527883
DOI : 10.1007/978-3-642-28968-2-50

Éditeur(s) : HAL CCSD
Résumé : 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.
Energy Procedia

hal-01273262
https://hal.archives-ouvertes.fr/hal-01273262
DOI : 10.1016/j.egypro.2015.07.897

Éditeur(s) : HAL CCSD European Geosciences Union (EGU)
Résumé : International audience
We consider here wind speed time series and the aggregate output wind power from a wind farm. We study their scaling statistics in the framework of fully developed turbulence and Kolmogorov's theory. We estimate their Fourier power spectra and consider their scaling properties in the physical space. We show that the atmospheric wind speed and the aggregate power output from a wind farm are intermittent and multifractal over a wide range of scales. The coupling between simultaneous data of the wind speed and aggregate power output is investigated through a joint multifractal description using the generalized correlation functions (GCFs). This multiscaling test is compatible with a linear relation between the wind speed and the aggregate power output fluctuations for timescales T ⩾ 103 s ≃ 15 min
ISSN: 1023-5809

hal-01527893
https://hal.archives-ouvertes.fr/hal-01527893
DOI : 10.5194/npg-21-379-2014

Éditeur(s) : HAL CCSD Intech
Résumé : International audience
The massive integration of sustainable energies into electrical grids (non-interconnectedor connected) is a major problem due to their stochastic character revealed by strongfluctuations at all scales. In this paper, the scaling behaviour or power law correlationsand the nature of scaling behaviour of sustainable resource data such as flow velocity,atmospheric wind speed, solar global solar radiation and sustainable energy such as,wind power output, are highlighted. For the first time, Fourier power spectral densitiesare estimated for each dataset. We show that the power spectrum densities obtained areclose to the 5/3 Kolmogorov spectrum. Furthermore, the multifractal and intermittentproperties of sustainable resource and energy data have been revealed by the concavityof the scaling exponent function. The proposed analysis frame allows a full descriptionof fluctuations of processes considered. A good knowledge of the dynamic of fluctua-tions is crucial to management of the integration of sustainable energies into a grid.
Sustainable Energy - Technological Issues, Applications and Case Studies

hal-01528087
https://hal.archives-ouvertes.fr/hal-01528087
DOI : 10.5772/106341

Éditeur(s) : HAL CCSD European Geosciences Union (EGU)
Résumé : International audience
We consider here wind speed time series and the aggregate output wind power from a wind farm. We study their scaling statistics in the framework of fully developed turbulence and Kolmogorov's theory. We estimate their Fourier power spectra and consider their scaling properties in the physical space. We show that the atmospheric wind speed and the aggregate power output from a wind farm are intermittent and multifractal over a wide range of scales. The coupling between simultaneous data of the wind speed and aggregate power output is investigated through a joint multifractal description using the generalized correlation functions (GCFs). This multiscaling test is compatible with a linear relation between the wind speed and the aggregate power output fluctuations for timescales T > 103 s ' 15min.
ISSN: 1023-5809

hal-00958490
https://hal.archives-ouvertes.fr/hal-00958490
DOI : 10.5194/npg-21-379-2014

Éditeur(s) : HAL CCSD Elsevier
Résumé : 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.
ISSN: 0167-6105

hal-01527886
https://hal.archives-ouvertes.fr/hal-01527886
DOI : 10.1016/j.jweia.2012.06.002

Éditeur(s) : HAL CCSD
Résumé : 32 pages
Wind energy production is very sensitive to instantaneous wind speed fluctuations. Thus rapid variation of wind speed due to changes in the local meteorological conditions can lead to electrical power variations of the order of the nominal power output. In small grids, as they exist for example on some islands in the French West Indies, such fluctuations can cause instabilities in case of intermediate power shortages. To palliate these difficulties, it is essential to identify and characterize the wind speed distributions. This allows to anticipate the eventuality of power shortage or power surge. Therefore, it is of interest to categorize wind speed fluctuations into distinct classes and to estimate the probability of a distribution to belong to a class. This paper presents a method for classifying wind speed histograms by estimating a finite mixture of Dirichlet distributions. The SAEM algorithm that we use provides a fine distinction between wind speed distribution classes. It's a new nonparametric method for wind speed sequences classification. However, we show that the wind speed distributions in each class correspond to specific Gram- Charlier densities.
https://hal.archives-ouvertes.fr/hal-00319608

hal-00319608
https://hal.archives-ouvertes.fr/hal-00319608
https://hal.archives-ouvertes.fr/hal-00319608v2/document
https://hal.archives-ouvertes.fr/hal-00319608/file/Article_dirichlet.pdf
ARXIV : 0810.4422

Éditeur(s) : HAL CCSD Elsevier
Résumé : 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 (IMF) using Empirical Mode Decomposition (EMD). We use a new approach, arbitrary order Hilbert spectral analysis, a combination of EMD approach with Hilbert spectral analysis (or Hilbert Huang Transform) and the classical structure function analysis to extract the scaling exponents or multifractal spectrum $zeta(q)$: 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, give 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.
Physica A

hal-01527887
https://hal.archives-ouvertes.fr/hal-01527887
DOI : 10.1016/j.physa.2013.04.038

Résumé : La forte variabilité de la vitesse du vent fait que l'énergie produite par un parc éolien n'est pas constante dans le temps. Le gestionnaire ne peut donc pas dimensionner son réseau électrique en prenant intégralement ce type de production en compte. L' une des solutions préconisées pour permettre le développement de l' éolien et son intégration avec une plus grande sureté aux réseaux, est de développer et d'améliorer les outils de prévisions. Le travail de thèse consiste à améliorer les performances d'un outil de prédiction basé sur les réseaux de neurones bayesiens, permettant la prédiction de la puissance à très court terme . Le prédicteur fonctionne notamment par J'ajustement de paramètres, certain se détermine « automatiquement » via le mécanisme des réseaux de neurones bayesiens d' autres, que nous nommerons paramètres temporels, sont à l' appréciation de l'utilisateur. Le travail mené consiste à établir un protocole pour la fixation de ces paramètres tout en améliorant les performances du prédicteur . Nous avons donc décidé de conditionner leurs valeurs en fonction de la variabilité des séquences de puissance précédent l'instant de prévision. Tout d'abord nous avons classifié des séquences de puissance en fonction de leurs coefficients de variation en appliquant la méthode des C-moyennes floues. Puis, chaque classe formée a été testée sur plusieurs valeurs de paramètres, les valeurs associées aux meilleures prédictions ont été retenues. Enfin, ces résultats couplés au formalisme des Chaines de Markov, par le biais de la matrice de transition , ont perm is d'obtenir des taux d'amélioration par rapport à la persistance allant de 7,73 à 23,22 % selon l'horizon de prédiction considéré
The high variability of the wind speed has for conse quences that the energy produced by a wind farm is not constant over time. Therefore, the manager can't size the electrical network by takin g into account this type of production. One solution advocated for the development of wind energy and its integrati on with greater security at network, is to develop and improve fore casting tools. The thesi s objective is to improve the performance of a predi ction tool based on Bayesian neural networks, allowing the predi ction of wind power for short timescales. The predictor works, in part icular by the adjustment of parameters, sorne is determined "automatically" through the mechan ism of neural networks Bayesian other , which we cali temporal parameters are at the discretion of the user. The work involves establishing a protocol for the determination of these parameters and improving the performance of the predictor. So, we decided to condition their values depending on the sequence variability of wind power previous the moment of the forecast. First we classified sequences of power according to their coefficients of variation using the method of fuzzy C-means. Then, each formed class was tested for several parameters values, the values associated with the best predictions were selected. Finally , these result s coupled with the formalism of Markov chains , through the transition matrix allowed to obtain rates of improvement over the persistence ranging from 7.73 to 23.22 % depending on the prediction horizon considered

http://www.theses.fr/2013AGUY0679/document

Résumé : Ce travail est l'expression d'une volonté de chercheurs, de la Carabe d'améliorer les connaissances scientifiques méso- et micro-météorologiques appliquées aux milieux insulaires sous influence des alizés et de développer la recherche dans ces domaines.On sait que le phénomène météorologique le plus remarquable impactant les îles de la Caraïbe reste le cyclone tropical. Mais d'autres phénomènes, a des échelles inferieures, telles que les pluies intenses, les houles, la dégradation de la qualité de l'air ont une importance aigüe en termes de risques naturels ou de risques sur la sante. Ces exemples attestent la nécessité d'utiliser des méthodes de descente d'échelle pour exploiter l'information météorologique et/ou climatique de grande échelle et dériver des scenarios locaux et régionaux appliques aux territoires insulaires. Ce défi est important car l'attente d'analyses scientifiques pertinentes dans ces domaines est grande.Les travaux présentés dans ce mémoire ont pour principaux objectifs la simulation numérique puis l'analyse des mécanismes méso- et micro-échelles qui induisent des circulations locales diurnes et nocturnes sur l'archipel de la Guadeloupe à l'aide de codes numériques météorologiques éprouves car largement utilises en recherche et en prévision opérationnelle.Ils constituent donc la première étude de modélisation numérique à haute résolution en basse atmosphère, par descente d'échelle dynamique, pour des intervalles d'espace compris entre 1 km et 111 m sur cet archipel.Le modelé atmosphérique Weather Research and Forecasting ARW V3.4 (WRF ARW), non-hydrostatique, a été utilise pour l'ensemble des simulations pour modéliser la troposphère depuis l'échelle globale à l'échelle de la turbulence.Trois situations météorologiques classiques réelles d'une durée de 48 heures, correspondant à 80 % des situations météorologiques observées dans la zone, alizes soutenus (AS), alizes moyens (AM), alizes faibles (AF) ont été examinées. Ces situations sont caractérisées par les valeurs du nombre de Froude local suivantes : 0,82 (AS), 0,41 (AM) et 0,21 (AF). Six domaines de modélisation ont été sélectionnés pour effectuer les descentes d'échelle dynamiques : D01 (maille de 27 km), D02 (maille de 9 km), D03 (maille de 3 km), D04 (maille de 1 km), D05 (maille de 333 m) et D06 (maille de 111 m) avec soixante-dix niveaux verticaux. Les quatre premiers domaines (D01 à D04) couvrent l'archipel de la Guadeloupe et sont utilisés en mode méso-échelle à l'aide d'un schéma d'ensemble de couche limite planétaire YSU. Les domaines D05 (couvrant l'île de la Basse-Terre et le centre de l'archipel) et D06 (couvrant la zone littorale et rurale du Petit Cul-de-Sac Marin et la zone urbaine de l'agglomération pointoise) sont utilisés en mode Large Eddy Simulation avec une fermeture de la turbulence 1,5 TKE 3D. Le modèle WRF a été forcé toutes les six heures par l'assimilation des champs d'analyses globales du modèle NCEP FNL (1° de résolution). Les simulations effectuées ont permis d'obtenir des champs de variables météorologiques 10-minutes à très hautes résolutions spatiales.Les résultats des simulations méso- et micro-échelles ont été confrontés aux valeurs expérimentales obtenues à l'aide de capteurs places sur des mâts météorologiques (campagne Atmo-Mangrov et réseau de mesure Météo-France). Il s'agissait d'optimiser l'utilisation des couplages de codes numériques tout en conservant la possibilité de les confronter aux observations expérimentales.Les résultats des simulations numériques micro-échelles, des différents cas (AS, AM, AF) sont utilisées pour forcer (c'est-à-dire définir les conditions limites) un modèle lagrangien de dispersion de particules : FLEXPART. Le système couple FLEXPART-WRF a été employé dans le domaine D06 pour étudier la dispersion du panache d'oxydes d'azote émis par la principale usine de production d'électricité de l'île.
The present work expresses the will of Caribbean researchers to improve the meso- and micro-meteorological scientific knowledge of the trade winds influenced island areas, and to develop research in these domains.It is well known that tropical hurricanes remain the most remarkable meteorological phenomena that affect the Caribbean islands. But some other phenomena, of smaller scale, such as intense rainfall events, swells, or air quality degradation, are of extreme importance for natural or health hazards. These examples show the need to use downscaling methods to exploit large scale meteorological or climatic information, and to obtain local and regional scenarios for the island areas. This is an important challenge, as sound scientific studies in these matters are eagerly expected. The aim of the research works exposed in the present dissertation is numerical simulation and analysis of the meso- and microscale mechanisms that induce diurnal and nocturnal local circulations in the Guadeloupe archipelago, using numerical meteorological models that are widely used in research and in operational forecasting.These works represent the first high-resolution (1 km to 111 m) numerical study of the lower atmosphere over the Guadeloupe archipelago. The Weather Research and Forecasting ARW 3.4 (WRF-ARW) model is used to simulate the troposphere from global scale to turbulence scale. Real cases of three typical weather types (80% of cases during a year) are examined during 48 hours : strong trade winds (STW), medium trade winds (MTW) and weak trade winds (WTW). These weather types are characterized by values of the local Froude number : 0.82 (STW), 0.41 (MTW) and 0.21 (WTW). Six domains have been selected for the dynamical downscaling : D01 (grid spacing of 27 km), D02 (grid spacing of 9 km), D03 (grid spacing of 3 km), D04 (grid spacing of 1 km), D05 (grid spacing of 333 m) and D06 (grid spacing of 111 m), including 70 vertical levels. The first four domains (D01 to D04) cover the Guadeloupe archipelago and are used in the meso-scale simulations with the planetary boundary layer scheme YSU (ensemble mean). Domain D05 (covering the Basse-Terre island and the middle of the archipelago) and domain D06 (covering the coastal and rural area of Le Petit Cul-de-Sac Marin and the urban area of Pointe-à-Pitre), are employed in the micro-scale simulation (LES) with the 3D TKE 1.5 order closure scheme. WRF has been 6 hourly reinitialized with the NCEP FNL global analyses (resolution of 1°). These simulations permitted to obtain 10-minutes meteorological variable fields with a very high resolution (111 m).Meso-scale and micro-scale model results have been evaluated with observational data from meteorological stations (field campaign Atmo-Mangrov, French Met Office).Once validated, the micro-scale model outputs have been used for the assimilation of the lagrangian particle dispersion model : FLEXPART. The coupling FLEXPART-WRF has been employed in domain D06, in order to analyze the dispersion of the nitrogen oxide plume emitted by the main power plant of the archipelago.

http://www.theses.fr/2014AGUY0735/document

Éditeur(s) : HAL CCSD Elsevier
Résumé : 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 β=1.68 close to the Kolmogorov value −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 ζV(q) 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.
ISSN: 0167-6105

hal-00779049
https://hal.archives-ouvertes.fr/hal-00779049
DOI : 10.1016/j.jweia.2012.06.002

Éditeur(s) : HAL CCSD European Geosciences Union
Résumé : International audience
We develop and implement a new method to take into account the impact of waves into the 3-D circulation model SYMPHONIE (Marsaleix et al., 2008, 2009a), following the simplified equations of Bennis et al. (2011) which use glm2z-RANS theory (Ardhuin et al., 2008b). These adiabatic equations are completed by additional parameterizations of wave breaking, bottom friction and wave-enhanced vertical mixing, making the forcing valid from the surf zone through to the open ocean. The wave forcing is performed by wave generation and propagation models WAVEWATCH III® (Tolman, 2008, 2009; Ardhuin et al., 2010) and SWAN (Booij et al., 1999). The model is tested and compared with other models for a plane beach test case, previously tested by Haas and Warner (2009) and Uchiyama et al. (2010). A comparison is also made with the laboratory measurements of Haller et al. (2002) of a barred beach with channels. Results fit with previous simulations performed by other models and with available observational data. Finally, a realistic case of energetic waves travelling over a coast of the Gulf of Lion (in the northwest of the Mediterranean Sea) for which currents are available at different depths as well as an accurate bathymetric database of the 0-10 m depth range, is then simulated. A grid nesting approach is used to account for the different forcings acting at different spatial scales. The simulation coupling the effects of waves and currents is successful to reproduce the powerful northward littoral drift in the 0-15 m depth zone. More precisely, two distinct cases are identified: when waves have a normal angle of incidence with the coast, they are responsible for complex circulation cells and rip currents in the surf zone, and when they travel obliquely, they generate a northward littoral drift. These features are more complicated than in the test cases, due to the complex bathymetry and the consideration of wind and non-stationary processes. Wave impacts in the inner shelf are less visible since wind and regional circulation seem to be the predominant forcings. Besides, a discrepancy between model and observations is noted at that scale, possibly linked to an underestimation of the wind stress. Lastly, this three-dimensional method allows a good representation of vertical current profiles and permits to calculate the shear stress associated with wave and current. Future work will focus on the combination with a sediment transport model.
ISSN: 1812-0806

hal-00766548
https://hal.archives-ouvertes.fr/hal-00766548
https://hal.archives-ouvertes.fr/hal-00766548/document
https://hal.archives-ouvertes.fr/hal-00766548/file/os-8-657-2012.pdf
DOI : 10.5194/osd-8-2417-2011

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
Tropical islands are characterized by thermal and orographical forcings which may generate microscale air mass circulations. The Lesser Antilles Arc includes small tropical islands (width lower than 50 km) where a total of one-and-a-half million people live. Air quality over this region is affected by anthropogenic and volcanic emissions, or saharan dust. To reduce risks for the population health, the atmospheric dispersion of emitted pollutants must be predicted. In this study, the dispersion of anthropogenic nitrogen oxides (NOx) is numerically modelled over the densely populated area of the Guadeloupe archipelago under weak trade winds, during a typical case of severe pollution. The main goal is to analyze how microscale resolutions affect air pollution in a small tropical island. Three resolutions of domain grid are selected: 1 km, 333 m and 111 m. The Weather Research and Forecasting model (WRF) is used to produce real nested microscale meteorological fields. Then the weather outputs initialize the Lagrangian Particle Dispersion Model (FLEXPART). The forward simulations of a power plant plume showed good ability to reproduce nocturnal peaks recorded by an urban air quality station. The increase in resolution resulted in an improvement of model sensitivity. The nesting to subkilometer grids helped to reduce an overestimation bias mainly because the LES domains better simulate the turbulent motions governing nocturnal flows. For peaks observed at two air quality stations, the backward sensitivity outputs identified realistic sources of NOx in the area. The increase in resolution produced a sharper inverse plume with a more accurate source area. This study showed the first application of the FLEXPART-WRF model to microscale resolutions. Overall, the coupling model WRF-LES-FLEXPART is useful to simulate the pollutant dispersion during a real case of calm wind regime over a complex terrain area. The forward and backward simulation results showed clearly that the subkilometer resolution of 333 m is necessary to reproduce realistic air pollution patterns in this case of short-range transport over a complex terrain area. Globally, this work contributes to enrich the sparsely documented domain of real nested microscale air pollution modelling. This study dealing with the determination of the proper resolution grid and proper turbulence scheme, is of significant interest to the near-source and complex terrain air quality research community.
ISSN: 1352-2310

hal-01349208
https://hal.archives-ouvertes.fr/hal-01349208
DOI : 10.1016/j.atmosenv.2016.05.028

Éditeur(s) : HAL CCSD Elsevier
Résumé : 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
Physica A

hal-00846643
https://hal.archives-ouvertes.fr/hal-00846643
DOI : 10.1016/j.physa.2013.04.038

Éditeur(s) : HAL CCSD European Geosciences Union
Résumé : International audience
Natural disturbances are the dominant form of forest regeneration and dynamics in unmanaged tropical forests. Monitoring the size distribution of treefall gaps is important to better understand and predict the carbon budget in response to land use and other global changes. In this study, we model the size frequency distribution of natural canopy gaps with a discrete power law distribution. We use a Bayesian framework to introduce and test, using Monte Carlo Markov chain and Kuo–Mallick algorithms, the effect of local physical environment on gap size distribution. We apply our methodological framework to an original light detecting and ranging dataset in which natural forest gaps were delineated over 30 000 ha of unmanaged forest. We highlight strong links between gap size distribution and environment, primarily hydrological conditions and topography, with large gaps being more frequent on floodplains and in wind-exposed areas. In the future, we plan to apply our methodological framework on a larger scale using satellite data. Additionally , although gap size distribution variation is clearly under environmental control, variation in gap size distribution in time should be tested against climate variability.
ISSN: 1726-4170

hal-01590729
https://hal-univ-guyane.archives-ouvertes.fr/hal-01590729
https://hal-univ-guyane.archives-ouvertes.fr/hal-01590729/document
https://hal-univ-guyane.archives-ouvertes.fr/hal-01590729/file/bg-14-353-2017.pdf
DOI : 10.5194/bg-14-353-2017

Éditeur(s) : HAL CCSD Oxford University Press (OUP)
Résumé : International audience
A temporary network of 10 broad-band seismic stations has been installed in French Polynesia for the Polynesian Lithosphere and Upper Mantle Experiment (PLUME). All the seismic stations were installed either on volcanic islands or on atolls of the various archipelagos of French Polynesia in a manner which complements the geographic coverage provided by the regional permanent stations. The primary aim of PLUME is to image the upper mantle structures related to plate motion and hotspot activity. However, because of its proximity to all sites, the ocean is responsible for a high level of noise in the seismic data and we show that these data can also be used to analyse ocean wave activity. The power spectral density (PSD) analyses of the seismic data recorded in French Polynesia show clear peaks in the 0.05– 0.10 Hz band (periods between 10 and 20 s), which corresponds to swell frequencies. Clear peaks in this frequency band are also observed in infrasonic data recorded on Tahiti. Ground motion analysis shows that the swell-related seismic noise (SRSN) is linearly polarized in the horizontal plane and its amplitude decreases rapidly with the distance from the shore. The microseismic and the infrasonic 'noise' amplitudes show very similar variations from station to station and both are strongly correlated with the swell amplitudes predicted by the National Oceanic and Atmospheric Administration (NOAA), wind-forced, 'WaveWatch' models. The swell direction can be estimated from SRSN polarization analysis but this has to be done with care since, for some cases, the ground motions are strongly controlled by the islands' anisometric shapes and by swell refraction processes. We find cases, however, such as Tahiti or roughly circular Tuamotu atolls, where the azimuth of the swell is in good agreement with the seismic estimates. We, therefore, demonstrate that the SRSN and the infrasonic signal observed in French Polynesia can be used in such cases as a proxy for swell amplitude and azimuth. From the continuous analysis of the data recorded in 2003 at the permanent seismic station PPTL in Tahiti, transfer functions have been obtained. This could provide a way to quantify the swell activity during the last two decades and, therefore, assist in the investigation of climate changes.
ISSN: 0956-540X

hal-01388809
http://hal.univ-reunion.fr/hal-01388809
http://hal.univ-reunion.fr/hal-01388809/document
http://hal.univ-reunion.fr/hal-01388809/file/Barruol_swell_GJI2006.pdf
DOI : 10.1111/j.1365-246X.2006.02871.x

Éditeur(s) : HAL CCSD Wiley
Résumé : Question: To establish a habitat classification based on functional group co-occurrence that may help the drawing up of conservation plans. Location: Riverine forest fragments in the Grand-duché de Luxembourg, Europe. Methods: Forest fragments were surveyed for their abundance of vascular plants. These were clustered into emergent groups according to 14 life-traits related 10 plant dispersal, establishment and persistence. Forest fragments were classified according to similar distribution of the identified emergent groups. Environmental factors were related to the emergent group richness in each forest type using generalized linear models. Results: Contrary to former species centred classification, only two groups of forests, each with clearly different emergent group composition and conservation requirements. Were detected: (1) swamp forests characterized by anemogamous perennials, annuals and hydrochorous perennials and (2) moist forests characterized by barochorous perennials, small geophytes and zoochorous phanerophytes. From a conservation point of view, priority should he given to large swamp forest with intact flooding regimes his is in accordance with the high wind and water dispersal capacities of their typical emergent groups. For the moist forests. conservation priorities should he high forest connectivity and historical continuity since dispersal and establishment of their characteristic emergent groups arc highly limited. Conclusions: The described methodology, situated at an intermediate integration level between the individual species and whole community descriptors. takes advantage of both conservation plans built for single species and the synthetic power of bread ecological measures.
ISSN: 1402-2001

hal-01031884
https://hal.archives-ouvertes.fr/hal-01031884