Éditeur(s) : University of Florida University of Florida
Résumé : "An IAI Initial Science Program. (ISP)-III Project." "This summary is an abridged, general audience version of a more technical report submitted to the IAI in October 2000."
(Funding) Electronic resources created as part of a prototype UF Institutional Repository and Faculty Papers project by the University of Florida.
Caribbean
North America -- United States of America -- Florida
Argentina
Costa Rica
Mexico

Droits : All rights reserved, Board of Trustees of the University of Florida
60338631

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
In this paper, we propose a benchmarking of supervised machine learning techniques (neural networks, Gaussian processes and support vector machines) in order to forecast the Global Horizontal solar Irradiance (GHI). We also include in this benchmark a simple linear autoregressive (AR) model as well as two naive models based on persistence of the GHI and persistence of the clear sky index (denoted herein scaled persistence model). The models are calibrated and validated with data from three French islands: Corsica (41.91°N; 8.73°E), Guadeloupe (16.26°N; 61.51°W) and Reunion (21.34°S ; 55.49°E). The main findings of this work are, that for hour ahead solar forecasting, the machine learning techniques slightly improve the performances exhibited by the linear AR and the scaled persistence model. However, the improvement appears to be more pronounced in case of unstable sky conditions. These nonlinear techniques start to outperform their simple counterparts for forecasting horizons greater than one hour.
ISSN: 0038-092X

Droits : info:eu-repo/semantics/OpenAccess
hal-01101564
https://hal.archives-ouvertes.fr/hal-01101564
https://hal.archives-ouvertes.fr/hal-01101564/document
https://hal.archives-ouvertes.fr/hal-01101564/file/Manuscript_Lauretetal_Rev_unmarked.pdf
DOI : 10.1016/j.solener.2014.12.014

Éditeur(s) : HAL CCSD
Résumé : International audience
In this work, we have led an analysis of the error of different global solar radiation prediction models according to the global solar radiation variability. Different predictions models where performed such as machine learning techniques (Neural Networks, Gaussian processes and support vector machines) in order to forecast the Global Horizontal solar Irradiance (GHI). We also include in this study a simple linear autoregressive (AR) model as well as two naive models based on persistence of the GHI and persistence of the clear sky index (denoted herein scaled persistence model). The models are calibrated and tested with data from three 3 French islands: Corsica (42.15°N ; 9.08°E), Guadeloupe (16.25°N ; 61.58°W) and Reunion (21.15°S ; 55.5°E). Guadeloupe and Reunion are located in a subtropical climatic zone whereas Corsica is in a tempered climatic zone. Hence the global solar radiation variation differs significantly. The output error of the different models was quantified by the nRSME. In order to quantify the influence of the global solar radiation variability on the forecasting models error we performed a classification of typical days according to different typical days. Each class of typical day is defined by a variation of global solar radiation rate. For each class and for each location, the selected forecasting models where performed and the error was quantified. With this analysis a global solar radiation forecasting models can be selected according to the location, the global solar radiation fluctuations and hence the meteorological conditions. INTRODUCTION Large and frequent variations of solar radiation can be observed in tropical climates with amplitudes reaching 800 W/m² and occurring within a short time interval, from few seconds to few minutes, according to the geographical location. Such fluctuations can be due for example to the dynamic of clouds which can be very complex and depend on cloud type, size, speed and spatial distribution and, more generally, due to some specific local meteorological conditions. Thus, the solar energy forecasting, a process used to predict the amount of solar energy available in the current and near terms, might be a difficult task. Some of the best predictors found in literature are Autoregressive and moving average (ARMA) [5,7,8], Bayesian inferences [9,10], Markov chains [11], k-Nearest-Neighbors predictors [12] or artificial intelligence techniques as the Artificial Neural Network (ANN) [9-11]. Although these methodologies are potentially good in many areas, we observed in our previous studies on global radiation prediction [9,13,14] that the simple model based on the persistence of the clear sky index gives often very good results with acceptable errors [15] for short term forecasting time horizon (<= 1 hour). The goal of this paper is to determinate the influence of solar radiation variability regarding different classes of days on the expected error provided by different forecasting methods that the modeller can possibly implement. The paper is organized as follow: Section 2 describes the data we have used. Section 3 exposes the classification methodology and the results obtained for the three studied locations. In the two following sections, the forecasting methods are exposed and then 3 the errors on the forecasting results for each location and for each class are exposed.
The Third Southern African Solar Energy Conference (SASEC2015)
Kruger National Park, South Africa

Droits : info:eu-repo/semantics/OpenAccess
hal-01099487
https://hal.archives-ouvertes.fr/hal-01099487
https://hal.archives-ouvertes.fr/hal-01099487/document
https://hal.archives-ouvertes.fr/hal-01099487/file/article%20SASEC.pdf

Éditeur(s) : HAL CCSD Wiley
Résumé : International audience
In the mid-afternoon of 15 July 2007, during the Convective and Orographically induced Precipitation Study (COPS), in a very warm and dry environment, an isolated, short-lived, deep convective system developed over the southern Black Forest. Most of the high-resolution, convection-permitting models involved in COPS were unable to capture this event whereas the Meso-NH forecast was quite skilful. To assess the Meso-NH performance further, the model results were carefully checked against the various and numerous COPS observations. In full agreement with clear-air radar observations, model results underlined the triggering role of a low-level convergence line that developed in the lee of the Feldberg. The main departure from the observations was found to be in the low-level moisture fields, which appeared significantly moister in the model than in the observations and also slightly moister than in the other models. Sensitivity studies showed that this departure from the observations was strongly controlled by the initial surface moisture conditions. When the surface moisture was reduced by 20% or replaced by the value derived from a different analysis, the evolution of the planetary boundary layer was more accurately represented while the storm evolution was still correctly captured. These results demonstrate that the quality of the initial forecast cannot be ascribed to the moist bias of the model. It could therefore be hypothesized that the key parameters for a satisfactory forecast of this event lie more in the ability of the model to reproduce the dynamical forcing accurately than in the characteristics of the air-mass instability.
ISSN: 0035-9009

hal-00554400
https://hal.archives-ouvertes.fr/hal-00554400
DOI : 10.1002/qj.710

Éditeur(s) : Wiley-Blackwell
Résumé : The Climate Forecast System Reanalysis (CFSR) provides a wealth of information spanning 1979–2009 for investigation of ocean wind and wave climate. Preprocessing of the data is necessary to remove the dominant seasonal signals and to create time series of semimonthly averaged wind speed and significant wave height over a 0.5° global grid. We perform an empirical orthogonal function (EOF) analysis to extract the dominant space-time patterns. The results for the three major ocean basins show strong zonal structures in the winds and saturation of the swells corroborating prior works with various data sets. We reexamine the CFSR data in the frequency domain to identify periodic signals associated with published climate indices. The Fourier transform of the preprocessed time series generates spectra ranging from 1 month to 15 years period for an EOF analysis. The results demonstrate the spatial structures and periods of climate phenomena. The Arctic Oscillation dominates the Atlantic basin with a broad range of intra-annual signals off the European coasts. The Indian and Pacific Oceans are strongly influenced by inter-annual cycles of the El Niño Southern Oscillation (ENSO) and the Antarctica Oscillation. The Indian Ocean also has strong intra-annual components ranging from 50 to 80 days period. The ENSO proves to be a ubiquitous signal around the globe, and in particular, saturates the Pacific with strong influences in the equatorial region and the Southern Hemisphere Westerlies. A commonality of all basins is that the magnitude and the spatial structure of the intra-annual and inter-annual signals are similar suggesting a wide range of periods in each of the climate cycles examined.
Journal of Geophysical Research: Oceans (21699275) (Wiley-Blackwell), 2014-08 , Vol. 119 , N. 8 , P. 5563-5584

Droits : 2014. American Geophysical Union. All Rights Reserved.
http://archimer.ifremer.fr/doc/00210/32149/30606.pdf
http://archimer.ifremer.fr/doc/00210/32149/30607.pdf
DOI:10.1002/2013JC009729
http://archimer.ifremer.fr/doc/00210/32149/

Éditeur(s) : HAL CCSD Wiley
Résumé : International audience
Within the framework of the international field campaign COPS (Convective and Orographically induced Precipitation Study), a large suite of state-of-the-art meteorological instrumentation was operated, partially combined for the first time. This includes networks of in situ and remote-sensing systems such as the Global Positioning System as well as a synergy of multi-wavelength passive and active remote-sensing instruments such as advanced radar and lidar systems. The COPS field phase was performed from 01 June to 31 August 2007 in a low-mountain area in southwestern Germany/eastern France covering the Vosges mountains, the Rhine valley and the Black Forest mountains. The collected dataset covers the entire evolution of convective precipitation events in complex terrain from their initiation, to their development and mature phase until their decay. Eighteen Intensive Observations Periods with 37 operation days and eight additional Special Observations Periods were performed, providing a comprehensive dataset covering different forcing conditions. In this article, an overview of the COPS scientific strategy, the field phase, and its first accomplishments is given. Highlights of the campaign are illustrated with several measurement examples. It is demonstrated that COPS research provides new insight into key processes leading to convection initiation and to the modification of precipitation by orography, in the improvement of quantitative precipitation forecasting by the assimilation of new observations, and in the performance of ensembles of convection-permitting models in complex terrain.
ISSN: 0035-9009

hal-00565513
https://hal.archives-ouvertes.fr/hal-00565513
DOI : 10.1002/qj.752

Éditeur(s) : Université des Antilles Études caribéennes
Résumé : L’application de modèles macro-économiques à l’analyse et la conception de politique économique ainsi qu’à la maitrise des déséquilibres macro-économiques est encore à un stade précoce dans les petits états insulaires en développement. La présente étude tente de combler cette lacune en proposant un modèle macro-économique applicable à chacun de ces territoires et destiné à l’analyse, la prévision et l’impact de chocs sur leurs économies. La Dominique, petit État insulaire en développement de la Caraïbe, a été choisie comme étude de cas pour un tel exercice. Ce modèle s’appuie sur les techniques analytiques de la cointégration et du modèle à correction d’erreur. Les équations du modèle sont spécifiées et leur performance prévisionnelle évaluée. Une fois élaboré et estimé, ce modèle est ensuite utilisé à des simulations de chocs issues de scénarios alternatifs afin de fournir des enseignements sur la trajectoire future des principales variables économiques de ce pays. L’un des principaux scénarios de l’étude consiste à déterminer le taux de croissance économique que la Dominique devrait cibler pour atteindre l’objectif de réduction de la pauvreté de moitié d’ici à 2015 et ce, conformément aux Objectifs du millénaire pour le développement (OMD), et de déterminer la politique budgétaire et monétaire compatible avec cet objectif. Enfin, l’intérêt d’une telle étude réside dans le fait qu’elle peut servir à réaliser les cadrages macro-économiques des stratégies de réduction de la pauvreté. Sa flexibilité peut en faire un instrument de décloisonnement administratif, favorisant ainsi la discussion avec toutes les parties prenantes de l’élaboration des politiques économiques.
The application of macroeconomic models to analyse and conceptualize the economic policy, as well as controlling macroeconomic imbalances, is still at an early stage in small islands developing states. This article tries to fill in this gap by proposing a macroeconomic model for analyzing, forecasting, and testing the effects of shocks to the economy, applicable for each of these territories. The case of Dominica, a small island developing state of Caribbean area, has been approched. This model draws on the analytical techniques of cointegration and error correction. The single equations are specified and their forecasting performance is assessed. Then, the model is constructed and shock simulations are performed and different scenarios are developed to give further insight in the future path of the main economic variables.One of the main scenarios of this study will determine in comparison of Millennium development goals (MDG), the economic growth rate of Dominica which would help to attain the objective of reduction poverty in half by 2015, as well as the fiscal and monetary policy compatible with this goal. Finally, it helps to make macroeconomic frameworks for strategy reduction of poverty. Its flexibility serves to aid the discussion with all parties.

Droits : info:eu-repo/semantics/openAccess
urn:doi:10.4000/etudescaribeennes.6283
http://journals.openedition.org/etudescaribeennes/6283

Éditeur(s) : Mercator Ocean
Résumé : Pre-operational system PREVIMER provides with coastal observations and forecasts along French coasts: currents, waves, sea levels, temperature, salinity, primary production and turbidity. These marine environmental data come from in situ observations, satellite images, and numerical models. They are centralized and archived in PREVIMER databases, then published on website (real time and historical data), and freely available to users, private companies as well as public administrations. This paper describes in details PREVIMER components and users.
Mercator Ocean - Quarterly Newsletter (Mercator Ocean), 2014 , N. 49 , P. 3-8

Droits : info:eu-repo/semantics/openAccess
http://archimer.ifremer.fr/doc/00189/30037/28523.pdf
http://archimer.ifremer.fr/doc/00189/30037/

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
Forecasting of sea-state characteristics, with warning time of a few hours, appears a necessity in Operational Oceanography. linking sophisticated marine monitoring systems with forecasting modeling tools. In this paper, instead of using conventional numerical models, a Takagi-Sugeno-rule-based Fuzzy Inference System (FIS) was developed aiming at forecasting wave parameters based on the wind speed and direction, and the lagged-wave characteristics. Initial and final antecedent fuzzy membership functions were identified using the subtractive clustering method. The model was applied on the wind and wave dataset recorded in years 2000-2006 by an oceanographic buoy deployed in the Aegean Sea. The model showed perfect fit for the training period (2000-2005; 12,274 data points), and expanded its hindcasting ability during 2006 (1044 data points), as the verification part of the series. Model results, for a lead time of 3 h, showed good agreement between the predicted and the observed significant wave height (RMSE=0.216) and zero-up-crossing period (RMSE=0.315). According to other model performance criteria, the fuzzy model slightly underpredicted both wave characteristics (the linear regression slope was 0.911 for wave height and 0.788 for wave period), and reduced its forecasting ability at higher prediction intervals (+6 to + 12 h). Overall, model results illustrated that the developed FIS could serve as a valuable tool for the operational prediction of wave characteristics in Northern Aegean Sea, through the utilization of the POSEIDON network.
ISSN: 0029-8018

hal-00456020
https://hal.archives-ouvertes.fr/hal-00456020
DOI : 10.1016/j.oceaneng.2009.08.016

Éditeur(s) : Londres : T. Woolmer
Siècle(s) traité(s) : 19
Provenance : Archives départementales de Guadeloupe
Permalien : http://www.manioc.org/patrimon/ADG18190
ADG18190

Éditeur(s) : Université des Antilles Études caribéennes
Résumé : Le changement climatique et le développement durable du tourisme représentent des enjeux majeurs pour l’avenir du tourisme dans plusieurs régions du monde, notamment aux Antilles françaises. Aussi, la présente étude se propose d’analyser et d’évaluer les effets économiques de la variation climatique sur le secteur touristique à la Guadeloupe et à la Martinique, pour quatre raisons essentielles : (a) le secteur du tourisme et les petites économies insulaires qui en dépendent, comme celles de la Guadeloupe et de la Martinique, sont fortement sensibles à la variabilité et au changement du climat. (b) la vulnérabilité intrinsèque de ces petites destinations et de leurs infrastructures à l’élévation du niveau de la mer et aux évènements climatiques extrêmes (cyclones, inondations, sécheresse), (c) la haute dépendance de l’industrie touristique régionale à l’utilisation des énergies fossiles, (d) enfin, en raison du fait qu’aucune évaluation économique chiffrée n’a été produite à ce jour sur les effets économiques de la la variation climatique sur le secteur touristique à la Guadeloupe et à la Martinique. Par conséquent, il importe de cerner dans ces deux régions les conséquences possibles de ce changement au plan touristique et d’envisager le cas échéant des stratégies d’adaptation et d’atténuation. Ce faisant, cette étude se fixe quatre objectifs principaux : (a) examiner les facteurs qui influencent la demande et l’offre de tourisme aux Antilles Françaises ; (b) effectuer à l’aide d’un modèle de demande touristique, l’impact économique de ces facteurs sur le nombre d’arrivées ainsi que sur la dépense touristique dans ces régions ; (c) évaluer et projeter en termes de coût, les effets du changement climatique sur l’activité touristique ; et (d) proposer aux autorités locales, des stratégies d’adaptation et d’atténuation face au défi du changement climatique.L’évaluation de ces différents effets est abordée ici à l’aide d’un modèle structurel de base (MSB) et d’un modèle structurel général (MSG), inspirés tous deux des travaux de Harvey (1990) pour capter à l’aide d’un indice climato-touristique, les éléments du climat qui impactent l’activité touristique. Cet indice synthétique est calculé en se basant sur les données climatiques du passé selon deux scénarios climatiques proposés par le groupe d’experts intergouvernemental sur l’évolution du climat (GIEC) – un scénario pessimiste A2, et un scénario optimiste B2-. Les résultats issus de l’application de ces modèles montrent que les caractéristiques climato-touristiques de la Guadeloupe et de la Martinique subiront vraisemblablement un déclin à long terme, et devraient au plan économique impacter négativement le secteur touristique de ces destinations, se traduisant par des pertes à la fois d’attractivité et de chiffre d’affaires du secteur. Les pertes subies par le tourisme en raison du changement climatique s’élèveraient à l’horizon 2100, et selon le scénario A2, à 45 millions d’euros à la Guadeloupe soit 0,7% de son PIB 2004, et à 60 millions d’euros à la Martinique soit 0,8% de son PIB 2004.
Climate change and the tourism sustainable development are important challenges for tourism future trends of many countries, including the French West Indies. Therefore, this study provides an evaluation of the likely economic effects of climate change on tourism sector in Guadeloupe and Martinique, and identifies four reasons why these countries should be concerned about the potential effects of climate change on tourism: (a) Guadeloupe and Martinique are island destinations very sensitive to climate change; (b) their intrinsic vulnerability and their infrastructure to sea level rise and extreme climatic events (e.g. hurricanes and floods); (c) the high dependence of their tourist industry on carbon-based fuels; and (d) up to date, no economic evaluation of climate change on tourism sector in Guadeloupe and Martinique is provided. Therefore, this study attempted to quantify the likely effects of the changes in the climatic factors on the economy of the French West Indies. There are four main objectives in this study. The first is to examine the factors that influence the demand and supply tourism in Guadeloupe and Martinique. The second is to forecast the impact of climate change to tourism arrivals until 2050 under two scenarios from the intergovernmental panel on climate change (IPCC) – A2: pessimistic scenario and B2: optimistic scenario-. Third is to evaluate and forecast the cost of climate change to the tourism sector until 2100. The fourth is to recommend to authorities the adaptation and mitigation strategies that can be undertaken by the tourism sector to French West Indies to address climate change.Following Harvey (1990), a Basic Structural Model (BSM) and a General structural Model (GSM), are employed to model tourist arrivals to Martinique. A tourism climatic index (TCI) conceptualized by Mieczkowski (1985) is used in this model to capture the elements of climate that impact on a destination’s experience. The results suggest that under both scenarios, the island’s key tourism climatic features will probably decline, and therefore, negatively impact on the destination experience of visitors. Tourism losses due to climate change are projected in 2100 to 45 millions euros in Guadeloupe, or 0.7% of its GDP, and to 60 millions euros in Martinique, or 0,8% of its GDP.
Guadeloupe
Martinique

Droits : info:eu-repo/semantics/openAccess
urn:doi:10.4000/etudescaribeennes.6750
http://journals.openedition.org/etudescaribeennes/6750

Éditeur(s) : HAL CCSD European Geosciences Union
Résumé : International audience
Impact of GPS (Global Positioning System) data assimilation is assessed here using a high-resolution numerical weather prediction system at 2.5 km horizontal resolution. The Zenithal Tropospheric Delay (ZTD) GPS data from mesoscale networks are assimilated with the 3DVAR AROME data assimilation scheme. Data from more than 280 stations over the model domain have been assimilated during 15-day long assimilation cycles prior each of the two studied events. The results of these assimilation cycles show that the assimilation of GPS ZTD with the AROME system performs well in producing analyses closer to the ZTD observations in average. Then the impacts of assimilating GPS data on the precipitation forecast have been evaluated. For the first case, only the AROME runs starting a few hours prior the triggering of the convective system are able to simulate the convective precipitation. The assimilation of GPS ZTD observations improves the simulation of the spatial extent of the precipitation, but slightly underestimates the heaviest precipitation in that case compared with the experiment without GPS. The accuracy of the precipitation forecast for the second case is much better. The analyses from the control assimilation cycle provide already a good description of the atmosphere state that cannot be further improved by the assimilation of GPS observations. Only for the latest day (22 November 2007), significant differences have been found between the two parallel cycles. In that case, the assimilation of GPS ZTD allows to improve the first 6 to 12 hours of the precipitation forecast.
ISSN: 0992-7689

hal-00403847
https://hal.archives-ouvertes.fr/hal-00403847
https://hal.archives-ouvertes.fr/hal-00403847/document
https://hal.archives-ouvertes.fr/hal-00403847/file/angeo-27-2739-2009.pdf

Éditeur(s) : HAL CCSD Wiley
Résumé : International audience
The Convective and Orographically-driven Precipitation Study (COPS) carried out in summer 2007 over northeastern France and southwestern Germany provided a fairly comprehensive description of the low-troposphere water-vapour field, thanks in particular to the deployment of two airborne differential absorption lidar systems. These lidar observations were assimilated using the 3D-Var assimilation system of the Application of Research to Operations at MEsoscale (AROME) numerical weather prediction mesoscale model. The assimilation was carried out for the period 4 July-3 August by running a three-hour forward intermittent assimilation cycle. First, the impact of the lidar observations was assessed by comparing the analyses with a set of more than 200 independent soundings. The lidar observations were found to have a positive impact on the analyses by reducing the dry bias in the first 500 m above ground level and by diminishing the root-mean-square error by roughly 15% in the first km. Then the impact of the lidar observations was assessed by comparing the precipitation forecasts (obtained with and without the lidar observations for the period 15 July-2 August) with the gridded precipitation observations provided by the Vienna Enhanced Resolution Analysis. In general, the impact was found to be positive but not significant for the 24 h precipitation and positive and significant for the 6 h precipitation, with an improvement lasting up to 24 h. Some selected case studies show that the improvement was obtained through a better depiction of convection initiation or through a more accurate positioning of the precipitation systems
ISSN: 0035-9009

hal-00659497
https://hal.archives-ouvertes.fr/hal-00659497
DOI : 10.1002/qj.1864

Éditeur(s) : American Geophysical Union
Résumé : [1] Extreme weather events such as tropical cyclones are difficult to observe with conventional means. Satellite-based observations provide essential measurements of key parameters governing tropical cyclones. They are critical for short-term forecasting. Radiometers onboard the Defense Meteorological Satellite Program satellite series, WindSat and Tropical Rainfall Measuring Mission satellites, scatterometers onboard the ERS, ADEOS, and QuikScat satellites offer unprecedented synoptic observations of surface wind and atmospheric liquid water content, revealing the storm structures with good accuracy. However, satellite estimates do not provide direct measurements of geophysical parameters and can suffer from limitations linked to the sensors characteristics, such as the signal wavelength and polarization or the measurement incidence angle. For example, measurements at Ku band are strongly affected by rain. Still, each observing system can offer specific information that can be combined with the others. In particular, we highlight the capabilities of dual-frequency altimeter to provide very high resolution measurements of rain rate, surface wind speed, and wave characteristics. A method is proposed to obtain continuous along-track 5 km resolution measurements of these parameters in the tropical cyclone Isabel. The results shows that dual-frequency altimeters can provide useful information to complement and validate the operational fields provided by the atmospheric numerical models and by NOAA observing systems.
Journal of Geophysical Union - Research C - Oceans (0148-0227) (American Geophysical Union), 2006 , Vol. 111 , N. C1 , P. NIL_38-NIL_50

Droits : 2006 American Geophysical Union
http://archimer.ifremer.fr/doc/2006/publication-1033.pdf
DOI:10.1029/2005JC003068
http://archimer.ifremer.fr/doc/00000/1033/

Éditeur(s) : HAL CCSD Springer Verlag (Germany) Springer Verlag
Résumé : Direct numerical simulations of flow through two millimeter-scale rock samples of limestone and sandstone are performed using three diverse fluid dynamic simulators. The resulting steady-state velocity fields are compared in terms of the associated empirical probability density functions (PDFs) and key statistics of the velocity fields. The pore space geometry of each sample is imaged at 5.06−μm voxel size resolution using X-ray microtomography. The samples offer contrasting characteristics in terms of total connected porosity (about 0.31 for the limestone and 0.07 for the sandstone) and are typical of several applications in hydrogeology and petroleum engineering. The three-dimensional fluid velocity fields within the explicit pore spaces are simulated using ANSYS® FLUENT® ANSYS Inc. (2009), EULAG Prusa et al. (Comput. Fluids 37, 1193–1207 2008), and SSTOKES Sarkar et al. (2002). These computational approaches are highly disperse in terms of algorithmic complexity, differ in terms of their governing equations, the adopted numerical methodologies, the enforcement of internal no-slip boundary conditions at the fluid-solid interface, and the computational mesh structure. As metrics of comparison to probe in a statistical sense the internal similarities/differences across sample populations of velocities obtained through the computational systems, we consider (i) integral quantities, such as the Darcy flux and (ii) main statistical moments of local velocity distributions including local correlations between velocity fields. Comparison of simulation results indicates that mutually consistent estimates of the state of flow are obtained in the analyzed samples of natural pore spaces despite the considerable differences associated with the three computational approaches. We note that in the higher porosity limestone sample, the structures of the velocity fields obtained using ANSYS FLUENT and EULAG are more alike than either compared against the results obtained using SSTOKES. In the low-porosity sample, the structures of the velocity fields obtained by EULAG and SSTOKES are more similar than either is to the fields obtained using ANSYS FLUENT. With respect to macroscopic quantities, ANSYS FLUENT and SSTOKES provide similar results in terms of the average vertical velocity for both of the complex microscale geometries considered, while EULAG tends to render the largest velocity values. The influence of the pore space structure on fluid velocity field characteristics is also discussed.
ISSN: 1420-0597

hal-01174152
https://hal.archives-ouvertes.fr/hal-01174152
DOI : 10.1007/s10596-015-9486-7

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
In this paper, we propose a benchmarking of supervised machine learning techniques (neural networks, Gaussian processes and support vector machines) in order to forecast the Global Horizontal solar Irradiance (GHI). We also include in this benchmark a simple linear autoregressive (AR) model as well as two naive models based on persistence of the GHI and persistence of the clear sky index (denoted herein scaled persistence model). The models are calibrated and validatedwith data from three French islands: Corsica (41.91°N; 8.73°E), Guadeloupe (16.26°N; 61.51°W) and Reunion (21.34°S ; 55.49°E). The main findings of this work are, that for hour ahead solar forecasting,the machine learning techniques slightly improve the performances exhibited by the linear AR and the scaled persistence model. However, the improvement appears to be more pronounced in case of unstable sky conditions.These nonlinear techniques start to outperform their simple counterparts for forecasting horizons greater than one hour.
ISSN: 0038-092X

Droits : info:eu-repo/semantics/OpenAccess
hal-01099211
https://hal.archives-ouvertes.fr/hal-01099211
https://hal.archives-ouvertes.fr/hal-01099211/document
https://hal.archives-ouvertes.fr/hal-01099211/file/Manuscript_Lauretetal_Rev_unmarked.pdf

Éditeur(s) : Neidine Editeurs
Résumé : The present article introduces and defines what are the rogue or freak waves. After an historical reminder on the recent consideration of their existence, several events of waves having struck big or small ships or still the coastline are presented. A paragraph is dedicated to the scientific explanation of the phenomenon and the difference with other phenomenons such tsunamis or tidal bores is clarified. After a reminder of the international mobilization towards a forecast system, a conclusion focuses on events met in New Caledonian waters and analyzes more exactly testimonies related to this type of phenomenon by trying to clarify their causes.
Le présent article introduit et définit ce que sont les vagues scélérates. Après un rappel historique sur la prise en compte récente de leur existence plusieurs cas de figure de vagues ayant frappé grands ou petits navires ou encore la côte sont présentés.Un paragraphe est consacré à l'explication scientifique du phénomène et la différence avec d'autres cas de figure tels les tsunamis ou les mascarets est explicitée. Après un rappel de la mobilisation internationale vers un système de prévision, une conclusion se focalise sur les cas de figure rencontrés dans les eaux calédoniennes et analyse plus précisément deux témoignages de ce type de phénomène en tentant d'en expliciter les causes.
Tai Kona (2269-7535) (Neidine Editeurs), 2014-02 , N. 7 , P. 26-40

Droits : Tai Kona
http://archimer.ifremer.fr/doc/00186/29724/28142.pdf
http://archimer.ifremer.fr/doc/00186/29724/

Éditeur(s) : HAL CCSD International Association for Energy Economics
Résumé : International audience
In this paper we propose to determinate and to test a set ofstatistical parameters (20)to estimate the predictability of the global horizontal irradiation time series and thereby propose a new prospective tool indicating the expected error regardlessthe forecasting methodsa modeller can possibly implement. The mean absolute log return, which is a tool usually used in econometry, proves to be a very good estimator. Some examples of the use of this tool are exposed, showing the interest of this statistical parameter in concrete cases of predictions or optimizations.
ISSN: 0195-6574

hal-01180041
https://hal.archives-ouvertes.fr/hal-01180041
https://hal.archives-ouvertes.fr/hal-01180041/document
https://hal.archives-ouvertes.fr/hal-01180041/file/discriminent_param.pdf

Éditeur(s) : HAL CCSD Wiley
Résumé : International audience
Climatic niche conservatism, the tendency of species-climate associations to remain unchanged across space and time, is pivotal for forecasting the spread of invasive species and biodiversity changes. Indeed, it represents one of the key assumptions underlying species distribution models (SDMs), the main tool currently available for predicting range shifts of species. However, to date, no comprehensive assessment of niche conservatism is available for the marine realm. We use the invasion by Indo-Pacific tropical fishes into the Mediterranean Sea, the world's most invaded marine basin, to examine the conservatism of the climatic niche. We show that tropical invaders may spread far beyond their native niches and that SDMs do not predict their new distributions better than null models. Our results suggest that SDMs may underestimate the potential spread of invasive species and call for prudence in employing these models in order to forecast species invasion and their response to environmental change.
ISSN: 1461-023X

hal-01136126
https://hal.archives-ouvertes.fr/hal-01136126
DOI : 10.1111/ele.12401

Éditeur(s) : Ieee-inst Electrical Electronics Engineers Inc
Résumé : The synthetic aperture radar (SAR) Doppler centroid has been used to estimate the scatter line-of-sight radar velocity. In weak to moderate ocean surface current environment, the SAR Doppler centroid is dominated by the directionality and strength of wave-induced ocean surface displacements. In this paper, we show how this sea state signature can be used to improve surface wind retrieval from SAR. Doppler shifts of C-band radar return signals from the ocean are thoroughly investigated by colocating wind measurements from the ASCAT scatterometer with Doppler centroid anomalies retrieved from Envisat ASAR. An empirical geophysical model function (CDOP) is derived, predicting Doppler shifts at both VV and HH polarization as function of wind speed, radar incidence angle, and wind direction with respect to radar look direction. This function is used into a Bayesian inversion scheme in combination with wind from a priori forecast model and the normalized radar cross section (NRCS). The benefit of Doppler for SAR wind retrieval is shown in complex meteorological situations such as atmospheric fronts or low pressure systems. Using in situ information, validation reveals that this method helps to improve the wind direction retrieval. Uncertainty of the calibration of Doppler shift from Envisat ASAR hampers the inversion scheme in cases where NRCS and model wind are accurate and in close agreement. The method is however very promising with respect of future SAR missions, in particular Sentinel-1, where the Doppler centroid anomaly will be more robustly retrieved.
Ieee Transactions On Geoscience And Remote Sensing (0196-2892) (Ieee-inst Electrical Electronics Engineers Inc), 2012-07 , Vol. 50 , N. 7 , P. 2901-2909

Droits : 2012 IEEE
http://archimer.ifremer.fr/doc/00088/19896/17554.pdf
DOI:10.1109/TGRS.2011.2174998
http://archimer.ifremer.fr/doc/00088/19896/