Éditeur(s) : HAL CCSD
Résumé : International audience
ABSTRACT :A satellite retrieval of surface solar irradiance (SSI) based on GOES satellite data is presented and validated for the French Guiana with three years of in situ measurements from six ground stations. We propose a particle filter approach combining GOES satellite observations and in situ data. We propose an original observation function based on a joint probability distribution and taking advantages of the characteristics of both the involved type of data. The statistical results are compared with those of existing estimation methods and they are found to be in accordance with them. The daily bias ranges from -12 W/m² (-6% of the mean of measurements) to 12 W/m² (6%), depending on the stations. The daily root mean square difference ranges between 23 W/m² (10%) and 27 W/m² (15%). The correlation coefficient is close to 0.92. There is no seasonal climatic effect on the method, the bias and RMSD remain similar for both the rainy and the dry season, but better correlation is observed in the rainy season than in the dry season. Uncertainties are mainly due to the presence of specific tropical atmospheric conditions during the dry season. The method has been tested through various tests: cross-validation scheme has highlighted the potential generalization of the model in a temporal dimension; the ability of the method to effectively duplicate anomalies in surface solar irradiance time series has also been tested. The robustness of the results shows the interest of the method compared to other existing estimation methods. Because of its simplicity of implementation this method opens new prospects in estimating surface solar irradiance. It is concluded that using a particle filter and original observation function method allow a high-quality surface solar irradiance estimation in French Guiana.RESUMEUne méthode d'estimation de l'irradiance solaire de surface (SSI) à partir de données satellites GOES est présentée et validée par comparaison avec trois années de mesures in situ provenant de six stations météorologiques de Guyane Française. Dans cet article, nous proposons une approche par filtre particulaire combinant observations du satellite GOES et données in situ. Nous proposons une fonction d'observation originale basée sur une distribution de probabilité conjointe des deux types de données. Les résultats statistiques sont conformes à ceux des méthodes existantes. Le biais journalier varie de -16 W / m² (-7% de la moyenne des mesures) à 12 W / m² (6%). L'erreur quadratique moyenne (RMSD) est comprise entre 23 W / m² (10%) et 27 W / m² (15%). Le coefficient de corrélation est de 0,92. La méthode est peu sensible aux variations climatiques saisonnières, le biais et RMSD restent similaires en saison des pluies comme en saison sèche, mais une meilleure corrélation est observée pendant la saison des pluies. Les incertitudes sont principalement dues à la présence de conditions atmosphériques tropicales spécifiques en saison sèche. La méthode a été soumise à différents tests : un processus de validation croisée a mis en évidence la possible généralisation du modèle dans une dimension temporelle, la capacité du modèle à reproduire efficacement des anomalies dans les séries temporelles d'irradiance solaire de surface a aussi été testée. La robustesse des résultats obtenus montrent l'intérêt du modèle par rapport aux autres méthodes d'estimation existantes. A cause de sa simplicité de mise en oeuvre cette méthode ouvre de nouvelles perspectives en matière d'estimation de l'irradiance solaire au sol. Nous concluons que l'utilisation d'un filtre particulaire combinée à une fonction d'observation originale permet une estimation de haute qualité de l'irradiance solaire au sol en Guyane Française.
Canadian Journal of Remote Sensing

meteo-01304574
https://hal-meteofrance.archives-ouvertes.fr/meteo-01304574
DOI : 10.1080/07038992.2015.1040150

Éditeur(s) : HAL CCSD
Résumé : Aricle soumis à Solar Energy
In order to qualify the fluctuating nature of solar radiation under tropical climate, we classify daily distributions of the clearness index kt by estimating a finite mixture of Dirichlet distributions without assuming any parametric hypothesis on these daily distributions. The method is applied to solar radiation measurements performed in Guadeloupe (16°2 N, 61 W) where important fluctuations can be observed even within a short period of a few minutes. The results put in evidence four distinct classes of distributions corresponding to different types of days. The sequence of such classes can be of interest for prediction.
https://hal.archives-ouvertes.fr/hal-00289567

hal-00289567
https://hal.archives-ouvertes.fr/hal-00289567
https://hal.archives-ouvertes.fr/hal-00289567/document
https://hal.archives-ouvertes.fr/hal-00289567/file/Article_Classif_soumis.pdf

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
Résumé : International audience
The Heliosat-II method was developed to process Meteosat satellite images in order to assess the solar irradiation at surface. It is modified for its use with GOES satellite images in order to estimate the solar irradiation over French Guiana.Modifications include a change in the calibration formula, in the calculation of the cloud albedo, and in the values of the Linke turbidity factor. These modifications allow the improvement of the performances of the Heliosat-II model in Intertropical zones in French Guiana. The outcomes were compared to coincident measurements of hourly irradiation performed by ground stations.The results show that the use of the maximum apparent albedo as the cloud albedo (ρcmax), along with a fixed value of the Linke turbidity factor produces the best results; the bias was less than 23.61 Wh/m2 (5% of the mean value of the measurements) overall, and the RMSE was less than 109.39 W/m2 (24%) overall when using hourly values. In the case of daily means, the RMSE drops to less than 10.08 W/m2 (10%) overall, whereas the overall bias remains unchanged, as expected. The model performs better in clear skies than in cloudy skies. The results suggest that the Linke turbidity factor used in the Heliosat-II method does not reproduce well the attenuation of the solar radiation in French Guiana. The results were compared to those obtained from Heliosat II method and Meteosat images (HelioClim-3 database) and we found a better accuracy for GOES satellite data, which exhibits smaller viewing angle. The use of the Heliosat II method with GOES images allows assessment of the SSI with a good accuracy and high temporal and spatial resolutions.
Canadian Journal of Remote Sensing

meteo-01304576
https://hal-meteofrance.archives-ouvertes.fr/meteo-01304576
DOI : 10.1080/07038992.2015.1040876

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
In order to qualify the fluctuating nature of solar radiation under tropical climate, we classify daily distributions of the clearness index kt by estimating a finite mixture of Dirichlet distributions without assuming any parametric hypothesis on these daily distributions. The method is applied to solar radiation measurements performed in Guadeloupe (16°2 N, 61 W) where important fluctuations can be observed even within a short period of a few minutes. The results put in evidence four distinct classes of distributions corresponding to different types of days. The sequence of such classes can be of interest for prediction.
ISSN: 0038-092X

hal-01527878
https://hal.archives-ouvertes.fr/hal-01527878
DOI : 10.1016/j.solener.2009.01.010

Éditeur(s) : HAL CCSD Public Library of Science
Résumé : Climate models predict a range of changes in tropical forest regions, including increased average temperatures, decreased total precipitation, reduced soil moisture and alterations in seasonal climate variations. These changes are directly related to the increase in anthropogenic greenhouse gas concentrations, primarily CO2. Assessing seasonal forest growth responses to climate is of utmost importance because woody tissues, produced by photosynthesis from atmospheric CO2, water and light, constitute the main component of carbon sequestration in the forest ecosystem. In this paper, we combine intra-annual tree growth measurements from published tree growth data and the corresponding monthly climate data for 25 pan-tropical forest sites. This meta-analysis is designed to find the shared climate drivers of tree growth and their relative importance across pan-tropical forests in order to improve carbon uptake models in a global change context. Tree growth reveals significant intra-annual seasonality at seasonally dry sites or in wet tropical forests. Of the overall variation in tree growth, 28.7% was explained by the site effect, i.e. the tree growth average per site. The best predictive model included four climate variables: precipitation, solar radiation (estimated with extrasolar radiation reaching the atmosphere), temperature amplitude and relative soil water content. This model explained more than 50% of the tree growth variations across tropical forests. Precipitation and solar radiation are the main seasonal drivers of tree growth, causing 19.8% and 16.3% of the tree growth variations. Both have a significant positive association with tree growth. These findings suggest that forest productivity due to tropical tree growth will be reduced in the future if climate extremes, such as droughts, become more frequent.
ISSN: 1932-6203

hal-01268529
https://hal.archives-ouvertes.fr/hal-01268529
https://hal.archives-ouvertes.fr/hal-01268529/document
https://hal.archives-ouvertes.fr/hal-01268529/file/journal.pone.0092337.PDF
DOI : 10.1371/journal.pone.0092337

Éditeur(s) : HAL CCSD Elsevier Masson
Résumé :  
Modeling soil water availability for tropical trees is a prerequisite to predicting the future impact of climate change on tropical forests. In this paper we develop a discrete-time deterministic water balance model adapted to tropical rainforest climates, and we validate it on a large dataset that includes micrometeorological and soil parameters along a topographic gradient in a lowland forest of French Guiana. The model computes daily water fluxes (rainfall interception, drainage, tree transpiration and soil plus understorey evapotranspiration) and soil water content using three input variables: daily precipitation, potential evapotranspiration and solar radiation. A novel statistical approach is employed that uses Time Domain Reflectometer (TDR) soil moisture data to estimate water content at permanent wilting point and at field capacity, and root distribution. Inaccuracy of the TDR probes and other sources of uncertainty are taken into account by model calibration through a Bayesian framework. Model daily output includes relative extractable water, REW, i.e. the daily available water standardized by potential available water. The model succeeds in capturing temporal variations in REW regardless of topographic context. The low Root Mean Square Error of Predictions suggests that the model captures the most important drivers of soil water dynamics, i.e. water refilling and root water extraction. Our model thus provides a useful tool to explore the response of tropical forests to climate scenarios of changing rainfall regime and intensity.
ISSN: 0168-1923

hal-01032181
https://hal.archives-ouvertes.fr/hal-01032181
DOI : 10.1016/j.agrformet.2011.04.012

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
The aim of this study is to assess the availability and quality of data from the International GNSS Service (IGS) Global Positioning System (GPS) network in Africa, especially for retrieving zenith tropospheric delay (ZTD), from which precipitable water vapour (PWV) can be derived, in view of application to the African Monsoon Multidisciplinary Analysis (AMMA) project. Three major error sources for the GPS data analysis evaluating PWV in Africa are the accuracy of the satellite orbits, the correction for the radio delay induced by the ionosphere and the vertical site displacements due to ocean loading. The first part of this study examines these error sources and the validity of GPS data for meteorological applications in Africa in dedicated analyses spanning the year 2001. These analyses were performed using the IGS precise orbits. Weak degradation of baseline precision with increasing baseline lengths suggests that the average orbital error is not limiting the GPS analysis in Africa. The impact of the ionosphere has been evaluated during a maximum of solar activity in 2001. The loss of L2 data has actually been observed. It amounts to 2% on average for 2001, with maxima of 8% during magnetic storm events. A slight decrease in formal accuracy of ZTD seems to be related to the loss of L2 data at the end of the day. This indicates that scintillation effects are present in the GPS observations but however are not a major limitation. The impact of ocean loading is found to be significant on ZTD estimates (up to ±2 mm in equivalent PWV). The use of a proper ocean loading model eliminates this effect. The second aspect of this study concerns the IGS analysis quality for the African stations. The accuracy has been assessed through position dispersion between individual solutions and the most recent version of the IGS combined solution IGb00, and residuals from the transformation of the IGS combined solution into the International Terrestrial Reference Frame 2005. The positioning performance of the IGS analysis is consistent with an accuracy in ZTD of ±6 mm (±1 mm in PWV), as requested for meteorological applications such as planned in AMMA.
ISSN: 1364-6826

insu-00347961
https://hal-insu.archives-ouvertes.fr/insu-00347961
DOI : 10.1016/j.jastp.2007.04.008

Éditeur(s) : HAL CCSD Taylor & Francis: STM, Behavioural Science and Public Health Titles
Résumé : International audience
Measurements of daily means of surface solar irradiance made at four ground stations in French Guiana are compared to estimates from the HelioClim-3 database produced by the Heliosat-2 method applied to Meteosat satellite images. The bias ranges from 12 W m−2 (6% of the mean of measurements) to 23 W m−2 (12%), depending on the stations. The root mean square difference ranges between 23 W m−2 (11%) and 35 W m−2 (18%). The correlation coefficient (r) is close to 0.9. Better results are observed during the rainy season than during the dry season. Uncertainties are mainly due to the presence of clouds, large viewing angles of the Meteosat satellite, and limitations of the atmospheric transmittance model under the tropical atmospheric conditions. It is concluded that the Heliosat-2 method provides new knowledge about solar radiation in French Guiana.
International Journal of Remote Sensing

hal-00779675
https://hal-mines-paristech.archives-ouvertes.fr/hal-00779675
https://hal-mines-paristech.archives-ouvertes.fr/hal-00779675/document
DOI : 10.1080/01431161.2012.756598

Éditeur(s) : HAL CCSD Wiley
Résumé :  
The lack of information on the ways seasonal drought modifies the CO2 exchange between Neotropical rainforest ecosystems and the atmosphere and the resulting carbon balance hinders our ability to precisely predict how these ecosystems will respond as global environmental changes force them to face increasingly contrasting conditions in the future. To address this issue, seasonal variations in daily net ecosystem productivity (NEPd) and two main components of this productivity, daily total ecosystem respiration (REd) and daily gross ecosystem productivity (GEPd), were estimated over 2 years at a flux tower site in French Guiana, South America (511605400N, 5215404400W). We compared seasonal variations between wet and dry periods and between dry periods of contrasting levels of intensity (i.e. mild vs. severe) during equivalent 93-day periods. During the wet periods, the ecosystem was almost in balance with the atmosphere (storage of 9.0 gCm_2). Seasonal dry periods, regardless of their severity, are associated with higher incident radiation and lower REd combined with reduced soil respiration associated with low soil water availability. During the mild dry period, as is normally the case in this region, the amount of carbon stored in the ecosystem was 32.7 gCm_2. Severe drought conditions resulted in even lower REd, whereas the photosynthetic activity was only moderately reduced and no change in canopy structure was observed. Thus, the severe dry period was characterized by greater carbon storage (64.6 gCm_2), emphasizing that environmental conditions, such as during a severe drought, modify the CO2 exchange between Neotropical rainforest ecosystems and the atmosphere and potentially the resulting carbon balance.
ISSN: 1354-1013

hal-01032067
https://hal.archives-ouvertes.fr/hal-01032067
DOI : 10.1111/j.1365-2486.2008.01610.x