Comparison between meteorological re-analyses from ERA-Interim and MERRA and measurements of daily solar irradiation at surface

International audienceThis paper compares the daily solar irradiation available at surface estimated by the MERRA (Modern-Era Retrospective Analysis for Research and Applications) re-analysis of the NASA and the ERA-Interim re-analysis of the European Center for Medium-range Weather Forecasts (ECMWF) against qualified ground measurements made in stations located in Europe, Africa and Atlantic Ocean. Using the clearness index, also known as atmospheric transmissivity or transmittance, this study evidences that the re-analyses often predict clear sky conditions while actual conditions are cloudy. The opposite is also true though less pronounced: actual clear sky conditions are predicted as cloudy. This overestimation of occurrence of clear sky conditions leads to an overestimation of the irradiation and clearness index by MERRA. The overall overestimation is less pronounced for ERA-Interim because the overestimation observed in clear sky conditions is counter-balanced by underestimation in cloudy conditions. The squared correlation coefficient for clearness index, also known as atmospheric transmissivity, ranges between 0.38 and 0.53, showing that a very large part of the variability in irradiation is not captured by the re-analyses. Within an irradiation homogeneous area, the variability of the bias, root mean square error and correlation coefficient are surprisingly large. MERRA and ERA-Interim should only be used in solar energy with proper understanding of the limitations and uncertainties. In regions where clouds are rare, e.g. North Africa, MERRA or ERA-Interim may be used to provide a gross estimate of monthly or yearly irradiation. Satellite-derived data sets offer less uncertainty and should be preferred

Modélisation de cisaillements de vent et assimilation de données dans la couche limite atmosphérique

L'objectif de cette thèse est d'étudier la capacité des modèles météorologiques à prévoir des épisodes de cisaillements de vent dans les basses couches de l'atmosphère sur une zone limitée à un aéroport et d'examiner l'apport pour la modélisation d'observations locales à haute fréquence. Nous avons choisi l'aéroport international de Nice, régulièrement soumis à des variations rapides de la direction et de l'intensité du vent selon l'horizontale dans la CLA, appelées aussi renverses. Un profileur de vent et trois anémomètres sont installés sur les pistes de l'aéroport. Au début de l'année 2009, une campagne de mesures incluant un lidar vent à balayage et un anémomètre sonique s'est déroulée sur l'aéroport fournissant des observations complémentaires. L'ensemble des mesures à haute fréquence temporelle et des simulations numériques obtenues avec le modèle de recherche Méso-NH à 2.5 km de résolution, a fourni une vision de l'enchaînement complexe des écoulements conduisant à des cisaillements de vent d'origine différente. Cette complémentarité a aussi permis d'estimer la capacité du modèle numérique à reproduire les cisaillements de vent. Pour les trois situations étudiées, il reproduit la structure horizontale et verticale de l'écoulement malgré des erreurs de placement spatio-temporel. Bien que les écoulements locaux participent à la mise en place des conditions nécessaires au cisaillement de vent, c'est l'écoulement de méso-échelle (ondes piégées ou talweg d'altitude) qui va déterminer la position du phénomène. Nous avons réalisé des comparaisons avec le modèle opérationnel de Météo-France AROME ainsi que des tests de sensibilité pour étudier l'influence des conditions de couplage et de la résolution. Nous avons, en particulier, augmenté la résolution horizontale de 2.5 km à 500 m sur un domaine centré sur l'aéroport de Nice sur les situations étudiées. Une résolution de 500 m permet d'améliorer la représentation d'écoulements locaux et de variations locales du vent mais n'améliore pas la position des cisaillements de vent par rapport à une échelle plus grossière. L'extension horizontale limitée du domaine à haute résolution augmente la sensibilité aux conditions aux limites de grande échelle. Pour améliorer les prévisions et contraindre le modèle numérique vers les observations disponibles sur le site d'étude, un système d'assimilation de données basé sur le 'nudging' et permettant de prendre en compte des données à haute fréquence temporelle, le ''nudging direct et rétrograde'' (BFN pour 'Back and Forth Nudging'), a été mis en place. Nous avons appliqué cet algorithme aux équations de Lorenz pour confirmer le comportement de cette méthode par rapport à des résultats publiés antérieurement avec d'autres méthodes d'assimilation de données. Les résultats encourageants, ont conduit à l'introduction du BFN dans Méso-NH. Nous avons mis en place des simulations avec assimilation de données simulées dans des conditions idéalisées qui ont montré une réponse cohérente du modèle numérique à l'introduction de profils verticaux de vent.The objective of this thesis is to study the ability of numerical weather prediction model to represent windshears in the lower layer of the atmosphere over an airport area and to determine the impact of high temporal frequency observations on predictions. The study focuses on the international Nice Côte d'Azur airport where horizontal windshears, also called wind reversals, happen regularly. A wind profiler and three anemometers were installed on the Nice airport runways. At the beginning of 2009, a field campaign with a wind lidar and a sonic anemometer took place in order to provide additional observations. Both high temporal frequency data and numerical simulations performed with the mesoscale research model Meso-NH supply a general picture of the evolution of the various flows leading to a windshear event over the airport. We also use observational data to validate the model predictions for three different situations of windshear. The simulations reproduce quite well the horizontal and vertical structure of the flow despite a spatio-temporal misplacement. Local flows such as land and valley breezes are important to generate low level conditions for a horizontal windshear event but the front position is mostly influenced by mesoscale flow (trapped gravity waves or low geopotential). We compared the Meso-NH simulations with the results of the operational model AROME and carried out sensitivity testing against initial and coupling conditions at 2.5 km resolution. We then ran experimental simulations at 500 m resolution, centered on the airport platform, to evaluate the impact of an increased resolution on the windshear predictions. Such a resolution provides improvement of local flow and generates rapid and local wind changes but does not improve the windshear front position compared to a 2.5 km resolution simulation. Moreover the small horizontal grid domain increased the sensitivity to large scale lateral boundary conditions. In order to constrain numerical simulations toward high temporal frequency observations we considered a data assimilation system based on the nudging technique called the 'Back and Forth Nudging' (BFN) technique. We first applied this algorithm to the Lorenz system to compare its behaviour with published results considering other data assimilation techniques. The promising results allowed the implementation of the BFN within the Meso-NH model. We performed assimilation experiments in idealized conditions with high temporal frequency of wind profiles that show a consistent response of the model

The Solar Forecast Similarity Method: a new method to compute solar radiation forecasts for the next day

International audienceThe need for PV plant owners to plan what they are injecting in the electricity grid is more and more stringent to avoid endangering the whole supply in electricity. A new solar forecast algorithm, named Solar Forecast Similarity Method, has been developed to predict irradiance for the next day based on a statistical study of the long term HelioClim-3 irradiation database. This algorithm searches in the past for the most similar days compared to the day of interest and uses their following days to produce a forecast. The model has been optimized against the database itself to compute the most adequate set of parameters over France and for the month of January 2014. With this configuration, the results are a null bias and a root mean square error of 48%. The algorithm outperforms the persistence by 20% and the error is similar to existing methods. An objective validation has then been carried out to compare the irradiance forecasts to high quality measurements from several Baseline Surface Radiation Network (BSRN) ground stations. The method is very promising since the comparison results are in line or lower than the one obtained with the first validation analysis performed on the HelioClim-3 database. For high frequencies, however, predictions have a high error for rapidly varying weather. This demonstrates that the method provides information for the averaged production the following day but requires another input to reliably predict high frequency irradiance

Are re-analyses from ERA or MERRA suitable to assess surface solar irradiance in solar energy applications?

Meteorological re-analyses such as the ERA-Interim and the MERRA ones provide surface solar irradiance (SSI) for long periods of time. This capability is appealing in solar energy as it may help in determining the potential of a given site in any part of the world. The present study presents a comparison made between ground measurements of daily means of the SSI with the same quantity extracted from the ERA-Interim and the MERRA respectively for the period 1985 to 2009. 40 stations with no marked orographic features were retained located in Europe and Africa. It was found that the SSI from re-analyses exhibit a strong bias, most often an over-estimation of the measured SSI. The correlation coefficient is low compared to what is usually observed when comparing satellite-derived assessments and ground measurements. Further analyses demonstrate that the cloud cover of the ERA-Interim and the MERRA re-analyses is not reliable in case of cloudy skies. The ERA-Interim and MERRA re-analyses often underestimate the cloud cover and therefore predict clear skies while the sky is actually overcast. It is concluded that the SSI derived from the ERA-Interim and MERRA re-analyses should not be recommended for use in solar energy applications

Modélisation de cisaillements de vent et assimilation de données dans la couche limite atmosphérique

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

Comparison of several databases of downward solar radiation data at ocean surface with PIRATA measurements

International audienceMeasurements of the downwelling shortwave irradiance at the surface (SSI) at the Atlantic ocean surface are verylimited in space and time. Re-analyses offers high quality and high resolution data of SSI. They can be usedin addition to in-situ measurements in order to increase the knowledge of the relationship between the SSI andatmospheric circulation. However, the accuracy of such re-analyses over the Atlantic ocean remains to assess. Toanswer this question, measurements of the SSI were collected from the Prediction and Research Moored Array inthe Tropical Atlantic (PIRATA) network of buoys located in the equatorial Atlantic ocean. The SSI from severalre-analyses were compared to these measurements. Quality-control was performed onto the measurements fromthe 17 buoys using recognized procedures. SSI from the ERA-Interim and MERRA-2 re-analyses were collectedfor the coincident period: 2011-2016 for the locations of the buoys. In addition, SSI were collected from threesatellite-derived databases: CAMS Radiation, HelioClim-3v4 and v5.Work is underway and exact results are unknown at the moment of submission. From preliminary results, thefollowing is expected. The re-analyses exhibit a tendency to underestimate the SSI in the equatorial Atlantic oceanwith a noticeable influence of the sky conditions on the bias. The re-analyses tend to predict cloud-free conditionswhile actual conditions are cloudy. The correlation coefficients are weak, showing that a large part of the temporalvariability is not captured.In contrast, the three satellite-derived databases offer a fair agreement with PIRATA measurements. Though thebias may be large at times, the standard deviations of the errors are small, meaning a limited scattering of errors. Thecorrelation coefficients are great, meaning that the satellite-derived databases capture a great part of the variabilityin time.It is concluded that efforts must be made on the re-analyses for a better modelling of the clouds. Meanwhile,satellite-derived data sets offer less uncertainties and should be preferred

Validation of a dynamical downscaling process in the context of wind resources mapping

International audienceWind resources mapping requires high frequency wind measurements regularly spatially distributed in the area of interest. In this study the goal is to provide a wind resources atlas in an area where the density of ground measurements stations is low. To make up for the lack of measurements, numerical meteorological models are used. However, the spatial and temporal resolutions of available global meteorological re-analysis products such as MERRA (Modern Era-Retrospective analysis for Research and Applications) or ERA-Interim (European Center for Medium-Range Weather Forecast Re-Analysis) do not fit these requirements. A meso-scale model, the Weather Research and Forecast (WRF) numerical model, is applied to dynamically downscale an ERA-Interim analysis 3D wind field. The WRF numerical model is set up, in particular, with a four dimensional data assimilation system (fdda) toward ERA-Interim. Analysis nudging avoids a rapid divergence of the predicted field compared to the ERA analysis. To assess the capability of the WRF model to provide a reliable prediction, we compared the WRF outputs with two analysis datasets. First, comparison to ERA-Interim analysis - used as boundary and initial conditions - can be used for the determination of the spin-up and stable time period of the WRF model. This information provides some guidance to realize a several year prediction i.e. initial spin-up period and longest possible runtime. The second comparison to MERRA analysis is used as a "cross-validation" of the prediction. This crosscomparison leads to the scale dependant errors and correlations over a long time period between high resolution prediction from WRF and low resolution analysis from MERRA. As a final result, the method and the results are validated with large scale analysis and ground based measurements. The resulting wind-energy resources atlas is therefore reliable for feasibility studies of wind-farm projects

Do modelled or satellite-based estimates of surface solar irradiance accurately describe its temporal variability?

International audienceThis study investigates the characteristic timescales of variability found in long-term time-series of daily means of estimates of surface solar irradiance (SSI). The study is performed at various levels to better understand the causes of variability in the SSI. First, the variability of the solar irradiance at the top of the atmosphere is scrutinized. Then, estimates of the SSI in cloud-free conditions as provided by the McClear model are dealt with, in order to reveal the influence of the clear atmosphere (aerosols, water vapour, etc.). Lastly, the role of clouds on variability is inferred by the analysis of in-situ measurements. A description of how the atmosphere affects SSI variability is thus obtained on a timescale basis. The analysis is also performed with estimates of the SSI provided by the satellite-derived HelioClim-3 database and by two numerical weather re-analyses: ERA-Interim and MERRA2. It is found that HelioClim-3 estimates render an accurate picture of the variability found in ground measurements, not only globally, but also with respect to individual characteristic timescales. On the contrary, the variability found in re-analyses correlates poorly with all scales of ground measurements variability

Adaptive variational multiscale method for turbulent flows past complex geometries

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Adaptive immersed method for turbulent flows with boundary layers

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