Publications

2010

• Reduced minimax state estimation
  
  • Mallet Vivien
  • Zhuk Sergiy
  , 2010, pp.23. A reduced minimax state estimation approach is proposed for high-dimensional models. It is based on the reduction of the ordinary differential equation with high state space dimension to the low-dimensional Differential-Algebraic Equation (DAE) and on the subsequent application of the minimax state estimation to the resulting DAE. The DAE is composed of a reduced state equation and of a linear algebraic constraint. The later allows to bound linear combinations of the reduced state's components in order to prevent possible instabilities, originating from the model reduction. The method is robust as it can handle model and observational errors in any shape, provided they are bounded. We derive a minimax algorithm adapted to computations in high-dimension. It allows to compute both the state estimate and the reachability set in the reduced space.
• Strategies for processing images with 4D-Var data assimilation methods
  
  • Herlin Isabelle
  • Béréziat Dominique
  • Mercier Nicolas
  , 2010. Data Assimilation is a well-known mathematical technic used, in environmental sciences, to improve, thanks to observation data, the forecasts obtained by meteorological, oceanographic or air quality simulation models. It aims to solve the evolution equations, describing the dynamics of the state variables, and an observation equation, linking at each space-time location the state vector and the observations. Data Assimilation allows to get a better knowledge of the actual system's state, named the reference. In this article, we first describe various strategies that can be applied in the framework of variational data assimilation to study various image processing issues. Second, we detail the mathematical setting and the analysis of pros and cons of each strategy for the issue of motion estimation. Last, results are provided on synthetic images and satellite acquisitions.
• Strategies for processing images with 4D-Var data assimilation methods
  
  • Herlin Isabelle
  • Béréziat Dominique
  • Mercier Nicolas
  , 2010, pp.23 pages. Data Assimilation is a well-known mathematical technic used, in environmental sciences, to improve, thanks to observation data, the forecasts obtained by meteorological, oceanographic or air quality simulation models. It aims to solve the evolution equations, describing the dynamics of the state variables, and an observation equation, linking at each space-time location the state vector and the observations. Data Assimilation allows to get a better knowledge of the actual system's state, named the reference. In this article, we first describe various strategies that can be applied in the framework of variational data assimilation to study various image processing issues. Second, we detail the mathematical setting and the analysis of pros and cons of each strategy for the issue of motion estimation. Last, results are provided on synthetic images and satellite acquisitions.
• Détermination de l'albédo des surfaces enneigées par télédétection : application à la reconstruction du bilan de masse du glacier de Saint Sorlin
  
  • Dumont Marie
  , 2010. L'albédo, fraction de rayonnement réfléchi dans le spectre solaire, est une variable clef du bilan énergétique des surfaces enneigées et englacées. Cette grandeur possède une forte variabilité spatio-temporelle ce qui fait de la télédétection un outil adapté pour son étude. L'albédo dépend à la fois des propriétés physiques du milieu considéré et des caractéristiques du rayonnement incident. Les différentes grandeurs liées à l'albédo sont fonction des domaines angulaires et spectraux des radiations considérées. Les mesures de répartition angulaire du rayonnement réfléchi par la neige ont montré que l'hypothèse lambertienne pouvait conduire à des erreurs non négligeables lors de la détermination de l'albédo par télédétection. La connaissance des caractéristiques de la répartition angulaire du rayonnement réfléchi par la neige permet de développer une nouvelle méthode de détermination de l'albédo en zones montagneuses. Cette méthode prend en compte les effets liés à la forte variabilité topographique des terrains de montagne, à l'anisotropie du rayonnement réfléchi par la neige et par la glace ainsi que les variations spectrales de l'albédo en fonction des propriétés physiques de la surface. Elle a été appliquée à deux types de données : des photographies terrestres visibles et proche infrarouges (résolution spatiale 10 m) et des images MODIS (résolution spatiale 250 m). L'incertitude sur la valeur de l'albédo ainsi déterminée est évaluée à ±10% grâce aux mesures de terrain effectuées sur le glacier de Saint Sorlin (massif des Grandes Rousses, France). L'étude des cartes d'albédo issues de dix années (2000-2009) d'images MODIS montre qu'il n'y a pas de décroissance marquée de la valeur de l'albédo en zone d'ablation au contraire de ce qui a été prouvé pour le glacier du Morteratsch (Suisse). De plus, il existe une corrélation très élevée entre la valeur minimale de la moyenne de l'albédo sur le glacier, i.e. l'albédo moyen du glacier le jour où la ligne de neige est proche de la ligne d'équilibre, et la valeur du bilan de masse annuel spécifique. L'assimilation des données d'albédo obtenues grâce aux images MODIS et aux photographies terrestres dans le modèle de neige CROCUS permet une bonne estimation du bilan de masse spatialisé du glacier de Saint Sorlin (rmse=0.5 m w.e. pour les cinq années hydrologiques étudiées). Les forçages météorologiques utilisés pour cette étude sont de moyenne échelle. L'analyse succincte de la contribution des différents flux atmosphériques au bilan d'énergie de surface montre qu'en zone d'ablation comme en zone d'accumulation, le bilan radiatif net courtes longueurs d'ondes constitue la source principale d'énergie et que la variabilité de ce flux explique la majeure partie de la variabilité journalière de la somme des flux atmosphériques. Appliquées à d'autres glaciers, ces méthodes permettraient de savoir si les conclusions établies pour notre seul glacier d'étude sont valables pour d'autres glaciers. Elles rendraient également possibles la reconstruction du bilan de masse spatialisé sur 10 ans d'autres glaciers et potentiellement une meilleure quantification des processus physiques mis en jeu dans le bilan de masse de ces glaciers tempérés (10.70675/26c0b2b9zf75az4b72za411zda3fe083d0fb)
  DOI : 10.70675/26c0b2b9zf75az4b72za411zda3fe083d0fb
• Ensemble forecast of analyses: Coupling data assimilation and sequential aggregation
  
  • Mallet Vivien
  Journal of Geophysical Research, American Geophysical Union, 2010, 115 (D24303). er based on past observations and past forecasts. This approach has several limitations: the weights are computed only at the locations and for the variables that are observed, and the observational errors are typically not accounted for. This paper introduces a way to address these limitations by coupling sequential aggregation and data assimilation. The leading idea of the proposed approach is to have the aggregation procedure forecast the forthcoming analyses, produced by a data assimilation method, instead of forecasting the observations. The approach is therefore referred to as ensemble forecasting of analyses. The analyses, which are supposed to be the best a posteriori knowledge of the model's state, adequately take into account the observational errors and they are naturally multivariable and distributed in space. The aggregation algorithm theoretically guarantees that, in the long run and for any component of the model's state, the ensemble forecasts approximate the analyses at least as well as the best constant (in time) linear combination of the ensemble members. In this sense, the ensemble forecasts of the analyses optimally exploit the information contained in the ensemble. The method is tested for ground-level ozone forecasting, over Europe during the full year 2001, with a twenty-member ensemble. In this application, the method proves to perform well with 28% reduction in RMSE compared to a reference simulation, to be robust in time and space, and to reproduce many spatial patterns found in the analyses only. (10.1029/2010JD014259)
  DOI : 10.1029/2010JD014259
• Variabilité intrasaisonnière de la mousson africaine : caractérisation et modélisation
  
  • Roehrig Romain
  , 2010. La variabilité intrasaisonnière de la mousson d'Afrique de l'Ouest se caractérise par une alternance de phases sèches et humides, dont les impacts pe uvent être dramatiques sur les populations locales. Cette variabilité met en jeu un grand nombre d'échelles spatiales et temporelles, rendant difficile sa compréhension, sa modélisation et sa prévision. Cette thèse propose quelques éclairages sur ces différentes thématiques. La dépression thermique saharienne est un acteur majeur de la mousson africaine. La caractérisation de sa variabilité intrasaisonnière a permis de mettre en évidence, à l'échelle de 15 jours, l'existence d'interactions entre les latitudes moyennes et l'Afrique de l'Ouest. Lors de son passage au-dessus de l'Atlantique et la Méditerranée, un train d'ondes de Rossby module les ventilations de la dépression thermique, et donc sa structure. Les anomalies de circulation, de température et d'humidité, ainsi induites sur le Sahel, pourraient alors expliquer une partie des fluctuations intrasaisonnières de la convection, notamment celles qui naissent sur l'est du Sahel, et qui se propagent ensuite vers l'ouest. L'état moyen et la variabilité intrasaisonnière de la mousson africaine restent un défi pour les modèles de climat, même pour la dernière génération, qui a participé à l'exercice d'intercomparaison CMIP3. La variabilité à haute fréquence de la convection est un élément particulièrement difficile à modéliser. Toutefois, la meilleure prise en compte de facteurs inhibant le développement de la convection pourrait être une étape importante pour améliorer la modélisation de la mousson et la prévision de ses fluctuations intrasaisonnières (10.70675/48942694zf34dz4fc0zb4acz7e65722f2789)
  DOI : 10.70675/48942694zf34dz4fc0zb4acz7e65722f2789
• Using models of dynamics for large displacement estimation on noisy acquisitions
  
  • Béréziat Dominique
  • Herlin Isabelle
  , 2010, pp.18. The paper discusses the issue of motion estimation on noisy images displaying large displacements, due to high velocity values. ``Noisy'' means that the data contain either missing acquisitions on isolated points, regions, frames or noisy measures. Assuming the dynamics is partially accessible from heuristics and modeled, the objective is to include this knowledge in the computation of the solution even if large displacements occur from one frame to the next one and if the data are noisy. This is performed by Data Assimilation techniques which simultaneously solve an evolution equation and an observation equation. The evolution equation includes the partial knowledge on the dynamics. The observation equation describes the transport of image brightness and is written in a non-linear form in order to better characterize large displacements. The assimilation method is a weak 4D-Var algorithm, in which each component of the Data Assimilation system is associated to an error. We prove that the observation covariance matrix can be used to discard the noisy data during the computation of the solution letting the evolution equation estimate motion from adjacent frames on these pixels. The method is quantified on synthetic data and illustrated on oceanographic satellite images.
• Influence dynamique de l'Himalaya sur le climat en Extrême-Orient
  
  • Mailler Sylvain
  , 2010. L'impact dynamique des montagnes sur la circulation de grande échelle de l'atmosphère passe généralement par des forces : pour cette raison, la partie de l'orographie qui n'est pas résolue par les modèles de circulation générale est prise en compte par la paramétrisations des forces qu'elle applique à l'atmosphère. Dans cette thèse , nous nous attacherons à comprendre l'impact des forces appliquées par les montagnes des moyennes latitudes, en particulier le Plateau tibétain, sur la circulation de l'atmosphère. Pour ce faire, nous utiliserons notamment le concept de couple appliqué par les montagnes sur l'atmosphère, traduction des forces à l'échelle globale. Les chaînes de montagnes les plus importantes des moyennes latitudes génèrent, à l'échelle synoptique, d'importantes vagues de froid appelées cold surges dans la littérature anglophone, un terme que nous traduirons littéralement par crues froides. L'importance du couple équatorial des montagnes dans l'initiation des crues froides sur l'Asie de l'Est (impact du Plateau tibétain), l'Amérique du Nord (impact des montagnes Rocheuses) et l'Amérique du sud (impact de la cordillère des Andes) est mise en évidence par une étude statistique. À l'aide d'un modèle dynamique simple, une interprétation du mécanisme sous-jacent à ce forçage est proposée, montrant que les forces de portance appliquées par la montagne à l'atmosphère dans la phase initiale des crues froides suffisent à leur déclenchement. L'impact dynamique du plateau tibétain sur la mousson d'hiver est-asiatique est important, en particulier sur les événements de convection en hiver sur la Mer de Chine Méridionale. Une séquence d'événements montrant cet impact a été identifiée statistiquement : un forçage dynamique de la circulation atmosphérique par le Plateau tibétain, se traduisant par un fort signal sur le couple des montagnes équatorial appliqué à l'atmosphère, est suivi par le déclenchement d'une crue froide puis, après quelques jours, par un renforcement de la convection profonde sur la Mer de Chine Méridionale. Cet effet dynamique du Plateau tibétain sur la mousson d'hiver s'étend au sud jusqu'à l'Indonésie et à l'ouest jusqu'à la Baie du Bengale. L'utilisation du modèle de circulation générale du Laboratoire de Métérorologie Dynamique, LMDz, permet de compléter les résultats observationnels décrits auparavant. Ce modèle ferme de manière satisfaisante le bilan de moment angulaire et permet de montrer que l'orographie sous-maille joue un rôle important sur la phase finale de l'évolution des crues froides. Des résultats nouveaux sont présentés sur le bilan de moment angulaire de l'atmosphère, en particulier en ce qui concerne l'impact du couple équatorial des montagnes et de la contribution du Plateau tibétain. Il est en particulier montré que le couple équatorial appliqué par le Plateau tibétain joue un rôle faible dans l'évolution temporelle du moment angulaire équatorial, mais un rôle significatif dans sa répartition spatiale (10.70675/efe01085z8de3z4fb3zb525z99be7ef343a0)
  DOI : 10.70675/efe01085z8de3z4fb3zb525z99be7ef343a0
• Development and application of a reactive plume-in-grid model: evaluation over Greater Paris
  
  • Korsakissok Irène
  • Mallet Vivien
  Atmospheric Chemistry and Physics, European Geosciences Union, 2010, 10 (18), pp.8917--8931. Emissions from major point sources are badly represented by classical Eulerian models. An overestimation of the horizontal plume dilution, a bad representation of the vertical diffusion as well as an incorrect estimate of the chemical reaction rates are the main limitations of such models in the vicinity of major point sources. The plume-in-grid method is a multiscale modeling technique that couples a local-scale Gaussian puff model with an Eulerian model in order to better represent these emissions. We present the plume-in-grid model developed in the air quality modeling system Polyphemus, with full gaseous chemistry. The model is evaluated on the metropolitan Île-de-France region, during six months (summer 2001). The subgrid-scale treatment is used for 89 major point sources, a selection based on the emission rates of NOx and SO2. Results with and without the subgrid treatment of point emissions are compared, and their performance by comparison to the observations on measurement stations is assessed. A sensitivity study is also carried out, on several local-scale parameters as well as on the vertical diffusion within the urban area. Primary pollutants are shown to be the most impacted by the plume-in-grid treatment. SO2 is the most impacted pollutant, since the point sources account for an important part of the total SO2 emissions, whereas NOx emissions are mostly due to traffic. The spatial impact of the subgrid treatment is localized in the vicinity of the sources, especially for reactive species (NOx and O3). Ozone is mostly sensitive to the time step between two puff emissions which influences the in-plume chemical reactions, whereas the almost-passive species SO2 is more sensitive to the injection time, which determines the duration of the subgrid-scale treatment. Future developments include an extension to handle aerosol chemistry, and an application to the modeling of line sources in order to use the subgrid treatment with road emissions. The latter is expected to lead to more striking results, due to the importance of traffic emissions for the pollutants of interest. (10.5194/acp-10-8917-2010)
  DOI : 10.5194/acp-10-8917-2010
• Modélisation inverse des sources de pollution atmosphérique accidentelle : progrès récents
  
  • Bocquet Marc
  Pollution Atmosphérique : climat, santé, société, APPA, 2010. Dans cette revue, nous discutons de progrès récents dans la modélisation inverse des sources de polluants atmosphériques, en particulier dʼorigine accidentelle, de lʼéchelle régionale à lʼéchelle continentale. Il sʼagit typiquement de caractériser et dʼestimer une source de pollution émanant dʼun site industriel au moyen dʼun modèle numérique de chimie-transport et de mesures de concentrations de ce polluant distribuées en espace et en temps. Le formalisme mathématique permettant dʼunifier ces informations est celui de lʼassimilation de données, qui offre un cadre bayésien. Nous montrons comment formuler mathématiquement un tel problème, puis comment le résoudre, notamment à lʼaide de techniques non-paramétriques. Parce que la chimie associée à un tel événement physique peut être souvent considérée linéaire à court terme, des méthodes mathématiques plus avancées peuvent être mises en œuvre avec des résultats mieux contraints. Au-delà de lʼestimation des sources, la caractérisation des incertitudes liées à ces estimations est ensuite discutée. Des exemples récents issus de la littérature sont donnés sur les cas dʼETEX, de lʼaccident de Tchernobyl, et de lʼincident dʼAlgésiras. Enfin, nous décrivons lʼimpact des résolutions spatiale et temporelle de lʼespace des paramètres sur la reconstruction de la source. Dans le contexte de la dispersion atmosphérique, lʼestimation de la source peut en dépendre significativement.
• Estimating apparent motion on satellite acquisitions with a physical dynamic model
  
  • Huot Etienne
  • Herlin Isabelle
  • Mercier Nicolas
  • Plotnikov Evgeny
  , 2010. The paper presents a motion estimation method based on data assimilation in a dynamic model, named Image Model, expressing the physical evolution of a quantity observed on the images. The application concerns the retrieval of apparent surface velocity from a sequence of satellite data, acquired over the ocean. The Image Model includes a shallow-water approximation for the dynamics of the velocity field (the evolution of the two components of motion are linked by the water layer thickness) and a transport equation for the image field. For retrieving the surface velocity, a sequence of Sea Surface Temperature (SST) acquisitions is assimilated in the Image Model with a 4D-Var method. This is based on the minimization of a cost function including the discrepancy between model outputs and SST data and a regularization term. Several types of regularization norms have been studied. Results are discussed to analyze the impact of the different components of the assimilation system. (10.1109/ICPR.2010.19)
  DOI : 10.1109/ICPR.2010.19
• Beyond Gaussian Statistical Modeling in Geophysical Data Assimilation
  
  • Bocquet Marc
  • Pires Carlos
  • Wu Lin
  Monthly Weather Review, American Meteorological Society, 2010, 138, pp.2997-3023. This review discusses recent advances in geophysical data assimilation beyond Gaussian statistical modeling, in the fields of meteorology, oceanography, as well as atmospheric chemistry. The non-Gaussian features are stressed rather than the nonlinearity of the dynamical models, although both aspects are entangled. Ideas recently proposed to deal with these non-Gaussian issues, in order to improve the state or parameter estimation, are emphasized. The general Bayesian solution to the estimation problem and the techniques to solve it are first presented, as well as the obstacles that hinder their use in high-dimensional and complex systems. Approximations to the Bayesian solution relying on Gaussian, or on second-order moment closure, have been wholly adopted in geophysical data assimilation (e.g., Kalman filters and quadratic variational solutions). Yet, nonlinear and non-Gaussian effects remain. They essentially originate in the nonlinear models and in the non-Gaussian priors. How these effects are handled within algorithms based on Gaussian assumptions is then described. Statistical tools that can diagnose them and measure deviations from Gaussianity are recalled. The following advanced techniques that seek to handle the estimation problem beyond Gaussianity are reviewed: maximum entropy filter, Gaussian anamorphosis, non-Gaussian priors, particle filter with an ensemble Kalman filter as a proposal distribution, maximum entropy on the mean, or strictly Bayesian inferences for large linear models, etc. Several ideas are illustrated with recent or original examples that possess some features of high-dimensional systems. Many of the new approaches are well understood only in special cases and have difficulties that remain to be circumvented. Some of the suggested approaches are quite promising, and sometimes already successful for moderately large though specific geophysical applications. Hints are given as to where progress might come from. (10.1175/2010MWR3164.1)
  DOI : 10.1175/2010MWR3164.1
• Monitoring land use changes around the indigenous lands of the Xingu basin in Mato Grosso, Brazil
  
  • Arvor Damien
  • Simões Penello Meirelles Margareth
  • Vargas Rafaela
  • Ladislau Araújo Skorupa
  • Cardoso Fidalgo Elaine Cristina
  • Dubreuil Vincent
  • Herlin Isabelle
  • Berroir Jean-Paul
  , 2010, pp.3190-3193. Indigenous lands represent an efficient way to protect indigenous communities and environment in Brazil. However, these lands are also highly affected y the land use changes occuring in its surroundings. We quantified the land use changes in the Xingu basin based on MODIS EVI data between 2000 and 2006. We estimated the deforested area inside and outside the indigenous lands, the crop expansion and intensification around the protected areas. Our results indicate that, even if indigenous lands are efficient to limit deforestation (97.5% of deforestation is outside the indigenous lands), crop expansion and intensification (double crop systems) are increasing rapidly, what may imply pollution of headwaters of the Xingu river which crosses the protected area. (10.1109/IGARSS.2010.5649659)
  DOI : 10.1109/IGARSS.2010.5649659
• Inverse problem for ill-posed linear differential-algebraic equations with variable coefficients
  
  • Zhuk Sergiy
  , 2010.
• Simulation of aerosols and gas-phase species over Europe with the POLYPHEMUS system. Part II: Model sensitivity analysis for 2011.
  
  • Roustan Yelva
  • Sartelet Karine
  • Tombette Maryline
  • Debry Edouard
  • Sportisse Bruno
  Atmospheric Environment, Elsevier, 2010, 44, pp.4219-4229. This paper presents a multi-pollutant sensitivity study of an air quality model over Europe with a focus on aerosols. Following the evaluation presented in the companion paper, the aim here is to study the sensitivity of the model to input data, mathematical parameterizations and numerical approximations. To that end, 30 configurations are derived from a reference configuration of the model by changing one input data set, one parameterization or one numerical approximation at a time. Each of these configu- rations is compared to the same reference simulation over two time periods of the year 2001, one in summer and one in winter. The sensitivity of the model to the different configurations is evaluated through a statistical comparison between the simulation results and through comparisons to available measurements. The species studied are ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), ammonia (NH3), coarse and fine aerosol particles (PMc and PM2.5), sulfate, nitrate, ammonium, chloride and sodium. For all species, the modeled concentrations are very sensitive to the parameterization used for vertical turbulent diffusion and to the number of vertical levels. For the other configurations considered in this work, the sensitivity of the modeled concentration to configuration choice varies with the species and the period of the year. O3 is impacted by options related to boundary conditions. PMc is sensitive to sea- salt related options, to options influencing deposition and to options related to mass transfer between gas and particulate phases. PM2.5 is sensitive to a larger number of options than PMc: sea-salt, boundary conditions, heterogeneous reactions, aqueous chemistry and gas/particle mass transfer. NO2 is strongly influenced by heterogeneous reactions. Nitrate shows the highest variability of all species studied. As with NO2, nitrate is strongly sensitive to heterogeneous reactions but also to mass transfer, thermody- namic related options, aqueous chemistry and computation of the wet particle diameter. While SO2 is mostly sensitive to aqueous chemistry, sulfate is also sensitive to boundary conditions and, to a lesser extent, to heterogeneous reactions. As with nitrate, ammonium is largely impacted by the different configuration choices, although the sensitivity is slightly lower than for nitrate. NH3 is sensitive to aqueous chemistry, mass transfer and heterogeneous reactions. Chloride and sodium are impacted by sea-salt related options, by options influencing deposition and by options concerning the aqueous-phase module.
• Model reduction via principal component truncation for the optimal design of atmospheric monitoring networks
  
  • Saunier Olivier
  • Bocquet Marc
  • Mathieu Anne
  • Abida Rachid
  , 2010, pp.906-910. IRSN is planning to renovate the French nuclear monitoring network. This renovated network should be able to forecast accurately the accidental plume by using only measures of this network. In this presentation, a numerically efficient methodology for the optimal design of monitoring networks is proposed. In this method, a large database of dispersion accidents over one year of meteorology and from 20 French nuclear sites is built and a cost function measures the ability of a potential network to provide measurements in order to reconstruct any accidental plume from the database. We introduce methods based on principal component analysis to optimally reduce this database and consequently decrease significantly CPU time. Then, the reduced optimisation method is applied to suggest an optimal strategy for the sequential deployment of the network. Finally, we propose the set-up of networks which take into account foreign potential radiological sources in Europe and French density population.
• Development and application of a reactive plume-in-grid model: evaluation over Greater Paris
  
  • Korsakissok Irène
  • Mallet Vivien
  , 2010. Classical air quality models at regional scale, based on Eulerian gridded approaches, suffer from several limitations when applied to the dispersion of elevated point emissions (e.g. from power plant stacks). In particular, emissions from point sources are assumed to mix immediately within a grid cell, whereas a typical point-source plume does not expand to the size of the grid cell for a substantial time period. In addition, the incorrect representation of concentrations within the plume leads to a poor estimation of the chemical reaction rates, in the case of reactive plumes. The plume-in-grid method is a multiscale modeling technique that couples a Gaussian puff model with an Eulerian model in order to better represent these emissions. We present the reactive plume-in-grid model developed in the air quality modeling system Polyphemus, and its evaluation for photochemical applications. The chosen application domain is the Ile-de-France region, during six months (summer 2001). There were 89 major point sources selected for the subgrid-scale treatment. Comparisons are made between the results with the Eulerian model alone, and with the plume-in-grid treatment. The analysis is based both on global results for the whole period, and on a few selected days of interest. A sensitivity study is also carried out, especially to point out the influence of the local-scale parameterizations.
• Towards the operational application of inverse modelling for the source identification and plume forecast of an accidental release of radionuclides
  
  • Winiarek Victor
  • Vira J.
  • Bocquet Marc
  • Sofiev Mikhail
  • Saunier Olivier
  , 2010, pp.921--923. In the event of an accidental atmospheric release of radionuclides from a nuclear power plant, accurate real-time forecasting of the activity concentrations of radionuclides is required by the decision makers for the preparation of adequate countermeasures. Yet, the accuracy of the forecast plume is highly dependent on the source term estimation. Inverse modelling and data assimilation techniques should help in that respect. In this presentation, a semi-automatic method is proposed for the sequential reconstruction of the plume, by implementing a sequential data assimilation algorithm based on inverse modelling, with a care to develop realistic methods for operational risk agencies. The performance of the assimilation scheme has been assessed through the intercomparison between French and Finnish frameworks. Three dispersion models have been used: Polair3D, with or without plume-in-grid, both developed at CEREA, and SILAM, developed at FMI. Different release locations, as well as different meteorological situations are tested. The existing and newly planned surveillance networks are used and realistically large observational errors are assumed. Statistical indicators to evaluate the efficiency of the method are presented and the results are discussed. In addition, in the case where the power plant responsible for the accidental release is not known, robust statistical tools aredeveloped and tested to discriminate candidate release sites.
• A new line source model for air quality impacts of roadway traffic
  
  • Briant Régis
  • Korsakissok Irène
  • Seigneur Christian
  , 2010, pp....................
• Inverse problems for linear ill-posed differential-algebraic equations with uncertain parameters
  
  • Zhuk Sergiy
  , 2010.
• Uncertainty characterization and quantification in air pollution models Application to the CHIMERE model
  
  • Debry Edouard
  • Mallet Vivien
  • Garaud Damien
  • Malherbe Laure
  • Bessagnet Bertrand
  • Rouil Laurence
  , 2010. Prev'Air is the French operational system for air pollution forecasting. It is developed and maintained by INERIS with financial support from the French Ministry for Environment. On a daily basis it delivers forecasts up to three days ahead for ozone, nitrogene dioxide and particles over France and Europe. Maps of concentration peaks and daily averages are freely available to the general public. More accurate data can be provided to customers and modelers. Prev'Air forecasts are based on the Chemical Transport Model CHIMERE. French authorities rely more and more on this platform to alert the general public in case of high pollution events and to assess the efficiency of regulation measures when such events occur. For example the road speed limit may be reduced in given areas when the ozone level exceeds one regulatory threshold. These operational applications require INERIS to assess the quality of its forecasts and to sensitize end users about the confidence level. Indeed concentrations always remain an approximation of the true concentrations because of the high uncertainty on input data, such as meteorological fields and emissions, because of incomplete or inaccurate representation of physical processes, and because of efficiencies in numerical integration [1]. We would like to present in this communication the uncertainty analysis of the CHIMERE model led in the framework of an INERIS research project aiming, on the one hand, to assess the uncertainty of several deterministic models and, on the other hand, to propose relevant indicators describing air quality forecast and their uncertainty. There exist several methods to assess the uncertainty of one model. Under given assumptions the model may be differentiated into an adjoint model which directly provides the concentrations sensitivity to given parameters. But so far Monte Carlo methods seem to be the most widely and oftenly used [2,3] as they are relatively easy to implement. In this framework one probability density function (PDF) is associated with an input parameter, according to its assumed uncertainty. Then the combined PDFs are propagated into the model, by means of several simulations with randomly perturbed input parameters. One may then obtain an approximation of the PDF of modeled concentrations, provided the Monte Carlo process has reasonably converged. The uncertainty analysis with CHIMERE has been led with a Monte Carlo method on the French domain and on two periods : 13 days during January 2009, with a focus on particles, and 28 days during August 2009, with a focus on ozone. The results show that for the summer period and 500 simulations, the time and space averaged standard deviation for ozone is 16 µg/m3, to be compared with an averaged concentration of 89 µg/m3. It is noteworthy that the space averaged standard deviation for ozone is relatively constant over time (the standard deviation of the timeseries itself is 1.6 µg/m3). The space variation of the ozone standard deviation seems to indicate that emissions have a significant impact, followed by western boundary conditions. Monte Carlo simulations are then post-processed by both ensemble [4] and Bayesian [5] methods in order to assess the quality of the uncertainty estimation. (1) Rao, K.S. Uncertainty Analysis in Atmospheric Dispersion Modeling, Pure and Applied Geophysics, 2005, 162, 1893-1917. (2) Beekmann, M. and Derognat, C. Monte Carlo uncertainty analysis of a regional-scale transport chemistry model constrained by measurements from the Atmospheric Pollution Over the Paris Area (ESQUIF) campaign, Journal of Geophysical Research, 2003, 108, 8559-8576. (3) Hanna, S.R. and Lu, Z. and Frey, H.C. and Wheeler, N. and Vukovich, J. and Arunachalam, S. and Fernau, M. and Hansen, D.A. Uncertainties in predicted ozone concentrations due to input uncertainties for the UAM-V photochemical grid model applied to the July 1995 OTAG domain, Atmospheric Environment, 2001, 35, 891-903. (4) Mallet, V., and B. Sportisse (2006), Uncertainty in a chemistry-transport model due to physical parameterizations and numerical approximations: An ensemble approach applied to ozone modeling, J. Geophys. Res., 111, D01302, doi:10.1029/2005JD006149. (5) Romanowicz, R. and Higson, H. and Teasdale, I. Bayesian uncertainty estimation methodology applied to air pollution modelling, Environmetrics, 2000, 11, 351-371.
• Construction optimale de réseaux fixes et mobiles pour la surveillance opérationnelle des rejets accidentels atmosphériques
  
  • Abida Rachid
  , 2010. Mon travail de thèse se situe dans le contexte général de l'optimisation de réseaux de mesure de pollution atmosphérique, mais plus spécifiquement centré sur la surveillance des rejets accidentels de radionucléides dans l'air. Le problème d'optimisation de réseaux de mesure de la qualité de l'air a été abordé dans la littérature. En revanche, il n'a pas été traité dans le contexte de la surveillance des rejets accidentels atmosphériques. Au cours de cette thèse nous nous sommes intéressés dans un premier temps à l'optimisation du futur réseau de télésurveillance des aérosols radioactifs dans l'air, le réseau DESCARTES. Ce réseau sera mis en œuvre par l'Institut de Radioprotection et de Sûreté Nucléaire (IRSN), afin de renforcer son dispositif de surveillance de radionucléides en France métropolitaine. Plus précisément, l'objectif assigné à ce réseau est de pouvoir mesurer des rejets atmosphériques de radionucléides, provenant de l'ensemble des installations nucléaires françaises ou étrangères. Notre principal rôle était donc de formuler des recommandations vis-à-vis aux besoins exprimés par l'IRSN, concernant la construction optimale du futur réseau. Á cette fin, l'approche que nous avons considérée pour optimiser le réseau (le futur réseau), vise à maximiser sa capacité à extrapoler les concentrations d'activité mesurées sur les stations du réseau sur tout le domaine d'intérêt. Cette capacité est évaluée quantitativement à travers une fonction de coût, qui mesure les écarts entre les champs de concentrations extrapolés et ceux de références. Ces derniers représentent des scénarios de dispersion accidentels provenant des 20 centrales nucléaires françaises et, calculés sur une année de météorologie. Nos résultats soulignent notamment l'importance du choix de la fonction coût dans la conception optimale du futur réseau de surveillance. Autrement dit, la configuration spatiale du réseau optimal s'avère extrêmement sensible à la forme de la fonction coût utilisée. La deuxième partie de mon travail s'intéresse essentiellement au problème du ciblage d'observations en cas d'un rejet accidentel de radionucléides, provenant d'une centrale nucléaire. En effet, en situation d'urgence, une prévision très précise en temps réel de la dispersion du panache radioactif est vivement exigée par les décideurs afin d'entreprendre des contre-mesures plus appropriées. Cependant, la précision de la prévision du panache est très dépendante de l'estimation du terme source de l'accident. À cet égard, les techniques d'assimilation de données et de modélisation inverse peuvent être appliquées. Toutefois, le nuage radioactif peut être localement très mince et pourrait s'échapper à une partie importante du réseau local, installé autour de la centrale nucléaire. Ainsi, un déploiement de stations de mesure mobiles en suivant l'évolution du nuage pourrait contribuer à améliorer l'estimation du terme source. À cet effet, nous avons exploré la possibilité d'améliorer la qualité de la prévision numérique du panache radioactif, en couplant une stratégie de déploiement optimal de stations mobiles avec un schéma d'assimilation de données pour la reconstruction séquentielle du panache radioactif. Nos résultats montrent que le gain d'information apporté par les observations ciblées est nettement mieux que l'information apportée par les observations fixes.
• Subgrid-scale treatment for major point sources in an Eulerian model: A sensitivity study on the European Tracer Experiment (ETEX) and Chernobyl cases
  
  • Korsakissok Irène
  • Mallet Vivien
  Journal of Geophysical Research, American Geophysical Union, 2010, 115 (D03303). We investigate the plume-in-grid method for a subgrid-scale treatment of major point sources in the passive case. This method consists in an on-line coupling of a Gaussian pu model and an Eulerian model, which better represents the point emissions without signicantly increasing the computational burden. In this paper, the plume-in-grid model implemented on the Polyphemus air quality modeling system is described, with an emphasis on the parameterizations available for the Gaussian dispersion, and on the coupling with the Eulerian model. The study evaluates the model for passive tracers at continental scale with the ETEX experiment and the Chernobyl case. The aim is to (1) estimate the model sensitivity to the local-scale parameterizations, and (2) to bring insights on the spatial and temporal scales that are relevant in the use of a plume-in-grid model. It is found that the plume-in-grid treatment improves the vertical diusion at local-scale, thus reducing the bias -- especially at the closest stations. Doury's Gaussian parameterization and a column injection method give the best results. There is a strong sensitivity of the results to the injection time and the grid resolution. The "best" injection time actually depends on the resolution, but is difficult to determine a priori. The plume-in-grid method is also found to improve the results at ne resolutions more than with coarse grids, by compensating the Eulerian tendency to over-predict the concentrations at these resolutions. (10.1029/2009JD012734)
  DOI : 10.1029/2009JD012734
• Subgrid-scale treatment for major point sources in an Eulerian model: A sensitivity study on the European Tracer Experiment (ETEX) and Chernobyl cases
  
  • Korsakissok Irène
  • Mallet Vivien
  Journal of Geophysical Research, American Geophysical Union, 2010, 115 (D03303). We investigate the plume-in-grid method for a subgrid-scale treatment of major point sources in the passive case. This method consists in an on-line coupling of a Gaussian pu model and an Eulerian model, which better represents the point emissions without signicantly increasing the computational burden. In this paper, the plume-in-grid model implemented on the Polyphemus air quality modeling system is described, with an emphasis on the parameterizations available for the Gaussian dispersion, and on the coupling with the Eulerian model. The study evaluates the model for passive tracers at continental scale with the ETEX experiment and the Chernobyl case. The aim is to (1) estimate the model sensitivity to the local-scale parameterizations, and (2) to bring insights on the spatial and temporal scales that are relevant in the use of a plume-in-grid model. It is found that the plume-in-grid treatment improves the vertical diusion at local-scale, thus reducing the bias -- especially at the closest stations. Doury's Gaussian parameterization and a column injection method give the best results. There is a strong sensitivity of the results to the injection time and the grid resolution. The "best" injection time actually depends on the resolution, but is difficult to determine a priori. The plume-in-grid method is also found to improve the results at ne resolutions more than with coarse grids, by compensating the Eulerian tendency to over-predict the concentrations at these resolutions. (10.1029/2009JD012734)
  DOI : 10.1029/2009JD012734
• Calibration d'ensemble pour l'estimation de l'incertitude en qualité de l'air
  
  • Garaud Damien
  • Mallet Vivien
  , 2010.