Publications

2013

• A new air quality modelling approach at the regional scale using lidar data assimilation
  
  • Wang Yiguo Y.
  , 2013. Assimilation of lidar observations for air quality modelling is investigated via the development of a new model, which assimilates ground-based lidar network measurements using optimal interpolation (OI) in a chemistry transport model. First, a tool for assimilating PM10 (particulate matter with a diameter lower than 10 um) concentration measurements on the vertical is developed in the air quality modelling platform POLYPHEMUS. It is applied to western Europe for one month from 15 July to 15 August 2001 to investigate the potential impact of future ground-based lidar networks on analysis and short-term forecasts (the description of the future) of PM10. The efficiency of assimilating lidar network measurements is compared to the efficiency of assimilating concentration measurements from the AirBase ground network, which includes about 500 stations in western Europe. A sensitivity study on the number and location of required lidars is also performed to help define an optimal lidar network for PM10 forecasts. Secondly, a new model for simulating normalised lidar signals (PR2) is developed and integrated in POLYPHEMUS. Simulated lidar signals are compared to hourly ground-based mobile and in-situ lidar observations performed during the MEGAPOLI (Megacities : Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation) summer experiment in July 2009. It is found that the model correctly reproduces the vertical distribution of aerosol optical properties and their temporal variability. Additionally, two new algorithms for assimilating lidar signals are presented and evaluated during MEGAPOLI. The aerosol simulations without and with lidar data assimilation are evaluated using the AIRPARIF (a regional operational network in charge of air quality survey around the Paris area) database to demonstrate the feasibility and the usefulness of assimilating lidar profiles for aerosol forecasts. Finally, POLYPHEMUS with the model for assimilating lidar signals is applied to the Mediterranean basin, where 9 ground-based lidar stations from the ACTRIS/EARLINET network and 1 lidar station in Corsica performed a 72-hour period of intensive and continuous measurements in July 2012. Several parameters of the assimilation system are also studied to better estimate the spatial and temporal influence of the assimilation of lidar signals on aerosol forecasts.
• Influence de l'évolution climatique sur la qualité de l'air en Europe
  
  • Lecoeur Eve
  , 2013. La pollution atmosphérique est le produit de fortes émissions de polluants (et de leurs précurseurs) et de conditions météorologiques défavorables. Les particules fines (PM2.5) sont l'un des polluants les plus dangereux pour la santé publique. L'exposition répétée ou prolongée à ces particules entraîne chaque année des maladies respiratoires et cardio-vasculaires chez les personnes exposées ainsi que des morts prématurées. L'évolution du climat dans les années à venir aura un impact sur des variables météorologiques (température, vents, précipitations, ...). Ces variables influencent à leur tour divers facteurs, qui affectent la qualité de l'air (émissions, lessivage par les précipitations, équilibre gaz/particule, ...). Si de nombreuses études ont déjà projeté l'effet du changement climatique sur les concentrations d'ozone, peu se sont intéressées à son effet sur les concentrations de particules fines, en particulier à l'échelle du continent européen. C'est ce que cette thèse se propose d'étudier. La circulation atmosphérique de grande échelle est étroitement liée aux variables météorologiques de surface. Par conséquent, il est attendu qu'elle ait également un impact sur les concentrations de PM2.5. Nous utilisons dans cette thèse une approche statistique pour estimer les concentrations futures de PM2.5 à partir d'observations présentes de PM2.5, de quelques variables météorologiques pertinentes et d'outils permettant de représenter cette circulation atmosphérique (régimes et types de temps). Le faible nombre d'observations journalières de PM2.5 et de ses composants en Europe nous a conduit à créer un jeu de données pseudo-observées à l'aide du modèle de qualité de l'air Polyphemus/Polair3D, puis à l'évaluer de façons opérationnelle et dynamique, afin de s'assurer que l'influence des variables météorologiques sur les concentrations de PM2.5 est reproduite de manière satisfaisante par le modèle. Cette évaluation dynamique d'un modèle de qualité de l'air est, à notre connaissance, la première menée à ce jour.Les projections de PM2.5 sur les périodes futures montrent une augmentation systématique des concentrations de PM2.5 au Royaume-Uni, dans le nord de la France, au Benelux et dans les Balkans, et une diminution dans le nord, l'est et le sud-est de l'Europe, en Italie et en Pologne. L'évolution de la fréquence des types de temps ne suffit pas toujours à expliquer l'évolution de ces concentrations entre les périodes historique et futures, car les relations entre circulation atmosphérique de grande échelle et types de temps, entre types de temps et variables météorologiques, et entre variables météorologiques et concentrations de PM2.5 sont amenées à évoluer dans le futur et contribuent à l'évolution des concentrations de PM2.5. L'approche statistique développée dans cette thèse est nouvelle pour l'estimation de l'impact du climat et du changement climatique sur les concentrations de PM2.5 en Europe. Malgré les incertitudes qui y sont associées, cette approche est facilement adaptable à différents modèles et scénarios, ainsi qu'à d'autres régions du monde et d'autres polluants. En utilisant des observations pour définir la relation polluant-météorologie, cette approche serait d'autant plus robuste (10.70675/cf49af7dz225dz4977z8f35z483b9a5f7962)
  DOI : 10.70675/cf49af7dz225dz4977z8f35z483b9a5f7962
• Votre air, votre santé
  
  • Herlin Isabelle
  • Mallet Vivien
  , 2013. No abstract.
• Optimal Orthogonal Basis and Image Assimilation: Motion Modeling
  
  • Huot Etienne
  • Herlin Isabelle
  • Papari Giuseppe
  , 2013. This paper describes modeling and numerical computation of orthogonal bases, which are used to describe images and motion fields. Motion estimation from image data is then studied on subspaces spanned by these bases. A reduced model is obtained as the Galerkin projection on these subspaces of a physical model, based on Euler and optical flow equations. A data assimilation method is studied, which assimilates coefficients of image data in the reduced model in order to estimate motion coefficients. The approach is first quantified on synthetic data: it demonstrates the interest of model reduction as a compromise between results quality and computational cost. Results obtained on real data are then displayed so as to illustrate the method.
• An inverse modeling method to assess the source term of the Fukushima Nuclear Power Plant accident using gamma dose rate observations
  
  • Saunier Olivier
  • Mathieu Anne
  • Didier Damien
  • Tombette Marilyne
  • Quélo Denis
  • Winiarek Victor
  • Bocquet Marc
  Atmospheric Chemistry and Physics, European Geosciences Union, 2013, 13 (22), pp.11403-11421. The Chernobyl nuclear accident, and more recently the Fukushima accident, highlighted that the largest source of error on consequences assessment is the source term, including the time evolution of the release rate and its distribution between radioisotopes. Inverse modeling methods, which combine environmental measurements and atmospheric dispersion models, have proven efficient in assessing source term due to an accidental situation (Gudiksen, 1989; Krysta and Bocquet, 2007; Stohl et al., 2012a; Winiarek et al., 2012). Most existing approaches are designed to use air sampling measurements (Winiarek et al., 2012) and some of them also use deposition measurements (Stohl et al., 2012a; Winiarek et al., 2014). Some studies have been performed to use dose rate measurements (Duranova et al., 1999; Astrup et al., 2004; Drews et al., 2004; Tsiouri et al., 2012) but none of the developed methods were carried out to assess the complex source term of a real accident situation like the Fukushima accident. However, dose rate measurements are generated by the most widespread measurement system, and in the event of a nuclear accident, these data constitute the main source of measurements of the plume and radioactive fallout during releases. This paper proposes a method to use dose rate measurements as part of an inverse modeling approach to assess source terms. The method is proven efficient and reliable when applied to the accident at the Fukushima Daiichi Nuclear Power Plant (FD-NPP). The emissions for the eight main isotopes 133Xe, 134Cs, 136Cs, 137Cs, 137mBa, 131I, 132I and 132Te have been assessed. Accordingly, 105.9 PBq of 131I, 35.8 PBq of 132I, 15.5 PBq of 137Cs and 12 134 PBq of noble gases were released. The events at FD-NPP (such as venting, explosions, etc.) known to have caused atmospheric releases are well identified in the retrieved source term. The estimated source term is validated by comparing simulations of atmospheric dispersion and deposition with environmental observations. In total, it was found that for 80% of the measurements, simulated and observed dose rates agreed within a factor of 2. Changes in dose rates over time have been overall properly reconstructed, especially in the most contaminated areas to the northwest and south of the FD-NPP. A comparison with observed atmospheric activity concentration and surface deposition shows that the emissions of caesiums and 131I are realistic but that 132I and 132Te are probably underestimated and noble gases are likely overestimated. Finally, an important outcome of this study is that the method proved to be perfectly suited to emergency management and could contribute to improve emergency response in the event of a nuclear accident. (10.5194/acp-13-11403-2013)
  DOI : 10.5194/acp-13-11403-2013
• Hyperparameter estimation for uncertainty quantification in mesoscale carbon dioxide inversions
  
  • Wu Lin
  • Bocquet Marc
  • Chevallier Frédéric
  • Lauvaux Thomas
  • Davis Kenneth
  Tellus B - Chemical and Physical Meteorology, Taylor & Francis, 2013, 65. Uncertainty quantification is critical in the inversion of CO2 surface fluxes from atmospheric concentration measurements. Here, we estimate the main hyperparameters of the error covariance matrices for a priori fluxes and CO2 concentrations, that is, the variances and the correlation lengths, using real, continuous hourly CO2 concentration data in the context of the Ring 2 experiment of the North American Carbon Program Mid Continent Intensive. Several criteria, namely maximum likelihood (ML), general cross-validation (GCV) and x2 test are compared for the first time under a realistic setting in a mesoscale CO2 inversion. It is shown that the optimal hyperparameters under the ML criterion assure perfect x2 consistency of the inverted fluxes. Inversions using the ML error variances estimates rather than the prescribed default values are less weighted by the observations, because the default values underestimate the model-data mismatch error, which is assumed to be dominated by the atmospheric transport error. As for the spatial correlation length in prior flux errors, the Ring 2 network is sparse for GCV, and this method fails to reach an optimum. In contrast, the ML estimate (e.g. an optimum of 20 km for the first week of June 2007) does not support long spatial correlations that are usually assumed in the default values. (10.3402/tellusb.v65i0.20894)
  DOI : 10.3402/tellusb.v65i0.20894
• Minimax filtering for sequential aggregation: Application to ensemble forecast of ozone analyses
  
  • Mallet Vivien
  • Nakonechny Alexander
  • Zhuk Sergiy
  Journal of Geophysical Research, American Geophysical Union, 2013, 118 (19), pp.11,294-11,303. This paper presents a new algorithm for sequential aggregation of an ensemble of forecasts. At any forecasting step, the aggregation consists of (1) computing new weights for the ensemble members represented by different numerical models and (2) forecasting with a weighted linear combination of the ensemble members. We assume that the time evolution of the weights is described by a linear equation with uncertain parameters and apply a minimax filter (and also Kalman filter, for comparison) in order to estimate the vector of weights given "observations". The "observation" equation for the filter compares the aggregated forecast with the analysis determined in a data assimilation cycle together with its variance. The minimax approach allows one to work with flexible uncertainty description: deterministic bounding sets for uncertain parameters in weight's equation, and error covariance matrices for the "observational" errors. Our key contribution is an uncertainty estimate of the aggregated forecast, for which we introduce an evaluation test. The performance of the method is assessed for the forecast of ground-level ozone daily peaks over Europe, for the year 2001. Compared to forecasts generated by classical data assimilation, the root mean square error is decreased by 16% for prediction of the analyses and by 20% for prediction of the observations. (10.1002/jgrd.50751)
  DOI : 10.1002/jgrd.50751
• An iterative ensemble Kalman smoother
  
  • Bocquet Marc
  • Sakov Pavel
  , 2013. No abstract.
• La qualité de l'air sous surveillance
  
  • Herlin Isabelle
  • Mallet Vivien
  Textes et documents pour la classe, SCEREN-CNDP (2002-2013), CANOPE (2014- ), INRDP (1967- ), 2013 (1062), pp.40-41. Etudier la qualité de l'air et son impact sanitaire est un sujet scientifique majeur dans la perspective du développement durable. Cela nécessite une estimation des sources de pollution, une modélisation des phénomènes physiques et chimiques en jeu et une étude épidémiologique des conséquences sur la santé, ce qui fait intervenir différents domaines de recherche.
• Joint state and parameter estimation with an iterative ensemble Kalman smoother
  
  • Bocquet Marc
  • Sakov Pavel
  Nonlinear Processes in Geophysics, European Geosciences Union (EGU), 2013, 20 (5), pp.803-818. Both ensemble filtering and variational data assimilation methods have proven useful in the joint estimation of state variables and parameters of geophysical models. Yet, their respective benefits and drawbacks in this task are distinct. An ensemble variational method, known as the iterative ensemble Kalman smoother (IEnKS) has recently been introduced. It is based on an adjoint model-free variational, but flow-dependent, scheme. As such, the IEnKS is a candidate tool for joint state and parameter estimation that may inherit the benefits from both the ensemble filtering and variational approaches. In this study, an augmented state IEnKS is tested on its estimation of the forcing parameter of the Lorenz-95 model. Since joint state and parameter estimation is especially useful in applications where the forcings are uncertain but nevertheless determining, typically in atmospheric chemistry, the augmented state IEnKS is tested on a new low-order model that takes its meteorological part from the Lorenz-95 model, and its chemical part from the advection diffusion of a tracer. In these experiments, the IEnKS is compared to the ensemble Kalman filter, the ensemble Kalman smoother, and a 4D-Var, which are considered the methods of choice to solve these joint estimation problems. In this low-order model context, the IEnKS is shown to significantly outperform the other methods regardless of the length of the data assimilation win- dow, and for present time analysis as well as retrospective analysis. Besides which, the performance of the IEnKS is even more striking on parameter estimation; getting close to the same performance with 4D-Var is likely to require both a long data assimilation window and a complex modeling of the background statistics. (10.5194/npg-20-803-2013)
  DOI : 10.5194/npg-20-803-2013
• Surface Circulation from Satellite Images: Reduced Model of the Black Sea
  
  • Huot Etienne
  • Herlin Isabelle
  • Papari Giuseppe
  • Drifi Karim
  , 2013. Estimating surface circulation from satellite images is a hot subject for a large range of applications. Motion estimation from image data has been studied for long in the literature of Image Processing, and more recently in that of Data Assimilation (DA). This paper describes how the construction of dedicated spaces for projecting motion and image fields allows applying DA methods with a reduced model and eases the estimation of surface circulation on the whole Black Sea basin.
• Object's tracking by advection of a distance map
  
  • Lepoittevin Yann
  • Herlin Isabelle
  • Béréziat Dominique
  , 2013, pp.3612-3616. This paper has two coupled objectives: estimating motion and tracking a given object on an image sequence. It relies on a data assimilation approach, that solves evolution equations of motion, those of image brightness, and those of the distance map modeling the object's boundary. The two last express the optical flow constraint, which assumes that image brightness and distance map are advected by velocity. The method assimilates contour points by an innovative approach combining two criteria. First, the boundary of the object should match contour points at acquisition dates; second, the control of the distance between each pixel and the object's boundary allows to better motion estimation on the whole domain. The method is tested on synthetic data and satellite acquisitions. (10.1109/ICIP.2013.6738745)
  DOI : 10.1109/ICIP.2013.6738745
• Online integrated meteorology-chemistry models: needs and benefits for numerical weather prediction, air quality and climate communities (European experience)
  
  • Baklanov A.
  • Heinke K.
  • Suppan P.
  • Baldasano Jm.
  • Brunner D.
  • Gauss M.
  • Moussiopoulos N.
  • Maurizi N.
  • Seigneur C.
  • Kong X.
  • Jorba O.
  • Joffre S.
  , 2013, pp.5952. No abstract available
• Estimation du mouvement par assimilation de données dans des modèles dynamiques d'ordre réduit
  
  • Drifi Karim
  , 2013. L'estimation du mouvement est un sujet fondamental pour l'interprétation de séquences d'images. Cette thèse concerne l'étude de la dynamique des écoulements géophysiques visualisée par l'imagerie satellitaire. Une bonne compréhension de ces écoulements géophysiques permet l'analyse et la prévision des phénomènes, par exemple en océanographie et en météorologie. L'assimilation de données constitue le cadre idéal pour prendre en compte de manière optimale les diverses sources d'informations disponibles et en particulier les modèles numériques et les données. On se propose donc, dans cette thèse, d'appliquer des méthodes d'assimilation variationnelles de données, dites4D-Var, pour estimer le mouvement sur les séquences d'images. Une des limitations des techniques 4D-Var est l'importance du temps de calcul et de la mémoire nécessaire lors de leur application. Nous nous proposons, dans ce document, de définir une méthodologie basée sur la réduction de modèle afin de réduire ces limitations de façon significative. Nous étudions les possibilités qu'offre la réduction d'un modèle dynamique pour estimer le mouvement, en particulier afin d'imposer des contraintes issues de la physique aux solutions calculées. Différentes réductions sont discutées, au moyen d'une décomposition orthogonale propre, sur une base sinus pour un mouvement à divergence nulle, ou sur une base dédiée au domaine spatial étudié. Dans chaque cas, les résultats d'expériences synthétiques et sur des données satellite sont présentés
• Compact modeling solutions for OxRAM memories
  
  • Bocquet Marc
  • Deleruyelle Damien
  • Aziza Hassen
  • Muller Christophe
  • Portal Jean-Michel
  , 2013, pp.1-4. Emerging non-volatile memories based on resistive switching mechanisms pull intense R&D efforts from both academia and industry. Oxide-based Resistive Random Acces Memories (namely OxRAM) gather noteworthy performances, such as fast write/read speed, low power and high endurance outperforming therefore conventional Flash memories. To fully explore new design concepts such as distributed memory in logic, OxRAM compact models have to be developed and implemented into electrical simulators to assess performances at a circuit level. In this paper, we present an compact models of the bipolar OxRAM memory based on physical phenomenons. This model was implemented in electrical simulators for single device up to circuit level. (10.1109/FTFC.2013.6577779)
  DOI : 10.1109/FTFC.2013.6577779
• Modélisation d'écoulements atmosphériques stratifiés par Large-Eddy Simulation à l'aide de Code_Saturne
  
  • Dall'Ozzo Cédric
  , 2013. La modélisation par simulation des grandes échelles (Large-Eddy Simulation - LES) des processus physiques régissant la couche limite atmosphérique (CLA) demeure complexe de part la difficulté des modèles à capter l'évolution de la turbulence entre différentes conditions de stratification. De ce fait, l'étude LES du cycle diurne complet de la CLA comprenant des situations convectives la journée et des conditions stables la nuit est très peu documenté. La simulation de la couche limite stable où la turbulence est faible, intermittente et qui est caractérisée par des structures turbulentes de petite taille est tout particulièrement compliquée. En conséquence, la capacité de la LES à bien reproduire les conditions météorologiques de la CLA, notamment en situation stable, est étudiée à l'aide du code de mécanique des fluides développé par EDF R&D, Code_Saturne. Dans une première étude, le modèle LES est validé sur un cas de couche limite convective quasi stationnaire sur terrain homogène. L'influence des modèles sous-maille de Smagorinsky, Germano-Lilly, Wong-Lilly et WALE (Wall-Adapting Local Eddy-viscosity) ainsi que la sensibilité aux méthodes de paramétrisation sur les champs moyens, les flux et les variances est discutées. Dans une seconde étude le cycle diurne complet de la CLA pendant la campagne de mesure Wangara est modélisé. L'écart aux mesures étant faible le jour, ce travail se concentre sur les difficultés rencontrées la nuit à bien modéliser la couche limite stable. L'impact de différents modèles sous-maille ainsi que la sensibilité au coefficient de Smagorinsky ont été analysés. Par l'intermédiaire d'un couplage radiatif réalisé en LES, les répercussions du rayonnement infrarouge et solaire sur le jet de basse couche nocturne et le gradient thermique près de la surface sont exposées. De plus l'adaptation de la résolution du domaine à l'intensité de la turbulence et la forte stabilité atmosphérique durant l'expérience Wangara sont commentées. Enfin un examen des oscillations numériques inhérentes à Code_Saturne est réalisé afin d'en limiter les effets (10.70675/380c7599z1e3fz4733z9143zd7869cbfd4e6)
  DOI : 10.70675/380c7599z1e3fz4733z9143zd7869cbfd4e6
• Assimilation de données pour estimer le mouvement et suivre un objet
  
  • Lepoittevin Yann
  • Herlin Isabelle
  • Béréziat Dominique
  , 2013. Cet article s'intéresse au problème de l'estimation du mouvement apparent sur une séquence d'images et au suivi d'un objet particulier. Pour ce faire, l'approche considérée est celle de l'assimilation de données, et, dans ce cas, de l'assimilation d'images. Cette approche repose sur les équations de la dynamique du système visualisé par la séquence d'images. Le modèle de dynamique considéré est la conservation lagrangienne de la vitesse et le transport des images et de la carte de distance qui modélise l'objet étudié. La méthode d'assimilation de données choisie, appelée 4D-Var, effectue une optimisation itérative d'une fonction de coût. Cette approche d'assimilation d'images est tout d'abord quantifiée au moyen d'une expérience jumelle, afin de démontrer l'amélioration obtenue sur l'estimation du mouvement. Puis la méthode est appliquée à une séquence d'images satellite météorologiques, avec l'objectif de suivre un nuage tropical. Les visualisations proposées illustrent les différentes composantes de la méthode.
• Reduction and emulation of ADMS Urban
  
  • Mallet Vivien
  • Tilloy Anne
  • Poulet David
  • Brocheton Fabien
  , 2013. ADMS Urban is a non-linear static model whose input data $p$ varies one simulated hour after the other. The model computes a high-dimensional concentration vector $y= ℳ(p)$ which can contain 10⁵ concentrations. A full-year simulation of $NO_2$ concentrations can take dozens of days of computations, which greatly limits the range of methods that can be applied to the model, especially for uncertainty quantification. This work proposes a method to replace ADMS Urban with a so-called emulator, i.e., a close approximation of ADMS Urban whose computational cost is negligible. First, the output concentration field $y$ is projected on a few modes of a proper orthogonal decomposition $[Ψ_1 ... Ψ_N]$, so that $y \simeq ∑^N_{j=1} \alpha_j Ψ_j$ where $\apha_j$ is the projection coefficient on $j$-th mode and $N$ smaller than 10. Then, the reduced model $f(p) = Ψ^T ℳ(p)$ is replaced by a statistical emulator $\hat{f}$ so that $\hat{f}(p) \simeq f(p)$ and the computational cost of $\hat{f}(p)$ is negligible.
• Estimation of volatile organic compound emissions for Europe using data assimilation
  
  • Koohkan Mohammad Reza
  • Bocquet Marc
  • Roustan Yelva
  • Kim Yongseob
  • Seigneur Christian
  Atmospheric Chemistry and Physics, European Geosciences Union, 2013, 13 (12), pp.5887-5905. The emissions of non-methane volatile organic compounds (VOCs) over western Europe for the year 2005 are estimated via inverse modelling by assimilation of in situ observations of concentration and then subsequently compared to a standard emission inventory. The study focuses on 15 VOC species: five aromatics, six alkanes, two alkenes, one alkyne and one biogenic diene. The inversion relies on a validated fast adjoint of the chemical transport model used to simulate the fate and transport of these VOCs. The assimilated ground-based measurements over Europe are provided by the European Monitoring and Evaluation Programme (EMEP) network. The background emission errors and the prior observational errors are estimated by maximum-likelihood approaches. The positivity assumption on the VOC emission fluxes is pivotal for a successful inversion, and this maximum-likelihood approach consistently accounts for the positivity of the fluxes. For most species, the retrieved emissions lead to a significant reduction of the bias, which underlines the misfit between the standard inventories and the observed concentrations. The results are validated through a forecast test and a cross-validation test. An estimation of the posterior uncertainty is also provided. It is shown that the statistically consistent non-Gaussian approach based on a reliable estimation of the errors offers the best performance. The efficiency in correcting the inventory depends on the lifetime of the VOCs and the accuracy of the boundary conditions. In particular, it is shown that the use of in situ observations using a sparse monitoring network to estimate emissions of isoprene is inadequate because its short chemical lifetime significantly limits the spatial radius of influence of the monitoring data. For species with a longer lifetime (a few days), successful, albeit partial, emission corrections can reach regions hundreds of kilometres away from the stations. Domain-wide corrections of the emission inventories of some VOCs are significant, with underestimations of the order of a factor of 2 for propane, ethane, ethylene and acetylene. (10.5194/acp-13-5887-2013)
  DOI : 10.5194/acp-13-5887-2013
• Using gamma dose rate monitoring with inverse modeling techniques to estimate the atmospheric release of a nuclear power plant accident: Application to the Fukushima case
  
  • Saunier Olivier
  • Mathieu Anne
  • Didier Damien
  • Tombette Marilyne
  • Quelo Denis
  • Winiarek Victor
  • Bocquet Marc
  , 2013, pp.670-677. The 'source term' including the time evolution of the release rate to the atmosphere and its distribution between radioisotopes remains one of the key uncertainties in the understanding of the consequences of the Fukushima Dai-Ichi accident. Inverse modeling methods have already proved to be efficient to estimate accidental releases. This paper presents a new inverse modeling approach to assess the source term by using gamma dose rate monitoring. The approach is applied to the Fukushima accident. The reliability of the retrieved source term is estimated by using model to data comparison and yields a good agreement. An important outcome on this study is its applicability during a response to an emergency situation.
• Estimation of the cesium-137 source term from the Fukushima Daiichi nuclear power plant using air concentration and deposition data
  
  • Winiarek Victor
  • Bocquet Marc
  • Duhanyan Nora
  • Roustan Yelva
  • Saunier Olivier
  • Mathieu Anne
  , 2013, pp.641-643. A major difficulty when inverting the source term of an atmospheric tracer dispersion problem is the estimation of the prior errors: those of the atmospheric transport model, those ascribed to the representativeness of the measurements, the instrumental errors, and those attached to the prior knowledge on the variables one seeks to retrieve. In the case of an accidental release of pollutant, and especially in a situation of poor observability, the reconstructed source is very sensitive to these assumptions. This sensitivity makes the quality of the retrieval dependent on the methods used to model and estimate the prior errors of the inverse modeling scheme. In order to use all the available data, we propose to extend the methods developed in Winiarek et al. (2012), which were designed for the inversion of one type of data, to the use of several types of data in the same inversion, such as activity concentrations in the air and fallout measurements. The idea is to simultaneously estimate the prior errors related to each dataset, in order to fully exploit the information content of each one. Using the activity concentration measurements, but also daily fallout data from prefectures and cumulated deposition data over a region lying approximately 150 km around the nuclear power plant, we can use a few thousands of data in the inverse modeling algorithm to reconstruct the cesium-137 source term. As expected, the different methods yield closer results as the number of data increases. The updated cesium-137 releases are estimated to be in the range 12-19 PBq, with a std. of 15-25%, depending on the methods and the data sets used in the inversion.
• Continuous tracking of structures from an image sequence
  
  • Lepoittevin Yann
  • Herlin Isabelle
  • Béréziat Dominique
  , 2013. The talk describes an innovative method to simultaneously estimate motion and track a structure on an image sequence. To process noisy images, assumptions on dynamics should be involved. Consequently, the method relies on the dynamics equations of the studied physical system. Promissing results have been obtained on twin experiments in order to quantify the accuracy of the method. The approach has also been tested on satellite acquisitions in order to track clouds an meteorological satellite acquisitions. Further research will concern the conception of a multi-object tracking method.
• Motion estimation on ocean satellite images by data assimilation in a wavelets reduced model
  
  • Huot Etienne
  • Papari Giuseppe
  • Herlin Isabelle
  • Drifi Karim
  , 2013, 15. This research concerns the issue of estimating surface motion from satellite images. The approach relies on a reduced model, obtained by Galerkin projection of dynamic equations on subspaces of velocity and image fields. The dynamics expresses the transport of image brightness and advection-diffusion of velocity. A data assimilation method is defined that assimilates image coefficients in the reduced model in order to estimate motion coefficients.
• État de la modélisation pour simuler l'accident nucléaire de la centrale Fukushima Daiichi
  
  • Mathieu Anne
  • Korsakissok Irène
  • Quélo Denis
  • Saunier Olivier
  • Groëll Jérôme
  • Didier Damien
  • Corbin Dominique
  • Denis Jean
  • Tombette Marilyne
  • Winiarek Victor
  • Bocquet Marc
  • Quentric Emmanuel
  • Benoit Jean-Pierre
  Pollution Atmosphérique : climat, santé, société, APPA, 2013 (217). Le 11 mars 2011, le tremblement de terre du Tohoku a déclenché un tsunami qui a dévasté la côte Pacifique du Japon et engendré l'accident nucléaire de la centrale de Fukushima Daiichi. Trois des cœurs des six réacteurs ont fusionné, entraînant d'importants rejets radioactifs. Deux ans après l'accident de Fukushima, de nombreuses incertitudes demeurent et limitent encore la connaissance de l'événement. L'article présente d'abord l'approche menée dès le début de l'accident pour comprendre son déroulement. Le transport des rejets atmosphériques est simulé et les résultats sont comparés aux observations. Quatre phases principales de rejet ont été identifiées. Deux d'entre elles n'ont pas eu de conséquences importantes sur le sol japonais puisque le panache radioactif est parti vers l'océan. Une troisième phase de rejet a causé la contamination principale au nord-ouest de l'installation nucléaire. La dernière phase de rejet a contribué à la contamination des sols au sud de l'installation et, plus particulièrement, de la région de Tokyo. De nombreuses incertitudes caractérisent encore le terme source de l'accident. Une nouvelle méthode basée sur la modélisation inverse et l'utilisation des mesures de débit de dose a été développée. Les résultats très prometteurs montrent comment la démarche mise en œuvre permet d'améliorer l'estimation du terme source. L'approche développée est parfaitement adaptée à une utilisation opérationnelle et devrait contribuer à améliorer la réponse de l'Institut de Radioprotection et de Sûreté Nucléaire en cas d'accident nucléaire.
• Continuous tracking of structures from an image sequence
  
  • Lepoittevin Yann
  • Béréziat Dominique
  • Herlin Isabelle
  • Mercier Nicolas
  , 2013, pp.386-389. The paper describes an innovative approach to estimate velocity on an image sequence and simultaneously segment and track a given structure. It relies on the underlying dynamics' equations of the studied physical system. A data assimilation method is applied to solve evolution equations of image brightness, those of motion's dynamics, and those of distance map modelling the tracked structures. Results are first quantified on synthetic data with comparison to ground-truth. Then, the method is applied on meteorological satellite acquisitions of a tropical cloud, in order to track this structure on the sequence. The outputs of the approach are the continuous estimation of both motion and structure's boundary. The main advantage is that the method only relies on image data and on a rough segmentation of the structure at initial date.