Publications

2011

• Air quality modeling : evaluation of chemical and meteorological parameterizations
  
  • Kim Youngseob
  , 2011. The influence of chemical mechanisms and meteorological parameterizations on pollutant concentrations calculated with an air quality model is studied. The influence of the differences between two gas-phase chemical mechanisms on the formation of ozone and aerosols in Europe is low on average. For ozone, the large local differences are mainly due to the uncertainty associated with the kinetics of nitrogen monoxide (NO) oxidation reactions on the one hand and the representation of different pathways for the oxidation of aromatic compounds on the other hand. The aerosol concentrations are mainly influenced by the selection of all major precursors of secondary aerosols and the explicit treatment of chemical regimes corresponding to the nitrogen oxides (NOx) levels. The influence of the meteorological parameterizations on the concentrations of aerosols and their vertical distribution is evaluated over the Paris region in France by comparison to lidar data. The influence of the parameterization of the dynamics in the atmospheric boundary layer is important ; however, it is the use of an urban canopy model that improves significantly the modeling of the pollutant vertical distribution (10.70675/56d182baze04dz4546za769z60459b04a72e)
  DOI : 10.70675/56d182baze04dz4546za769z60459b04a72e
• Estimation des incertitudes et prévision des risques en qualité de l'air
  
  • Garaud Damien
  , 2011. Ce travail porte sur l'estimation des incertitudes et la prévision de risques en qualité de l'air. Il consiste dans un premier temps à construire un ensemble de simulations de la qualité de l'air qui prend en compte toutes les incertitudes liées à la modélisation de la qualité de l'air. Des ensembles de simulations photochimiques à l'échelle continentale ou régionale sont générés automatiquement. Ensuite, les ensembles générés sont calibrés par une méthode d'optimisation combinatoire qui sélectionne un sous-ensemble représentatif de l'incertitude ou performant (fiabilité et résolution) pour des prévisions probabilistes. Ainsi, il est possible d'estimer et de prévoir des champs d'incertitude sur les concentrations d'ozone ou de dioxyde d'azote, ou encore d'améliorer la fiabilité des prévisions de dépassement de seuil. Cette approche est ensuite comparée avec la calibration d'un ensemble Monte Carlo. Ce dernier, moins dispersé, est moins représentatif de l'incertitude. Enfin, on a pu estimer la part des erreurs de mesure, de représentativité et de modélisation de la qualité de l'air (10.70675/67ba6d88zdcdfz4667zbff6z233cabfa2163)
  DOI : 10.70675/67ba6d88zdcdfz4667zbff6z233cabfa2163
• Below-cloud scavenging by rain of atmospheric gases and particulates
  
  • Duhanyan Nora
  • Roustan Yelva
  Atmospheric Environment, Elsevier, 2011, 45 (39), pp.7201-7217. Below-cloud scavenging (BCS) by rain is one of the phenomena that control the removal of atmospheric pollutants from air. The present work introduces a detailed review of the most literature referred theories and parameterisations to describe the below-cloud scavenging by rain in air quality modelling. The theories and parameterisations in question concern the raindrop size distribution (RSD), the terminal velocity of raindrops, and the below-cloud scavenging coefficient for gaseous and particulate pollutants. 0D computations are run to calculate the latter coefficient with the help of the current theories and parameterisations thus extracted from the literature. As a result to improve the atmospheric modelling studies, it can be mentioned that the choice of the raindrop terminal velocity among the available parameterisations does not matter much and therefore, the practice of the most simple formulae is advised. On the other hand, a great dispersion on the scavenging coefficient (several orders of magnitude) is observed related to the variations of the RSD. Therefore, a great care is recommended in the choice of the RSD with respect to the type of rain and sampling duration involved (e.g. thunderstorm, widespread, shower, etc.; long or instantaneous sampling duration). Many uncertainties do remain due to the lack of precision in the experimental records after which the RSD parameterisations are established or to the poor level of accuracy of the theoretical models. (10.1016/j.atmosenv.2011.09.002)
  DOI : 10.1016/j.atmosenv.2011.09.002
• Estimating the effect of on-road vehicle emission controls on future air quality in Paris, France
  
  • Roustan Yelva
  • Pausader Marie
  • Seigneur Christian
  Atmospheric Environment, Elsevier, 2011, 45 (37), pp.6828 - 6836. For several years several vehicle emission control technologies have been developed and introduced to reduce the contribution of road traffic to air pollution. However, this contribution in the Île de France region, around Paris, France, has been estimated to still be significant. We present a modeling study of the effect of the future evolution of traffic emissions on air quality at the urban scale. The aim is to assess the respective contribution of the different processes involved in the nonlinear chemistry of photochemical air pollution (change in emissions and/or chemical behaviour) that explain the observed evolution of concentrations of traffic-related pollutants at monitoring urban background stations. The modeling results suggest that the reduction of NOx emissions must be coupled with more stringent measures on NMVOC emissions than those currently planned in the transportation sector to avoid an increase of O3 concentrations in some densely populated areas. The modeled NO2 concentrations in Paris reach a maximum in 2010 due to an increase of the NO2 emissions related to the evolution of the NO2/NOx ratio of the Diesel vehicle emissions. The reduction of PM emissions leads to a non-proportional decrease in PM concentrations, which results mostly from the decrease in Diesel particulate emissions. (10.1016/j.atmosenv.2010.10.010)
  DOI : 10.1016/j.atmosenv.2010.10.010
• Contribution à l'estimation des précipitations tropicales : préparation aux missions Megha-Tropiques et Global Precipitation Measurement
  
  • Chambon Philippe
  , 2011. Les précipitations résultent d'un phénomène atmosphérique caractérisé par une variabilité spatiale et temporelle forte. Cette variabilité dans la distribution des pluies et des évènements intenses a des impacts en hydrologie de surface (e.g. inondations) variés selon les régions du monde. Toute modification du climat tropical est associée à une modification du cycle de l'eau et de l'énergie dans ces régions. Dans un contexte de changement climatique, il est donc important de développer des outils permettant d'estimer quantitativement les précipitations, à l'échelle du globe, à la fois sur les surfaces continentales et les surfaces océaniques. Les travaux présentés dans cette thèse s'intéressent à l'observation des précipitations depuis l'espace. En effet, la mesure des pluies nécessite une densité d'observations élevée qui, sur l'ensemble des Tropiques, n'est accessible qu'à partir d'observations spatiales. Depuis plusieurs décades, les moyens satellitaires à disposition ont beaucoup évolué et offrent aujourd'hui une densité d'observations de plus en plus fortes. Grâce aux nouvelles missions déployées telles que Megha-Tropiques au sein de la future constellation GPM (Global Precipitation Measurement), on a accès à un ensemble de systèmes d'observations qui amène à une densité accrue d'observations spatiales. L'estimation quantitative des précipitations n'était possible qu'à l'échelle mensuelle, il est maintenant envisageable d'estimer la pluie par satellite à des échelles de temps de plus en plus fines. Cette thèse s'intéresse aux échelles 1°/1-jour, échelle clé pour les études météorologiques et hydrologiques. Il existe un large spectre de méthodes d'estimations de précipitations par satellite, de qualité inégale. Dans un premier temps, une analyse des produits issus des développements les plus récents montre que leur qualité a atteint un degré suffisant pour être utilisé de manière quantitative aux échelles de temps pertinentes en météorologie. Il apparaît également qu'à ces échelles de temps, il est nécessaire d'utiliser les estimations de cumul de précipitations conjointement avec leurs barres d'erreurs. Une nouvelle méthode d'estimations de précipitations sur l'ensemble de la ceinture tropicale, appelé TAPEER (Tropical Amount of Precipitation with an Estimate of ERrors), est donc développée dans le but d'estimer des cumuls de pluie et leurs erreurs associées à l'échelle 1°/1-jour. Cette approche est fondée sur une méthode de fusion de données de l'imagerie Infrarouge d'une constellation de satellites géostationnaires et d'estimations de taux de pluie issues de radiomètres Micro-ondes d'une constellation de satellites défilant. Des techniques modélisations sont mises en oeuvre afin d'associer une erreur aux cumuls de pluie produits. Une investigation détaillée du bilan d'erreur de la méthode TAPEER montre que les sources principales d'incertitudes sont liées à l'échantillonnage et aux biais systématiques sur les taux de pluie d'intensité moyenne. Une étude sur l'été 2009 révèle l'importance de l'utilisation de la barre d'erreur dans l'analyse de la distribution des pluies, en particulier pour les plus forts cumuls sur la ceinture tropicale (10.70675/008b8bf2zed5az4d48z8293zabd5fec2eb53)
  DOI : 10.70675/008b8bf2zed5az4d48z8293zabd5fec2eb53
• Three-dimensional modeling of radiative and convective exchanges in the urban atmosphere
  
  • Qu Yongfeng
  , 2011. In many micrometeorological studies, building resolving models usually assumea neutral atmosphere. Nevertheless, urban radiative transfers play an important role because of their influence on the energy budget. In order to take into account atmospheric radiation and the thermal effects of the buildings in simulations of atmospheric flow and pollutant dispersion in urban areas, we have developed a three-dimensional (3D) atmospheric radiative scheme, in the atmospheric module of the Computational Fluid Dynamics model Code_Saturne. The radiative scheme was previously validated with idealized cases, using as a first step, a constant 3D wind field. In this work, the full coupling of the radiative and thermal schemes with the dynamical model is evaluated. The aim of the first part is to validate the full coupling with the measurements of the simple geometry from the ‘Mock Urban Setting Test' (MUST) experiment. The second part discusses two different approaches to model the radiative exchanges in urban area with a comparison between Code_Saturne and SOLENE. The third part applies the full coupling scheme to show the contribution of the radiative transfer model on the airflow pattern in low wind speed conditions in a 3D urban canopy. In the last part we use the radiative-dynamics coupling to simulate a real urban environment and validate the modeling approach with field measurements from the ‘Canopy and Aerosol Particle Interactions in Toulouse Urban Layer' (CAPITOUL) (10.70675/9b294492z1e94z42f2z867cz8b74d1b992b3)
  DOI : 10.70675/9b294492z1e94z42f2z867cz8b74d1b992b3
• Optimal representation of source-sink fluxes for mesoscale carbon dioxide inversion with synthetic data
  
  • Wu Lin
  • Bocquet Marc
  • Lauvaux Thomas
  • Chevallier Frédéric
  • Rayner Peter
  • Davis Kenneth
  Journal of Geophysical Research: Atmospheres, American Geophysical Union, 2011, 116 (D21304). The inversion of CO2 surface fluxes from atmospheric concentration measurements involves discretizing the flux domain in time and space. The resolution choice is usually guided by technical considerations despite its impact on the solution to the inversion problem. In our previous studies, a Bayesian formalism has recently been introduced to describe the discretization of the parameter space over a large dictionary of adaptive multiscale grids. In this paper, we exploit this new framework to construct optimal space-time representations of carbon fluxes for mesoscale inversions. Inversions are performed using synthetic continuous hourly CO2 concentration data in the context of the Ring 2 experiment in support of the North American Carbon Program Mid Continent Intensive (MCI). Compared with the regular grid at finest scale, optimal representations can have similar inversion performance with far fewer grid cells. These optimal representations are obtained by maximizing the number of degrees of freedom for the signal (DFS) that measures the information gain from observations to resolve the unknown fluxes. Consequently information from observations can be better propagated within the domain through these optimal representations. For the Ring 2 network of eight towers, in most cases, the DFS value is relatively small compared to the number of observations d (DFS/d < 20%). In this multiscale setting, scale-dependent aggregation errors are identified and explicitly formulated for more reliable inversions. It is recommended that the aggregation errors should be taken into account, especially when the correlations in the errors of a priori fluxes are physically unrealistic. The optimal multiscale grids allow to adaptively mitigate the aggregation errors. (10.1029/2011JD016198)
  DOI : 10.1029/2011JD016198
• HyMeX - The regional coupled system WRF-NEMO over the Mediterranean (MORCE plateform): impacts of mesoscale coupled processes on the water budget estimation
  
  • Béranger Karine
  • Lebeaupin Brossier Cindy
  • Drobinski Philippe
  • Bastin Sophie
  • Mailler Sylvain
  • Samson Guillaume
  • Masson Sébastien
  • Madec Gurvan
  • Valcke Sophie
  • Coquart Laure
  • Maisonnave Éric
  , 2011, pp.TH225. The Mediterranean climate and water cycle are strongly affected by fine-scale and coupled processes, which generally involve all the Earth system compartments (ocean - atmosphere - land surface). Their investigation by modelling needs the development of accurate coupled and mesoscale numerical systems. We build at IPSL the MORCE (Model Of the Regional Coupled Earth system) plateform over the Mediterranean area. It includes the regional air-sea coupled system WRF-OASIS-NEMO. The horizontal resolutions are 20km for the non-hydrostatic atmospheric model WRF and 1/12o for the eddy-resolving ocean circulation model NEMO-MED12. The Sea Surface Temperature (SST) and fluxes exchanges between the two models are managed via the OASIS coupler. Three simulations are currently available: (1)The downscaling of the ERA-interim reanalyses (1989-2008) by WRF. This simulation is also part of the Med-CORDEX project; (2)The NEMO-MED12 simulation for the same period, driven by air-sea fluxes provided by simulation (1) every 3 hours; (3)The two-way interactive coupled run (MORCE experiment). The coupling frequency chosen is 3 hours. The comparison of the uncoupled/coupled runs is done to evaluate the role of mesoscale coupled processes on the water budget. Compared to reanalyses, the coupled system better represents the mean SST, especially in summer. The coupling produces mesoscale patterns in the turbulent fluxes that slightly modify the general and thermohaline circulations. In the atmospheric model, the SST modifications between uncoupled and coupled runs induce strong retroactions on the Precipitation (P) and Evaporation (E) fields. We found a significant spatial correspondence between the SST anomalies and the P and E anomalies. The fine-scale P anomalies extend over the coastal area, but the extension seems to be limited by the surrounding orography. The wind speed is also decreased in the coupled mode over the whole domain, except over some SST anomaly hot-spots. Finally, the annual cycles of P, E and E-P over sea show weak differences. This highlights that the coupled processes major role is the redistribution of the water at mesoscale.
• The "Votre Air" project: development of a modelling tool to assess the real atmospheric exposure in Paris
  
  • Pradelle Frédéric
  • Brocheton Fabien
  • Chabanon Benjamin
  • Honoré Cécile
  • Dugay Fabrice
  • Léger Karine
  • Dambre François
  • Mallet Vivien
  • Tilloy Anne
  • Olesen R.
  • Higson Helen
  , 2011, pp.448-451. Traffic generates about 60% of the Paris nitrogen dioxide and particles emissions, and the levels of these pollutants are a major concern, in particular nearby the road traffic. Therefore, the realistic characterization of the population exposure draws special attention from the concerned actors. Nowadays, high resolution modelling tools like Urban'Air well reproduce the spatial distribution of atmospheric pollutants concentrations at the city scale. One limitation of these new modelling tools is that they are most of the time provided with "standard temporal profiles" of emissions data (weekly and monthly profiles), instead of real-time traffic data. Moreover, the pollution measured at the monitoring stations is not generally taken into account in the computations. The "Votre Air" project's aim was to develop a numerical tool to provide realistic and real-time estimation of the air quality at the scale over Paris Center. In this paper, we especially detail how the real-time concentration observations are assimilated in order to better reproduce the chemical state of the atmosphere. The results are illustrated with nitrogen dioxide.
• Ensemble Kalman filtering without the intrinsic need for inflation
  
  • Bocquet Marc
  Nonlinear Processes in Geophysics, European Geosciences Union (EGU), 2011, 18 (5), pp.735--750. The main intrinsic source of error in the ensemble Kalman filter (EnKF) is sampling error. External sources of error, such as model error or deviations from Gaussianity, depend on the dynamical properties of the model. Sampling errors can lead to instability of the filter which, as a consequence, often requires inflation and localization. The goal of this article is to derive an ensemble Kalman filter which is less sensitive to sampling errors. A prior probability density function conditional on the forecast ensemble is derived using Bayesian principles. Even though this prior is built upon the assumption that the ensemble is Gaussian-distributed, it is different from the Gaussian probability density function defined by the empirical mean and the empirical error covariance matrix of the ensemble, which is implicitly used in traditional EnKFs. This new prior generates a new class of ensemble Kalman filters, called finite-size ensemble Kalman filter (EnKF-N). One deterministic variant, the finite-size ensemble transform Kalman filter (ETKF-N), is derived. It is tested on the Lorenz '63 and Lorenz '95 models. In this context, ETKF-N is shown to be stable without inflation for ensemble size greater than the model unstable subspace dimension, at the same numerical cost as the ensemble transform Kalman filter (ETKF). One variant of ETKF-N seems to systematically outperform the ETKF with optimally tuned inflation. However it is shown that ETKF-N does not account for all sampling errors, and necessitates localization like any EnKF, whenever the ensemble size is too small. In order to explore the need for inflation in this small ensemble size regime, a local version of the new class of filters is defined (LETKF-N) and tested on the Lorenz '95 toy model. Whatever the size of the ensemble, the filter is stable. Its performance without inflation is slightly inferior to that of LETKF with optimally tuned inflation for small interval between updates, and superior to LETKF with optimally tuned inflation for large time interval between updates. (10.5194/npg-18-735-2011)
  DOI : 10.5194/npg-18-735-2011
• Automatic calibration of an ensemble for uncertainty estimation and probabilistic forecast: Application to air quality
  
  • Garaud Damien
  • Mallet Vivien
  Journal of Geophysical Research, American Geophysical Union, 2011, 116 (D19304). This paper addresses the problem of calibrating an ensemble for uncertainty estimation. The calibration method involves (1) a large, automatically generated ensemble, (2) an ensemble score such as the variance of a rank histogram, and (3) the selection based on a combinatorial algorithm of a sub-ensemble that minimizes the ensemble score. The ensemble scores are the Brier score (for probabilistic forecasts), or derived from the rank histogram or the reliability diagram. These scores allow us to measure the quality of an uncertainty estimation, and the reliability and the resolution of an ensemble. The ensemble is generated on the Polyphemus modeling platform so that the uncertainties in the models' formulation and their input data can be taken into account. A 101-member ensemble of ground-ozone simulations is generated with full chemistry-transport models run across Europe during the year 2001. This ensemble is evaluated with the aforementioned scores. Several ensemble calibrations are carried out with the different ensemble scores. The calibration makes it possible to build 20- to 30-member ensembles which greatly improves the ensemble scores. The calibrations essentially improve the reliability, while the resolution remains unchanged. The spatial validity of the uncertainty maps is ensured by cross validation. The impact of the number of observations and observation errors is also addressed. Finally, the calibrated ensembles are able to produce accurate probabilistic forecasts and to forecast the uncertainties, even though these uncertainties are found to be strongly time-dependent. (10.1029/2011JD015780)
  DOI : 10.1029/2011JD015780
• Learning reduced models for motion estimation on ocean satellite images
  
  • Herlin Isabelle
  • Béréziat Dominique
  • Drifi Karim
  , 2011. The paper describes a learning method on sliding windows for estimating apparent motion on long temporal satellite sequences acquired over oceans. A "full model", which is defined on the pixel grid, is chosen to describe the dynamics of motion fields and images, based on heuristics of divergence-free motion and advection of image brightness by the velocity. The image sequence is split into small temporal windows that half overlap in time. Image assimilation in the full model is applied on the first window to retrieve its motion field. This makes it possible to define subspaces of motion fields and images and a "reduced model" is defined by applying the Galerkin projection of the full model on these subspaces. Data assimilation in the reduced model is applied on this second window. The process is iterated for the next window until the end of the whole image sequence. Each reduced model is then learned from the previous one. The main advantage of the approach is the small computational requirements of the assimilation in the reduced models that make it feasible to process in quasi-real time image acquisitions. Twin experiments have been designed to quantify the full model and the learning method on sliding windows and demonstrate the quality of the motion fields estimated by the approach.
• Motion estimation from satellite image sequences: validation
  
  • Huot Etienne
  • Herlin Isabelle
  • Mercier Nicolas
  • Korotaev Gennady K.
  • Plotnikov Evgeny
  , 2011. No abstract.
• Assimilation d'images dans un modèle réduit pour l'estimation du mouvement
  
  • Drifi Karim
  • Herlin Isabelle
  , 2011. Cet article décrit une méthode d'estimation du champ de vitesse apparent, sous-jacent à l'évolution temporelle d'une séquence d'images. Un modèle d'évolution, dit complet, est choisi pour représenter la dynamique du champ de vitesse et des images. La méthode de décomposition orthogonale propre est appliquée et fournit des bases de représentation des champs de vitesse et des images. La projection de Galerkin du modèle complet sur ces bases réduites définit alors le modèle réduit. Un algorithme d'assimilation variationelle de données est conçu afin d'estimer les coefficients des champs de vitesse à partir des coefficients des images observées. Le mouvement est ensuite restitué à partir de ces coefficients estimés. La méthode est validée sur des données synthétiques afin de quantifier les résultats.
• Validation de la vitesse estimée à partir d'images satellite
  
  • Huot Etienne
  • Herlin Isabelle
  • Mercier Nicolas
  • Korotaev Gennady K.
  • Plotnikov Evgeny
  , 2011. Cet article concerne la validation de l'estimation de la vitesse de surface à partir d'images satellite. Cette estimation est effectuée avec un modèle de la dynamique, basé sur les équations shallow-water. Nous comparons d'abord l'hypothèse de stationnarité aux équations shallow-water afin de justifier notre choix. Puis, nous quantifions la qualité des estimations en mesurant l'écart entre la sortie du modèle et les mesures d'altimétrie. Les expérimentations sont effectuées en utilisant des données de température de surface, acquises au-dessus de la Mer Noire avec les satellites NOAA/AVHRR. Les mesures altimétriques proviennent de deux capteurs radar : Envisat et GFO. La bonne adéquation entre la sortie du modèle shallow-water et les données altimétriques valide notre approche d'estimation du mouvement.
• Reduced minimax filtering by means of Differential-Algebraic equations
  
  • Mallet Vivien
  • Zhuk Sergiy
  , 2011. 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.
• A new algorithm to solve condensation/evaporation growth, coagulation and nucleation of nanoparticles
  
  • Devilliers Marion
  • Seigneur Christian
  • Debry Edouard
  • Sartelet Karine
  , 2011.
• Bayesian design of control space for optimal assimilation of observations. Part I: Consistent multiscale formalism
  
  • Bocquet Marc
  • Wu Lin
  • Chevallier Frédéric
  Quarterly Journal of the Royal Meteorological Society, Wiley, 2011, 137 (658), pp.1340-1356. In geophysical data assimilation, the control space is by definition the set of parameters which are estimated through the assimilation of observations. It has recently been proposed to design the discretizations of control space in order to assimilate observations optimally. The present paper describes the embedding of that formalism in a consistent Bayesian framework. General background errors are now accounted for. Scale-dependent errors, such as aggregation errors (that lead to representativeness errors) are consistently introduced. The optimal adaptive discretizations of control space minimize a criterion on a dictionary of grids. New criteria are proposed: degrees of freedom for the signal (DFS) built on the averaging kernel operator, and an observation-dependent criterion. These concepts and results are applied to atmospheric transport of pollutants. The algorithms are tested on the European tracer experiment (ETEX), and on a prototype of CO2 flux inversion over Europe using a simplified CarboEurope-IP network. New types of adaptive discretization of control space are tested such as quaternary trees or factorised trees. Quaternary trees are proven to be both economical, in terms of storage and CPU time, and efficient on the test cases. This sets the path for the application of this methodology to high-dimensional and noisy geophysical systems. Part II of this article will develop asymptotic solutions for the design of control space representations that are obtained analytically and are contenders to exact numerical optimizations. Copyright © 2011 Royal Meteorological Society (10.1002/qj.837)
  DOI : 10.1002/qj.837
• Bayesian design of control space for optimal assimilation of observations. Part II: Asymptotic solutions
  
  • Bocquet Marc
  • Wu Lin
  Quarterly Journal of the Royal Meteorological Society, Wiley, 2011, 137 (658), pp.1357-1368. A consistent formalism for a Bayesian design of control space for an optimal assimilation of observations was proposed in Part I of this two-part article. This optimal discretization of control space leads to an efficient data assimilation scheme implementation. However, the construction of the grid itself, prior to its use for data assimilation, requires an optimization that may be challenging for high-dimensional systems. This paper derives analytical solutions for these optimal grids in the limit where the discretization of control space has a large number of grid cells. Analytical solutions for the density of grid cells are obtained for the so-called tilings, qtrees and ftrees, that represent different types of adaptive grids, with more or fewer degrees of freedom. These analytical solutions are explicit and the algorithms that allow densities to be converted into discrete adaptive grids are costless. The approach is tested with a simplified physics in the Jacobian matrix in a tracer dispersion context in which radionuclides are monitored by the global observation network operated by the Comprehensive Nuclear Test Ban Treaty Organisation of the United Nations. The asymptotic solutions are then compared to the optimal grids obtained from the methodology perfected in Part I. In this example, and using qtree representations, the discrepancy between the approximate solution and the exact solution almost vanishes when the number of grid cells represents as few as 1% of the total number of grid cells in the finest grid. This opens the way to the application of this multiscale data assimilation framework to computationally challenging problems. Copyright © 2011 Royal Meteorological Society (10.1002/qj.841)
  DOI : 10.1002/qj.841
• Constraining surface emissions of air pollutants using inverse modelling: method intercomparison and a new two-step two-scale regularization approach
  
  • Saide Pablo
  • Bocquet Marc
  • Osses Axel
  • Gallardo Laura
  Tellus B - Chemical and Physical Meteorology, Taylor & Francis, 2011, 63 (3), pp.360-370. When constraining surface emissions of air pollutants using inverse modelling one often encounters spurious corrections to the inventory at places where emissions and observations are colocated, referred to here as the colocalization problem. Several approaches have been used to deal with this problem: coarsening the spatial resolution of emissions; adding spatial correlations to the covariance matrices; adding constraints on the spatial derivatives into the functional being minimized; and multiplying the emission error covariance matrix by weighting factors. Intercomparison of methods for a carbon monoxide inversion over a city shows that even though all methods diminish the colocalization problem and produce similar general patterns, detailed information can greatly change according to the method used ranging from smooth, isotropic and short range modifications to not so smooth, non-isotropic and long range modifications. Poisson (non-Gaussian) and Gaussian assumptions both show these patterns, but for the Poisson case the emissions are naturally restricted to be positive and changes are given by means of multiplicative correction factors, producing results closer to the true nature of emission errors. Finally, we propose and test a new two-step, two-scale, fully Bayesian approach that deals with the colocalization problem and can be implemented for any prior density distribution. (10.1111/j.1600-0889.2011.00529.x)
  DOI : 10.1111/j.1600-0889.2011.00529.x
• Validation of surface velocity estimated from satellite images
  
  • Huot Etienne
  • Herlin Isabelle
  • Mercier Nicolas
  • Korotaev Gennady K.
  • Plotnikov Evgeny
  , 2011, pp.17. This report concerns the validation of surface velocity estimated from satellite images. The estimation is obtained with a dynamic model based on shallow-water equations. We first compare the stationary assumption to the shallow-water heuristics to justify our choice. Second, we quantify the quality of the estimation by measuring the misfit between the model output and the altimetry measures. Experiments are achieved on Sea Surface Temperature data acquired by the NOAA/AVHRR satellites over the Black Sea. The altimetry measures are obtained by two radar sensors: Envisat and GFO. The good adequacy between the shallow-water output and the altimetry data validates our motion estimation approach.
• Real-Time Quasi Dense Two-Frames Depth Map for Autonomous Guided Vehicles
  
  • Ducrot André
  • Dumortier Yann
  • Herlin Isabelle
  • Ducrot Vincent
  , 2011, pp.497-503. This paper presents a real-time and dense structure from motion approach, based on an efficient planar parallax motion decomposition, and also proposes several optimizations to improve the optical flow firstly computed. Later, it is estimated using our own GPU implementation of the well-known pyramidal algorithm of Lucas and Kanade. Then, each pair of points previously matched is evaluated according to the spatial continuity constraint provided by the Tensor Voting framework applied in the 4-D joint space of image coordinates and motions. Thus, assuming the ground locally planar, the homography corresponding to its image motion is robustly and quickly estimated using RANSAC on designated well-matched pairwise by the prior Tensor Voting process. Depth map is finally computed from the parallax motion decomposition. The initialization of successive runs is also addressed, providing noticeable enhancement, as well as the hardware integration using the CUDA technology. (10.1109/IVS.2011.5940507)
  DOI : 10.1109/IVS.2011.5940507
• Micrometerological modeling of radiative and convective effects with a building resolving code
  
  • Qu Yongfeng
  • Milliez Maya
  • Musson-Genon Luc
  • Carissimo Bertrand
  , 2010, pp...........................
• Towards the operational estimation of a radiological plume using data assimilation after a radiological accidental atmospheric release
  
  • Winiarek Victor
  • Vira J.
  • Bocquet Marc
  • Sofiev Mikhail
  • Saunier Olivier
  Atmospheric Environment, Elsevier, 2011, 45 (17), pp.2944-2955. 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. The accuracy of the forecast plume is highly dependent on the source term estimation. On several academic test cases, including real data, inverse modelling and data assimilation techniques were proven to help in the assessment of the source term. In this paper, 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. Two dispersion models have been used: Polair3D and Silam developed in two different research centres. Different release locations, as well as different meteorological situations are tested. The existing and newly planned surveillance networks are used and realistically large multiplicative observational errors are assumed. The inverse modelling scheme accounts for strong error bias encountered with such errors. The efficiency of the data assimilation system is tested via statistical indicators. For France and Finland, the average performance of the data assimilation system is strong. However there are outlying situations where the inversion fails because of a too poor observability. In addition, in the case where the power plant responsible for the accidental release is not known, robust statistical tools are developed and tested to discriminate candidate release sites. (10.1016/j.atmosenv.2010.12.025)
  DOI : 10.1016/j.atmosenv.2010.12.025
• Recovering missing data on satellite images
  
  • Herlin Isabelle
  • Béréziat Dominique
  • Mercier Nicolas
  , 2011, 6688, pp.697-707. Data Assimilation is commonly used in environmental sciences to improve forecasts, obtained by meteorological, oceanographic or air quality simulation models, with observation data. It aims to solve an evolution equation, describing the dynamics, and an observation equation, measuring the misfit between the state vector and the observations, to get a better knowledge of the actual system's state, named the reference. In this article, we describe how to use this technique to recover missing data and reduce noise on satellite images. The recovering process is based on assumptions on the underlying dynamics displayed by the sequence of images. This is a promising alternative to methods such as space-time interpolation. In order to better evaluate our approach, results are first quantified for an artificial noise applied on the acquisitions and then displayed for real data. (10.1007/978-3-642-21227-7_65)
  DOI : 10.1007/978-3-642-21227-7_65