Publications

2012

• Image Assimilation and Motion Estimation of Geophysical Fluids
  
  • Herlin Isabelle
  • Béréziat Dominique
  • Huot Etienne
  , 2012, pp.2325-2332. Simulation models and image data are simultaneously available for numerous scientific domains, such as oceanography and meteorology. They are indeed two complementary descriptions of the same complex system. Data Assimilation is a well-known mathematical technique used, in environmental sciences, to improve forecasts obtained from the simulation models, thanks to the observation data. One class of data assimilation algorithms, named 4D-Var, globally adjusts the model output to the observations, that are available over a period of time. The question of how to derive accurate characteristic features from images, with an optimal use of the simulation model, is of major interest for the image processing community. In this article, we consider applying data assimilation methods for motion estimation on a sequence of satellite images acquired over the ocean. We describe various strategies that can be derived in the framework of variational data assimilation (4D-Var). They mostly depend on the choice of the state vector itself. According to this definition, the dynamics has to be described and observation operators specified in order to characterize the information displayed by the image sequence. We detail the mathematical setting of these strategies and analyze their properties. Results are provided on twin experiments to quantify the methods and on satellite acquisitions acquired over the Black Sea.
• Computing Two-fluid Models of Compressible Water-vapour Flows with Mass Transfer
  
  • Hérard Jean-Marc
  • Hurisse Olivier
  , 2012. (10.2514/6.2012-2959)
  DOI : 10.2514/6.2012-2959
• Combining inflation-free and iterative ensemble Kalman filters for strongly nonlinear systems
  
  • Bocquet Marc
  • Sakov Pavel
  Nonlinear Processes in Geophysics, European Geosciences Union (EGU), 2012, 19 (3), pp.383-399. The finite-size ensemble Kalman filter (EnKF-N) is an ensemble Kalman filter (EnKF) which, in perfect model condition, does not require inflation because it partially accounts for the ensemble sampling errors. For the Lorenz '63 and '95 toy-models, it was so far shown to perform as well or better than the EnKF with an optimally tuned inflation. The iterative ensemble Kalman filter (IEnKF) is an EnKF which was shown to perform much better than the EnKF in strongly nonlinear conditions, such as with the Lorenz '63 and '95 models, at the cost of iteratively updating the trajectories of the ensemble members. This article aims at further exploring the two filters and at combining both into an EnKF that does not require inflation in perfect model condition, and which is as efficient as the IEnKF in very nonlinear conditions. In this study, EnKF-N is first introduced and a new implementation is developed. It decomposes EnKF-N into a cheap two-step algorithm that amounts to computing an optimal inflation factor. This offers a justification of the use of the inflation technique in the traditional EnKF and why it can often be efficient. Secondly, the IEnKF is introduced following a new implementation based on the Levenberg-Marquardt optimisation algorithm. Then, the two approaches are combined to obtain the finite-size iterative ensemble Kalman filter (IEnKF-N). Several numerical experiments are performed on IEnKF-N with the Lorenz '95 model. These experiments demonstrate its numerical efficiency as well as its performance that offer, at least, the best of both filters. We have also selected a demanding case based on the Lorenz '63 model that points to ways to improve the finite-size ensemble Kalman filters. Eventually, IEnKF-N could be seen as the first brick of an efficient ensemble Kalman smoother for strongly nonlinear systems. (10.5194/npg-19-383-2012)
  DOI : 10.5194/npg-19-383-2012
• Network design for mesoscale inversions of CO2 sources and sinks
  
  • Lauvaux Thomas
  • Schuh Andrew E.
  • Bocquet Marc
  • Wu Lin
  • Richardson Scott
  • Miles Natasha
  • Davis Kenneth J.
  Tellus B - Chemical and Physical Meteorology, Taylor & Francis, 2012, 64. Recent instrumental deployments of regional observation networks of atmospheric CO2 mixing ratios have been used to constrain carbon sources and sinks using inversion methodologies. In this study, we performed sensitivity experiments using observation sites from the Mid Continent Intensive experiment to evaluate the required spatial density and locations of CO2 concentration towers based on flux corrections and error reduction analysis. In addition, we investigated the impact of prior flux error structures with different correlation lengths and biome information. We show here that, while the regional carbon balance converged to similar annual estimates using only two concentration towers over the region, additional sites were necessary to retrieve the spatial flux distribution of our reference case (using the entire network of eight towers). Local flux corrections required the presence of observation sites in their vicinity, suggesting that each tower was only able to retrieve major corrections within a hundred of kilometres around, despite the introduction of spatial correlation lengths (~100 to 300 km) in the prior flux errors. We then quantified and evaluated the impact of the spatial correlations in the prior flux errors by estimating the improvement in the CO2 model-data mismatch of the towers not included in the inversion. The overall gain across the domain increased with the correlation length, up to 300 km, including both biome-related and non-biome-related structures. However, the spatial variability at smaller scales was not improved. We conclude that the placement of observation towers around major sources and sinks is critical for regional-scale inversions in order to obtain reliable flux distributions in space. Sparser networks seem sufficient to assess the overall regional carbon budget with the support of flux error correlations, indicating that regional signals can be recovered using hourly mixing ratios. However, the smaller spatial structures in the posterior fluxes are highly constrained by assumed prior flux error correlation lengths, with no significant improvement at only a few hundreds of kilometres away from the observation sites. (10.3402/tellusb.v64i0.17980)
  DOI : 10.3402/tellusb.v64i0.17980
• Impact of biogenic emissions on air quality over Europe and North America
  
  • Sartelet Karine
  • Couvidat Florian
  • Seigneur Christian
  • Roustan Yelva
  Atmospheric Environment, Elsevier, 2012, 53, pp.131 - 141. This study aims to compare the relative impact of biogenic emissions on ozone (O3) and particulate matter (PM) concentrations between North America (NA) and Europe. The simulations are conducted with the Polyphemus air quality modeling system over July and August 2006. Prior to the sensitivity study on the impact of biogenic emissions on air quality, the modeling results are compared to observational data, as well as to the concentrations obtained by other modeling teams of the Air Quality Model Evaluation International Initiative (AQMEII) study. Over Europe, three distinct emission inventories are used. Model performance is satisfactory for O3, PM10 and PM2.5 with all inventories with respect to the criteria described in the literature. Furthermore, the rmse and errors are lower than the average rmse and errors of the AQMEII simulations. Over North America, the model performance satisfies the criteria described in the literature for O3, PM10 and PM2.5. Polyphemus results are within the range of the AQMEII model results. Although the rmse and errors are higher than the average of the AQMEII simulations for O3, they are lower for PM10 and PM2.5. The impact of biogenic and anthropogenic emissions on O3 and PM concentrations is studied by removing alternatively biogenic and anthropogenic emissions in distinct simulations. Because biogenic species interact strongly with NOx, the impact of biogenic emissions on O3 concentrations varies with variations of the Volatile Organic Compound (VOC)/NOx ratio. This impact is larger over NA than Europe. O3 decreases by 10–11% on average over Europe and 20% over NA. Locally, the relative impact is also higher in NA (60% maximum) than in Europe (35% maximum). O3 decreases near large urban centers where biogenic emissions are large (e.g. Los Angeles, Chicago, Houston in NA, Milan in Europe). Most of secondary organic aerosols (SOA) formed at the continental scale over Europe and NA are biogenic aerosols. Eliminating biogenic emissions reduces SOA by 72–88% over Europe and by 90% over NA. However, biogenic SOA are not only impacted by biogenic but also by anthropogenic emissions: eliminating all anthropogenic emissions affects oxidant levels and the absorbing carbon mass, reducing the formation of SOA by 15–16% over Europe and by about 10% over NA; Furthermore, locally, the reduction may be as large as 50%, especially over large urban centers in Europe and NA. (10.1016/j.atmosenv.2011.10.046)
  DOI : 10.1016/j.atmosenv.2011.10.046
• Does Pupil Constriction under Blue and Green Monochromatic Light Exposure Change with Age?
  
  • Daneault Véronique
  • Vandewalle Gilles
  • Hébert Marc
  • Teikari Petteri
  • Mure Ludovic
  • Doyon Julien
  • Gronfier Claude
  • Cooper Howard
  • Dumont Marie
  • Carrier Julie
  Journal of Biological Rhythms, SAGE Publications, 2012, 27 (3), pp.257-264. Many nonvisual functions are regulated by light through a photoreceptive system involving melanopsin-expressing retinal ganglion cells that are maximally sensitive to blue light. Several studies have suggested that the ability of light to modulate circadian entrainment and to induce acute effects on melatonin secretion, subjective alertness, and gene expression decreases during aging, particularly for blue light. This could contribute to the documented changes in sleep and circadian regulatory processes with aging. However, age-related modification in the impact of light on steady-state pupil constriction, which regulates the amount of light reaching the retina, is not demonstrated. We measured pupil size in 16 young (22.8 ± 4 years) and 14 older (61 ± 4.4 years) healthy subjects during 45-second exposures to blue (480 nm) and green (550 nm) monochromatic lights at low (7 × 10 12 photons/cm 2 /s), medium (3 × 10 13 photons/cm 2 /s), and high (10 14 photons/cm 2 /s) irradiance levels. Results showed that young subjects had consistently larger pupils than older subjects for dark adaptation and during all light exposures. Steady-state pupil constriction was greater under blue than green light exposure in both age groups and increased with increasing irradiance. Surprisingly, when expressed in relation to baseline pupil size, no significant age-related differences were observed in pupil constriction. The observed reduction in pupil size in older individuals, both in darkness and during light exposure, may reduce retinal illumination and consequently affect nonvisual responses to light. The absence of a significant difference between age groups for relative steady-state pupil constriction suggests that other factors such as tonic, sympathetic control of pupil dilation, rather than light sensitivity per se, account for the observed age difference in pupil size regulation. Compared to other nonvisual functions, the light sensitivity of steady-state pupil constriction appears to remain relatively intact and is not profoundly altered by age. (10.1177/0748730412441172)
  DOI : 10.1177/0748730412441172
• Selected topics in multiscale data assimilation
  
  • Bocquet Marc
  • Wu Lin
  • Chevallier Frédéric
  • Koohkan Mohammad Reza
  , 2014, Special Issue, pp.415-431. (10.1093/acprof:oso/9780198723844.003.0018)
  DOI : 10.1093/acprof:oso/9780198723844.003.0018
• An introduction to inverse modelling and parameter estimation for atmosphere and ocean sciences
  
  • Bocquet Marc
  , 2012, Special Issue, pp.461-493.
• The HEROIC project : coordinated efforts towards the harmonization and cross-fertilization of human and environmental risk assessment of chemical substances
  
  • Capri Ettore
  • Aicher Lothar
  • Barcelo Damià
  • Ciffroy Philippe
  • Faust Michael
  • Glass Richard
  • Machera Kiki
  • Pery Alexandre R.R.
  • Schuurmann Gerrit
  • Wilks Martin
  , 2012. Today, human risk assessment (HRA) and environmental risk assessment (ERA) are typically separated. There is a lack of mutual understanding between experts and data from toxicological and ecotoxicological studies are not readily accessible by risk assessors of the two disciplines. The need for RA will continue to increase (e.g. REACH or toxicity of mixtures) along with budget restrictions and political and public pressure to reduce the number of animal tests. Therefore more cost effective, predictive and rapid tests for high quality sustainable RA are needed, including a better exploitation of existing data. The HEROIC project - a coordination action of the 7th FP - will provide a platform for networking among all the relevant stakeholders in the RA value chain and will provide them with the most relevant background information to contribute to the development of harmonised approaches which meet the challenges of RA. The project will enable the improvement and harmonisation of tools and methods in RA, by exploring how data generated in ecotoxicology and human toxicology can be applied across disciplines for integrated RA, and develop a framework for integrated methodologies and approaches for RA. This will increase transparency in RA and allow better risk communication to maintain public trust and to give unambiguous guidance for improved risk management. HEROIC starts with a comprehensive landscaping exercise to identify common methodological and data needs in current human and environmental risk assessment practices. We will then evaluate existing in-vivo, in-vitro and in-silico methods for hazard and exposure assessment. The selection process ranks and weights data based on their reliability and relevance and uses a Weight-of-Evidence approach to integrate such information to develop an Integrated Testing Strategy (ITS) for decision making. A dedicated web portal called 'Tox-Hub' that presents information from diverse sources and that functions as a central point of access to the most relevant toxicological and ecotoxicological information will be created. A diverse range of dedicated activities is planned for information, dissemination, capacity building and communication. These coordinating activities will result in enhanced sharing of knowledge, building consensus and development of clear, easily understood, transparent and unambiguous integrated RA procedures.
• Ensemble forecasting coupled with data assimilation, and threshold exceedance detection on Prev'Air
  
  • Debry Edouard
  • Mallet Vivien
  • Malherbe Laure
  • Meleux Frédérik
  • Bessagnet Bertrand
  • Rouil Laurence
  , 2014, pp.211-214. In this study the benefits of coupling data assimilation with ensemble forecasting are demonstrated for the production of improved air quality forecasts and detection of threshold exceedances. (10.1007/978-94-007-5577-2_36)
  DOI : 10.1007/978-94-007-5577-2_36
• Coupling traffic, pollutant emission, air and water quality models: Technical review and perspectives
  
  • Fallahshorshani Masoud
  • André Michel
  • Bonhomme Céline
  • Seigneur Christian
  , 2012, 48, pp.1794-1804. Models for simulating air quality due to vehicles and their effect on runoff quality in an urban environment and their coupling are examined. In order to achieve this aim, the selection of models (traffic, emission, atmospheric dispersion, stormwater) must be carefully made according to the special requirements and level of details needed for the integrated system. Therefore a variety of these models are reviewed. Although a fair amount of research has been conducted in the past to link air pollution and road traffic, many questions related to spatio-temporal scales, domains of validity, consistency among models and interfaces between models remain open. Furthermore, the link between traffic emissions, atmospheric deposition and the contamination of water runoff in urban areas has not been treated yet in a comprehensive manner. The aim of this study is to review the current status of the relationships between traffic, emissions and air and water quality models, to recommend an integrated modelling approach and to propose some directions for advancing the state of the art.
• Parameter-field estimation for atmospheric dispersion: application to the Chernobyl accident using 4D-Var
  
  • Bocquet Marc
  Quarterly Journal of the Royal Meteorological Society, Wiley, 2012, 138 (664), pp.664-681. Atmospheric chemistry and air-quality numerical models are driven by uncertain forcing fields: emissions, boundary conditions, wind fields, vertical turbulent diffusivity, kinetic chemical rates, etc. Data assimilation can help to assess these parameters or fields of parameters. Because such parameters are often much more uncertain than the fields diagnosed in meteorology and oceanography, data assimilation is much more of an inverse modelling challenge in this context. In this article these ideas are experimented with by revisiting the Chernobyl accident dispersion event over Europe. A fast four-dimensional variational scheme (4D-Var) is developed, which seems appropriate for the retrieval of large parameter fields from large observation sets and the retrieval of parameters that are nonlinearly related to concentrations. The 4D-Var, and especially an approximate adjoint of the transport model, is tested and validated using several advection schemes that are influential on the forward simulation as well as on the data-assimilation results. Firstly, the inverse modelling system is applied to the assessment of the dry and wet deposition parameters. It is then applied to the retrieval of the emission field alone, the joint optimization of removal-process parameters and source parameters and the optimization of larger parameter fields such as horizontal and vertical diffusivities or the dry-deposition velocity field. The physical parameters used so far in the literature for the Chernobyl dispersion simulation are partly supported by this study. The crucial question of deciding whether such an inversion is merely a tuning of parameters or a retrieval of physically meaningful quantities is discussed. Even though inversion of parameter fields may fail to determine physical values for the parameters, it achieves statistical adaptation that partially corrects for model errors and, using the inverted parameter fields, leads to considerable improvement in the simulation scores. Copyright c 2011 Royal Meteorological Society (10.1002/qj.961)
  DOI : 10.1002/qj.961
• Uncertainty Estimation and Decomposition based on Monte Carlo and Multimodel Photochemical Simulations
  
  • Garaud Damien
  • Mallet Vivien
  , 2012, pp.33. This paper investigates (1) the main sources of uncertainties in ground-level ozone simulations, (2) the best method to estimate them, and (3) the decomposition of the errors in measurement, representativeness and modeling errors. It first compares the Monte Carlo approach, solely based on perturbations in the input fields and parameters, with the multimodel approach, which relies on an ensemble of models with different chemical, physical and numerical formulations. Two ensembles of 100 members are generated for the full year 2001 over Europe. Their uncertainty estimations for ground-level ozone are compared. For both ensembles, we select a sub-ensemble that minimizes the variance of the rank histogram, so that it is supposed to better represent the uncertainties. The multimodel (sub-)ensemble shows more variability and seems to better represent the uncertainties (especially for the localization of the covariances) than the Monte Carlo (sub-)ensemble. The main sources of the uncertainties originating in the input fields and parameters are then identified with a linear regression of the output ozone concentrations on the applied perturbations. The uncertainty ranges due to the different input fields and parameters are computed at urban, rural and background observation stations. For both the multimodel ensemble and the Monte Carlo ensemble, ozone boundary conditions play an important role, even at continental scale; but many other fields or parameters appear to be a significant source of uncertainty. The discrepancies between observations and model simulations are due to measurement errors, representativeness errors and modeling errors (i.e., shortcomings in the model formulation or in its input data). Using two independent methods, we estimate the variance of the representativeness errors. We conclude that the measurement errors are comparatively low, and that the representativeness errors can explain at least a third of the variance of the discrepancies.
• Estimation of errors in the inverse modeling of accidental release of atmospheric pollutant: Application to the reconstruction of the cesium-137 and iodine-131 source terms from the Fukushima Daiichi power plant
  
  • Winiarek Victor
  • Bocquet Marc
  • Saunier Olivier
  • Mathieu Anne
  Journal of Geophysical Research: Atmospheres, American Geophysical Union, 2012, 117 (D05122). 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 representativity of the measurements, those that are instrumental, and those attached to the prior knowledge on the variables one seeks to retrieve. In the case of an accidental release of pollutant, the reconstructed source is 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. We propose to use an estimation method for the errors' amplitude based on the maximum likelihood principle. Under semi-Gaussian assumptions, it takes into account, without approximation, the positivity assumption on the source. We apply the method to the estimation of the Fukushima Daiichi source term using activity concentrations in the air. The results are compared to an L-curve estimation technique and to Desroziers's scheme. The total reconstructed activities significantly depend on the chosen method. Because of the poor observability of the Fukushima Daiichi emissions, these methods provide lower bounds for cesium-137 and iodine-131 reconstructed activities. These lower bound estimates, 1.2 × 1016 Bq for cesium-137, with an estimated standard deviation range of 15%-20%, and 1.9 − 3.8 × 1017 Bq for iodine-131, with an estimated standard deviation range of 5%-10%, are of the same order of magnitude as those provided by the Japanese Nuclear and Industrial Safety Agency and about 5 to 10 times less than the Chernobyl atmospheric releases. (10.1029/2011JD016932)
  DOI : 10.1029/2011JD016932
• What eddy-covariance measurements tell us about prior land flux errors in CO2-flux inversion schemes
  
  • Chevallier Frédéric
  • Wang Tao
  • Ciais Philippe
  • Maignan Fabienne
  • Bocquet Marc
  • Arain M. Altaf
  • Cescatti Alessandro
  • Chen Jiquan
  • Dolman A. Johannes
  • Law Beverly E.
  • Margolis Hank A.
  • Montagnani Leonardo
  • Moors Eddy J.
  Global Biogeochemical Cycles, American Geophysical Union, 2012, 26 (GB1021). To guide the future development of CO2-atmospheric inversion modeling systems, we analyzed the errors arising from prior information about terrestrial ecosystem fluxes. We compared the surface fluxes calculated by a process-based terrestrial ecosystem model with daily averages of CO2 flux measurements at 156 sites across the world in the FLUXNET network. At the daily scale, the standard deviation of the model-data fit was 2.5 gC*m−2*d−1; temporal autocorrelations were significant at the weekly scale (>0.3 for lags less than four weeks), while spatial correlations were confined to within the first few hundred kilometers (<0.2 after 200 km). Separating out the plant functional types did not increase the spatial correlations, except for the deciduous broad-leaved forests. Using the statistics of the flux measurements as a proxy for the statistics of the prior flux errors was shown not to be a viable approach. A statistical model allowed us to upscale the site-level flux error statistics to the coarser spatial and temporal resolutions used in regional or global models. This approach allowed us to quantify how aggregation reduces error variances, while increasing correlations. As an example, for a typical inversion of grid point (300 km × 300 km) monthly fluxes, we found that the prior flux error follows an approximate e-folding correlation length of 500 km only, with correlations from one month to the next as large as 0.6. (10.1029/2010GB003974)
  DOI : 10.1029/2010GB003974
• Improvement of motion estimation by assessing the errors on the evolution equation
  
  • Herlin Isabelle
  • Béréziat Dominique
  • Mercier Nicolas
  , 2012, 2, pp.235-240. Image assimilation methods are nowadays widely used to retrieve motion from image sequences with heuristics on the underlying dynamics. A mathematical model on the temporal evolution of the motion field has to be chosen, according to these heuristics, that approximately describes the evolution of the velocity at a pixel over the sequence. In order to quantify this approximation, we add an error term in the evolution equation of the motion field and design a weak formulation of 4D-Var image assimilation. The designed cost function simultaneously depends on the initial motion field and on the error value at each time step. The BFGS solver performs minimization to retrieve both motion field and errors. The method is evaluated and quantified on twin experiments, as no ground truth would be available for real data. The results demonstrate that the motion field is better estimated thanks to the error control.
• A hydrophilic/hydrophobic organic ((HO)-O-2) aerosol model: Development, evaluation and sensitivity analysis
  
  • Couvidat Florian
  • Debry Edouard
  • Sartelet Karine
  • Seigneur Christian
  Journal of Geophysical Research: Atmospheres, American Geophysical Union, 2012, 117 (D10304). A secondary organic aerosol (SOA) model, the Hydrophilic/Hydrophobic Organic model ((HO)-O-2), is presented and evaluated over Europe. (HO)-O-2 uses surrogate organic molecules to represent the myriad of SOA species and distinguishes two kinds of surrogate species: hydrophilic species (which condense preferentially into an aqueous phase) and hydrophobic species (which condense only into an organic phase). These surrogate species are formed from the oxidation in the atmosphere of volatile organic compounds. (HO)-O-2 includes several important processes, including the effect of nitrogen oxides (NOX) on SOA formation, the dissociation of organic acids in an aqueous phase, the oligomerization of aldehydes, the non-ideality of the particle phase and the hygroscopicity of organics. Concentrations of organic aerosols were simulated over Europe from July 2002 to July 2003 for comparison with measurements of the European Monitoring Evaluation Program (EMEP). In (HO)-O-2, primary organic aerosols (POA) are considered as semi-volatile organic compounds (SVOC) present in both the gas phase and the particle phase. Taking into account the gas-phase fraction of SVOC increases significantly organic PM concentrations, particularly in winter, in better agreement with observations. The impacts on organic aerosol formation of ideality, of the choice of the parameterization for isoprene SOA formation, and of the OM/OC ratio of the model were also investigated. Assuming ideality in (HO)-O-2 was found to lead to a small decrease in OM. Compared to a two-product parameterization, the parameterization of Couvidat and Seigneur [2011] for SOA formation from isoprene oxidation leads to a significant increase in isoprene SOA by taking into account their hydrophilic properties and suggests that most models may currently underestimate isoprene SOA. (10.1029/2011JD017214)
  DOI : 10.1029/2011JD017214
• Coupling Traffic, Pollutant Emission, Air and Water Quality Models: Technical Review and Perspectives
  
  • Fallah Shorshani Masoud
  • Andre Michel
  • Bonhomme Céline
  • Seigneur Christian
  Procedia - Social and Behavioral Sciences, Elsevier, 2012 (48), pp.pp. 1794-1804. Models for simulating air quality due to vehicles and their effect on runoff quality in an urban environment and their coupling are examined. In order to achieve this aim, the selection of models (traffic, emission, atmospheric dispersion, stormwater) must be carefully made according to the special requirements and level of details needed for the integrated system. Therefore a variety of these models are reviewed. Although a fair amount of research has been conducted in the past to link air pollution and road traffic, many questions related to spatio-temporal scales, domains of validity, consistency among models and interfaces between models remain open. Furthermore, the link between traffic emissions, atmospheric deposition and the contamination of water runoff in urban areas has not been treated yet in a comprehensive manner. The aim of this study is to review the current status of the relationships between traffic, emissions and air and water quality models, to recommend an integrated modelling approach and to propose some directions for advancing the state of the art. (10.1016/j.sbspro.2012.06.1154)
  DOI : 10.1016/j.sbspro.2012.06.1154
• An optimal control methodology for plant growth--Case study of a water supply problem of sunflower
  
  • Wu Lin
  • Le Dimet François-Xavier
  • de Reffye Philippe
  • Hu Bao-Gang
  • Cournède Paul-Henry
  • Kang Meng-Zhen
  Mathematics and Computers in Simulation, Elsevier, 2012, 82 (5), pp.909-923. An optimal control methodology is proposed for plant growth. This methodology is demonstrated by solving a water supply problem for optimal sunflower fruit filling. The functional-structural sunflower growth is described by a dynamical system given soil water conditions. Numerical solutions are obtained through an iterative optimization procedure, in which the gradients of the objective function, i.e. the sunflower fruit weight, are calculated efficiently either with adjoint modeling or by differentiation algorithms. Further improvements in sunflower yield have been found compared to those obtained using genetic algorithms in our previous studies. The optimal water supplies adapt to the fruit filling. For instance, during the mid-season growth, the supply frequency condenses and the supply amplitude peaks. By contrast, much less supplies are needed during the early and ending growth stages. The supply frequency is a determining factor, whereas the sunflower growth is less sensitive to the time and amount of one specific irrigation. These optimization results agree with common qualitative agronomic practices. Moreover they provide more precise quantitative control for sunflower growth. (10.1016/j.matcom.2011.12.007)
  DOI : 10.1016/j.matcom.2011.12.007
• A Lagrangian model of air-mass photochemistry and mixing using a trajectory ensemble: the Cambridge Tropospheric Trajectory model of Chemistry And Transport (CiTTyCAT) version 4.2
  
  • Pugh T. A. M.
  • Cain M.
  • Methven J.
  • Wild O.
  • Arnold S. R.
  • Real Elsa
  • Law Kathy S.
  • Emmerson K. M.
  • Owen M. S.
  • Pyle J. A.
  • Hewitt C. N.
  • Mackenzie A. R.
  Geoscientific Model Development, European Geosciences Union, 2012, 5 (1), pp.193-221. A Lagrangian model of photochemistry and mixing is described (CiTTyCAT, stemming from the Cambridge Tropospheric Trajectory model of Chemistry And Transport), which is suitable for transport and chemistry studies throughout the troposphere. Over the last five years, the model has been developed in parallel at several different institutions and here those developments have been incorporated into one "community" model and documented for the first time. The key photochemical developments include a new scheme for biogenic volatile organic compounds and updated emissions schemes. The key physical development is to evolve composition following an ensemble of trajectories within neighbouring air-masses, including a simple scheme for mixing between them via an evolving "background profile", both within the boundary layer and free troposphere. The model runs along trajectories pre-calculated using winds and temperature from meteorological analyses. In addition, boundary layer height and precipitation rates, output from the analysis model, are interpolated to trajectory points and used as inputs to the mixing and wet deposition schemes. The model is most suitable in regimes when the effects of small-scale turbulent mixing are slow relative to advection by the resolved winds so that coherent air-masses form with distinct composition and strong gradients between them. Such air-masses can persist for many days while stretching, folding and thinning. Lagrangian models offer a useful framework for picking apart the processes of air-mass evolution over inter-continental distances, without being hindered by the numerical diffusion inherent to global Eulerian models. The model, including different box and trajectory modes, is described and some output for each of the modes is presented for evaluation. The model is available for download from a Subversion-controlled repository by contacting the corresponding authors. (10.5194/gmd-5-193-2012)
  DOI : 10.5194/gmd-5-193-2012
• Model evaluation and ensemble modelling of surface-level ozone in Europe and North America in the context of AQMEII
  
  • Solazzo Efisio
  • Bianconi Roberto
  • Vautard Robert
  • Appel K. Wyat
  • Moran Michael D.
  • Hogrefe Christian
  • Bessagnet Bertrand
  • Brandt Jorgen
  • Christensen Jesper H.
  • Chemel Charles
  • Coll Isabelle
  • Denier van Der Gon Hugo
  • Ferreira Joana
  • Forkel Renate
  • Francis Xavier V.
  • Grell George
  • Grossi Paola
  • Hansen Ayoe B.
  • Jericevic Amela
  • Kraljevic Luksa
  • Miranda Ana Isabel
  • Nopmongcol Uarporn
  • Pirovano Guido
  • Prank Marje
  • Riccio Angelo
  • Sartelet Karine N.
  • Schaap Martijn
  • Silver Jeremy D.
  • Sokhi Ranjeet S.
  • Vira Julius
  • Werhahn Johannes
  • Wolke Ralf
  • Yarwood Greg
  • Zhang Junhua
  • Rao S. Trivikrama
  • Galmarini Stefano
  Atmospheric Environment, Elsevier, 2012, 53, pp.60-74. More than ten state-of-the-art regional air quality models have been applied as part of the Air Quality Model Evaluation International Initiative (AQMEII). These models were run by twenty independent groups in Europe and North America. Standardised modelling outputs over a full year (2006) from each group have been shared on the web-distributed ENSEMBLE system, which allows for statistical and ensemble analyses to be performed by each group. The estimated ground-level ozone mixing ratios from the models are collectively examined in an ensemble fashion and evaluated against a large set of observations from both continents. The scale of the exercise is unprecedented and offers a unique opportunity to investigate methodologies for generating skilful ensembles of regional air quality models outputs. Despite the remarkable progress of ensemble air quality modelling over the past decade, there are still outstanding questions regarding this technique. Among them, what is the best and most beneficial way to build an ensemble of members? And how should the optimum size of the ensemble be determined in order to capture data variability as well as keeping the error low? These questions are addressed here by looking at optimal ensemble size and quality of the members. The analysis carried out is based on systematic minimization of the model error and is important for performing diagnostic/probabilistic model evaluation. It is shown that the most commonly used multi-model approach, namely the average over all available members, can be outperformed by subsets of members optimally selected in terms of bias, error, and correlation. More importantly, this result does not strictly depend on the skill of the individual members, but may require the inclusion of low-ranking skill-score members. A clustering methodology is applied to discern among members and to build a skilful ensemble based on model association and data clustering, which makes no use of priori knowledge of model skill. Results show that, while the methodology needs further refinement, by optimally selecting the cluster distance and association criteria, this approach can be useful for model applications beyond those strictly related to model evaluation, such as air quality forecasting. (10.1016/j.atmosenv.2012.01.003)
  DOI : 10.1016/j.atmosenv.2012.01.003
• Operational model evaluation for particulate matter in Europe and North America in the context of AQMEII
  
  • Solazzo Efisio
  • Bianconi Roberto
  • Pirovano Guido
  • Matthias Volker
  • Vautard Robert
  • Moran Michael D.
  • Appel K. Wyat
  • Bessagnet Bertrand
  • Brandt Jorgen
  • Christensen Jesper H.
  • Chemel Charles
  • Coll Isabelle
  • Ferreira Joana
  • Forkel Renate
  • Francis Xavier V.
  • Grell Georg
  • Grossi Paola
  • Hansen Ayoe B.
  • Miranda Ana Isabel
  • Nopmongcol Uarporn
  • Prank Marje
  • Sartelet Karine N.
  • Schaap Martijn
  • Silver Jeremy D.
  • Sokhi Ranjeet S.
  • Vira Julius
  • Werhahn Johannes
  • Wolke Ralf
  • Yarwood Greg
  • Zhang Junhua
  • Rao S. Trivikrama
  • Galmarini Stefano
  Atmospheric Environment, Elsevier, 2012, 53, pp.75-92. Ten state-of-the-science regional air quality (AQ) modeling systems have been applied to continental-scale domains in North America and Europe for full-year simulations of 2006 in the context of Air Quality Model Evaluation International Initiative (AQMEII), whose main goals are model inter-comparison and evaluation. Standardised modeling outputs from each group have been shared on the web-distributed ENSEMBLE system, which allows statistical and ensemble analyses to be performed. In this study, the one-year model simulations are inter-compared and evaluated with a large set of observations for ground-level particulate matter (PM10 and PM2.5) and its chemical components. Modeled concentrations of gaseous PM precursors, SO2 and NO2, have also been evaluated against observational data for both continents. Furthermore, modeled deposition (dry and wet) and emissions of several species relevant to PM are also inter-compared. The unprecedented scale of the exercise (two continents, one full year, fifteen modeling groups) allows for a detailed description of AQ model skill and uncertainty with respect to PM. Analyses of PM10 yearly time series and mean diurnal cycle show a large underestimation throughout the year for the AQ models included in AQMEII. The possible causes of PM bias, including errors in the emissions and meteorological inputs (e.g., wind speed and precipitation), and the calculated deposition are investigated. Further analysis of the coarse PM components, PM2.5 and its major components (SO4, NH4, NO3, elemental carbon), have also been performed, and the model performance for each component evaluated against measurements. Finally, the ability of the models to capture high PM concentrations has been evaluated by examining two separate PM2.5 episodes in Europe and North America. A large variability among models in predicting emissions, deposition, and concentration of PM and its precursors during the episodes has been found. Major challenges still remain with regards to identifying and eliminating the sources of PM bias in the models. Although PM2.5 was found to be much better estimated by the models than PM10, no model was found to consistently match the observations for all locations throughout the entire year. (10.1016/j.atmosenv.2012.02.045)
  DOI : 10.1016/j.atmosenv.2012.02.045
• An atmospheric emission inventory of anthropogenic and biogenic sources for Lebanon
  
  • Waked Antoine
  • Afif Charbel
  • Seigneur Christian
  Atmospheric Environment, Elsevier, 2012, 50, pp.88--96. A temporally-resolved and spatially-distributed emission inventory was developed for Lebanon to provide quantitative information for air pollution studies as well as for use as input to air quality models. This inventory covers major anthropogenic and biogenic sources in the region with 5 km spatial resolution for Lebanon and 1 km spatial resolution for its capital city Beirut and its suburbs. The results obtained for CO, NOx, SO2, NMVOC, NH3, PM10 and PM2.5 for the year 2010 were 563, 75, 62, 115, 4,12, and 9 Gg, respectively. About 93% of CO emissions, 67% of NMVOC emissions and 52% of NOx emissions are calculated to originate from the on-road transport sector while 73% of SO2 emissions, 62% of PM10 emissions and 59% of PM2.5 emissions are calculated to originate from power plants and industrial sources. The spatial allocation of emissions shows that the city of Beirut and its suburbs encounter a large fraction of the emissions from the on-road transport sector while urban areas such as Zouk Mikael, Jieh, Chekka and Selaata are mostly affected by emissions originating from the industrial and energy production sectors. Temporal profiles were developed for several emission sectors. (C) 2012 Elsevier Ltd. All rights reserved. (10.1016/j.atmosenv.2011.12.058)
  DOI : 10.1016/j.atmosenv.2011.12.058
• Eyjafjallajökull ash concentrations derived from both lidar and modeling
  
  • Chazette Patrick
  • Bocquet Marc
  • Royer Philippe
  • Winiarek Victor
  • Raut Jean-Christophe
  • Labazuy Philippe
  • Gouhier Mathieu
  • Lardier Mélody
  • Cariou Jean-Pierre
  Journal of Geophysical Research: Atmospheres, American Geophysical Union, 2012, 117, pp.D00U14. Following the eruption of the Icelandic volcano Eyjafjallajökull on the 14 April 2010, ground-based N2-Raman lidar (GBL) measurements were used to trace the temporal evolution of the ash plume from 16 to 20 April 2010 above the southwestern suburb of Paris. The nighttime overpass of the Cloud-Aerosol LIdar with Orthogonal Polarization onboard Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation satellite (CALIPSO/CALIOP) on 17 April 2010 was an opportunity to complement GBL observations. The plume shape retrieved from GBL has been used to assess the size range of the particles size. The lidar-derived aerosol mass concentrations (PM) have been compared with model-derived PM concentrations held in the Eulerian model Polair3D transport model, driven by a source term inferred from the SEVIRI sensor onboard Meteosat satellite. The consistency between model and ground-based wind lidar and CALIOP observations has been checked. The spatial and temporal structures of the ash plume as estimated by each instrument and by the Polair3D simulations are in agreement. The ash plume was associated with a mean aerosol optical thickness of 0.1{plus minus}0.06 and 0.055{plus minus}0.053 for GBL (355 nm) and CALIOP (532 nm), respectively. Such values correspond to ash mass concentrations of ~400{plus minus}160 and ~720{plus minus}670 µg m-3, respectively, within the ash plume, which was lower than 0.5 km in width. The relative uncertainty is ~75% and mainly due to the assessment of the specific cross-section assuming an aerosol density of 2.6 g cm-3. The simulated ash plume is smoother leading to integrated mass of the same order of magnitude (between 50 and 250 mg m-2) (10.1029/2011JD015755)
  DOI : 10.1029/2011JD015755