Simulation of ozone production in a complex circulation region using nested grids

International audienceDuring ESCOMPTE precampaign (15 June to 10 July 2000), three days of intensive pollution (IOP0) have been observed and simulated. The comprehensive RAMS model, version 4.3, coupled online with a chemical module including 29 species, has been used to follow the chemistry of the zone polluted over southern France. This online method can be used because the code is paralleled and the SGI 3800 computer is very powerful. Two runs have been performed: run1 with one grid and run2 with two nested grids. The redistribution of simulated chemical species (ozone, carbon monoxide, sulphur dioxide and nitrogen oxides) was compared to aircraft measurements and surface stations. The 2-grid run has given substantially better results than the one-grid run only because the former takes the outer pollutants into account. This online method helps to explain dynamics and to retrieve the chemical species redistribution with a good agreement

GeoQAIR : Quantification de l'apport d'une plateforme d'observations Géostationnaires pour la surveillance de la Qualité de l'AIR en Europe

Monitoring of air quality (AQ) and its transport at the continental scale, as well as the development of efficient forecast systems for air quality is one of the issues included in the GMES (Global Monitoring for Environment and Security) European Programme for the establishment of a European capacity for Earth Observation. The availability of satellite instruments which have the ability to monitor tropospheric ozone in the lowermost troposphere would be a step forward for this system. To monitor small scale and short term processes as involved in pollution event development, a geostationary Earth orbit (GEO) observing system is particularly well adapted. Future GEO missions dedicated to air quality monitoring using thermal infrared (TIR) instruments are planned to be operating over the USA, Japan and Korea, while existing and planned missions over Europe are not well adapted for this task. One of the objectives of the GeoQAIR project is to evaluate different satellite instrument concepts for their ability to monitor AQ and in particular quantify the possible impact for AQ forecasting. Four instruments have been considered for this study: the existing instrument IASI on MetOp-A (Low Earth Orbit - LEO - mission), the planned IASI-NG on the EPS-SG platform (LEO mission) and IRS on Sentinel4/MTG platform (GEO mission mainly dedicated to meteorology) and a new GEO mission concept, MAGEAQ, dedicated to AQ monitoring and proposed at the last Earth Explorer 8 call of ESA. Pseudo-observations for the four instruments have been generated to simulate one month of ozone observations over Europe. About 45 millions of individual measurements have been simulated using the EGI facilities. A first analysis of the performances of the different instruments to measure ozone in the lowermost troposphere demonstrates that the short time and space scale processes implied in air pollution development will not be correctly apprehended with the current existing and planned missions. Dedicated instrument with sufficient spectral resolution and signal to noise ratio, as proposed within the MAGEAQ mission concept, are necessary to correctly represent these processes

Results of the first European Source Apportionment intercomparison for Receptor and Chemical Transport Models

In this study, the performance of the source apportionment model applications were evaluated by comparing the model results provided by 44 participants adopting a methodology based on performance indicators: z-scores and RMSEu, with pre-established acceptability criteria. Involving models based on completely different and independent input data, such as receptor models (RMs) and chemical transport models (CTMs), provided a unique opportunity to cross-validate them. In addition, comparing the modelled source chemical profiles, with those measured directly at the source contributed to corroborate the chemical profile of the tested model results. The most used RM was EPA- PMF5. RMs showed very good performance for the overall dataset (91% of z-scores accepted) and more difficulties are observed with SCE time series (72% of RMSEu accepted). Industry resulted the most problematic source for RMs due to the high variability among participants. Also the results obtained with CTMs were quite comparable to their ensemble reference using all models for the overall average (>92% of successful z-scores) while the comparability of the time series is more problematic (between 58% and 77% of the candidates’ RMSEu are accepted). In the CTM models a gap was observed between the sum of source contributions and the gravimetric PM10 mass likely due to PM underestimation in the base case. Interestingly, when only the tagged species CTM results were used in the reference, the differences between the two CTM approaches (brute force and tagged species) were evident. In this case the percentage of candidates passing the z-score and RMSEu tests were only 50% and 86%, respectively. CTMs showed good comparability with RMs for the overall dataset (83% of the z-scores accepted), more differences were observed when dealing with the time series of the single source categories. In this case the share of successful RMSEu was in the range 25% - 34%.JRC.C.5-Air and Climat

Analyse des données satellitaires de l'instrument IASI/MetOp-A : quelles possibilités pour la surveillance de la qualité de l'air en Europe ?

Analyse des données satellitaires de l'instrument IASI/MetOp-A : quelles possibilités pour la surveillance de la qualité de l'air en Europe

Etude numérique multi échelle des processus dynamiques et photochimique contrôlant les distributions troposphériques de l'ozone et de ses précurseurs (impact des circulations locales et de la convection profonde dans le cadre de l'expérience INDOEX)

CLERMONT FD-BCIU Sci.et Tech. (630142101) / SudocSudocFranceF

Assimilation des observations pour la modélisation de la qualité de l'air

Lors de ce travail de thèse, nous nous sommes focalisés sur l'assimilation des observations d'ozone de surface au sein du modèle CHIMERE sur le continent Européen à l'aide d'un filtre de Kalman d'Ensemble. Une première expérience d'assimilation a été présentée et évaluée pour un épisode de pollution photochimique. La comparaison entre l'analyse et la simulation de référence montre d'excellents résultats. On note en effet une amélioration pour l'ensemble des indicateurs statistiques et pour tous les types de stations. A partir de cette expérience, différents paramètres de l'algorithme d'assimilation ont été optimisés, en particulier la variance des erreurs d'observation et la variance/covariance de l'erreur d'ébauche. Nous avons alors employé différents diagnostics a posteriori réalisés dans l'espace des observations. Ces diagnostics nous ont permis d'estimer l'erreur modèle et d'observation et de vérifier leur cohérence avec les innovations obtenues. Enfin, nous avons étudié la possibilité de prescrire les valeurs diagnostiquées de ces erreurs au cours des cycles d'analyse et de prévisions. Il apparaît que les erreurs ont un cycle diurne marqué qu'il faut prendre en compte et qu'une part importante de l'erreur est causée par la représentativité spatiale. Par ailleurs, nous avons développé une approche basée sur la perturbation des paramètres physiques du modèle, mais qui ne génère pas assez de variabilité. Finalement, nous avons pu montrer la robustesse de ce système d'assimilation et la reproductibilité des résultats par rapport à ces paramètres, pour l'épisode de pollution et pour une expérience d'assimilation sur un été.In this thesis, an Ensemble Kalman Filter has been coupled to the CHIMERE chemical transport model in order to assimilate ozone ground measurements at continental scale. A first assimilation experiment during a summertime photochemical pollution episode is presented and evaluated. The comparison between the analysis and the reference run shows excellent results. We note for the analysis an improvement regarding to the whole set of statistical indicators and for all stations types. Based on this experiment, different parameters of the data assimilation algorithm were optimized, in particular the observation space were employed. These diagnostics were used to estimate model and observation errors and to verify that they were consistent with obtained innovations. Finally, we investigated the application of diagnosed error values during an analysis-forecast cycle. It appears that errors have a clear diurnal cycle which needs to be taken into account and that an important part of these errors related to the spatial representativeness. We also developed an approach based on perturbations of model physical parameters but which fails in generating enough variability in the model ensemble. Finally, we demonstrate the robustness of the data assimilation system and reproducibility of the results with respect to the chosen parameters, for the specific pollution and for an entire summer assimilation period.PARIS7-Bibliothèque centrale (751132105) / SudocSudocFranceF