Observation Impact over the Antarctic During the Concordiasi Field Campaign

The impact of observations on analysis uncertainty and forecast performance was investigated for Austral Spring 2010 over the Southern polar area for four different systems (NRL, GMAO, ECMWF and Meteo-France), at the time of the Concordiasi field experiment. The largest multi model variance in 500 hPa height analyses is found in the southern sub-Antarctic oceanic region, where there are strong atmospheric dynamics, rapid forecast error growth, and fewer upper air wind observation data to constrain the analyses. In terms of data impact the most important observation components are shown to be AMSU, IASI, AIRS, GPS-RO, radiosonde, surface and atmospheric motion vector observations. For sounding data, radiosondes and dropsondes, one can note a large impact of temperature at low levels and a large impact of wind at high levels. Observing system experiments using the Concordiasi dropsondes show a large impact of the observations over the Antarctic plateau extending to lower latitudes with the forecast range, with a large impact around 50 to 70deg South. These experiments indicate there is a potential benefit of better using radiance data over land and sea-ice and innovative atmospheric motion vectors obtained from a combination of various satellites to fill the current data gaps and improve NWP in this region

Towards IASI-New Generation (IASI-NG): impact of improved spectral resolution and radiometric noise on the retrieval of thermodynamic, chemistry and climate variables

Besides their strong contribution to weather forecast improvement through data assimilation, thermal infrared sounders onboard polar-orbiting platforms are now playing a key role for monitoring atmospheric composition changes. The Infrared Atmospheric Sounding Interferometer (IASI) instrument developed by the French space agency (CNES) and launched by Eumetsat onboard the Metop satellite series is providing essential inputs for weather forecasting and pollution/climate monitoring owing to its smart combination of large horizontal swath, good spectral resolution and high radiometric performance. EUMETSAT is currently preparing the next polar-orbiting program (EPS-SG) with the Metop-SG satellite series that should be launched around 2020. In this framework, CNES is studying the concept of a new instrument, the IASI-New Generation (IASI-NG), characterized by an improvement of both spectral and radiometric characteristics as compared to IASI, with three objectives: (i) continuity of the IASI/Metop series; (ii) improvement of vertical resolution; (iii) improvement of the accuracy and detection threshold for atmospheric and surface components. In this paper, we show that an improvement of spectral resolution and radiometric noise fulfill these objectives by leading to (i) a better vertical coverage in the lower part of the troposphere, thanks to the increase in spectral resolution; (ii) an increase in the accuracy of the retrieval of several thermodynamic, climate and chemistry variables, thanks to the improved signal-to-noise ratio as well as less interferences between the signatures of the absorbing species in the measured radiances. The detection limit of several atmospheric species is also improved. We conclude that IASI-NG has the potential for strongly benefiting the numerical weather prediction, chemistry and climate communities now connected through the European GMES/Copernicus initiative

Towards IASI-New Generation (IASI-NG): impact of improved spectral resolution and radiometric noise on the retrieval of thermodynamic, chemistry and climate variables

Besides their strong contribution to weather forecast improvement through data assimilation, thermal infrared sounders onboard polar-orbiting platforms are now playing a key role for monitoring atmospheric composition changes. The Infrared Atmospheric Sounding Interferometer (IASI) instrument developed by the French space agency (CNES) and launched by Eumetsat onboard the Metop satellite series is providing essential inputs for weather forecasting and pollution/climate monitoring owing to its smart combination of large horizontal swath, good spectral resolution and high radiometric performance. EUMETSAT is currently preparing the next polar-orbiting program (EPS-SG) with the Metop-SG satellite series that should be launched around 2020. In this framework, CNES is studying the concept of a new instrument, the IASI-New Generation (IASI-NG), characterized by an improvement of both spectral and radiometric characteristics as compared to IASI, with three objectives: (i) continuity of the IASI/Metop series; (ii) improvement of vertical resolution; (iii) improvement of the accuracy and detection threshold for atmospheric and surface components. In this paper, we show that an improvement of spectral resolution and radiometric noise fulfill these objectives by leading to (i) a better vertical coverage in the lower part of the troposphere, thanks to the increase in spectral resolution; (ii) an increase in the accuracy of the retrieval of several thermodynamic, climate and chemistry variables, thanks to the improved signal-to-noise ratio as well as less interferences between the signatures of the absorbing species in the measured radiances. The detection limit of several atmospheric species is also improved. We conclude that IASI-NG has the potential for strongly benefiting the numerical weather prediction, chemistry and climate communities now connected through the European GMES/Copernicus initiative

Aérosols: Document du Comité Scientifique Consultatif de Météo-France 2020

Document du Comité Scientifique Consultatif de Météo-France 202

Aérosols: Document du Comité Scientifique Consultatif de Météo-France 2020

Document du Comité Scientifique Consultatif de Météo-France 202

Evaluation of the benefits of assimilating IASI-NG radiances for ozone in a Chemistry-Transport Model

International audienceThe next generation of infrared atmospheric sounding interferometer, IASI-NG, will be put into orbit soon. It contains twice more channels than it predecessor IASI. Beside the awaited improvements for numerical weather prediction (NWP), our study aims at evaluating the benefits of IASI-NG radiance assimilation in a chemistry-transport model (CTM) for ozone, compared to IASI. As IASI-NG is not yet in orbit, we used an Observing System Simulation Experiments method (OSSE) both to simulate IASI and IASI-NG synthetic data and to evaluate the impact of their assimilation. The selected time period ranges from 15/05/2019 to 31/08/2019. Our OSSE framework uses the CTM MOCAGE developed at Météo-France, which models both stratosphere and troposphere, over the globe. The ozone spectral band in the long wave band is 980 – 1100cm-1; with 468 channels for IASI, and 936 channels for IASI-NG. We carefully evaluated the ozone Jacobians for all channels in this band, over various scenes. This helped us to reduce the spectral band to 993 – 1069 cm-1, counting 608 IASI-NG channels and 304 IASI channels. RTTOV has been used as a radiative transfer model in this study, both for Jacobian computation and for the direct assimilation of radiances. After having created the synthetic observations from the Nature Run for both IASI and IASI-NG, we evaluated their differences with the Control Run, in order to evaluated their characteristics for assimilation. Then, assimilation trials of IASI and IASI-NG synthetic radiances will be evaluated to assess the benefits of IASI-NG compared to IASI for ozone assimilation. Our presentation will show these impacts, using various assimilation settings

Multi-scale data assimilation in a meteorological regional model.

Nowadays, most limited area meteorological models have their own data assimilation system. Theses analyses generaly mix a first-guess, which is taken from the forecast model, with observations in order to freshen up the patterns described by the limited area model. Nevertheless, the coupling model can also be of some interest. Indeed, the coupling model is generaly a global model, that benefits from top-of-the-range data assimilation techniques, and thus has a good description of the larger scales. The goal of this PhD thesis is to bring information from the coupling model directly into the 3-dimensional variational assimilation (3D-VAR) of the limited area model (LAM), as a new source of information. In concrete terms, the input information vector in the LAM assimilation is the concatenation of various sources of information : a first-guess from the model, observations and larger scales from the coupling model analysis. This formalism uses a measure on the uncertainty of the sources of information, which is described by the covariances between the errors of the sources of information. Some simplifications on the cross-covariances between the sources are proposed, so that these developments are suitable for an easy implementation in the current analysis software. A first evaluation of this new formulation is performed within the framework of a unidimensional “shallow water” model, using both coupling and coupled models. These experiments show a neutral to a positive impact, depending on the setting of the experiments, which is limited by the simplified framework of this academic model. In the framework of the application of thismethod in the models used atMétéo-France (global model ARPÈGE and LAM ALADIN), the statistics on the errors of the sources of information have been evaluated. Firstly, the scales to be taken from the global model analysis have been selected, in order to keep only the larger patterns (roughly 240 km). Then, using previous studies based on ensemble methods to sample the errors, statistics have been computed, which enabled a description of the error covariances (standard deviations, isotropy, etc.) and to quantify the error induced by the proposed simplifications. The implementation of the method in ALADIN has been evaluated on 15-day long assimilation cycles, which resulted in a slightly positive impact of the introduction a the larger scales from the global model analysis on objective scores. Nevertheless, in spite of visible and systematic differences due to the new source of information, no specific case study on diagnostic fields, such as precipitation, illustrates the benefit on present weather or on particular meteorological phenomenon. This PhD thesis introduces an innovative assimilation technique in a LAM which takes into account information from the coupling model, in addition to the observations, to correct the model first-guess. It is an open way for further researches, for instance, adding the time dimension or through a modification of the scale selection of the patterns taken from the coupling model.Les modèles météorologiques à aire limitée sont aujourd'hui dotés de systèmes d'analyse de données observées propres, pour la plupart. Ces analyses combinent en général une ébauche provenant du modèle et des observations dans le but de rafraîchir les structures décrites par le modèle à aire limitée. Néanmoins, l'information provenant du modèle coupleur présente également un intérêt. En effet, le modèle coupleur est en général un modèle global bénéficiant de techniques d'assimilation de données performantes, qui permet de fournir une bonne description des grandes échelles notamment. L'objectif de ce travail de thèse est d'injecter l'information issue du modèle coupleur directement dans l'assimilation variationnelle tridimensionnelle (3D-VAR) du modèle à aire limitée, en tant que nouvelle source d'information. Concrètement, on décrit le vecteur d'information entrant dans l'assimilation du modèle à aire limitée comme étant la concaténation des différentes sources d'information : l'ébauche du modèle, les observations et les grandes échelles de l'analyse du modèle coupleur. Ce formalisme utilise une mesure de l'incertitude sur les sources d'information, décrite par les covariances entre les erreurs des différentes sources d'information. Des simplifications sur les covariances croisées entres les sources d'information sont proposées, afin de pouvoir développer le formalisme en vue de le rendre applicable simplement dans un logiciel d'analyse déjà existant. Une première utilisation de ce nouveau formalisme est faite dans un modèle académique unidimensionnel “en eaux peu profondes”, en mettant en oeuvre un modèle coupleur et un modèle couplé. Ces expériences montrent des résultats neutres à positifs, suivant les configurations, limités par le cadre simplifié de ce modèle académique. Dans le cadre de l'application de cette méthode dans les modèles utilisés à Météo- France (modèle global ARPÈGE et modèle à aire limitée ALADIN), une évaluation des statistiques liées aux erreurs sur les sources d'information est menée. Tout d'abord le choix des échelles venant de l'analyse du modèle global est fait, pour ne garder que les plus grandes structures (environ 240 km). Puis les statistiques sont calculées à partir de travaux précédents utilisant des méthodes ensemblistes pour échantillonner les erreurs. L'étude de ces statistiques permet de décrire les propriétés des covariances d'erreurs (écarts types, isotropie, etc.) et de quantifier l'erreur commise en appliquant les simplifications proposées. L'évaluation sur des cycles d'assimilation d'une quinzaine de jours montre que l'introduction des grandes échelles de l'analyse du modèle global a un impact légèrement positif en terme de score objectif. Néanmoins, malgré des différences visibles et systématiques engendrées par l'utilisation de cette nouvelle source d'information, aucun cas d'étude sur des champs diagnostiques, comme les précipitations, ne permet d'illustrer cet apport en terme de temps sensible ou de phénomènes météorologiques spécifiques. Ce travail de thèse propose donc une technique d'analyse en aire limitée permettant de prendre en compte des informations provenant du modèle coupleur, en plus des observations, pour corriger l'ébauche du modèle. Il ouvre la voie à d'autres recherches, notamment en sélectionnant d'autres échelles venant du modèle coupleur à considérer ou en l'étendant par l'ajout de la dimension temporelle

Near real-time assimilation of volcanic sulfur dioxide from different satellites in the MOCAGE model during volcanic eruptions

International audienceSulfur dioxide emissions during volcanic eruptions can have a significant impact on air trafic. Indeed, sulfur dioxide is a precursor of sulfuric acid which is highly corrosive and damages aircraft engines when they pass through an plume of sulfur dioxide.Currently, to predict the concentration of sulfur dioxide of volcanic origin in the French chemistry-model MOCAGE, SO2 total columns providing from TROPOMI and IASI satellites are assimilated in MOCAGE. Nevertheless, we assume that the SO2 plume is between 3 and 10km of altitude, which is not the case for all volcanic eruptions. A way to improve our analyses and the forecasts is to use information about the height of the plume.TROPOMI on Sentinel-5p is able to measure SO2 columns with high horizontal resolution from the surface to the top of the atmosphere with an information altitude of the plume for the strong total columns. The IASI instruments on Metop B and C measure total SO2 columns with a lower resolution than TROPOMI and do not give any information on the presence of volcanic SO2 below 5km altitude, but they give an information about height even for weak SO2 total columns. Height is used to constrain the altitude of plume and the thickness in the model. This presentation will give a comparison between the assimilation with and without height information on different eruptive events

A step further in the assimilation of IASI and CrIS radiances for O 3 and CO in operations

International audienceIASI and CrIS, hyperspectral infrared instruments on board polar-orbiting operational meteorological satellites, have been assimilated in Numerical Weather Prediction models for more than a decade, providing huge improvements in forecast skills. In the same time, level 2 products from these sensors have been introduced in some atmospheric composition numerical prediction models, for carbon monoxide, for instance. Previous work has led to a first set of evaluation of IASI and CrIS radiances assimilation in the chemistry transport model MOCAGE for ozone, showing a good impact but also highlighting the need of further improvements in assimilation settings. The present work will introduce recent steps towards a better use of infrared radiances in MOCAGE for ozone and also for carbon monoxide. First the evaluation of new background error statistics will be presented, using the so-called NMC method both applied to ozone and carbon monoxide. Then the channel selection will be presented for both instruments and both species. Assimilation trials in MOCAGE will be evaluated against independent observations such as ozone-sondes, IAGOS measurements, MLS profiles ans ground-based in situ observations