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À la Météorologie nationale, trois modèles de prévision du projet Améthyste étaient opérationnels en 1980. Des innovations scientifiques, des échanges avec le Centre européen pour les prévisions météorologiques à moyen terme (CEPMMT) et l'arrivée d'un calculateur Cray-1 en 1983 incitèrent à développer de nouveaux modèles. Au début de l'année 1985, le modèle spectral Émeraude et le modèle sur domaine limité Péridot remplacèrent les anciens modèles. L'enthousiasme et la compétence de Jean-François Geleyn, permirent de renouveler en profondeur les paramétrisations physiques. Ces nouveaux modèles améliorèrent les prévisions jusqu'au temps sensible. Enfin de nouvelles techniques de prévision numérique tant pour les modèles de prévision que pour l'assimilation de données allaient ouvrir la voie aux projets Arpège et Aladin. At the Météorologie nationale, at the beginning of the 1980's, there were three operational models. Scientific innovation, fruitful exchanges with scientists at the European Centre for Medium Range Weather Forecasts (ECMWF) and the arrival of a Cray-1 computer in 1983 prompted to develop new models. At the beginning of year 1985 the Émeraude spectral model and the Péridot limited area model replaced the old models. The enthusiasm and the competence of Jean-François Geleyn enabled to deeply renew the physical parameterizations. These new models led to a substantial improvement of the forecasts including local screen level values. Finally new numerical weather prediction techniques both in numerical models and data assimilation were going to open the way for the new Arpège and Aladin projects.

À Météo-France, la décennie 1985-1995 a vu une profonde transformation de la prévision numérique du temps (PNT) qui a d'abord conduit au remplacement des modèles de prévision opérationnels Émeraude et Péridot par Arpège et Aladin. Dans la même période, un vaste programme de recherche et de développement a été lancé conjointement avec le CEPMMT concernant l'initialisation des modèles par des techniques d'assimilation de données dites « variationnelles ». Cette période a été aussi marquée par un virage vers beaucoup plus de coopération entre institutions travaillant sur la PNT dans les différents pays européens. Jean-François Geleyn s'est trouvé en première ligne de cette profonde transformation, toujours impliqué dans les décisions stratégiques, mais aussi souvent impliqué comme expert dans les études et développements touchant plusieurs aspects scientifiques. At Météo-France, the 1985-1995 decade was marked by a complete transformation of Numerical Weather Prediction (NWP) which led first to the replacement of the operational models Émeraude and Péridot by Arpège and Aladin. In the same period, a large research and development programme was initiated jointly with ECMWF on model initialisation through so-called 'variational' assimilation techniques. This period was also marked by an important change towards closer cooperation between the different institutions working on NWP in European countries. Jean-François Geleyn was instrumental in this complete transformation of NWP. He was always involved in the strategic decisions, but also as an expert in the studies and developments on several scientific aspects.

The lack or inadequate representation of uncertainties in the surface initial conditions (ICs) affects the quality of ensemble forecast, in particular the near surface temperature and precipitation. In this paper, a strategy for perturbing surface ICs in limited area model ensemble prediction system, noncycling surface breeding (NCSB) is proposed. The strategy combines short-range surface forecasts driven by perturbed atmospheric forcing and the breeding method for generating the perturbation to surface ICs. NCSB is implemented and tested in Aire Limitee Adaptation dynamique Developpement InterNational-limited area ensemble forecasting (ALADIN-LAEF). Statistical verification demonstrates that the application of NCSB improves the ALADIN-LAEF 2m temperature and precipitation forecast. Positive impacts are also obtained for temperature and specific humidity in the lower atmosphere. Copyright © 2010 Royal Meteorological Society

The prime aim of the Atmospheric Dynamics Mission is to demonstrate measurements of vertical wind profiles from space. Extensive studies conducted by the European Space Agency over the past 15 years have culminated in the selection of a high-performance Doppler wind lidar based on direct-detection interferometric techniques. Such a system, with a pulsed laser operating at 355-nm wavelength, would utilize both Rayleigh scattering from molecules and Mie scattering from thin cloud and aerosol particles; measurement of the residual Doppler shift from successive levels in the atmosphere provides the vertical wind profiles. The lidar would be accommodated on a satellite flying in a sun-synchronous orbit, at an altitude of ~400 km, providing near-global coverage; target date for launch is in 2007. Processing of the backscatter signals will provide about 3000 globally distributed wind profiles per day, above thick clouds or down to the surface in clear air, at typically 200-km separation along the satellite track...

L'idee de modeliser l'atmosphere pour prevoir son evolution remonte a pres d'une centaine d'annees. Mais c'est a partir des annees 70 que cette idee s'est vraiment concretisee par des modeles numeriques operationnels dans beaucoup de services meteorologiques developpes, ou ils sont devenus un outil essentiel de la prevision du temps. Depuis lors, la meteorologie (avec maintenant sa composante « simulation du climat futur ) a toujours ete une application grosse consommatrice de ressources « calcul numeriqueet l'une des vitrines des constructeurs de super-calculateurs. Les applications meteologiques necessitent souvent une forte synergie entre la modelisation de l'atmosphere d'une part, son observation d'autre part ; d'ou l'importance de la partie de la modelisation appelee « assimilation de donnees .

In the first of this set of three papers, the formulation of the European Centre for Medium-Range Weather Forecasts (ECMWF) implementation of 3D-Var is described. In the second, the specification of the structure function is presented, and the last is devoted to the results of the extensive numerical experimentation programme which was conducted. The 3D-Var formulation uses a spherical-harmonic expansion, much as the ECMWF optimal interpolation (OI) scheme used an expansion of Bessel functions. This formulation is introduced using a convolution algebra over the sphere expressed directly in spectral space. It is shown that all features of the OI statistical model can be implemented within 3D-Var. Furthermore, a non-separable statistical model is described. In the present formulation, geostrophy is accounted for through a Hough-modes separation of the gravity and Rossby components of the analysis increments. As in OI, the tropical analysis remains essentially non-divergent and with a weak mass-wind coupling. The observations used, as well as their specified statistics of errors, are presented, together with some implementation details. In the light of the results, 3D-Var was implemented operationally at the end of January 1996.

The present status of development of data assimilation techniques for high resolution limited area models is reviewed and various candidates for a new generation of a data assimilation system are compared. It is concluded that data assimilation based on 3-dimensional or 4-dimensional variational techniques is the most promising approach. Further investigations are needed, however, to find out whether variational data assimilation is feasible over "limited" model integration areas or whether global/hemispheric model integration areas have to be introduced for high resolution limited area data assimilation purposes. The main problem in this connection is the rapid propagation of forecast errors on a global or at least hemispheric atmospheric scale within a time-scale of a few days.

The direct use of TOVS (TIROS Operational Vertical Sounder) cloud-cleared radiances in a three/four-dimensional variational data assimilation scheme is described. This scheme uses a fast radiative transfer model and its adjoint. Radiances are used together with all the other observational data. Global spectral fields of mass, wind and humidity are analysed simultaneously under certain mass/wind balance constraints which control the degree to which gravity waves enter into the analysis. In this way the need for a subsequent initialization is avoided. The scheme thus combines retrieval, analysis and initialization in one step and makes it possible to achieve a more optimal combination of the information contained in the radiances, the conventional data and the background (a six-hour forecast). At spectral truncation T63, a global three-dimensional variational analysis (3D-Var) of TOVS radiances and conventional data is compared with the ECMWF operational Optimum Interpolation scheme, which uses TOVS radiance information in the form of profiles of temperature and humidity, retrieved using a one-dimensional variational method. The results of 3D-Var are in good agreement with the operational analysis at the same resolution. In an application of the four-dimensional scheme (4D-Var), data covering a period of 24 hours were used simultaneously. In 4D-Var consistency in time is ensured through the evolution of the forecast model and its adjoint. Using the adiabatic version of the ECMWF forecast model (spectral resolution T42) we show that 4D-Var is able to extract additional information from the dynamics of the model. In particular we show an impact on the tropical wind field from the use of the humidity-sensitive TOVS channels.

The aim of this study is to make a strict comparison between two assimilation algorithms, sequential and four-dimensional variational, on a 24-hour period extracted from a baroclinic instability situation representative of mid-latitude dynamics. In the case of linear dynamics, and under the hypothesis of a perfect model, these two four-dimensional algorithms are known to lead to the same optimal estimate of the atmosphere at the end of the assimilation period, and both methods can be generalized in the nonlinear case. Because the full sequential algorithm is too resource-demanding to be implemented as such, we shall test the four-dimensional variational method (4D-VAR), and a simplified sequential method based on three-dimensional variational analysis (3D-VAR), deliberately not exceeding the range of validity of the tangent-linear model in the experiments. 4D-VAR is then expected to be almost equivalent to the generalization of the sequential Kalman filter in the nonlinear case, i.e. the extended Kalman filter. As for the simplified sequential algorithm, it can be seen as an approximation of this full extended Kalman filter, for which the forecast error matrices are evaluated only approximately before each analysis, instead of being explicitly computed from the complete dynamical equations. In the four-dimensional variational scheme, the consistency of the propagation of information with the dynamics is illustrated in an experiment assimilating some localized AIREP data. The large impact which these additional observations have over a large geographical area appears to be very beneficial for the quality of the analysis. Comparing the results of both methods in various configurations, we found that 4D-VAR systematically behaved substantially better than the simplified sequential algorithm, and had a more accurate analysis at the end of the assimilation period and a much smaller error growth rate in subsequent forecasts. On the one hand, extremely bad specifications of initial forecast errors were found to be detrimental to both algorithms. On the other hand, the four-dimensional variational algorithm proves to be more robust to the way by which gravity-wave control is implemented.

The paper describes a four-dimensional variational assimilation using a multilevel global primitive-equation spectral model. The experiments consist in minimizing the distance between the model solution and conventional observations spread over 24 hours. A first set of experiments was performed at low resolution (spectral truncation T21). The model solution converges to fit the observations satisfactorily over the whole assimilation period. The meteorological quality of the analyses, in terms of the large-scale part of the flow, is comparable with the ECMWF operational analysis. Confirming early results, the control of gravity waves in the solution can be easily handled using a combination of a penalty term and a normal-mode initialization scheme within the forward-backward process of the variational assimilation. Experiments excluding data over an area with a strong baroclinic development show that the information contained in the dynamics of the model is used successfully in the analysis over this area. In addition, the dynamics are able to inter implicitly flow-dependent structure functions. Higher-resolution experiments (spectral truncation T42) were performed and compared with optimum interpolation (OI) analyses performed under the same conditions. Although the lack of a first-guess term in the cost function leads to small-scale noise generation if the minimization is pursued, the quality of the variational assimilation is comparable with OI, and the error growth of the following 24-hour forecast is smaller when performed from the variational analysis. Moreover, experiments excluding wind data from aircraft show a clear advantage for the variational approach against OI in using, in a consistent way, the information coming from the model and the observations.

Hydrologists are increasingly using numerical weather forecasting products as an input to their hydrological models. These products are often generated on relatively coarse scales compared with hydrologically relevant basin units and suffer systematic biases that may have considerable impact when passed through the nonlinear hydrological filters. Therefore, the data need processing before they can be used in hydrological applications. This manuscript summarises discussions and recommendations of the first workshop on Postprocessing and Downscaling Atmospheric Forecasts for Hydrologic Applications held at Meteo France, Toulouse, France, 15¿18 June 2008. The recommendations were developed by work groups that considered the following three areas of ensemble prediction: (1) short range (0¿2 days), (2) medium range (3 days to 2 weeks), and (3) sub-seasonal and seasonal (beyond 2 weeks)., JRC.H.7-Climate Risk Management

An operational Numerical Weather Prediction model producing forecasts beyond day 3 has to be global. A good global satellite observing system is then crucial for forecasting, as no other observing system is able to provide a full 3D data coverage. Some practical aspects of an operational model used for global medium range forecasting are discussed (e.g. data volume, cut-off time). A simple example of use of TOVS retrieved profiles in an optimum interpolation analysis is presented, in order to highlight the advantages and the limitations of such a technique. Prospects and potential improvements of a variational analysis scheme are also discussed.

This is an evaluation of a retrieval, data assimilation, and forecast experiment on satellite sounding data from the NOAA-9 and NOAA-10 polar orbiting satellites during a 15.5 day period in January–February 1987. Retrievals were produced globally through the 3I (improved initialization inversion) scheme developed at Laboratoire de Meteorologie Dynamique, Paris. In this paper we use the European Centre for Medium Range Weather Forecasts (ECMWF) global data assimilation system to evaluate the global performance of the 3I retrieval scheme. The 3I-retrieved temperature profiles have also been compared with the operational retrievals produced by NESDIS (National Environmental Satellite, Data, and Information Service), Washington. It is shown that the large airmass-dependent biases, characteristic of the NESDIS retrievals, also occur with 3I, but with smaller amplitude. Some large local 3I retrieval errors are identified and explained, and their impact on analysis and forecasts demonstrated. The foreca...

EnglishThe main tools used for forecasting the weather (mainly the numerical models simulating the atmospheric evolution) are described. Objective criteria and scores which provide an estimation of the forecast quality are then presented. These criteria show large variations depending on the space-time scale used for evaluating the forecast, the forecast range (generally presented in deterministic mode in the short-range, in probabilistic mode beyond), but also on the more or less extreme character of the event to forecast. A regular verification of weather forecasts provides an assessment of the long-term progress (achieved over several decades), as well as a detailed evaluation of scientific and technical changes made on the forecasting system on a given date. francaisApres un rappel des principaux outils servant a la prevision du temps (essentiellement les modeles numeriques simulant l'evolution de l'atmosphere), on decrit les criteres et scores objectifs permettant de juger la qualite de la prevision. Ces criteres varient beaucoup suivant l'echelle spatio-temporelle a laquelle on cherche a evaluer la prevision, l'echeance de la prevision (generalement presentee en mode deterministe a courte echeance, en mode probabiliste au-dela),mais aussi les caracteristiques plus ou moins extremes de l'evenement que l'on cherche a prevoir. Une verification reguliere des previsions permet aussi bien un suivi sur plusieurs decennies mettant en evidence les progres a long terme qu'une evaluation detaillee des changements scientifiques et techniques effectues sur la chaine de prevision a une date donnee.

EnglishFor the last 25 years, research and development activities in Numerical Weather Prediction (NWP) have been carried out in Meteo-France within a close collaboration with the European Centre for Medium-Range Weather Forecasts (ECMWF), through the IFS/Arpege global modelling project. The 25-year history of this project is presented in this article, with its important scientific and technical milestones, as well as its operational outcomes.The details are not comprehensive in terms of NWP at Meteo-France. They describe only global modelling, not high resolution limited area modelling. The « non-NWP » aspects of the project, such as climate modelling, are not presented either. francaisDurant les 25 dernieres annees, les recherches et developpements en prevision numerique du temps (PNT) a Meteo-France ont ete menes en etroite collaboration avec le Centre europeen pour les previsions meteorologiques a moyen terme (CEPMMT), a travers le projet de modelisation globale IFS/Arpege. Les 25 ans d'histoire de ce projet sont presentes dans cet article, avec ses grandes etapes scientifiques et techniques, ainsi que ses debouches operationnels. Les details presentes ne sont pas exhaustifs en termes de PNT a Meteo-France. Ils ne decrivent que la modelisation globale, pas la modelisation fine sur domaine limite. Ils ne decrivent pas non plus les aspects « non PNT » du projet tels que la modelisation climatique.

Dispersion en mer des radionucleides de la centrale de Fukushima. / Par Claude Estournel. -- Lancement d'Aquarius sur SAC-D. -- Un prix pour l'innovation en meteorologie. / Par Dominique Marbouty. -- La campagne de mesures ParisFog. / Par Jean-Charles Dupont. -- Le prix Prud'homme 2011 attribue a Camille Yver. -- La campagne de mesures BLLAST : quand l'atmosphere s'endort. / Par Marie Lothon. -- Jean Labrousse nous a quittes. / Par Jean-Francois Geleyn, Jean Pailleux et Jean Coiffier.

Thorpex is a research programme of the World Meteorological Organization (WMO) aiming at accelerating any type of progress in Numerical Weather Prediction (NWP). The history of NWP is recalled, as well as how it led to starting the Thorpex programme, shortly after 2000. Then the different scientific components of the programme are described. More details are given on the current (2010) Thorpex events, such as the Mediterranean and polar campaigns. The likely future evolution of the Thorpex programme is briefly described in the conclusion.

On examine dans cet article l'adequation entre les besoins des modeles de prevision numerique et les observations existantes. On decrit aussi l'evolution de ces aspects sur les trente dernieres annees. On essaie enfin d'extrapoler leur evolution future, en s'appuyant sur l'exemple d'une mission d'observation du vent developpee par l'Agence spatiale europeenne, la mission ADM-Aeolus.

C'est en 1987 que debuta a Meteo-France la conception du modele de prevision numerique planetaire baptise Arpege, qui a ete un element essentiel pour la prevision du temps durant les annees quatre-vingt-dix et qui le restera certainement bien au-dela de l'an 2000. Arpege a ete concu, developpe et entretenu en collaboration etroite avec le CEPMMT. Aladin, version a domaine limite du modele Arpege, est un autre element essentiel pour la prevision du temps : il est le resultat d'un projet s'appuyant fortement sur Arpege et lance en 1990 dans le cadre d'une collaboration avec plusieurs autres services meteorologiques. Cet article decrit d'abord les differentes motivations, scientifiques, techniques et meme politiques, qui ont ete a l'origine des projets Arpege et Aladin. Les principaux ingredients scientifiques de ces modeles sont exposes, ainsi que leur evolution depuis 1987, tant pour la partie prevision que pour la partie assimilation de donnees. Les versions d'Arpege et d'Aladin utilisees quotidiennement a Meteo-France au debut de l'annee 2000 sont decrites ainsi que leur mise en oeuvre operationnelle. On examine ensuite les performances des previsions numeriques de Meteo-France, en suivant l'evolution sur plusieurs annees de scores mesurant ces performances et en les comparant aux previsions numeriques faites en routine dans d'autres centres. Enfin, les plans et perspectives en prevision numerique sont evoques et discutes.

EnglishFor about twenty years, numerical prediction models have used satellite data on a daily basis. After a brief description of the instruments and the processing of the data, this paper tries to quantify their impact on the quality of the numerical forecasts. A review of the use of satellite data in numerical weather prediction since the end of the seventies is given, using the results from several impact-studies carried out in a few important centres, especially at the European Centre for Medium range Weather Forecasts, situated in Reading, England. francaisDepuis une vingtaine d'annees, les modeles de prevision numerique utilisent quotidiennement certaines donnees des satellites meteorologiques. Apres une presentation sommaire des instruments et des traitements a l'origine de ces donnees, cet article essaie de chiffrer leur impact sur la qualite de la prevision numerique. Pour cela, on dresse un historique de l'utilisation des donnees satellitales dans les modeles de prevision numerique, depuis la fin des annees soixante-dix, et on s'appuie sur plusieurs etudes d'impact effectuees dans quelques grands centres de prevision numerique, en particulier au Centre europeen pour les previsions meteorologiques a moyen terme, se trouvant a Reading en Angleterre.