Journal articles on the topic 'Climatologie du métro'

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1

Beauvais, François, Olivier Cantat, Philippe Madeline, Patrick Le Gouée, Sophie Brunel-Muguet, and Mohand Medjkane. "Quelles conséquences du changement climatique sur le blé tendre en Normandie aux horizons 2050 et 2100 ?" Climatologie 16 (2019): 129–60. http://dx.doi.org/10.4267/climatologie.1414.

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En Normandie, la culture du blé qui occupe 24 % de la SAU régionale tient une place importante parmi les productions végétales. Le changement climatique peut-il avoir des conséquences sur le cycle de cette céréale et perturber les pratiques et les espaces concernés ? Cet article projette la phénologie et les performances culturales de l’agrosystème céréalier régional d’ici la fin du 21ème siècle. Il s’appuie sur une modélisation bioclimatique qui mobilise les données CNRM-2014 du CNRS et de Météo-France sorties du modèle régional ALADIN-Climat pour trois scénarios RCP du GIEC. Dans le cas de dates de semis inchangées aux horizons 2050 et 2100 et d’un changement climatique prononcé, l’élévation des températures engendrerait un raccourcissement du cycle et donc une anticipation calendaire de la phénologie. Ce qui éviterait un chevauchement de la fin du cycle avec la période estivale à laquelle sont associés des événements de sécheresse et de vagues de chaleur dont la fréquence pourrait augmenter dans les prochaines décennies. En conséquence, l’échaudage thermique et le déficit hydrique seraient moindres que ce que l’on pouvait envisager. Toutefois, cette précocité pourrait perturber des stades plus précoces de développement du blé tendre : basses températures à la méiose et déficit de rayonnement au début de la montaison. De plus, la douceur accrue des hivers pourrait engendrer une diminution du nombre de jours de vernalisation, phase nécessaire pour la floraison des variétés d’hiver. Cette étude démontre l’intérêt des modèles bioclimatiques pour envisager les modifications possibles de la phénologie des cultures attendus d'ici la fin du siècle.
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2

Kastendeuch, Pierre P., and Georges Najjar. "Une simulation des interactions ville-atmosphère à différentes échelles : application sur Strasbourg." Climatologie 12 (2015): 44–64. http://dx.doi.org/10.4267/climatologie.1118.

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Plusieurs modèles météorologiques ont été utilisés pour simuler les interactions ville-atmosphère à différentes échelles. Cette chaîne de simulation implique l’utilisation de réanalyses globales d’une résolution de 16 km comme données de forçage météorologique. Ce forçage est utilisé pour contraindre un modèle de méso-échelle qui permet d’atteindre une résolution de 250 m sur la ville grâce à la technique du grid-nesting. Finalement les champs du modèle à 250 m ont été utilisés comme forçage météorologique pour un modèle de simulation de canopée urbaine en 3D qui fonctionne avec une résolution de quelques mètres. Les outils utilisés pour atteindre cet objectif sont : les réanalyses du CEPMMT, le modèle Méso-NH & SURFEX (de Météo-France et du Laboratoire d’Aérologie) et le modèle de canopée urbaine LASER/F (Icube). Une simulation a été réalisée sur Strasbourg pour tester cette chaîne sur une période qui va du 13 au 17 août 2002. Les validations montrent que les processus de surface et atmosphériques simulés par Méso-NH & SURFEX pour la résolution de 250 m sont en accord avec les mesures de terrain. Pour s’assurer que le modèle de canopée urbaine en 3D s’intègre bien dans la chaîne de simulation, ses résultats sont comparés à ceux de SURFEX pour un quartier. Les analyses montrent que les résultats obtenus par ce modèle sont en accord avec ceux de SURFEX. L’introduction de la géométrie réelle du quartier en 3D permet même un gain appréciable pour certaines variables. Vu la cohérence des résultats obtenus, l’adjonction du modèle de canopée urbaine se justifie dans cette chaîne. Et ceci d’autant plus que ce type de modèle permet l’accès à de nouvelles informations avec un haut niveau de détails.
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Specq, Damien. "Titre de la thèse : Prévisibilité des fortes précipitations aux échéances infra-saisonnières sur le Pacifique Sud-Ouest tropical." Climatologie 19 (2022): 2. http://dx.doi.org/10.1051/climat/202219002.

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Cet article est un condensé de la thèse soutenue par l’auteur le 6 novembre 2020 et récompensée par le prix Gérard Beltrando de l’Association Internationale de Climatologie au titre de l’année 2021. Cette thèse a été préparée au Centre National de Recherches Météorologiques (UMR 3589, Météo-France & CNRS) entre 2017 et 2020 sous la direction de Lauriane Batté et Michel Déqué.
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Besson, François, Pierre Etchevers, Florence Habets, Patrick Le Moigne, Fabienne Rousset-Regimbeau, Jean-Michel Soubeyroux, Christian Viel, and Béatrice Vincendon. "Suivi en temps réel des sécheresses : de l'analyse à la prévision saisonnière." La Houille Blanche, no. 4 (August 2020): 82–92. http://dx.doi.org/10.1051/lhb/2020042.

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Météo-France opère en temps réel depuis 2003 la chaîne de modélisation hydro-météorologique SIM, composée du module d'analyse des conditions atmosphériques en surface (SAFRAN), d'une modélisation détaillée des interactions sol-biosphère-atmosphère (ISBA) et du modèle hydrogéologique MODCOU. Cette chaîne a connu une évolution majeure en 2016 afin d'améliorer certains de ses composants. Cette application temps-réel, complétée par une réanalyse depuis 1958 permet de caractériser la situation par rapport aux années antérieures pour plusieurs variables du cycle hydrologique (précipitations, humidité du sol, enneigement). Les épisodes de sécheresse, l'évolution du stock nival, etc. peuvent ainsi être suivis au jour le jour sur l'ensemble de la France métropolitaine. Des applications de prévisions ont également été mises en place pour anticiper l'évolution de la situation hydrologique. L'initialisation des conditions hydrologiques provient de la chaîne d'analyse temps-réel et des données météorologiques prévues sont utilisées en entrée d'ISBA-MODCOU. Ainsi une application pour les échéances allant jusqu'à 10 jours utilise comme forçage météorologique les prévisions d'ensemble du CEPMMT (Centre Européen de Prévision Météorologique à Moyen Terme). Chaque jour des prévisions sont produites sur différentes zones (départements, bassins versants, etc.), l'ensemble de prévision fournit des informations pour les différentes variables hydrologiques au pas de temps quotidien. De plus la visualisation de la dispersion des prévisions renseigne sur l'incertitude associée à chaque prévision. Pour des échéances plus lointaines (jusqu'à 6 mois), deux applications de prévisions sont opérées tous les mois. La première utilise en entrée des scénarios météorologiques issus de la climatologie, alors que la seconde utilise des données issues du modèle de prévisions saisonnières atmosphériques de Météo-France. Malgré l'incertitude des prévisions, l'exploitation complémentaire des prévisions climatologique et saisonnière est un outil pour la gestion des ressources en eau. Les débits moyens mensuels prévus pour chacune des applications comparés aux débits des années précédentes permettent en effet de caractériser la situation pour les mois à venir et l'incertitude associée.
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Garcelon, Laurent, Sébastien Brana, Julien Didez, and Frédéric Ameye. "StatIC : un réseau d'observation au service d'une information de proximité et de vulgarisation scientifique." La Météorologie, no. 122 (2023): 037. http://dx.doi.org/10.37053/lameteorologie-2023-0071.

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Depuis 20 ans, l'association Infoclimat développe un réseau de stations normalisées en complément de l'observation visuelle réalisée par ses passionnés. Ces observations, qui s'inscrivent dans la durée et sont pour certaines dans la continuité des postes du Réseau climatologique d'État précédemment exploités par Météo-France, sont les témoins d'un changement climatique de plus en plus prégnant et rapide. La mine d'or qu'elles représentent aujourd'hui permet la réalisation d'outils pédagogiques au service de la vulgarisation scientifique. For 20 years, Infoclimat, a non-profit organization, has developed a network of standardized weather stations across France in addition to the visual observation carried by its enthusiasts. These observations are complementary of the official network operated by Météo-France and many of them are the continuity of the State climatological network. Year after year, they are recording the impact of climate change in France. Nowadays, the network of Infoclimat is used as a tool for education and vulgarization.
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Sorel, Matthieu, Jean-Michel Soubeyroux, Agathe Drouin, Sylvie Jourdain, Maryvonne Kerdoncuff, Béatrice Cassaigne, Marie-Hélène Théron, Patrick Josse, and Christine Lacanal. "Normales climatiques 1991-2020." La Météorologie, no. 119 (2022): 073. http://dx.doi.org/10.37053/lameteorologie-2022-0086.

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Les normales climatologiques sont des produits statistiques calculés à partir de séries de données sur des périodes de 30 ans. Elles comprennent aussi bien des valeurs moyennes que d'autres paramètres statistiques, les quantiles par exemple. Définies par l'Organisation météorologique mondiale, elles permettent de caractériser le climat sur ces périodes et servent de référence pour analyser les événements climatiques en temps réel. Météo-France a entrepris depuis janvier 2021 le calcul des nouvelles normales climatiques 1991-2020 et les utilise dans l'ensemble de sa production climatologique depuis le 28 juin 2022. Climatological normals are defined as statistical products computed over a 30-year period; they include both mean and other statistical parameters, e.g. quantiles. Defined by the World Meteorological Organization, they are used to define the conditions most likely to be experienced in a given location over a period of time. They also serve as a basis in order to monitor climate events in real time. Météo-France started to compute the new climatological normals 1991-2020 and started to use them in its climatological production from June 28th, 2022.
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7

Trzaska, S., V. Moron, and B. Fontaine. "Global atmospheric response to specific linear combinations of the main SST modes. Part I: numerical experiments and preliminary results." Annales Geophysicae 14, no. 10 (October 31, 1996): 1066–77. http://dx.doi.org/10.1007/s00585-996-1066-7.

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Abstract. This article investigates through numerical experiments the controversial question of the impact of El Niño-Southern Oscillation (ENSO) phenomena on climate according to large-scale and regional-scale interhemispheric thermal contrast. Eight experiments (two considering only inversed Atlantic thermal anomalies and six combining ENSO warm phase with large-scale interhemispheric contrast and Atlantic anomaly patterns) were performed with the Météo-France atmospheric general circulation model. The definition of boundary conditions from observed composites and principal components is presented and preliminary results concerning the month of August, especially over West Africa and the equatorial Atlantic are discussed. Results are coherent with observations and show that interhemispheric and regional scale sea-surface-temperature anomaly (SST) patterns could significantly modulate the impact of ENSO phenomena: the impact of warm-phase ENSO, relative to the atmospheric model intercomparison project (AMIP) climatology, seems stronger when embedded in global and regional SSTA patterns representative of the post-1970 conditions [i.e. with temperatures warmer (colder) than the long-term mean in the southern hemisphere (northern hemisphere)]. Atlantic SSTAs may also play a significant role.
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8

Wang, D., C. Prigent, L. Kilic, S. Fox, C. Harlow, C. Jimenez, F. Aires, C. Grassotti, and F. Karbou. "Surface Emissivity at Microwaves to Millimeter Waves over Polar Regions: Parameterization and Evaluation with Aircraft Experiments." Journal of Atmospheric and Oceanic Technology 34, no. 5 (May 2017): 1039–59. http://dx.doi.org/10.1175/jtech-d-16-0188.1.

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AbstractThe Tool to Estimate Land Surface Emissivity from Microwave to Submillimeter Waves (TELSEM2) is linked to a climatology of monthly emissivity estimates and provides a parameterization of the surface emissivity up to 700 GHz, in the framework of the preparation for the Ice Cloud Imager (ICI) on board the Meteorological Operational Satellite Second Generation (MetOp-SG). It is an updated version of the Tool to Estimate Land Surface Emissivities at Microwave Frequencies (TELSEM; Aires et al. 2011). This study presents the parameterization of continental snow and ice and sea ice emissivities in TELSEM2. It relies upon satellite-derived emissivities up to 200 GHz, and it is anchored to the Special Sensor Microwave Imager (SSM/I) TELSEM monthly climatology dataset (19–85 GHz). Emissivities from Météo-France and the National Oceanic and Atmospheric Administration (NOAA) at frequencies up to 190 GHz were used, calculated from the Special Sensor Microwave Imager/Sounder (SSMIS) and the Advanced Microwave Sounding Unit-B (AMSU-B) observations. TELSEM2 has been evaluated up to 325 GHz with the observations of the International Submillimeter Airborne Radiometer (ISMAR) and the Microwave Airborne Radiometer Scanning System (MARSS), which were operated on board the Facility for Airborne Atmospheric Measurements (FAAM) aircraft during the Cold-Air Outbreak and Submillimeter Ice Cloud Study (COSMICS) campaign over Greenland. Above continental snow and ice, TELSEM2 is very consistent with the aircraft estimates in spatially homogeneous regions, especially at 89 and 157 GHz. Over sea ice, the aircraft estimates are very variable spatially and temporally, and the comparisons with the TELSEM2 were not conclusive. TELSEM2 will be distributed in the new version of the RTTOV radiative transfer community code, to be available in 2017.
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9

Lémond, J., Ph Dandin, S. Planton, R. Vautard, C. Pagé, M. Déqué, L. Franchistéguy, et al. "DRIAS: a step toward Climate Services in France." Advances in Science and Research 6, no. 1 (July 7, 2011): 179–86. http://dx.doi.org/10.5194/asr-6-179-2011.

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Abstract. DRIAS (Providing access to Data on French Regionalized climate scenarios and Impacts on the environment and Adaptation of Societies) is a 2-yr project (2010–2012). It is funded by the GICC (Management and Impact of Climate Change) program of the French Ministry of Ecology, Sustainable Development, Transportation, and Housing (MEDDTL). DRIAS is to provide easy access to French regional climate data and products in order to facilitate mitigation and adaptation studies. The DRIAS project focuses on existing French regional climate projections obtained from national modelling groups such as: IPSL, CERFACS, and CNRM. It is more than a data server, it also delivers all kinds of climate information from numerical data to tailored climate products. Moreover, guidance is to be provided to end-users in order to promote best practices and know-how. Whilst the project is coordinated by the Department of Climatology at Météo-France, a multidisciplinary group of users and stakeholders at large concerned by climate change issues is also involved with the project. The ultimate goal will be to identify societal needs, validate the decision making processes, and thus facilitate exchanges between producers and practitioners. Key results from the DRIAS project will contribute to the implementation of French Climate Services.
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Batté, Lauriane, Constantin Ardilouze, and Michel Déqué. "Forecasting West African Heat Waves at Subseasonal and Seasonal Time Scales." Monthly Weather Review 146, no. 3 (March 1, 2018): 889–907. http://dx.doi.org/10.1175/mwr-d-17-0211.1.

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Abstract Early indication of an increased risk of extremely warm conditions could help alleviate some of the consequences of severe heat waves on human health. This study focuses on boreal spring heat wave events over West Africa and the Sahel and examines the long-range predictability and forecast quality of these events with two coupled forecasting systems designed at Météo-France, both based on the CNRM-CM coupled global climate model: the operational seasonal forecasting System 5 and the experimental contribution to the World Weather Research Programme/World Climate Research Programme (WWRP/WCRP) subseasonal-to-seasonal (S2S) project. Evaluation is based on past reforecasts spanning 22 years, from 1993 to 2014, compared to reference data from reanalyses. On the seasonal time scale, skill in reproducing interannual anomalies of heat wave duration is limited at a gridpoint level but is significant for regional averages. Subseasonal predictability of daily humidity-corrected apparent temperature drops sharply beyond the deterministic range. In addition to reforecast skill measures, the analysis of real-time forecasts for 2016, both in terms of anomalies with respect to the reforecast climatology and using a weather-type approach, provides additional insight on the systems’ performance in giving relevant information on the possible occurrence of such events.
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11

Vincendon, Béatrice, Simon Edouard, and Véronique Ducrocq. "De l'incertitude dans un système de prévision d'ensemble des crues rapides méditerranéennes." La Houille Blanche, no. 3-4 (October 2019): 22–30. http://dx.doi.org/10.1051/lhb/2019051.

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Il est crucial d'augmenter le délai d'anticipation des crues rapides méditerranéennes pour mieux anticiper leur impact. Mais la prévision hydrométéorologique est affectée par plusieurs sources d'incertitude : l'incertitude majeure qui provient des prévisions de précipitations utilisées en entrée des modèles hydrologiques, mais aussi la connaissance de l'humidité initiale du sol et le modèle hydrologique lui-même. Pour échantillonner ces incertitudes, des systèmes de prévision d'ensemble hydrométéorologique sont conçus et comparés. Ils sont basés sur le modèle atmosphérique à l'échelle kilométrique AROME de Météo-France et sur le modèle hydrologique ISBA-TOP, dédié aux bassins méditerranéens à réponse rapide. L'incertitude sur la prévision des pluies est échantillonnée en utilisant la PEARO, prévision d'ensemble avec AROME, en entrée d'ISBA-TOP ou en introduisant dans les sorties déterministes d'AROME des perturbations basées sur des climatologies d'erreur de prévision de la pluie. Pour considérer les incertitudes sur la modélisation hydrologique et sur l'état initial du sol, des méthodes de perturbation des paramètres les plus sensibles d'ISBA-TOP et de l'humidité initiale du sol ont été conçues. Les scenarii de précipitations de la PEARO sont ensuite utilisés en entrée d'une version d'ISBA-TOP où ces méthodes de perturbation sont appliquées. Ce système de prévision prenant en compte différentes sources d'incertitude englobe bien les observations de débits sur plusieurs cas d'étude et bassins versants. Un petit nombre de membres permet déjà de meilleures performances en termes de prévisions de débits qu'une prévision déterministe.
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12

Durand, Yves, Martin Laternser, Gérald Giraud, Pierre Etchevers, Bernard Lesaffre, and Laurent Mérindol. "Reanalysis of 44 Yr of Climate in the French Alps (1958–2002): Methodology, Model Validation, Climatology, and Trends for Air Temperature and Precipitation." Journal of Applied Meteorology and Climatology 48, no. 3 (March 1, 2009): 429–49. http://dx.doi.org/10.1175/2008jamc1808.1.

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Abstract Since the early 1990s, Météo-France has used an automatic system combining three numerical models to simulate meteorological parameters, snow cover stratification, and avalanche risk at various altitudes, aspects, and slopes for a number of mountainous regions in France. Given the lack of sufficient directly observed long-term snow data, this “SAFRAN”–Crocus–“MEPRA” (SCM) model chain, usually applied to operational avalanche forecasting, has been used to carry out and validate retrospective snow and weather climate analyses for the 1958–2002 period. The SAFRAN 2-m air temperature and precipitation climatology shows that the climate of the French Alps is temperate and is mainly determined by atmospheric westerly flow conditions. Vertical profiles of temperature and precipitation averaged over the whole period for altitudes up to 3000 m MSL show a relatively linear variation with altitude for different mountain areas with no constraint of that kind imposed by the analysis scheme itself. Over the observation period 1958–2002, the overall trend corresponds to an increase in the annual near-surface air temperature of about 1°C. However, variations are large at different altitudes and for different seasons and regions. This significantly positive trend is most obvious in the 1500–2000-m MSL altitude range, especially in the northwest regions, and exhibits a significant relationship with the North Atlantic Oscillation index over long periods. Precipitation data are diverse, making it hard to identify clear trends within the high year-to-year variability.
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Lee, Chia-Ying, Suzana J. Camargo, Fréderic Vitart, Adam H. Sobel, Joanne Camp, Shuguang Wang, Michael K. Tippett, and Qidong Yang. "Subseasonal Predictions of Tropical Cyclone Occurrence and ACE in the S2S Dataset." Weather and Forecasting 35, no. 3 (April 22, 2020): 921–38. http://dx.doi.org/10.1175/waf-d-19-0217.1.

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Abstract Probabilistic tropical cyclone (TC) occurrence, at lead times of week 1–4, in the Subseasonal to Seasonal (S2S) dataset are examined here. Forecasts are defined over 15° in latitude × 20° in longitude regions, and the prediction skill is measured using the Brier skill score with reference to climatological reference forecasts. Two types of reference forecasts are used: a seasonally constant one and a seasonally varying one, with the latter used for forecasts of anomalies from the seasonal climatology. Models from the European Centre for Medium-Range Weather Forecasts (ECMWF), Australian Bureau of Meteorology, and Météo-France/Centre National de Recherche Météorologiques have skill in predicting TC occurrence four weeks in advance. In contrast, only the ECMWF model is skillful in predicting the anomaly of TC occurrence beyond one week. Errors in genesis prediction largely limit models’ skill in predicting TC occurrence. Three calibration techniques, removing the mean genesis and occurrence forecast biases, and a linear regression method, are explored here. The linear regression method performs the best and guarantees a higher skill score when applied to the in-sample dataset. However, when applied to the out-of-sample data, especially in areas where the TC sample size is small, it may reduce the models’ prediction skill. Generally speaking, the S2S models are more skillful in predicting TC occurrence during favorable Madden–Julian oscillation phases. Last, we also report accumulated cyclone energy predictions skill using the ranked probability skill score.
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Tabary, P. "The New French Operational Radar Rainfall Product. Part I: Methodology." Weather and Forecasting 22, no. 3 (June 1, 2007): 393–408. http://dx.doi.org/10.1175/waf1004.1.

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Abstract A new radar-based rainfall product has been developed at Météo-France and is currently being deployed within the French operational Application Radar à la Météorologie Infra-Synoptique (ARAMIS) radar network. The rainfall product is based entirely on radar data and comprises the following successive processing steps: 1) dynamic identification of ground clutter based on the pulse-to-pulse fluctuation of the radar signal, 2) reflectivity-to-rain-rate conversion using the Marshall–Palmer Z–R relationship, 3) correction for partial beam blocking using numerical simulations of the interaction between the radar wave and the terrain, 4) correction for vertical profile of reflectivity (VPR) effects based on ratio curves and a priori climatology-based VPR candidates, 5) correction for nonsimultaneity of radar measurements by making use of a cross-correlation advection field, 6) weighted linear combination of the corrected reflectivity measurements gathered at the various elevation angles of the volume coverage pattern, and 7) production of a 5-min rain accumulation using the advection field to mitigate undersampling effects. In addition to the final Cartesian, 512 km × 512 km, 1 km2 in resolution, radar rainfall product, a map of quality indexes is automatically generated that allows for assessing empirically the accuracy of the estimation. This new product has been validated using 27 episodes observed during the autumns of 2002 and 2003 and the winter of 2005 by three S-band radars of the network. This paper is entirely devoted to the description of the methodology.
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Teyssèdre, H., M. Michou, H. L. Clark, B. Josse, F. Karcher, D. Olivié, V. H. Peuch, et al. "A new chemistry-climate tropospheric and stratospheric model MOCAGE-Climat: evaluation of the present-day climatology and sensitivity to surface processes." Atmospheric Chemistry and Physics Discussions 7, no. 4 (August 2, 2007): 11295–398. http://dx.doi.org/10.5194/acpd-7-11295-2007.

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Abstract. We present the chemistry-climate configuration of the Météo-France Chemistry and Transport Model, MOCAGE-Climat. MOCAGE-Climat is a state-of-the-art model that simulates the global distribution of ozone and its precursors (82 chemical species) both in the troposphere and the stratosphere, up to the mid-mesosphere (~70 km). Surface processes (emissions, dry deposition), convection, and scavenging are explicitly described in the model that has been driven by the ECMWF operational analyses of the period 2000–2005, on T21 and T42 horizontal grids and 60 hybrid vertical levels, with and without a procedure that reduces calculations in the boundary layer, and with on-line or climatological deposition velocities. Model outputs have been compared to available observations, both from satellites (TOMS, HALOE, SMR, SCIAMACHY, MOPITT) and in-situ instrument measurements (ozone sondes, MOZAIC and aircraft campaigns) at climatological timescales. The distribution of long-lived species is in fair agreement with observations in the stratosphere putting apart shortcomings linked to the large-scale circulation. The variability of the ozone column, both spatially and temporarily, is satisfactory. However, the too fast Brewer-Dobson circulation accumulates too much ozone in the lower to mid-stratosphere at the end of winter. Ozone in the UTLS region does not show any systematic bias. In the troposphere better agreement with ozone sonde measurements is obtained at mid and high latitudes than in the tropics and differences with observations are the lowest in summer. Simulations using a simplified boundary layer lead to ozone differences between the model and the observations up to the mid-troposphere. NOx in the lowest troposphere is in general overestimated, especially in the winter months over the northern hemisphere, which might result from a positive bias in OH. Dry deposition fluxes of O3 and nitrogen species are within the range of values reported by recent inter-comparison model exercises. The use of climatological deposition velocities versus deposition velocities calculated on-line had greatest impact on HNO3 and NO2 in the troposphere.
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Viel, Christian, Anne-Lise Beaulant, Jean-Michel Soubeyroux, and Jean-Pierre Céron. "How seasonal forecast could help a decision maker: an example of climate service for water resource management." Advances in Science and Research 13 (April 12, 2016): 51–55. http://dx.doi.org/10.5194/asr-13-51-2016.

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Abstract. The FP7 project EUPORIAS was a great opportunity for the climate community to co-design with stakeholders some original and innovative climate services at seasonal time scales. In this framework, Météo-France proposed a prototype that aimed to provide to water resource managers some tailored information to better anticipate the coming season. It is based on a forecasting system, built on a refined hydrological suite, forced by a coupled seasonal forecast model. It particularly delivers probabilistic river flow prediction on river basins all over the French territory. This paper presents the work we have done with "EPTB Seine Grands Lacs" (EPTB SGL), an institutional stakeholder in charge of the management of 4 great reservoirs on the upper Seine Basin. First, we present the co-design phase, which means the translation of classical climate outputs into several indices, relevant to influence the stakeholder's decision making process (DMP). And second, we detail the evaluation of the impact of the forecast on the DMP. This evaluation is based on an experiment realised in collaboration with the stakeholder. Concretely EPTB SGL has replayed some past decisions, in three different contexts: without any forecast, with a forecast A and with a forecast B. One of forecast A and B really contained seasonal forecast, the other only contained random forecasts taken from past climate. This placebo experiment, realised in a blind test, allowed us to calculate promising skill scores of the DMP based on seasonal forecast in comparison to a classical approach based on climatology, and to EPTG SGL current practice.
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Vernay, Matthieu, Matthieu Lafaysse, Diego Monteiro, Pascal Hagenmuller, Rafife Nheili, Raphaëlle Samacoïts, Deborah Verfaillie, and Samuel Morin. "The S2M meteorological and snow cover reanalysis over the French mountainous areas: description and evaluation (1958–2021)." Earth System Science Data 14, no. 4 (April 13, 2022): 1707–33. http://dx.doi.org/10.5194/essd-14-1707-2022.

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Abstract. This work introduces the S2M (SAFRAN–SURFEX/ISBA–Crocus–MEPRA) meteorological and snow cover reanalysis in the French Alps, Pyrenees and Corsica, spanning the time period from 1958 to 2021. The simulations are made over elementary areas, referred to as massifs, designed to represent the main drivers of the spatial variability observed in mountain ranges (elevation, slope and aspect). The meteorological reanalysis is performed by the SAFRAN system, which combines information from numerical weather prediction models (ERA-40 reanalysis from 1958 to 2002, ARPEGE from 2002 to 2021) and the best possible set of available in situ meteorological observations. SAFRAN outputs are used to drive the Crocus detailed snow cover model, which is part of the land surface scheme SURFEX/ISBA. This model chain provides simulations of the evolution of the snow cover, underlying ground and the associated avalanche hazard using the MEPRA model. This contribution describes and discusses the main climatological characteristics (climatology, variability and trends) and the main limitations of this dataset. We provide a short overview of the scientific applications using this reanalysis in various scientific fields related to meteorological conditions and the snow cover in mountain areas. An evaluation of the skill of S2M is also displayed, in particular through comparison to 665 independent in situ snow depth observations. Further, we describe the technical handling of this open-access dataset, available at https://doi.org/10.25326/37#v2020.2. The S2M data are provided by Météo-France – CNRS, CNRM, Centre d'Études de la Neige, through AERIS (Vernay et al., 2022).
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18

Gao, Ya, Huijun Wang, and Dong Chen. "The Capability of ENSEMBLES Models in Predicting the Principal Modes of Pan-Asian Monsoon Precipitation." Journal of Climate 28, no. 21 (October 30, 2015): 8486–510. http://dx.doi.org/10.1175/jcli-d-15-0010.1.

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Abstract The predictability of the dominant modes of summer (June–September) precipitation in the pan-Asian monsoon region is evaluated based on 1-month-lead retrospective forecasts in five state-of-the-art coupled models from the ENSEMBLES project for the period 1979–2005. The results show that the models and their multimodel ensemble mean (MME) perform well in reproducing the interannual variability of the climatology and the spatiotemporal distribution of the first mode of summer precipitation in the pan-Asian monsoon region. The associated oceanic and atmospheric circulation indicators are also well captured, such as the spatiotemporal structures of the simultaneous El Niño–Southern Oscillation (ENSO) and Antarctic Oscillation in the Pacific Ocean (AAOSP). Moreover, the interannual variation of the preceding AAOSP can also be captured by some of the coupled models. For individual models, the ECMWF, Météo-France, and Met Office models exhibit better skill with respect to the first mode of summer precipitation in the pan-Asian monsoon region, which displays a tripole pattern from north to south over 80°–140°E. In addition, these models can successfully predict the intensity and location of the associated ENSO, as well as the simultaneous summer AAOSP distributions. By contrast, the prediction capabilities of the Leibniz Institute of Marine Sciences (IFM-GEOMAR) and Euro-Mediterranean Center for Climate Change (CMCC-INGV) models are relatively weaker. Furthermore, the predictions of the second mode of the summer precipitation in the pan-Asian monsoon region are investigated. Some of the ENSEMBLES models show good capability in predicting the spatiotemporal distribution of the second mode, owing to the successful prediction of the atmospheric convection activities over the tropical Indian Ocean.
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19

Durand, Yves, Gérald Giraud, Martin Laternser, Pierre Etchevers, Laurent Mérindol, and Bernard Lesaffre. "Reanalysis of 47 Years of Climate in the French Alps (1958–2005): Climatology and Trends for Snow Cover." Journal of Applied Meteorology and Climatology 48, no. 12 (December 1, 2009): 2487–512. http://dx.doi.org/10.1175/2009jamc1810.1.

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Abstract Since the early 1990s, Météo-France has used an automatic system combining three numerical models to simulate meteorological parameters, snow cover stratigraphy, and avalanche risk at various altitudes, aspects, and slopes for a number of mountainous regions (massifs) in the French Alps and the Pyrenees. This Système d’Analyse Fournissant des Renseignements Atmosphériques à la Neige (SAFRAN)–Crocus–Modèle Expert de Prévision du Risque d’Avalanche (MEPRA) model chain (SCM), usually applied to operational daily avalanche forecasting, is here used for retrospective snow and climate analysis. For this study, the SCM chain used both meteorological observations and guess fields mainly issued from the newly reanalyzed atmospheric model 40-yr ECMWF Re-Analysis (ERA-40) data and ran on an hourly basis over a period starting in the winter of 1958/59 until recent past winters. Snow observations were finally used for validation, and the results presented here concern only the main climatic features of the alpine modeled snowfields at different spatial and temporal scales. The main results obtained confirm the very significant spatial and temporal variability of the modeled snowfields with regard to certain key parameters such as those describing ground coverage or snow depth. Snow patterns in the French Alps are characterized by a marked declining gradient from the northwestern foothills to the southeastern interior regions. This applies mainly to both depths and durations, which exhibit a maximal latitudinal variation at 1500 m of about 60 days, decreasing strongly with the altitude. Enhanced at low elevations, snow depth shows a mainly negative temporal variation over the study period, especially in the north and during late winters, while the south exhibits more smoothed features. The number of days with snow on the ground shows also a significant general signal of decrease at low and midelevation, but this signal is weaker in the south than in the north and less visible at high elevation. Even if a statistically significant test cannot be performed for all elevations and areas, the temporal decrease is present in all the studied quantities. Concerning snow duration, this general decrease can also be interpreted as a sharp variation of the mean values at the end of the 1980s, inducing a step effect in its time series rather than a constant negative temporal trend. The results have also been interpreted in terms of potential for a viable ski industry, especially in the southern areas, and for different changing climatic conditions. Presently, French downhill ski resorts are economically viable from a range of about 1200 m MSL in the northern foothills to 2000 m in the south, but future prospects are uncertain. In addition, no clear and direct relationship between the North Atlantic Oscillation (NAO) or the ENSO indexes and the studied snow parameters could be established in this study.
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20

Tabary, P., J. Desplats, K. Do Khac, F. Eideliman, C. Gueguen, and J.-C. Heinrich. "The New French Operational Radar Rainfall Product. Part II: Validation." Weather and Forecasting 22, no. 3 (June 1, 2007): 409–27. http://dx.doi.org/10.1175/waf1005.1.

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Abstract A new operational radar-based rainfall product has been developed at Météo-France and is currently being deployed within the French operational network. The new quantitative precipitation estimation (QPE) product is based entirely on radar data and includes a series of modules aimed at correcting for ground clutter, partial beam blocking, and vertical profile of reflectivity (VPR) effects, as well as the nonsimultaneity of radar measurements. The surface rainfall estimation is computed as a weighted mean of the corrected tilts. In addition to the final QPE, a map of quality indexes is systematically generated. This paper is devoted to the validation of the new radar QPE. The VPR identification module has been specifically validated by analyzing 489 precipitation events observed over 1 yr by a representative eight-radar subset of the network. The conceptual model of VPR used in the QPE processing chain is shown to be relevant. A climatology of the three shape parameters of the conceptual VPR (brightband peak, brightband thickness, and upper-level decreasing rate) is established and the radar-derived freezing-level heights are shown to be in good agreement with radiosonde data. A total of 27 precipitation events observed by three S-band radars of the network during the winter of 2005 and the autumns of 2002 and 2003 are used to compare the new radar QPE to the old one. Results are stratified according to the distance to the radar and according to the height of the freezing level. The Nash criterion is increased from 0.23 to 0.62 at close range (below 50 km) and from 0.35 to 0.42 at long range (between 100 and 150 km). The relevance of the proposed quality indexes is assessed by examining their statistical relationship with long-term radar–rain gauge statistics. Mosaics of QPE and quality indexes are also illustrated.
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21

Teyssèdre, H., M. Michou, H. L. Clark, B. Josse, F. Karcher, D. Olivié, V. H. Peuch, et al. "A new tropospheric and stratospheric Chemistry and Transport Model MOCAGE-Climat for multi-year studies: evaluation of the present-day climatology and sensitivity to surface processes." Atmospheric Chemistry and Physics 7, no. 22 (November 26, 2007): 5815–60. http://dx.doi.org/10.5194/acp-7-5815-2007.

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Abstract. We present the configuration of the Météo-France Chemistry and Transport Model (CTM) MOCAGE-Climat that will be dedicated to the study of chemistry and climate interactions. MOCAGE-Climat is a state-of-the-art CTM that simulates the global distribution of ozone and its precursors (82 chemical species) both in the troposphere and the stratosphere, up to the mid-mesosphere (~70 km). Surface processes (emissions, dry deposition), convection, and scavenging are explicitly described in the model that has been driven by the ECMWF operational analyses of the period 2000–2005, on T21 and T42 horizontal grids and 60 hybrid vertical levels, with and without a procedure that reduces calculations in the boundary layer, and with on-line or climatological deposition velocities. Model outputs have been compared to available observations, both from satellites (TOMS, HALOE, SMR, SCIAMACHY, MOPITT) and in-situ instrument measurements (ozone sondes, MOZAIC and aircraft campaigns) at climatological timescales. The distribution of long-lived species is in fair agreement with observations in the stratosphere putting aside the shortcomings associated with the large-scale circulation. The variability of the ozone column, both spatially and temporarily, is satisfactory. However, because the Brewer-Dobson circulation is too fast, too much ozone is accumulated in the lower to mid-stratosphere at the end of winter. Ozone in the UTLS region does not show any systematic bias. In the troposphere better agreement with ozone sonde measurements is obtained at mid and high latitudes than in the tropics and differences with observations are the lowest in summer. Simulations using a simplified boundary layer lead to larger ozone differences between the model and the observations up to the mid-troposphere. NOx in the lowest troposphere is in general overestimated, especially in the winter months over the Northern Hemisphere, which may result from a positive bias in OH. Dry deposition fluxes of O3 and nitrogen species are within the range of values reported by recent inter-comparison model exercises. The use of climatological deposition velocities versus deposition velocities calculated on-line had greatest impact on HNO3 and NO2 in the troposphere.
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22

Terzago, Silvia, Giulio Bongiovanni, and Jost von Hardenberg. "Seasonal forecasting of snow resources at Alpine sites." Hydrology and Earth System Sciences 27, no. 2 (January 27, 2023): 519–42. http://dx.doi.org/10.5194/hess-27-519-2023.

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Abstract. Climate warming in mountain regions is resulting in glacier shrinking, seasonal snow cover reduction, and changes in the amount and seasonality of meltwater runoff, with consequences on water availability. Droughts are expected to become more severe in the future with economical and environmental losses both locally and downstream. Effective adaptation strategies involve multiple timescales, and seasonal forecasts can help in the optimization of the available snow and water resources with a lead time of several months. We developed a prototype to generate seasonal forecasts of snow depth and snow water equivalent with a starting date of 1 November and a lead time of 7 months, so up to 31 May of the following year. The prototype has been co-designed with end users in the field of water management, hydropower production and mountain ski tourism, meeting their needs in terms of indicators, time resolution of the forecasts and visualization of the forecast outputs. In this paper we present the modelling chain, based on the seasonal forecasts of the ECMWF and Météo-France seasonal prediction systems, made available through the Copernicus Climate Change Service (C3S) Climate Data Store. Seasonal forecasts of precipitation, near-surface air temperature, radiative fluxes, wind and relative humidity are bias-corrected and downscaled to three sites in the Western Italian Alps and finally used as input for the physically based multi-layer snow model SNOWPACK. Precipitation is bias-corrected with a quantile mapping method using ERA5 reanalysis as a reference and then downscaled with the RainFARM stochastic procedure in order to allow an estimate of uncertainties due to the downscaling method. The impacts of precipitation bias adjustment and downscaling on the forecast skill have been investigated. The skill of the prototype in predicting the deviation of monthly snow depth with respect to the normal conditions from November to May in each season of the hindcast period 1995–2015 is demonstrated using both deterministic and probabilistic metrics. Forecast skills are determined with respect to a simple forecasting method based on the climatology, and station measurements are used as reference data. The prototype shows good skills at predicting the tercile category, i.e. snow depth below and above normal, in the winter (lead times: 2–3–4 months) and spring (lead times: 5–6–7 months) ahead: snow depth is predicted with higher accuracy (Brier skill score) and higher discrimination (area under the relative operating characteristics (ROC) curve skill score) with respect to a simple forecasting method based on the climatology. Ensemble mean monthly snow depth forecasts are significantly correlated with observations not only at short lead times of 1 and 2 months (November and December) but also at lead times of 5 and 6 months (March and April) when employing the ECMWFS5 forcing. Moreover the prototype shows skill at predicting extremely dry seasons, i.e. seasons with snow depth below the 10th percentile, while skills at predicting snow depth above the 90th percentile are model-, station- and score-dependent. The bias correction of precipitation forecasts is essential in the case of large biases in the global seasonal forecast system (MFS6) to reconstruct a realistic snow depth climatology; however, no remarkable differences are found among the skill scores when the precipitation input is bias-corrected, downscaled, or bias-corrected and downscaled, compared to the case in which raw data are employed, suggesting that skill scores are weakly sensitive to the treatment of the precipitation input.
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23

Barbu, A. L., J. C. Calvet, J. F. Mahfouf, and S. Lafont. "Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over France." Hydrology and Earth System Sciences 18, no. 1 (January 14, 2014): 173–92. http://dx.doi.org/10.5194/hess-18-173-2014.

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Abstract. The land monitoring service of the European Copernicus programme has developed a set of satellite-based biogeophysical products, including surface soil moisture (SSM) and leaf area index (LAI). This study investigates the impact of joint assimilation of remotely sensed SSM derived from Advanced Scatterometer (ASCAT) backscatter data and the Copernicus Global Land GEOV1 satellite-based LAI product into the the vegetation growth version of the Interactions between Soil Biosphere Atmosphere (ISBA-A-gs) land surface model within the the externalised surface model (SURFEX) modelling platform of Météo-France. The ASCAT data were bias corrected with respect to the model climatology by using a seasonal-based CDF (Cumulative Distribution Function) matching technique. A multivariate multi-scale land data assimilation system (LDAS) based on the extended Kalman Filter (EKF) is used for monitoring the soil moisture, terrestrial vegetation, surface carbon and energy fluxes across the domain of France at a spatial resolution of 8 km. Each model grid box is divided into a number of land covers, each having its own set of prognostic variables. The filter algorithm is designed to provide a distinct analysis for each land cover while using one observation per grid box. The updated values are aggregated by computing a weighted average. In this study, it is demonstrated that the assimilation scheme works effectively within the ISBA-A-gs model over a four-year period (2008–2011). The EKF is able to extract useful information from the data signal at the grid scale and distribute the root-zone soil moisture and LAI increments throughout the mosaic structure of the model. The impact of the assimilation on the vegetation phenology and on the water and carbon fluxes varies from one season to another. The spring drought of 2011 is an interesting case study of the potential of the assimilation to improve drought monitoring. A comparison between simulated and in situ soil moisture gathered at the twelve SMOSMANIA (Soil Moisture Observing System–Meteorological Automatic Network Integrated Application) stations shows improved anomaly correlations for eight stations.
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24

Bourras, Denis. "Comparison of Five Satellite-Derived Latent Heat Flux Products to Moored Buoy Data." Journal of Climate 19, no. 24 (December 15, 2006): 6291–313. http://dx.doi.org/10.1175/jcli3977.1.

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Abstract Five satellite products of latent heat flux at the sea surface were compared to bulk fluxes calculated with data from 75 moored buoys, on almost 36 successive months from 1998 to 2000. The five products compared are the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Dataset (HOAPS-2), the Japanese Ocean Flux Datasets with Use of Remote Sensing Observations (J-OFURO), the Jones dataset, the Goddard Satellite-Based Surface Turbulent Fluxes, version 2 (GSSTF-2), and the Bourras–Eymard–Liu dataset (BEL). The comparisons were performed under tropical and midlatitude environmental conditions, with three datasets based on 66 Tropical Atmosphere–Ocean array (TAO) buoys in the tropical Pacific, nine National Data Buoy Center (NDBC) buoys off the U.S. coasts, and four Met Office/Météo-France (UK–MF) moorings west of the United Kingdom and France, respectively. The satellite products did not all compare well to surface data. However, for each in situ dataset (TAO, NDBC, or UK–MF) at least one satellite product was found that had a good fit to surface data, that is, an rms deviation of 15–30 W m−2. It was found that HOAPS-2, J-OFURO, GSSTF-2, and BEL satellite products had moderate systematic errors with respect to surface data, from −13 to 26 W m−2, and small biases at midlatitudes (6–8 W m−2). Most of the satellite products were able to render the seasonal cycle of the latent heat flux calculated with surface data. The estimation of near-surface specific humidity was found to be problematic in most products, but it was best estimated in the HOAPS-2 product. GSSTF-2 and J-OFURO strongly overestimated the surface flux variations in time and space compared to surface data and to a flux climatology. With respect to TAO data, Jones fluxes yielded good results in terms of rms deviation (27 W m−2) but also presented a large systematic deviation. Overall, for application of the satellite fluxes to the world oceans, it was found that HOAPS-2 was the most appropriate product, whereas for application to the Tropics, BEL fluxes had the best performance in rms with respect to TAO data (24 W m−2).
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25

Cantat, Olivier. "Dynamique spatio-temporelle d’un événement météo-climatique extrême : la canicule de l’été 2003 en Europe de l’ouest." Climatologie, Volume 2 (2005). http://dx.doi.org/10.4267/climatologie.908.

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26

"Les phénomènes climatiques extrêmes en France." Revue Générale Nucléaire, no. 2 (March 2021): 24–25. http://dx.doi.org/10.1051/rgn/20212024.

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De quelle nature sont les phénomènes climatiques extrêmes en France ? Comment évoluent-ils et comment les étudie-t-on ? Décryptage avec Jean-Michel Soubeyroux, directeur scientifique adjoint de la climatologie et des services climatiques à Météo France
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"Quatrième Rencontre Météo Jeunes - 25 et 26 mai 2002 - Météopole de Toulouse (31) - la climatologie : mémoire et évolution du climat." La Météorologie 8, no. 37 (2002): 13. http://dx.doi.org/10.4267/2042/35943.

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