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The CLARIS-LPB project, funded from 2008 to 2012 by the 7th Framework Programme of the European Commission, aimed at projecting regional climate change impacts in the La Plata Basin (LPB) in southeastern South America focusing on the periods 2010-2040 and 2070-2100. Such a coordinated projection of regional climate change scenarios was key in successfully designing adaptation strategies for land-use, agriculture, rural development, hydro power production, river transportation, water resources and wetland ecosystems. Topics covered in this special include characteristics of climate variability over the region, together with trends, extreme events and uncertainties for modelled regional climate projections.

The study of psychological barriers and the attribution of social meaning is a complex and subjective process, but essential for the development of strategies to adapt to climate change and land-use management. The objective of this paper is to point out and discuss aspects that comprise climate vulnerability, especially regarding the climate perceptions understood as an element for the development of community adaptation strategies. The first part presents two study cases and the second part presents propositions for developing climate adaptation strategies based on the results of these cases. The paper focuses on two aspects: the perception of climate dynamics and the relationship between vulnerability and local climate dynamics. In order to establish the relationship between climate dynamics and the level of vulnerability perceived, a qualitative approach was adopted. Field data collection consisted of observing local civil association meetings and conducting semi-structured interviews with local actors. Although both communities studied are strongly affected by climate events, their perception of climate influences is essentially different. The difference in perception arises mainly from the different context in which climate events acquire meaning, rather than any ability of assigning meaning to possible climate change. To understand the dynamics of establishing an adaptation strategy, the motivational problems would be a stimulus, a causative agent of reflections on the conditions of vulnerability to climate change and reflection about their limit-situations. The final propositions present "Adaptation learning process pre-steps framework" that emerges from the description of contrasts in perceptions/cognitions observed between the two study cases. It is a model for the visualization of different and better living conditions, the unknown-viable, which enable social actors to become aware of capacity of acting and governance.

We explore the bias in monthly and seasonal mean precipitation simulated by ensembles of different regional climate models over South America within the context of the EU-FP6 CLARIS project (A Europe-South America Network for Climate Change Assessment and Impact Studies). We briefly described two series of coordinated simulations: (i) Case studies of anomalous months for south-eastern South America performed with an ensemble of six models, and (ii) A multiyear simulation of the period 1991–2000 performed by four models. The models have been forced with the European Centre for Medium Range Weather Forecasting Reanalysis (ERA-40) and are compared to observational data compiled by the Climatic Research Unit (CRU). The ensemble-mean bias can be large when simulating particular extreme periods in La Plata Basin. Our multi-model analysis suggests that even though the ten-year ensemble mean is able to capture the major regional characteristics of seasonal mean precipitation for South America, models individually display considerable precipitation biases especially in tropical areas. The relatively good performance of the multimodel annual average over La Plata Basin results from the cancelation of offsetting errors in the individual models. Im EU-FP6 Projekt CLARIS (” Climate Change Assessment and Impact Studies“ – ein europ¨aischs ¨udamerikanisches Netzwerk f ¨ur die Absch¨atzung von Klima¨anderungen und Wirkungsstudien) wird die Abweichung im Monats- und jahreszeitlichem mittleren Niederschlag ¨uber S ¨udamerika f ¨ur ein Ensemble von regionalen Klimamodellen berechnet. Es werden zwei Arten von Simulationen beschrieben: (i) Fallstudien mit einem Ensemble von sechs Modellen f ¨ur auff¨allige Monate ¨uber dem S ¨udosten von S ¨udamerika, und (ii) eine Simulation ¨uber mehrere Jahre (1991–2000) mit vier Modellen. Die Modelle werden mit Reanalysen (ERA-40) des Europ¨aischen Zentrums f ¨ur Mittelfristige Wettervorhersage angetrieben und mit Beobachtungsdatens¨atzen der Climate Research Unit (CRU) verglichen. F ¨ur das Ensemblemittel ergeben sich ¨uber dem La Plata Einzugsgebiet f ¨ur spezielle Extremereignisse große Abweichungen. Die Analyse mehrerer Modelle legt nahe, dass, obwohl die 10-Jahres-Ensembles die wesentlichen Eigenschaften des mittleren jahreszeitlichen Niederschlags ¨uber S ¨udamerika wiedergeben k¨onnen, einzelne Modelle jedoch wesentliche Abweichungen im Niederschlag zeigen, speziell ¨uber tropischen Gebieten. Das relativ gute Ergebnis des mittleren Jahresniederschlags im Ensemblemittel ¨uber dem La Plata Einzugsgebiet ist darauf zur ¨uckzuf ¨uhren, dass sich die Fehler der einzelnen Modelle bei der Mittelung nahezu aufheben. Fil: Menendez, Claudio Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmosfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmosfera; Argentina Fil: de Castro, Manuel. Universidad de Castilla-La Mancha; España Fil: Sörensson, Anna. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmosfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmosfera; Argentina Fil: Boulanger, Jean Philippe. Laboratoire d’Océanographie et du Climat; Francia Fil: CLARIS Modeling Groups. No especifica

The present paper describes the quality-control component of an automatic procedure (APACH: A Procedure for Automated Quality Control and Homogenization of Weather Station Data) developed to control quality and homogenize the historical daily temperature and precipitation data from meteorological stations. The quality-control method is based on a set of decision-tree algorithms analyzing separately precipitation and minimum and maximum temperature. All our tests are non-parametric and therefore are potentially useful in regions or countries presenting different climates as those observed in Argentina. The method is applied to the 1959-2005 historical daily database of the Argentine National Weather Service. Our results are coherent with the history of the Weather Service and more specifically with the history of implementation of systematized quality control processes. In temperature, our method detects a larger number of suspect values before 1967 (when there was no quality control) and after 1997 (when only real-time quality control had been applied). In precipitation, the detection of error in extreme precipitations is complex, but our method clearly detected a strong decrease in the number of potential outliers after 1976 when the National Weather Service was militarized, and the network was strongly reduced, focusing more on airport weather stations. Also in precipitation, we analyze in detail the long dry sequences and are able to identify potential long erroneous sequences. This is important for the use of the data for hydrological or agricultural impact studies. Finally, all the data are flagged with codes representing the path followed by the record in our decision-tree algorithms. While each code is associated to one of the categories ("Useful", "Need-Check", "Doubtful" or "Suspect"), the final user is free to redefine such category-assignment.

The goal of the CLARIS project was to build an integrated European-South American network dedicated to promote common research strategies to observe and predict climate changes and their consequent socio-economic impacts taking into account the climate and societal peculiarities of South America. Reaching that goal placed the present network as a privileged advisor to contribute to the design of adaptation strategies in a region strongly affected by and dependent on climate variability (e. g. agriculture, health, hydro-electricity). Building the CLARIS network required fulfilling the following three objectives: (1) The first objective of CLARIS was to set up and favour the technical transfer and expertise in earth system and regional climate modelling between Europe and South America together with the providing of a list of climate data (observed and simulated) required for model validations; (2) The second objective of CLARIS was to facilitate the exchange of observed and simulated climate data between the climate research groups and to create a South American high-quality climate database for studies in extreme events and long-term climate trends; (3) Finally, the third objective of CLARIS was to strengthen the communication between climate researchers and stakeholders, and to demonstrate the feasibility of using climate information in the decision-making process.

Dans le cadre de la participation française au programme international TOGA, la campagne SURTROPAC 16 a eu lieu du 19 janvier au 17 février 1992, le long du méridien 165°E de 20°S à 10°N. Cette campagne a été réalisée par le Groupe SURTROPAC du Centre ORSTOM de Nouméa, Nouvelle-Calédonie, avec la collaboration du Groupe FLUPAC de ce même centre et le PMEL-NOAA de Seattle aux Etats-Unis. Elle s'est déroulée à bord du navire océanographique LE NOROIT de la flotte océanographique nationale. Au cours de la campagne SURTROPAC 16 les travaux suivants ont été effectués : 54 stations à la sonde CTDO2 (O-1000 m) avec prélèvements à la rosette, 58 tirs XBT, des mesures en continu du courant absolu (0-400 m) à l'aide d'un profileur de courant à effet Doppler acoustique, des mesures en continu de la température et de la salinité de surface, des observations météorologiques, des largages de bouées dérivantes ainsi que des relevages, poses et vérifications de mouillages du réseau multinational TOGA-TAO. Ce rapport décrit le déroulement de la campagne ainsi que le matériel et les méthodes utilisés. Il présente également les figures correspondant aux premiers résultats. (Résumé d'auteur)

Los problemas de calidad en series de datos meteorológicos resultan principalmentede errores de medición o registro y de cambios en las condicionesde medición o en el entorno de la estación meteorológica (inhomogeneidades). Cuando no se dispone de información adicional (metadata) es necesario contarcon una metodología confiable de control de calidad que permita detectar,en una serie de datos meteorológicos proveniente de una estación, errores einhomogeneidades. En esta tesis se presenta una caracterización detalladade las series de datos de temperatura y precipitación, y se discuten las diferenciasentre estos dos tipos de variables. Se introduce un marco conceptualbasado en modelos estadísticos para los problemas de detección de errores yde detección de inhomogeneidades (puntos de corte en la serie). Se muestra laimportancia de la apropiada selección del modelo y se propone metodologíapara cada uno de los problemas en los dos tipos de variables meteorológicas. Características de los métodos propuestos para controlar la serie dedatos de una estación objetivo: 1) Multivariados, usan las series de observacionesde estaciones cercanas; 2) No hacen supuestos sobre la distribuciónde los datos; 3) Usan procedimientos de estimación robustos; 4) Atiendena la estructura de correlación presente en la serie de datos; 5) Son capacesde detectar múltiples tipos de inhomogeneidades. Usando datos de modelosnuméricos regionales se estudia el desempeño de los métodos propuestos bajodiferentes escenarios. The lack of quality in climate data is mostly the result of measurementor recording errors and arbitrary changes in the monitoring conditions orsurrounding environment (inhomogeneities). When additional information (metadata) is not available, a reliable methodology to detect errors and inhomogeneitiesis required. In this thesis we present a detailed characterizationof temperature and precipitation time series, while discussing their basic differences. We introduce a conceptual framework based on statistical modelsfor the error and inhomogeneity detection issues. The relevance in the choiceof the statistical model is shown, and separate methods are developed forboth problems and these two main meteorological variables. Main featuresof the proposed methods, to control the target station time series, are: 1) Multivariate, they use data from nearby stations; 2) No specific assumptionsabout the distribution of data; 3) Use of robust estimation procedures; 4) They respond to the actual correlation structure present in data; 5) Capableof detecting several types of inhomogeneities. Finally, we study the performanceof the methods through the use of numerical regional models underchanging scenarios. Fil: Farall, Rodolfo Andrés. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.