Climate Change Impacts on Atmospheric Circulation and Daily Precipitation in the Argentine Pampas Region

Pollution & threats to the environmen

Reducing techno-anxiety in high school teachers by improving their ICT problem-solving skills

Teachers need to continuously update their information and communication technologies (ICT) knowledge, but they are usually not trained to deal with the problems arising from their use. In fact, studies in the literature report techno-anxiety (i.e. unpleasant physiological activation and discomfort due to present or future use of ICT) in teachers. Thus, the goal of this action research is to study if teachers’ techno-anxiety can be reduced by increasing their ability to solve technological problems. An inter-subject experiment has been carried out with 46 teachers. High school teachers were chosen because they are digital immigrants, while at the moment of this research their students are digital natives (born around year 2000). Since we could not find any specific training for teachers to increase their resolution skills of technological problems, in order to apply the treatment for our study, we have designed and deployed an online course about ICT problem-solving skills based on the 70/20/10 model for learning and development. Results show the success of the course when it comes to increasing the ICT problem-solving skills and to reducing techno-anxiety.Preprin

Estimación de valores diarios de precipitación y temperaturas en la Cuenca del Plata: reducción de escala estadística

Ponencia presentada en: VI Congreso Internacional de la Asociación Española de Climatología celebrado en Tarragona del 8 al 11 de octubre de 2008.[ES]La Cuenca del Plata, ubicada en el sur de Sudamérica, es la tercera cuenca del mundo por su magnitud. La economía de los países que la conforman depende de la agricultura y la producción hidroeléctrica, sectores que son fuertemente afectados por la variabilidad climática. De manera que es necesario disponer de información climática en escalas que van de la local a la regional a fin de realizar proyecciones a mediano y a largo plazo. En este contexto, en este trabajo se estimaron valores diarios de temperaturas máxima y mínima y la precipitación a escala local en la región de interés, a partir de la información de la circulación atmosférica de gran escala. Para ello se utilizó un método de reducción de escala estadística en dos pasos a fin de estimar las variables climáticas de alta resolución. Los resultados de la validación muestran que la técnica de reducción de escala utilizada tiene un buen desempeño en la región de estudio en escala temporal estacional y anual. Asimismo, el método muestra una capacidad apropiada para reproducir la variabilidad interanual de las variables analizadas.[EN]La Plata Basin, located in southern South America, is the third basin worldwide considering its extent. The region economic wealth depends on agriculture and hydropower production. These sectors are strongly affected by climate variability. Therefore, it is necessary to have climatic information at local to regional scales in order to prospect possible climate evolution at midand long- term. In this context, daily maximum and minimum temperatures and precipitation values were estimated at the local scale using information from large-scale circulation information. For this purpose, a two step statistical downscaling method was used to estimate high-resolution variables. Validation results as a whole show that the downscaling performance is good enough to estimate seasonal and annual mean values and temporal variability of precipitation and maximum and minimum temperatures.Este trabajo fue solventado por los proyectos de la Universidad de Buenos Aires X135, X170 y X605, BID 1728/OC-AR-PICT 38273, CLARIS Project (European Commission Project 001454) y CLARIS LPB

Temporal variability in the length of no-rain spells in Argentina

There is general agreement that changes in the frequency or intensity of extreme weather and climate events would have profound impacts on both human society and the natural environment. Any change in the probability of no rain spell would cause significant damage to agriculture, hydrology, etc. The objectives of this work are to analyze the length of the no-rain spells, the number of days comprising them and their temporal variability. The definition of no-rain spells is based on the length of the sequences of days without precipitation. Forty-two raingages of the National Weather Service were selected for the shorter period 1950-2003 and the longest one 1908-2003, being representatives of the different types of climate existing in Argentina. The data used were processed to obtain consistent homogeneous databases, with less than 10% of months missing for their period of record. The analyses of spatial and temporal patterns of no-rain days are analyzed over the whole period of each station. The annual percentage of no-rain days is greater than 70% in all the Argentinean stations, with an annual cycle: minimum values around 50% in central and northern regions during summer months and maximum values greater than 90% in western and northwestern stations in winter. The empiric frequency distribution of the no-rain spells is analyzed for each series. A major number of cases in the sequence of one day is observed, asymptotically diminishing to zero in length of 35 days towards the northeast to 60 days in the northwest. The maximum lengths of the no-rain spells depending on the region; arriving to extreme cases in the northwestern area and in the station near the Andes which presented sequences of more than 100 days. In order to analyze if there is a change in the length of the dry spells the differences between the empiric frequency distribution of no-rain spells for 198190 and 196070 are analyzed. The widest differences occur in two regions. In the last decade, there is an increase in the empirical frequency in no-rain spell of 3 to 5 days, in the northern stations. Meanwhile in stations located in the center of Argentina there is a decrease in the empirical frequency of the dry spells of 6 to 10 days..Pages: 333-33

Análisis estacional de la frecuencia diaria y la intensidad de los extremos de precipitación sobre el sudeste de Sudamérica Seasonal analysis of daily frequency and extreme intensity of precipitation in the Southeast of South America

En este trabajo se profundiza en el conocimiento de la variabilidad espacial de la precipitación, estudiando la cantidad de días con precipitación y la intensidad media diaria (en milímetros por día), con énfasis en los extremos, definidos a partir de diferentes umbrales. La base de datos utilizada en este trabajo consta de 58 estaciones pluviométricas ubicadas al sudeste de Sudamérica, para la segunda mitad del siglo XX. De noviembre a marzo, dos áreas núcleos centradas en 68º O - 25º S y 45º O - 22º S, presentan más de 50% de días de precipitación por encima de 0,1 mm, mientras que para el resto de la región no se supera el 32%. El patrón de extremos de precipitación, por encima del percentil 75, no muestra grandes diferencias espaciales y estacionales con respecto a los del umbral 0,1mm. Sin embargo la intensidad media diaria de precipitación extrema se incrementa considerablemente con respecto al umbral 0,1mm. En el área núcleo centrada en 45º O - 22º S, la intensidad es de 36 mm/día en verano, y de 20 mm/día en invierno. Mientras que sobre el noroeste de Argentina, supera 38mm/día (8 mm/día) en verano (invierno). En la provincia de Buenos Aires la intensidad media diaria extrema de precipitación es de 32mm/día (20mm/día) en verano (invierno).<br>In this paper the climatology of the different components that composed the monthly rainfall was actualized and extended. For this purpose, we calculated the frequency of daily rainfall and the mean daily intensity for the second half of the century. 58 stations were used for this study. In addition we calculated the climatology for the daily extreme rainfall and its intensity, defining different thresholds according to the regions. Between November and March, we observed two centers (65º W -25º S and 45º W - 22º S) with more than 50% of days with daily rainfall above 0.1 millimeters (mm) , and lower values in the rest of the region. Spatial patterns and seasonal variation of daily rainfall above 75th percentile show similar patterns. Nevertheless, mean daily intensity increased respect to 0.1mm threshold. The centre 45º W - 22º S, in summer, takes values of 36 mm/day and 20 mm/day in winter and 36 mm/day (8 mm/day) in the northeast of Argentina in summer (winter). In the center east of Argentina the intensity of the extreme rainfall exceeds 32mm/day (20mm/day) in summer (winter)

Regionalización de los días secos en Argentina: Un enfoque metodológico Regionalization of dry days in Argentina: A methodological approach

La regionalización de diferentes variables climáticas ha sido llevada a cabo en diversas zonas del mundo, dado que para distintos propósitos es conveniente dividir espacialmente la climatología de una variable en un número de áreas cuasi-homogéneas. El objetivo de este trabajo es la obtención de una regionalización objetiva de las distintas variabilidades temporales de las cantidades de días secos en la República Argentina durante el trimestre de verano. Con el fin de lograr regiones con similar variabilidad temporal en las cantidades de días secos se exploraron dos métodos: Análisis de Componentes Principales (ACP) y el algoritmo de agrupamiento no-jerárquico de k-means. En base a una evaluación de los patrones espaciales, la regionalización obtenida mediante el método de k-means aplicado sobre las componentes principales rotadas más importantes, es más apropiada en comparación con la determinada por el método de ACP rotadas. Mediante este método, el territorio nacional presenta seis regiones principales: las regiones Centro- Este; Noreste; Centro y Sur Bonaerense; Noroeste; Centro-Oeste y Patagónica, las cuales son climáticamente coherentes.Objective regionalizations of different climatic variables have been performed in many regions of the World. For different purposes is convenient to make a spatial regionalization to find quasi-homogeneous climatic regions. The main objective of this work is to identify spatially homogeneous regions of dry days in Argentina with different temporal variabilities during summer season. In order to achieve regions with similar temporal variability in the amount of dry days, two methods are explored: principal component analysis (PCA) and k-means nonhierarchical cluster method. By means of a spatial patterns examination, the regionalization derived by k-means on the most important rotated principal components extracted is more adequate in comparison with the proposed by PCA method. Through this methodology, the country is divided in six main regions: Northeast region; Central-East region; Central and South Buenos Aires region; Northwest region; Central-West region; and Patagonia region, which are climatically consistent

Reducing techno-anxiety in high school teachers by improving their ICT problem-solving skills

Teachers need to continuously update their information and communication technologies (ICT) knowledge, but they are usually not trained to deal with the problems arising from their use. In fact, studies in the literature report techno-anxiety (i.e. unpleasant physiological activation and discomfort due to present or future use of ICT) in teachers. Thus, the goal of this action research is to study if teachers’ techno-anxiety can be reduced by increasing their ability to solve technological problems. An inter-subject experiment has been carried out with 46 teachers. High school teachers were chosen because they are digital immigrants, while at the moment of this research their students are digital natives (born around year 2000). Since we could not find any specific training for teachers to increase their resolution skills of technological problems, in order to apply the treatment for our study, we have designed and deployed an online course about ICT problem-solving skills based on the 70/20/10 model for learning and development. Results show the success of the course when it comes to increasing the ICT problem-solving skills and to reducing techno-anxiety

Yield estimation and sowing date optimization based on seasonal climate information in the three CLARIS sites

International audienceThe present article is a contribution to the CLARIS WorkPackage "Climate and Agriculture", and aims at testing whether it is possible to predict yields and optimal sowing dates using seasonal climate information at three sites (Pergamino, Marcos Juarez and Anguil) which are representative of different climate and soil conditions in Argentina. Considering that we focus on the use of climate information only, and that official long time yield series are not always reliable and often influenced by both climate and technology changes, we decided to build a dataset with yields simulated by the DSSAT (Decision Support System for Agrotechnology Transfer) crop model, already calibrated in the selected three sites and for the two crops of interest (maize and soybean). We simulated yields for three different sowing dates for each crop in each of the three sites. Also considering that seasonal forecasts have a higher skill when using the 3-month average precipitation and temperature forecasts, and that regional climate change scenarios present less uncertainty at similar temporal scales, we decided to focus our analysis on the use of quarterly precipitation and temperature averages, measured at the three sites during the crop cycle. This type of information is used as input (predictand) for non-linear statistical methods (Multivariate Adaptive Regression Splines, MARS; and classification trees) in order to predict yields and their dependency to the chosen sowing date. MARS models show that the most valuable information to predict yield amplitude is the 3-month average precipitation around flowering. Classification trees are used to estimate whether climate information can be used to infer an optimal sowing date in order to optimize yields. In order to simplify the problem, we set a default sowing date (the most representative for the crop and the site) and compare the yield amplitudes between such a default date and possible alternative dates sometimes used by farmers. Above normal average temperatures at the beginning and the end of the crop cycle lead to respectively later and earlier optimal sowing. Using this classification, yields can be potentially improved by changing sowing date for maize but it is more limited for soybean. More generally, the sites and crops which have more variable yields are also the ones for which the proposed methodology is the most efficient. However, a full evaluation of the accuracy of seasonal forecasts should be the next step before confirming the reliability of this methodology under real conditions. © Springer Science + Business Media B.V. 2009