The aim is to determine the magnitude of flow variables for return periods much longer than the observed and to obtain the correspondent quantil for sites with scarce data using a Regional Frequency Analysis approach based on $L-moment$ statistics ($ARF-LM$). The area under analysis comprises mountain basins between the Bermejo and the Santa Cruz rivers. Thirty-two gauging stations were analyzed and five variables were determined: annual flow ($Q_{a tilde{n}o}$) and seasonal flows: winter $Q_I$ (july, august, september), spring $Q_P$ (october, november, december), summer $Q_V$ (january, february, march) and autumn $Q_O$ (april, may, june), from the average daily flow observed. Independence, randomness, normalcy, and homogeneity conditions were verified. Normalcy is rejected in 60 % of the cases, summer and autumn flows being the variables with the least degree of normalcy. Lack of both independence and randomness occurs in 34 % of the series analyzed, notably the winter and autumn flows with a level of significance of 5 %. The Los Patos, San Juan, Cuevas, Diamante, Atuel, Grande, Valenzuela, Poti Malal, Neuquén and Santa Cruz rivers did not show any significant trends in the variables analyzed. A statistically significant increasing trend was detected in some variables and locations of northwestern and central-western of Argentina while a decreasing trend was observed in some variables and locations in the Patagonian Andes. Flows $Q_{a tilde{n}o}$), $Q_I$ and $Q_V$ show abrupt changes in over 65 % of the cases while $Q_P$ only in 44 %. In general, the jump in mean values took place in the 1970s.A homogeneous region was identified for each of the five variables. Homogeneity was verified by means of discordance and heterogeneity tests and the best-fit distribution through $Z^{DIST}$ and $PUM_T$ measures. The distributions used were: generalized extreme values, generalized logistic, generalized normal, normal, Gumbel, generalized Pareto, exponential, and Pearson III. In all cases the homogeneous region includes only stations in the southern Central Andes, from the Tunuyan to the Colorado river. The Pearson III and Gumbel distributions exhibit the best fit.

El objetivo es determinar la magnitud del caudal anual y estacional, para periodos de retorno mucho mayores que los observados y obtener el cuantil correspondiente en sitios sin información, a partir del Análisis Regional de Frecuencias basadas en la estadística de momentos $L$ ($ARF-LM$). El área de estudio abarca las cuencas cordilleranas desde el río Bermejo hasta el río Santa Cruz. Los sitios analizados fueron 32 y se determinaron 5 variables: caudal anual ($Q_{a tilde{n}o}$) y caudales estacionales: invierno $Q_I$ (julio, agosto, setiembre), primavera $Q_P$ (octubre, noviembre, diciembre), verano $Q_V$ (enero, febrero, marzo) y otoño $Q_O$ (abril, mayo, junio), a partir del caudal medio diario observado. Se verificaron las condiciones de independencia, aleatoriedad, normalidad y homogeneidad. La normalidad es rechazada en el 60 % de los casos, particularmente en los caudales de verano y otoño; la ausencia de independencia y aleatoriedad ocurre en el 34 % de las series analizadas, destacándose el caudal de invierno y otoño, para un nivel de significancia de $ alpha=5 %$. Los ríos Los Patos, San Juan, Las Cuevas, Diamante, Atuel, Grande, Valenzuela, Poti Malal, Neuquén y Santa Cruz no mostraron tendencias significativas en ninguna de las variables. Se detectaron tendencia creciente significativa en variables y sitios del noroeste y centro-oeste argentino y tendencia decreciente en variables y sitios de Los Andes patagónicos. Los caudales $Q_a tilde{n}o$, $Q_I$ y $Q_V$ muestran cambios abruptos en el 65 % de los casos, el $Q_P$, en un 44 %. El salto en los valores medios generalmente se produce en la década del 70. Se identificaron las regiones homogéneas para las 5 variables analizadas. La homogeneidad se verificó mediante pruebas de Discordancia y Heterogeneidad y la adopción de la distribución de mejor ajuste por medio de la medida $Z^{DIST}$ y $PUM_T$. Las distribuciones empleadas son: Generalizada de Valores Extremos, Logística Generalizada, Generalizada Normal, Normal, Gumbel, Pareto Generalizada, Exponencial y Pearson III. En todos los casos, la región homogénea encontrada incluye solamente estaciones de Los Andes Centrales sur, desde el río Tunuyan al Colorado. La función Pearson III y Gumbel, son las que presentan el mejor ajuste.

Este trabalho analisa as condições meteorológicas que levaram à ocorrência de uma intensa onda de calor na região subtropical da América do Sul, com temperaturas máximas superiores aos 40°C imediatamente à leste dos Andes, na última semana de Janeiro de 2003. Para isso, os termos da Equação Termodinâmica foram avaliados a partir de simulações numéricas realizadas com o modelo regional Eta/CPTEC. O forte aumento da temperatura foi provocado pelo aquecimento por compressão adiabática, produto da subsidência, e pelo aquecimento superficial imediatamente a leste dos Andes. A análise da Equação Omega Quase-Geostrófica permitiu estabelecer que a subsidência de grande escala se deveu fundamentalmente ao avanço de uma crista de onda longa nos níveis meios da atmosfera. Além disso, as observações e as simulações numéricas apontam para a ocorrência de subsidência forçada (vento Zonda) a leste dos Andes, associada ao deslocamento de um cavado de onda curta imerso na crista de onda longa, à aproximação de uma frente fria e ao deslocamento para o sul da Baixa Termo-orográfica. Esse fato, muito pouco freqüente no verão, em combinação com os processos descritos anteriormente, explicaria a ocorrência de recordes históricos de temperatura no oeste da Argentina.

This work analyzes the meteorological conditions that caused the occurrence of an intense heat wave over subtropical South America, with temperatures higher than 40°C immediately to the east of the Andes, during the last week of January 2003. To that purpose the terms of the thermodynamic equation were evaluated through numerical simulations performed with the Eta/CPTEC regional model. The strong temperature increase was caused by adiabatic warming (subsidence) as well as by the net positive surface heat flux, especially to the east of the Andes. The qualitative analysis of the Quasi-Geostrophic Omega Equation revealed that the large-scale subsidence was the result of the cold horizontal temperature advection and the advance of a wide ridge at midlevels. Additionally, the presence of forced orographic subsidence (Zonda wind) is evident from observations and numerical simulations in connection with the passage of a short trough immerse in the wider ridge, the approach of a cold front and the southward progress of the thermal-orographic low. Since this phenomenon is quite uncommon during summer, its incidence in combination to the other processes previously described would explain the occurrence of extreme maximum temperatures over western Argentina.