Descripción: This study analyses heating degree-days (HDDs) in Argentina during the period 1900-2008. Gridded temperature data provided by the University of Delaware were analysed to calculate monthly and annual cumulative HDDs. Mean, maximum and minimum values as well as the average duration of the heating season are used to characterize the mean features of the region. Spatial variations are driven by latitude and altitude. The analysis of the temporal distribution of HDDs reveals that the centre of the mean heating season varies from mid-June to mid-July. The length of the cold season grows with increasing latitude and westward with increasing altitude. In the high Andes, the heating season extends all year round. S-mode principal component analysis is used to identify sub-groups of grid points with similar temporal variability. Negative trends in annual cumulative HDDs are detected in most of the country. Linear and nonlinear trends as well as temporal statistics are examined for inter- and intra-annual variability of HDDs to discuss its potential incidence on residential use of natural gas. Seasonal increases in natural gas consumption in the country, including the effect of regional price benefits, could be now better explained not only by population growth but also by the spatial and temporal characterization of the HDD season. © 2012 Royal Meteorological Society.

Descripción: Water resources management and agriculture planning models require a statistical synthesis of some rainfall features, in particular those representing dry atmospheric conditions. The bigger the basin, the more important these features become, as is the case of the La Plata Basin (LPB). This paper focuses on the precipitation variability in the large LPB in South America, analysing the number of months per year with low rainfall and the sequences of months with low rainfall, their theoretical distributions and stability, which are needed as input for the models mentioned above. Long time series are used to analyse the low-frequency variability and the relative importance of decadal variability. Changes are evident in the number of months per year with low rainfall, with a decrease of about 20% in the period after 1970. Theoretical distribution models (binomial and geometric) are fitted to these empirical distributions, and the regional variability of the fitting parameters is shown. In practically the entire region, the goodness-of-fit of the two theoretical models considered is statistically satisfactory. The temporal variability of the parameters of the theoretical binomial (p) and geometric (α) distributions is analysed, in excluding sub-periods of 10 and 5 years, respectively. The results show low-frequency variability overlapped on a decadal variability, with low homogeneous regional behaviour. The distribution models have proven to be efficient for frequency adjustments of the rainfall properties studied. These results are an acceptable and necessary input to decision models in LPB. They also make it possible to infer effects of climate change. Copyright © 2008 Royal Meteorological Society.

Descripción: A Singular value decomposition (SVD) analysis was performed jointly on the daily intensity of extreme rainfall (DIER) over Argentina and the sea surface temperature (SST) of all the oceans from 17.5°N to 90°S in order to identify the large-scale variability of the SSTs related to extreme rainfall, in the period 1962-2005. The main objective of the article is to objectively recognize regions of the tropical and subtropical oceans that could be related with the extreme rainfall over Argentina. Spring is the season that is best represented by the first mode, accounting for up to 45% of the covariance between the DIER and SST. The first SVD mode of spring, summer and autumn presents a pattern of SST relating to the El Niño-Southern Oscillations (ENSO) phenomena with an enhanced DIER in different zones of centre and east of Argentina. In the second SVD mode of spring and summer, the SST patterns show cold conditions in the tropical and subtropical Atlantic and near Indonesia with an enhancement of the DIER in the centre and east of Argentina. These modes show a significant decadal variability. In the third SVD mode of spring and summer, the SST patterns present warm and cold conditions in the Indian Ocean and the centre and western Pacific Ocean (PO) with decreased rainfall in the northern and eastern portion of Argentina, respectively. This mode shows a significant period of temporal variability of around 14 years. The third mode of autumn presents warm conditions in the tropical Atlantic and the southwest PO with a low DIER in the centre and east of Argentina. This mode also presents temporal variability of around 14 years. The correlation between each mode derived from analysis of SVD and climate indices related with SST were computed. © 2012 Royal Meteorological Society.

Descripción: This work proposes to employ the number of dry days (days without precipitation) as a variable of study, and to analyse their spatial and temporal variability in Argentina. Climatological aspects of dry days, such as their annual mean values and its seasonal cycle, were discussed and compared with precipitation features in the country. Linear trends in the annual number of dry days (ANDD) were identified for the period 1960-2005. Most of the regions exhibited decreasing trends, but few stations showed significant ones. The most important trends were present in the Central-West region and over the Patagonian coast and their magnitudes indicated a decrease of two to six dry days per decade. These trends coincide with the observed increase of accumulated precipitation in part of the country during the second half of the 20th century. To identify long-term fluctuations in the ANDD, a low pass filter, a wavelet analysis and a cubic polynomial fit was applied to the longest time series of the selected locations. Through these methodologies, periodicities were identified in the inter-annual and inter-decadal ranges for the last 80 years. The most important significant cycles were observed in the range of 10-24 years, but also, depending on the region, significant inter-annual variations were found. © 2012 Royal Meteorological Society.

Descripción: This paper reviews recent progress made in our understanding of the functioning and variability of the South American Monsoon System (SAMS) on time scales varying from synoptic to long-term variability and climate change. The SAMS contains one of the most prominent summertime climate patterns in South America, featuring a strong seasonal variability in a region lying between the Amazon and the La Plata Basin. Much of the recent progress is derived from complementary international programs, such as the Monsoon Experiment South America (MESA), as well as from ongoing international programs such as the Large Scale Biosphere Atmosphere Experiment in the Amazon Basin (LBA) and the La Plata Basin (LPB) Regional Hydroclimate Project, which includes the CLARIS LPB Europe-South America Network for Climate Change Assessment and Impact Studies in La Plata Basin Project. The latter assesses atmosphere-land surface interactions, the role of land use changes and aerosols from biomass burning considered as sources of variability and change in the SAMS functioning, characteristics and behaviour. The SAMS region is particularly susceptible to variations of climate due to the importance of hydroelectricity generation and the agricultural base of local economies. Also addressed in this report are projections of climate change and extremes, which are important for impact and vulnerability assessments. This discussion includes the need to identify and understand important processes that control the monsoonal climate, how these processes may vary and change, and how they may interact with key societal sectors, including water resource management, hydroelectric generation, agriculture, and agribusiness. This paper reports on the major contributions of MESA to the knowledge of characteristics, functioning and variability of the SAMS, and is based on recent studies and publications, and can be considered as an update of a previous review by C. S. Vera et al. (2006a). © 2010 Royal Meteorological Society.

Descripción: A database of daily extreme temperature was created for as many stations as possible for Uruguay, as far back as possible. This is the first attempt to gather all the different data sources together, perform a quality control and homogeneity assessment. We work with seven stations; it should be taken into account that Uruguay is a small country (around 177 000 km2) and this represents most of the available data. There are three old series with starting dates in 1930, and four that start around 1950. From this database, a set of four extreme temperature indices was constructed for the oldest five stations, warm days (TX90), cold days (TX10), warm nights (TN90) and cold nights (TN10). The index TN10 shows the largest significant negative trend for the period 1960-2002, while TN90 shows a positive but not significant trend for this period indicating a strong warming of nighttime temperature. A spectral analysis was performed using the multi taper methods (MTM) to the de-trended annual, summer Dec-Feb (DJF) and winter Jun-Aug (JJA) indices time-series. This analysis shows that on inter-annual timescales, the most significant range of frequencies is from 2 to 2.5 years and from 3 to 6 years. Low frequencies of variability were detected when the MTM was applied to de-trended smoothed annual time-series, around the range of frequencies of 15-25 years for almost all the indices analysed. Links with global sea surface temperature (SST) were studied for two stations (Paysandu and Rocha), and it was found that the indices showed largest correlations with SST anomalies in the Pacific Ocean. We detected changes in the response of the TN10 index for Rocha station when the series was split up into two different periods (1942-1976 and 1977-2005). Copyright © 2007 Royal Meteorological Society.

Descripción: For the purposes of estimating local changes in surface climate at selected stations in the central Argentina region, induced by an enhanced CO2 concentration, projected by general circulation models (GCM), a statistical method to derive local scale monthly mean minimum, maximum and mean temperatures from large-scale atmospheric predictors is presented. Empirical relationships are derived among selected variables from the NCEP re-analyses and local data for summer and winter months, tested against an independent set of observed data and subsequently applied to the HADAM and MPI GCM control runs. Finally, the statistical approach is applied to a climate change experiment performed with the MPI model to construct a local climate change scenario. The comparison between the estimated versus the observed mean temperature ffields shows good agreement and the temporal evolution of the estimated variables is well-captured, though, the estimated temperatures contain less interannual variability than the observations. For the present day climate simulation, the results from the HADAM and MPI GCMs are used. It is shown that the pattern of estimated temperatures obtained using the MPI large-scale predictors matches the observations for summer months, though minimum and mean temperatures are slightly underestimated in the southeast part of the domain. However, the differences are well within the range of the observed variability. The possible anthropogenic climate change at the local scale is assessed by applying the statistical method to the results of the perturbed run conducted with the MPI model. For summer and winter months, the local temperature increase is smaller for minimum temperature than for maximum temperature for almost all the stations, yielding an enhanced temperature amplitude in both seasons. The temperature amplitude (difference between maximum and minimum) for summer months was larger than for winter months. The estimated maximum temperature increase is found to be larger for summer months than for winter months for all the stations, while for the minimum, temperature increases for summer and winter months are similar.

Descripción: A Singular Value Decomposition (SVD) analysis was performed jointly on extreme temperature events in Argentina and sea surface temperature (SST) in the South Atlantic and South Pacific. Sea level pressure (SLP) patterns associated with the first SVD coupled mode were also analyzed. Winter is the season of the year that is best represented by the first mode, accounting for up to 70% of the winter covariance between temperature events and SST. The warm and cold events in Argentina are essentially a consequence of the creation of meridional atmospheric circulations over the continent. Such atmospheric patterns result from displacements and intensity changes of the subtropical anticyclones over the oceans and of the continental low-pressure center in northwestern Argentina. The temperature events in southern Argentina are also closely related to the warming and cooling of the coastal waters in the South Atlantic and South Pacific. The analysis suggests that in summer and winter, high (low) occurrence of warm events and low (high) occurrence of cold events are related to similar oceanic and atmospheric circulation situations. The temperature events in Argentina show higher correlation with the Atlantic than with the Pacific, which reflects the importance of the "orographic barrier" of the Andes Mountains in driving the atmospheric circulation. The only exception to this rule concerns the warm events in spring, for which the warming of the equatorial Pacific (the ENSO pattern) appears as the dominant mode. The temporal patterns of the temperature events in Argentina exhibit significant interannual variability in fall, winter, and spring, with periods of 3 to 5 years. The summer patterns suggest a very low-frequency variation with a period longer than 20 years. Copyright 2003 by the American Geophysical Union.

Descripción: The objective of the present paper is to analyse the possible impact of ENSO events on the spatial and the temporal distribution of frost occurrences, within the central region of Argentina. Therefore, the minimum temperature series have been studied for 41 meteorological stations within the Pampa Humeda region and, for a period of 30 years from 1961 to 1990, exploring possible relationships with El Nino (EN)/La Nina (LN) events and the changes in the Southern Oscillation. It can be concluded that part of the frost frequency variability within this region is explained by the ENSO cycle. Results indicate that, for at least 1 of the 2 years in which the EN event takes place, the mean number of frost occurrences drops below the climatological value. The low phase of the Southern Oscillation Index (SOI) also coincides with those years for which the number of frost events remained below the total annual mean in all cases, with the year 1965 as an exception. Conversely, during the high phase of the SOI, this number was above the total annual mean for four of the six classified cases. In the particular case of seasonal frost occurrence, it is related to the warm event development state, exhibiting a greater impact during the autumn and winter months, for which the cold event also seems to have influence. Copyright (C) 2000 Royal Meteorological Society.

Descripción: The inversion polymorphism of the cactophilic fly Drosophila buzzatii was studied in two natural populations. We assessed the temporal changes and microspatial population structure. We observed a significant increase in the frequency of arrangement 2J at the expense of 2ST in both populations. These gene arrangements appear to affect the life-history of flies differently. Environmental heterogeneity explains the karyotype coexistence in nature. The analysis of population structure showed that differentiation of inversion frequencies among individual breeding sites, the rotting clacodes of Opuntia vulgaris, was highly significant. The karyotypic frequencies did not depart significantly from Hardy-Weinberg expectations, neither in individual rots nor in the total population. These results suggest that the observed population structure can be easily accounted by random genetic drift.

Descripción: It is universally true in ecological communities, terrestrial or aquatic, temperate or tropical, that some species are very abundant, others are moderately common, and the majority are rare. Likewise, eukaryotic genomes also contain classes or "species" of genetic elements that vary greatly in abundance: DNA transposons, retrotransposons, satellite sequences, simple repeats and their less abundant functional sequences such as RNA or genes. Are the patterns of relative species abundance and diversity similar among ecological communities and genomes? Previous dynamical models of genomic diversity have focused on the selective forces shaping the abundance and diversity of transposable elements (TEs). However, ideally, models of genome dynamics should consider not only TEs, but also the diversity of all genetic classes or "species" populating eukaryotic genomes. Here, in an analysis of the diversity and abundance of genetic elements in >500 eukaryotic chromosomes, we show that the patterns are consistent with a neutral hypothesis of genome assembly in virtually all chromosomes tested. The distributions of relative abundance of genetic elements are quite precisely predicted by the dynamics of an ecological model for which the principle of functional equivalence is the main assumption. We hypothesize that at large temporal scales an overarching neutral or nearly neutral process governs the evolution of abundance and diversity of genetic elements in eukaryotic genomes. © 2013 Serra et al.