A recent field campaign aimed at obtaining an improved temporal and spatial description of the tropospheric flow over central South America was essential for the validation, and improvement of, short-and long-term predictions in the region.

Abstract.Projections of changes in climate extremes are critical to assessing the potential impacts of climate change on human and natural systems. Therefore, especial care should be put on the validation of those extremes derived for present climate in both spatial and temporal variability. We analyze historical simulations of three such indicators as derived from seven GCMs contributing to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR4) for the XX century. Our focus is on the consensus in the geographical and temporal variability of temperature and rainfall extreme trends between observations and the GCMs, in terms of direction and significance of the changes at the scale of South America south of 10 o S. The climate extremes described by the 3 indices include warm nights, heavy rainfall amounts and dry spells. The observed historical trends in extremes generally agree with previous observational studies that used other indicators of extremes, and the favorable comparison in the warm nights and extreme rainfall in some regions provides a basic sense of reliability for the GCM simulations. For any specific temperature index, minor differences appear in the spatial distribution of the changes across models in some regions, while substantial differences appear in regions in interior tropical and subtropical South America. The differences are in the relative magnitude of the trends. Consensus and significance are less strong when regional patterns are considered, with the exception of the La Plata Basin, where observed and simulated trends in warm nights and extreme rainfall are evident. This analysis provides a first overview of simulated trends in extremes for present climates, and further work is focused on projected changes in climate extremes from the IPCC-AR4 models.

We analyzed trends, interdecadal variability, and the quantification of the changes in the frequency of daily rainfall for two thresholds: 0.1 mm and percentile 75th, using high quality daily series from 52 stations in the La Plata Basin (LPB). We observed increases in the annual frequencies in spatially coherent areas. This coherence was more marked in austral summer, autumn, and spring, during which the greatest increases occurred in southern Brazil, especially during extreme events. In winter, the low and middle basins of the Río Uruguay and Río Paraná showed negative trends, some of which were significant. Interdecadal variability is well defined in the region with more pronounced positive jumps west of the basin between 1950 and 2000. This variability was particularly more marked during periods of extreme rainfall in summer, autumn, and spring, unlike in winter when extreme daily rainfall in the lower Rio Paraná basin decreased by up to 60%. The changes in the past century during extreme rainfall produced modifications in the annual rainfall cycle. The annual cycle of both indices was broader during the last period which is mainly explained by the strong decreases in winter.

Long, annual precipitation time series from central-northeastern Argentina are analysed with special attention to interdecadal and interannual variations. The results show a variability that is highly nonstationary. The most outstanding feature is the difference in annual precipitation before and after the 1950s. The interdecadal variability is particularly well defined in the west, and there is a significant linear trend in the study area. Negative anomalies of the areal-averaged annual precipitation can be observed in all the areas around 1910 and 1930 or 1940. In the western zone there are two better-defined negative periods around 1950 and 1970, and a gradual increase can be observed in the eastern zones starting in the 1950s. The interdecadal and interannual variations affect the behaviour of extreme precipitation on the annual scale and during the months with maximum precipitation in the region. In support of these conclusions, different representation methods are used (running means, power spectrum analysis, and wavelet transforms). The variations in the annual cycle of extreme precipitation under different conditions are analysed by applying harmonic analysis. The wettest years are represented by an annual and semi-annual cycle, whereas dry years need the input of lower frequency cycles.

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This study aims to compare simulated soil moisture anomalies derived from different versions of the Global Land Data Assimilation System (GLDAS), the standardized precipitation index (SPI), and a new multisatellite surface soil moisture product over southern South America. The main motivation is the need for assessing the reliability of GLDAS variables to be used in the characterization of soil state and its variability at the regional scale. The focus is on the southeastern part of South America (SESA), which is part of the La Plata basin, one of the largest basins of the world, where agriculture is the main source of income. The results show that GLDAS data capture soil moisture anomalies and their variability, taking into account regional and seasonal dependencies and showing correspondence with other proxies used to characterize soil states. Over large portions of the domain, and particularly over SESA, the correlation with the SPI is very high, with the second version of GLDAS, version 2 (GLDAS-2 v2), exhibiting the highest values regardless of the season. Similar results were obtained by comparing the surface soil moisture anomalies from the GLDAS land surface model (LSM) against the satellite estimations for a shorter period of time. This work documents that the precipitation dataset used to force each LSM and the choice of the LSM are of major relevance for representing soil conditions in an adequate manner. The results are considered to support the use of GLDAS as an indicator of soil moisture states and for developing new soil moisture–monitoring indices that can be applied, for example, in the context of agricultural production management.

The ability of four regional climate models to reproduce the present-day South American climate is examined with emphasis on La Plata Basin. Models were integrated for the period 1991-2000 with initial and lateral boundary conditions from ERA-40 Reanalysis. The ensemble sea level pressure, maximum and minimum temperatures and precipitation are evaluated in terms of seasonal means and extreme indices based on a percentile approach. Dispersion among the individual models and uncertainties when comparing the ensemble mean with different climatologies are also discussed. The ensemble mean is warmer than the observations in South Eastern South America (SESA), especially for minimum winter temperatures with errors increasing in magnitude towards the tails of the distributions. The ensemble mean reproduces the broad spatial pattern of precipitation, but overestimates the convective precipitation in the tropics and the orographic precipitation along the Andes and over the Brazilian Highlands, and underestimates the precipitation near the monsoon core region. The models overestimate the number of wet days and underestimate the daily intensity of rainfall for both seasons suggesting a premature triggering of convection. The skill of models to simulate the intensity of convective precipitation in summer in SESA and the variability associated with heavy precipitation events (the upper quartile daily precipitation) is far from satisfactory. Owing to the sparseness of the observing network, ensemble and observations uncertainties in seasonal means are comparable for some regions and seasons. © 2012 Springer-Verlag Berlin Heidelberg