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Gridded precipitation (PRP) data have been largely used in diagnostic studies on the climate variability in several time scales, as well as to validate model results. The three most used gauge-based PRP datasets are from the Global Precipitation Climatology Centre (GPCC), University of Delaware (UDEL), and Climate Research Unit (CRU). This paper evaluates the performance of these datasets in reproducing spatiotemporal PRP climatological features over the entire South America (SA) for the 1901–2015 period, aiming to identify the differences and similarities among the datasets as well as time intervals and areas with potential uncertainties involved with these datasets. Comparisons of the PRP annual means and variances between the 1901–2015 period and the non-overlapping 30-year subperiods of 1901–1930, 1931–1960, 1961–1990, and the 25-year subperiod of 1991–2015 for each dataset show varying means of the annual PRP over SA depending on the subperiod and dataset. Consistent patterns among datasets are found in most of southeastern SA and southeastern Brazil, where they evolved gradually from less to more rainy conditions from 1901–1930 to the 1991–2015 subperiod. All three datasets present limitations and uncertainties in regions with poor coverage of gauge stations, where the differences among datasets are more pronounced. In particular, the GPCC presents reduced PRP variability in an extensive area west of 50° W and north of 20° S during the 1901–1930 subperiod. In monthly time scale, PRP time series in two areas show differences among the datasets for periods before 1941, which are likely due to spurious or missing data: central Bolivia (CBO), and central Brazil (CBR). The GPCC has less monthly variability before 1940 than the other two datasets in these two areas, and UDEL presents reduced monthly variability before 1940 and spurious monthly values from May to September of the years from 1929 to 1941 in CBO. Thus, studies with these three datasets might lead to different results depending on the study domain and period of analysis, in particular for those including years before 1941. The results here might be relevant for future diagnostic and modelling studies on climate variability from interannual to multidecadal time scales. [ABSTRACT FROM AUTHOR]

The Andes Cordillera plays a role in driving moisture and heat from tropical onto subtropical South America. It forces the development of a lee-side trough that covers most of western Argentina and a low-level jet that maximizes over Paraguay, eastern Bolivia and northern Argentina and is tightly linked to precipitation variability over much of central and southeastern South America. Its steep slopes and the large zonal gradients in topography between the Equator and 40°S are misrepresented in climate simulations using Global Climate Models (GCM) with resolutions coarser than about 100 km, since they naturally have a poor representation of the Andes and related circulation features. This paper analyses the impact of varying artificially the altitude of the Andes Cordillera in a GCM as well as increasing the horizontal resolution to study how these variations determine moisture fluxes and precipitation over selected regions of South America. Results show that the height of the Andes is crucial in shaping moisture fluxes pathways onto subtropical South America all year long. In particular, the low-level jet is only simulated when the Andes heights are doubled. At the same time, the relationship between the Andes shape and the location of the Bolivian High in summer is also discussed. In terms of precipitation, the lowest bias in the simulations is achieved when the horizontal resolution is increased, while in particular near the Andes foothills the simulated annual rainfall is largely determined by the Mountains shape. [ABSTRACT FROM AUTHOR]

On a hemispheric scale, it is now well established that stratospheric ozone depletion has been the principal driver of externally forced atmospheric circulation changes south of the Equator in the last decades of the 20th Century. The impact of ozone depletion has been felt over the entire hemisphere, as reflected in the poleward drift of the midlatitude jet, the southward expansion of the summertime Hadley cell and accompanying precipitation trends deep into the subtropics. On a regional scale, however, surface impacts directly attributable to ozone depletion have yet to be identified. In this paper we focus on South Eastern South America (SESA), a region that has exhibited one of the largest wetting trends during the 20th Century. We study the impact of ozone depletion on SESA precipitation using output from 6 different climate models, spanning a wide range of complexity. In all cases we contrast pairs of model integrations with and without ozone depletion, but with all other forcings identically specified. This allows for unambiguous attribution of the computed precipitation trends. All 6 climate models consistently reveal that stratospheric ozone depletion results in a significant wetting of SESA over the period 1960-1999. Taken as a whole, these model results strongly suggest that the impact of ozone depletion on SESA precipitation has been as large as, and quite possibly larger than, the one caused by increasing greenhouse gases over the same period. [ABSTRACT FROM AUTHOR]

An important goal of the Climate Variability and Predictability (CLIVAR) research on the American monsoon systems is to determine the sources and limits of predictability of warm season precipitation, with emphasis on weekly to interannual time scales. This paper reviews recent progress in the understanding of the American monsoon systems and identifies some of the future challenges that remain to improve warm season climate prediction. Much of the recent progress is derived from complementary international programs in North and South America, namely, the North American Monsoon Experiment (NAME) and the Monsoon Experiment South America (MESA), with the following common objectives: 1) to understand the key components of the American monsoon systems and their variability, 2) to determine the role of these systems in the global water cycle, 3) to improve observational datasets, and 4) to improve simulation and monthly-to-seasonal prediction of the monsoons and regional water resources. Among the recent observational advances highlighted in this paper are new insights into moisture transport processes, description of the structure and variability of the South American low-level jet, and resolution of the diurnal cycle of precipitation in the core monsoon regions. NAME and MESA are also driving major efforts in model development and hydrologic applications. Incorporated into the postfield phases of these projects are assessments of atmosphere–land surface interactions and model-based climate predictability experiments. As CLIVAR research on American monsoon systems evolves, a unified view of the climatic processes modulating continental warm season precipitation is beginning to emerge. [ABSTRACT FROM AUTHOR]

Background: Global warming and climate change are threats to the world. Warmer temperatures and changes in precipitation patterns alter water availability and increase the occurrence of extreme weather events. South America and the Andes are vulnerable regions to climate change due to inequity and the uneven distribution of resources. Climate change evaluation often relies on the use of general circulation models (GCMs). However, the spatial resolution is too coarse and does not provide a realistic climate representation at a local level. This is of particular importance in mountain areas such as the Andes range, where the heterogeneous topography requires a finer spatial resolution to represent the local physical processes. To this end, statistical and/or dynamical downscaling methods are required. Several approaches and applications of downscaling procedures have been carried out in the countries of this region, with different purposes and performances. However, the main objective is to improve the representation of meteorological variables such as precipitation and temperature. A systematic review of these downscaling applications will identify the performance of the methods applied in the Andes region for the downscaling of precipitation and temperature. In addition, the meta-analysis could detect factors influencing the performance. The overall goal is to highlight promising methods in terms of fitness for use and identify knowledge gaps in the region. Methods: The review will search and examine published and grey literature on downscaling applications of temperature and precipitation in the Andes region. Predetermined criteria for eligibility will allow the screening of the evidence. Then, the method used in each application will be coded and mapped according to the country, purpose, variable, and type of downscaling. At the same time, quantitative and qualitative data will be extracted. The performance metrics are particularly interesting for this review. A meta-analysis will be conducted for those studies with comparable metrics. A narrative synthesis, maps and heatmaps will show the results. Tables, funnel plots, and meta-regressions will present the meta-analysis. Throughout the review, a critical appraisal step will categorize the validity of the evidence. [ABSTRACT FROM AUTHOR]

This paper identifies two sources of uncertainties in model projections of temperature and precipitation: internal and inter-model variability. Eight models of WCRP-CMIP3 and WCRP-CMIP5 were compared to identify improvements in the reliability of projections from new generation models. While no significant differences are observed between both datasets, some improvements were found in the new generation models. For example, in summer CMIP5 inter-model variability of temperature was lower over northeastern Argentina, Paraguay and northern Brazil, in the last decades of the 21st century. Reliability of temperature projections from both sets of models is high, with signal to noise ratio greater than 1 over most of the study region. Although no major differences were observed in both precipitation datasets, CMIP5 inter-model variability was lower over northern and eastern Brazil in summer (especially at the end of the 21st century). Reliability of precipitation projections was low in both datasets. However, the signal to noise ratio in new generation models was close to 1, and even greater than 1 over eastern Argentina, Uruguay and southern Brazil in some seasons. [ABSTRACT FROM AUTHOR]

Interannual variability is an important modulator of synoptic and intraseasonal variability in South America. This paper seeks to characterize the main modes of interannual variability of seasonal precipitation and some associated mechanisms. The impact of this variability on the frequency of extreme rainfall events and the possible effect of anthropogenic climate change on this variability are reviewed. The interannual oscillations of the annual total precipitation are mainly due to the variability in austral autumn and summer. While autumn is the dominant rainy season in the northern part of the continent, where the variability is highest (especially in the northeastern part), summer is the rainy season over most of the continent, thanks to a summer monsoon regime. In the monsoon season, the strongest variability occurs near the South Atlantic Convergence Zone (SACZ), which is one of the most important features of the South American monsoon system. In all seasons but summer, the most important source of variability is ENSO (El Niño Southern Oscillation), although ENSO shows a great contribution also in summer. The ENSO impact on the frequency of extreme precipitation events is also important in all seasons, being generally even more significant than the influence on seasonal rainfall totals. Climate change associated with increasing emission of greenhouse gases shows potential to impact seasonal amounts of precipitation in South America, but there is still great uncertainty associated with the projected changes, since there is not much agreement among the models' outputs for most regions in the continent, with the exception of southeastern South America and southern Andes. Climate change can also impact the natural variability modes of seasonal precipitation associated with ENSO. [ABSTRACT FROM AUTHOR]

This paper documents the main features of the weather, climate and climate variability over Andes cordillera in South America on the basis of instrumental observations. We first provide a basic physical understanding of the mean annual cycle of the atmospheric circulation and precipitation and over the Andes and adjacent lowlands. In particular, the diversity of precipitation, temperature and wind patterns is interpreted in terms of the long meridional extent of the Andes and the disruption of the large-scale circulation by this formidable topographic barrier. We also document the impact of the El Niño Southern Oscillation phenomenon on the temperature and precipitation regimes along the Andes. [ABSTRACT FROM AUTHOR]

Aim Species richness depends on climate and land use. Maintaining locations with favourable climate and land-use patterns is critical for protecting biodiversity because the loss of either can reduce the species richness that an area supports. Currently, the Guiana Shield (GS) receives abundant precipitation and has relatively light land use. For species richness this constitutes a good–good combination of climate and land use, respectively. In contrast, much of eastern Brazil receives low levels of precipitation and has heavy land use, which is a bad–bad combination for species richness. Thus, the current distribution of precipitation and land use in northern South America is relatively favourable for biodiversity. Palaeoclimate and model studies suggest, however, that the precipitation patterns for the two regions have switched before and could switch in response to greenhouse gas emissions. This paper examines the potential consequences of reconfiguring climate with respect to existing land-use patterns using South America as an example. Location South America north of 20° S and east of the Andes. Methods Ecosystem structure and function are modelled under (1) historical climate and (2) altered precipitation following a shift in the location of the Inter-Tropical Convergence Zone (ITCZ). The distribution of precipitation, biomes, net primary productivity (NPP) and land use are then used to predict levels of species richness under the two climate scenarios. Results Climate changes could shift the distribution of vegetation and NPP such that conditions favourable for species richness in the GS region disappear. If land-use patterns were not prohibitive in eastern Brazil, the improved climate conditions there could compensate for the GS loss (assuming migratory barriers are overcome). Instead, existing land-use patterns cause the combined species richness projected for the two regions to plummet. Main conclusions Human activities will alter current configurations of land use and climate throughout the world. For species richness, new configurations are likely to include both positive and negative combinations of climate and land use. However, the irreversibility of past extinctions due to land-use patterns loads the dice against species richness. [ABSTRACT FROM AUTHOR]

Evaluating the response of climate to greenhouse gas forcing is a major objective of the climate community, and the use of large ensemble of simulations is considered as a significant step toward that goal. The present paper thus discusses a new methodology based on neural network to mix ensemble of climate model simulations. Our analysis consists of one simulation of seven Atmosphere–Ocean Global Climate Models, which participated in the IPCC Project and provided at least one simulation for the twentieth century (20c3m) and one simulation for each of three SRES scenarios: A2, A1B and B1. Our statistical method based on neural networks and Bayesian statistics computes a transfer function between models and observations. Such a transfer function was then used to project future conditions and to derive what we would call the optimal ensemble combination for twenty-first century climate change projections. Our approach is therefore based on one statement and one hypothesis. The statement is that an optimal ensemble projection should be built by giving larger weights to models, which have more skill in representing present climate conditions. The hypothesis is that our method based on neural network is actually weighting the models that way. While the statement is actually an open question, which answer may vary according to the region or climate signal under study, our results demonstrate that the neural network approach indeed allows to weighting models according to their skills. As such, our method is an improvement of existing Bayesian methods developed to mix ensembles of simulations. However, the general low skill of climate models in simulating precipitation mean climatology implies that the final projection maps (whatever the method used to compute them) may significantly change in the future as models improve. Therefore, the projection results for late twenty-first century conditions are presented as possible projections based on the “state-of-the-art” of present climate modeling. First, various criteria were computed making it possible to evaluate the models’ skills in simulating late twentieth century precipitation over continental areas as well as their divergence in projecting climate change conditions. Despite the relatively poor skill of most of the climate models in simulating present-day large scale precipitation patterns, we identified two types of models: the climate models with moderate-to-normal (i.e., close to observations) precipitation amplitudes over the Amazonian basin; and the climate models with a low precipitation in that region and too high a precipitation on the equatorial Pacific coast. Under SRES A2 greenhouse gas forcing, the neural network simulates an increase in precipitation over the La Plata basin coherent with the mean model ensemble projection. Over the Amazonian basin, a decrease in precipitation is projected. However, the models strongly diverge, and the neural network was found to give more weight to models, which better simulate present-day climate conditions. In the southern tip of the continent, the models poorly simulate present-day climate. However, they display a fairly good convergence when simulating climate change response with a weak increase south of 45°S and a decrease in Chile between 30 and 45°S. Other scenarios (A1B and B1) strongly resemble the SRES A2 trends but with weaker amplitudes. [ABSTRACT FROM AUTHOR]

The purposes of this paper are to evaluate the new version of the regional model, RegCM3, over South America for two test seasons, and to select a domain for use in an experimental nested prediction system, which incorporates RegCM3 and the European Community-Hamburg (ECHAM) general circulation model (GCM). To evaluate RegCM3, control experiments were completed with RegCM3 driven by both the NCEP/NCAR Reanalysis (NNRP) and ECHAM, using a small control domain (D-CTRL) and integration periods of January–March 1983 (El Niño) and January–March 1985 (La Niña). The new version of the regional model captures the primary circulation and rainfall differences between the two years over tropical and subtropical South America. Both the NNRP-driven and ECHAM-driven RegCM3 improve the simulation of the Atlantic intertropical convergence zone (ITCZ) compared to the GCM. However, there are some simulation errors. Irrespective of the driving fields, weak northeasterlies associated with reduced precipitation are observed over the Amazon. The simulation of the South Atlantic convergence zone is poor due to errors in the boundary condition forcing which appear to be amplified by the regional model. To select a domain for use in an experimental prediction system, sensitivity tests were performed for three domains, each of which includes important regional features and processes of the climate system. The domain sensitivity experiments were designed to determine how domain size and the location of the GCM boundary forcing affect the regional circulation, moisture transport, and rainfall in two years with different large scale conditions. First, the control domain was extended southward to include the exit region of the Andes low level jet (D-LLJ), then eastward to include the South Atlantic subtropical high (D-ATL), and finally westward to include the subsidence region of the South Pacific subtropical high and to permit the regional model more freedom to respond to the increased resolution of the Andes Mountains (D-PAC). In order to quantify differences between the domain experiments, measures of bias, root mean square error, and the spatial correlation pattern were calculated between the model results and the observed data for the seasonal average fields. The results show the GCM driving fields have remarkable control over the RegCM3 simulations. Although no single domain clearly outperforms the others in both seasons, the control domain, D-CTRL, compares most favorably with observations. Over the ITCZ region, the simulations were improved by including a large portion of the South Atlantic subtropical high (D-ATL). The methodology presented here provides a quantitative basis for evaluating domain choice in future studies. [ABSTRACT FROM AUTHOR]

Differences between climate conditions during the Last Glacial Maximum (LGM) and the Mid-Holocene (MH) in southern South America inferred from the state-of-the-art PMIP3 paleoclimatic simulations are described for the first time in this paper. The aim is to expose characteristics of past climate changes occurred without human influence. In this context, numerical simulations are an indispensable tool for inferring changes in near-surface air temperature and precipitation in regions where proxy information is scarce or absent. The analyzed PMIP3 models describe MH temperatures significantly warmer than those of LGM with magnitudes of change depending on the season and the specific geographic region. In addition, models indicate that seasonal mean precipitation during MH increased with respect to LGM values in wide southern continental areas to the east of the Andes Cordillera whereas seasonal precipitation developed in areas to the west of Patagonian Andes reduced from LGM to MH. [ABSTRACT FROM AUTHOR]

Abstract: This paper documents the main features of the climate and climate variability over South America, on the basis of instrumental observations gathered during the 20th Century. It should provide a modern reference framework for paleoclimate research in South America, targeting high-resolution proxies over the past few centuries. Several datasets suitable for present-day climate research are first described, highlighting their advantages as well as their limitations. We then provide a basic physical understanding of the mean annual cycle of the precipitation and atmospheric circulation over the continent and the adjacent oceans. In particular, the diversity of precipitation, temperature and wind patterns is interpreted in terms of the long meridional extent of the continent and the disruption of the large-scale circulation caused by the Andes cordillera, the contrasting oceanic boundary conditions and the landmass distribution. Similarly, the intensity and timing of the interannual and interdecadal climatic fluctuations exhibit considerable geographical dependence, as some regions are more influenced by large-scale phenomena rooted in the tropical oceans while others are more influenced by high-latitude phenomena. The impact of these large-scale phenomena over South America is documented by a regression analysis between selected atmospheric indices and the precipitation and temperature fields. We have included a discussion on the seasonality and long-term stability of such impacts, and complemented our general description by an updated review of the literature on climate variability over specific regions. [Copyright &y& Elsevier]

Patagonia is thought to be one of the wettest regions on Earth, although available regional precipitation estimates vary considerably. This uncertainty complicates understanding and quantifying the observed environmental changes, such as glacier recession, biodiversity decline in fjord ecosystems and enhanced net primary production. The Patagonian Icefields, for example, are one of the largest contributors to sea-level rise outside the polar regions, and robust hydroclimatic projections are needed to understand and quantify current and future mass changes. The reported projections of precipitation from numerical modelling studies tend to overestimate those from in situ determinations, and the plausibility of these numbers has never been carefully scrutinized, despite the significance of this topic to our understanding of observed environmental changes. Here I use simple physical arguments and a linear model to test the plausibility of the current precipitation estimates and its impact on the Patagonian Icefields. The results show that environmental conditions required to sustain a mean precipitation amount exceeding 6.09±0.64 m yr -1 are untenable according to the regional moisture flux. The revised precipitation values imply a significant reduction in the surface mass balance of the Patagonian Icefields compared to previously reported values. This yields a new perspective on the response of Patagonia's glaciers to climate change and their sea-level contribution and might also help reduce uncertainties in the change of other precipitation-driven environmental phenomena. [ABSTRACT FROM AUTHOR]

The results of an ensemble of regional climate model (RCM) simulations over South America are presented. This is the first coordinated exercise of regional climate modelling studies over the continent, as part of the CLARIS-LPB EU FP7 project. The results of different future periods, with the main focus on (2071-2100) is shown, when forced by several global climate models, all using the A1B greenhouse gases emissions scenario. The analysis is focused on the mean climate conditions for both temperature and precipitation. The common climate change signals show an overall increase of temperature for all the seasons and regions, generally larger for the austral winter season. Future climate shows a precipitation decrease over the tropical region, and an increase over the subtropical areas. These climate change signals arise independently of the driving global model and the RCM. The internal variability of the driving global models introduces a very small level of uncertainty, compared with that due to the choice of the driving model and the RCM. Moreover, the level of uncertainty is larger for longer horizon projections for both temperature and precipitation. The uncertainty in the temperature changes is larger for the subtropical than for the tropical ones. The current analysis allows identification of the common climate change signals and their associated uncertainties for several subregions within the South American continent. [ABSTRACT FROM AUTHOR]

We investigate the temporal evolution of moisture divergence and its spatial clustering properties over South America. Our analysis focuses on dependencies on the phase of the El Niño Southern Oscillation (ENSO). Moisture divergence is computed from daily reanalysis data of vertically integrated moisture flux provided by Modern-Era Retrospective Analysis for Research and Applications for the time period from 1979 to 2010. We use a sliding-window approach to construct a sequence of complex networks, each obtained from synchronization of events of strong positive (negative) moisture divergence, which we interpret as strong evapotranspiration (precipitation) events. We make the following three key observations: (1) Moisture divergence values over the Amazon rainforest are typically higher during positive ENSO periods (El Niño events). (2) The spatial coherence of strong positive (upwelling) events assumes a characteristic pattern of reduced coherence in this area during El Niño conditions. This influence of ENSO on moisture divergence and its spatial coherence is dominated by the El Niño events of 1982, 1987, and 1997. (3) The clustering characteristics of the obtained climate networks qualitatively agree with the spatial distribution of connected regions with simultaneous events (i.e., events that occur at the same time), but provide a more detailed view on the spatial organization of strong atmospheric upwelling events. Interestingly, no comparable results are found for negative extremes of moisture divergence (strong precipitation events). [ABSTRACT FROM AUTHOR]

This research investigates spatial patterns of Normalized Difference Vegetation Index (NDVI) and rainfall variability in South America and their relationships based on analyses of the Standardized Difference Vegetation Index (SDVI) and the Standardized Precipitation Index (SPI) for the period April 1998-March 2012. The time series of SPOT-Vegetation 10-daily composite NDVI data at 1-km resolution was smoothed and subsequently synthesized to monthly images using the maximum value composite technique. Furthermore, 10-daily rainfall estimates at 0.25° resolution, available from the European Centre for Medium-Range Weather Forecasts through MeteoConsult and the Monitoring Agricultural ResourceS unit, were combined to retrieve monthly composites. In order to assess spatial patterns and rates of change, linear least squares trend analyses were performed on the SDVI time series and the SPI time series, taking into account the accumulated rainfall over the respective best lag. Only trends with Pearson's correlation coefficients significantly different from zero ( p < 0.05) were considered significant. The results indicated that vegetation degradation is coupled to a significant decrease in the amount of rainfall in the last 14 years in 8 % of South America's area. In contrast, in 18 % of the subcontinental area, vegetation greenness has significantly increased over the last 14 years, coupled to an increase in rainfall. For 46 % of the study area, significant degradation or greening processes could not be linked to changes in rainfall over time, indicating human impact or the influence of other climatic factors, such as temperature and net radiation. [ABSTRACT FROM AUTHOR]

A dipole pattern in convection between the South Atlantic convergence zone and the subtropical plains of southeastern South America characterizes summer intraseasonal variability over the region. The dipole pattern presents two main bands of temporal variability, with periods between 10 and 30 days, and 30 and 90 days; each influenced by different large-scale dynamical forcings. The dipole activity on the 30-90-day band is related to an eastward traveling wavenumber-1 structure in both OLR and circulation anomalies in the tropics, similar to that associated with the Madden-Julian oscillation. The dipole is also related to a teleconnection pattern extended along the South Pacific between Australia and South America. Conversely, the dipole activity on the 10-30-day band does not seem to be associated with tropical convection anomalies. The corresponding circulation anomalies exhibit, in the extratropics, the structure of Rossby-like wave trains, although their sources are not completely clear. [ABSTRACT FROM AUTHOR]

This study addresses the predictability of rainfall variations over South America and the Amazon basin. A primary factor leading to model inaccuracy in precipitation forecasts is the coarse resolution data utilized by coupled models during the training phase. By using MERRA reanalysis and statistical downscaling along with the superensemble methodology, it is possible to obtain more precise forecast of rainfall anomalies over tropical South America during austral fall. Selective inclusion (and exclusion) of member models also allows for increased accuracy of superensemble forecasts. The use of coupled atmospheric-ocean numerical models to predict the rainfall anomalies has had mixed results. Improvement in individual member models is also possible on smaller spatial scales and in regions where substantial topographical changes were not handled well under original model initial conditions. The combination of downscaling and superensemble methodologies with other research methods presents the potential opportunity for increased accuracy not only in seasonal forecasts but on shorter temporal scales as well. [ABSTRACT FROM AUTHOR]

This study identifies possible hotspots of climate change in South America through an examination of the spatial pattern of the Regional Climate Change Index (RCCI) over the region by the end of the twenty-first century. The RCCI is a qualitative index that can synthesize a large number of climate model projections, and it is suitable for identifying those regions where climate change could be more pronounced in a warmer climate. The reliability and uncertainties of the results are evaluated by using numerous state-of-the-art general circulation models (GCMs) and forcing scenarios from the Coupled Model Intercomparison Project phases 3 and 5. The results show that southern Amazonia and the central-western region and western portion of Minas Gerais state in Brazil are persistent climate change hotspots through different forcing scenarios and GCM datasets. In general, as the scenarios vary from low- to high-level forcing, the area of high values of RCCI increase and the magnitude intensify from central-western and southeast Brazil to northwest South America. In general, the climatic hotspots identified in this study are characterized by an increase of mean surface air temperature, mainly in the austral winter; by an increase of interannual temperature variability, predominantly in the austral summer; and by a change in the mean and interannual variability of precipitation during the austral winter. [ABSTRACT FROM AUTHOR]

Intraseasonal (IS) variability in South America is analyzed during the cold season using 10-90 day bandpass filtered OLR anomalies (FOLR). IS variability explains a large percentage of variance with maximum values over Paraguay, northeastern Argentina, and southern Brazil. The leading pattern of FOLR, as isolated from an EOF analysis, (Cold Season IS pattern, CSIS), is characterized by a monopole centered over southeastern South America (SESA) with a northwest-southeast orientation. CSIS induces a large modulation on daily precipitation anomalies, especially on both wet spells and daily precipitation extremes, which are favored during positive (wet) CSIS phases. Large-Scale OLR anomalies over the tropical Indian and west Pacific Oceans associated with CSIS exhibit eastward propagation along tropical latitudes. In addition, circulation anomalies in the Southern Hemisphere reveal the presence of an anticyclonic anomaly over Antarctica with opposite-sign anomalies in middle latitudes 10 days before CSIS is maximum as well as evidence of Rossby wave-like patterns. Positive precipitation anomalies in SESA are favored during wet CSIS phases by the intensification of a cyclonic anomaly located further south, which is discernible over the southeastern Pacific for at least 14 days before CSIS peaks. The cyclonic anomaly evolution is accompanied by the intensification of an upstream anticyclonic anomaly, which remains quasi-stationary near the Antarctica Peninsula before the CSIS peak. We speculate that the stationary behavior of the anticyclonic center is favored by a hemispheric circulation anomaly pattern resembling that associated with a negative southern annular mode phase and a wavenumber 3-4 pattern at middle latitudes. [ABSTRACT FROM AUTHOR]

The capability of a set of 7 coordinated regional climate model simulations performed in the framework of the CLARIS-LPB Project in reproducing the mean climate conditions over the South American continent has been evaluated. The model simulations were forced by the ERA-Interim reanalysis dataset for the period 1990-2008 on a grid resolution of 50 km, following the CORDEX protocol. The analysis was focused on evaluating the reliability of simulating mean precipitation and surface air temperature, which are the variables most commonly used for impact studies. Both the common features and the differences among individual models have been evaluated and compared against several observational datasets. In this study the ensemble bias and the degree of agreement among individual models have been quantified. The evaluation was focused on the seasonal means, the area-averaged annual cycles and the frequency distributions of monthly means over target sub-regions. Results show that the Regional Climate Model ensemble reproduces adequately well these features, with biases mostly within ±2 °C and ±20 % for temperature and precipitation, respectively. However, the multi-model ensemble depicts larger biases and larger uncertainty (as defined by the standard deviation of the models) over tropical regions compared with subtropical regions. Though some systematic biases were detected particularly over the La Plata Basin region, such as underestimation of rainfall during winter months and overestimation of temperature during summer months, every model shares a similar behavior and, consequently, the uncertainty in simulating current climate conditions is low. Every model is able to capture the variety in the shape of the frequency distribution for both temperature and precipitation along the South American continent. Differences among individual models and observations revealed the nature of individual model biases, showing either a shift in the distribution or an overestimation or underestimation of the range of variability. [ABSTRACT FROM AUTHOR]

In this study, we assess how the anthropogenically induced increase in greenhouse gas concentrations affects the climate of central and southern South America. We utilise two regional climate simulations for present day (PD) and pre-industrial (PI) times. These simulations are compared to historical reconstructions in order to investigate the driving processes responsible for climatic changes between the different periods. The regional climate model is validated against observations for both re-analysis data and GCM-driven regional simulations for the second half of the 20th century. Model biases are also taken into account for the interpretation of the model results. The added value of the regional simulation over global-scale modelling relates to a better representation of hydrological processes that are particularly evident in the proximity of the Andes Mountains. Climatic differences between the simulated PD minus PI period agree qualitatively well with proxy-based temperature reconstructions, albeit the regional model overestimates the amplitude of the temperature increase. For precipitation the most important changes between the PD and PI simulation relate to a dipole pattern along the Andes Mountains with increased precipitation over the southern parts and reduced precipitation over the central parts. Here only a few regions show robust similarity with studies based on empirical evidence. However, from a dynamical point-of-view, atmospheric circulation changes related to an increase in high-latitude zonal wind speed simulated by the regional climate model are consistent with numerical modelling studies addressing changes in greenhouse gas concentrations. Our results indicate that besides the direct effect of greenhouse gas changes, large-scale changes in atmospheric circulation and sea surface temperatures also exert an influence on temperature and precipitation changes in southern South America. These combined changes in turn affect the relationship between climate and atmospheric circulation between PD and PI times and should be considered for the statistical reconstruction of climate indices calibrated within presentday climate data. [ABSTRACT FROM AUTHOR]

The objective of this study is to assess the climate projections over South America using the Eta-CPTEC regional model driven by four members of an ensemble of the Met Office Hadley Centre Global Coupled climate model HadCM3. The global model ensemble was run over the twenty-first century according to the SRES A1B emissions scenario, but with each member having a different climate sensitivity. The four members selected to drive the Eta-CPTEC model span the sensitivity range in the global model ensemble. The Eta-CPTEC model nested in these lateral boundary conditions was configured with a 40-km grid size and was run over 1961-1990 to represent baseline climate, and 2011-2100 to simulate possible future changes. Results presented here focus on austral summer and winter climate of 2011-2040, 2041-2070 and 2071-2100 periods, for South America and for three major river basins in Brazil. Projections of changes in upper and low-level circulation and the mean sea level pressure (SLP) fields simulate a pattern of weakening of the tropical circulation and strengthening of the subtropical circulation, marked by intensification at the surface of the Chaco Low and the subtropical highs. Strong warming (4-6°C) of continental South America increases the temperature gradient between continental South America and the South Atlantic. This leads to stronger SLP gradients between continent and oceans, and to changes in moisture transport and rainfall. Large rainfall reductions are simulated in Amazonia and Northeast Brazil (reaching up to 40%), and rainfall increases around the northern coast of Peru and Ecuador and in southeastern South America, reaching up to 30% in northern Argentina. All changes are more intense after 2040. The Precipitation-Evaporation (P-E) difference in the A1B downscaled scenario suggest water deficits and river runoff reductions in the eastern Amazon and São Francisco Basin, making these regions susceptible to drier conditions and droughts in the future. [ABSTRACT FROM AUTHOR]

•We used a climate–vegetation–natural fire (CVNF) conceptual model to evaluate the sensitivity and vulnerability of forest, savanna, and the forest–savanna transition to environmental changes in tropical South America. •Initially, under current environmental conditions, CVNF model results suggested that, in the absence of fires, tropical forests would extend c. 200 km into the presently observed savanna domain. •Environmental changes were then imposed upon the model in temperature, precipitation and lightning strikes. These changes ranged from 2 to 6°C warming, +10 to −20% precipitation change and 0 to 15% increase in lightning frequency, which, in aggregate form, represent expected future climatic changes in response to global warming and deforestation. •The most critical vegetation changes are projected to take place over the easternmost portions of the basin, with a widening of the forest–savanna transition. The transition width would increase from 150 to c. 300 km, with tree cover losses ranging from 20 to 85%. This means that c. 6% of the areas currently covered by forests could potentially turn into grass-dominated savanna landscapes. The mechanism driving tree cover reduction consists of the combination of less favorable climate conditions for trees and more fire activity. In addition, this sensitivity analysis predicts that the current dry shrubland vegetation of northeast Brazil could potentially turn into a bare soil landscape. [ABSTRACT FROM AUTHOR]

The mechanisms associated with the intraseasonal variability of precipitation over South America during the spring season are investigated with emphasis on the influence of a quasi-stationary anomalous circulation over the southeastern South Pacific Ocean (SEP). A spectral analysis performed to the bandpass-filtered time series of daily precipitation anomalies for the La Plata Basin (LPB) and the South Atlantic convergence zone (SACZ) regions revealed several statistically relevant peaks corresponding to periods of roughly 23 days and 14–16 days—with the lower (higher) frequency peaks more prevalent for the SACZ (LPB). The large-scale circulation patterns preconditioning precipitation variability over both regions were explored by means of a regression analysis performed on the daily 500-hPa geopotential anomaly field provided by the NCEP–NCAR reanalysis dataset. The most prominent feature of the regression fields is the presence of a quasi-stationary anomalous anticyclonic (cyclonic) circulation over the southeastern South Pacific Ocean associated with positive rainfall anomalies over the LPB (SACZ) and, emanating from that high (low), an external Rossby wave propagating northeastward toward the South American continent. The synoptic-scale activity, quantified in terms of a frontal activity index, showed a strong influence on precipitation over the LPB and to a lesser extent over the SACZ. Moreover, the frontal activity is actually modulated by the anomalous high circulation over the SEP region. The behavior of this anomalous circulation may be supported by a positive feedback mechanism that can enhance the response of the high anomaly itself, which in turns reinforces the Rossby wave train propagating toward the South American continent. [ABSTRACT FROM AUTHOR]

Dynamical downscaling of global climate simulations is the most adequate tool to generate regional projections of climate change. This technique involves at least a present climate simulation and a simulation of a future scenario, usually at the end of the twenty first century. However, regional projections for a variety of scenarios and periods, the 2020s or the 2050s, are often required by the impact community. The pattern scaling technique is used to estimate information on climate change for periods and scenarios not simulated by the regional model. We based our study on regional simulations performed over southern South America for present climate conditions and two emission scenarios at the end of the twenty first century. We used the pattern scaling technique to estimate mean seasonal changes of temperature and precipitation for the 2020s and the 2050s. The validity of the scalability assumptions underlying the pattern scaling technique for estimating near future regional climate change scenarios over southern South America is assessed. The results show that the pattern scaling works well for estimating mean temperature changes for which the regional changes are linearly related to the global mean temperature changes. For precipitation changes, the validity of the scalability assumption is weaker. The errors of estimating precipitation changes are comparable to those inherent to the regional model and to the projected changes themselves. [ABSTRACT FROM AUTHOR]

We assess the likely changes in climate extremes under enhanced greenhouse gases over the southern extratropics, with emphasis in southern South America and sub-Antarctic seas, through the analysis of extreme indices measured from models participating in the IPCC 4th Assessment Report. We discuss how the anthropogenic climate change under A1B scenario influences both the patterns of mean change of extreme indices and the likelihood of occurrence of severe extreme indices. The likelihood of occurrence of a year with a large number of days with “warm” minimum temperatures is estimated to increase by a factor of 4 by the end of this century over most of the southern extratropics. By that time, the risk of “severe” precipitation intensity is projected to rise in most areas with the exception of the subtropical anticyclones, which experience particularly strong drying. Over the Southern Ocean this likelihood has increased to over 60%. Corresponding estimates of the changing likelihood for very long dry spells show a banded structure with positive ratios to the north of about 50° S and negative ratios in the sub Antarctic seas. In southern South America this risk about doubled between present and future climates. Then, we explore if the Southern Annular Mode influences the occurrence of severe extreme indices during the period 2070–2099. Its positive phase inhibits the extremely warm minimum temperatures in the Southern Ocean, with the exception of the eastern Bellingshausen Sea, and favors severe frost days to the north of the Ross Sea. Temperature indices show very little change induced by the SAM to the north of 50° S. Severe dry spells are inhibited during the positive phase along the sub Antarctic seas, while the mid-latitudes, including most of Patagonia, show the opposite behaviour. The Southern Ocean reveals a non-uniform distribution with both increases and decreases in the occurrence of heavier precipitation during positive SAM. [ABSTRACT FROM AUTHOR]

The article presents a study on the temperature and precipitation extreme in South America based on the Providing Regional Climate for Impacts Studies (PRECIS) regional climate modeling (RCM) system. The study compared the simulation trends in the 1961-1990 of the HadRM3P, the RCM within PRECIS, with the actual observations. It reveals that HadRM3P simulated trends show the similarity in the patterns of negative trends in the cold nights in South America and Southeastern South America.

Precipitation and temperature climate indices are calculated using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and validated against observational data from some stations over Brazil and other data sources. The spatial patterns of the climate indices trends are analyzed for the period 1961–1990 over South America. In addition, the correlation and linear regression coefficients for some specific stations were also obtained in order to compare with the reanalysis data. In general, the results suggest that NCEP/NCAR reanalysis can provide useful information about minimum temperature and consecutive dry days indices at individual grid cells in Brazil. However, some regional differences in the climate indices trends are observed when different data sets are compared. For instance, the NCEP/NCAR reanalysis shows a reversal signal for all rainfall annual indices and the cold night index over Argentina. Despite these differences, maps of the trends for most of the annual climate indices obtained from the NCEP/NCAR reanalysis and BRANT analysis are generally in good agreement with other available data sources and previous findings in the literature for large areas of southern South America. The pattern of trends for the precipitation annual indices over the 30 years analyzed indicates a change to wetter conditions over southern and southeastern parts of Brazil, Paraguay, Uruguay, central and northern Argentina, and parts of Chile and a decrease over southwestern South America. All over South America, the climate indices related to the minimum temperature (warm or cold nights) have clearly shown a warming tendency; however, no consistent changes in maximum temperature extremes (warm and cold days) have been observed. Therefore, one must be careful before suggesting any trends for warm or cold days. [ABSTRACT FROM AUTHOR]

The climate of the last glacial maximum (LGM) is simulated with a high-resolution atmospheric general circulation model, the NCAR CCM3 at spectral truncation of T170, corresponding to a grid cell size of roughly 75 km. The purpose of the study is to assess whether there are significant benefits from the higher resolution simulation compared to the lower resolution simulation associated with the role of topography. The LGM simulations were forced with modified CLIMAP sea ice distribution and sea surface temperatures (SST) reduced by 1°C, ice sheet topography, reduced CO2, and 21,000 BP orbital parameters. The high-resolution model captures modern climate reasonably well, in particular the distribution of heavy precipitation in the tropical Pacific. For the ice age case, surface temperature simulated by the high-resolution model agrees better with those of proxy estimates than does the low-resolution model. Despite the fact that tropical SSTs were only 2.1°C less than the control run, there are many lowland tropical land areas 4–6°C colder than present. Comparison of T170 model results with the best constrained proxy temperature estimates (noble gas concentrations in groundwater) now yield no significant differences between model and observations. There are also significant upland temperature changes in the best resolved tropical mountain belt (the Andes). We provisionally attribute this result in part as resulting from decreased lateral mixing between ocean and land in a model with more model grid cells. A longstanding model-data discrepancy therefore appears to be resolved without invoking any unusual model physics. The response of the Asian summer monsoon can also be more clearly linked to local geography in the high-resolution model than in the low-resolution model; this distinction should enable more confident validation of climate proxy data with the high-resolution model. Elsewhere, an inferred salinity increase in the subtropical North Atlantic may have significant implications for ocean circulation changes during the LGM. A large part of the Amazon and Congo Basins are simulated to be substantially drier in the ice age—consistent with many (but not all) paleo data. These results suggest that there are considerable benefits derived from high-resolution model regarding regional climate responses, and that observationalists can now compare their results with models that resolve geography at a resolution comparable to that which the proxy data represent. [ABSTRACT FROM AUTHOR]

This study investigates the capabilities of two regional models (the ICTP RegCM3 and the climate version of the CPTEC Eta model – EtaClim) in simulating the mean climatological features of the summer quasi-stationary circulations over South America. Comparing the results with the NCEP/DOE reanalysis II data it is seen that the RegCM3 simulates a weaker and southward shifted Bolivian high (BH). But, the Nordeste low (NL) is located close to its climatological position. In the EtaClim the position of the BH is reproduced well, but the NL is shifted towards the interior of the continent. To the east of Andes, the RegCM3 simulates a weaker low level jet and a weaker basic flow from the tropical Atlantic to Amazonia while they are stronger in the EtaClim. In general, the RegCM3 and EtaClim show, respectively a negative and positive bias in the surface temperature in almost all regions of South America. For both models, the correlation coefficients between the simulated precipitation and the GPCP data are high over most of South America. Although the RegCM3 and EtaClim overestimate the precipitation in the Andes region they show a negative bias in general over the entire South America. The simulations of upper and lower level circulations and precipitation fields in EtaClim were better than that of the RegCM3. In central Amazonia both models were unable to simulate the precipitation correctly. The results showed that although the RegCM3 and EtaClim are capable of simulating the main climatological features of the summer climate over South America, there are areas which need improvement. This indicates that the models must be more adequately tuned in order to give reliable predictions in the different regions of South America. [ABSTRACT FROM AUTHOR]

This study investigates the capabilities of two regional models (the ICTP RegCM3 and the climate version of the CPTEC Eta model – EtaClim) in simulating the summer quasi-stationary circulations over South America during two extreme cases: the 1997–1998 El Niño and 1998–1999 La Niña. The results showed that both the models are successful in simulating the interannual variability of summer quasi-stationary circulation over South America. Both the models simulated the intensification of subtropical jet stream during the El Niño event, which favoured the blocking of transient systems and increased the precipitation over south Brazil. The models simulated the increase (decrease) of precipitation over north (west) Amazonia during the La Niña (El Niño) event. The upper level circulation is in agreement with the simulated distribution of precipitation. In general, the results showed that both the models are capable of capturing the main changes of the summer climate over South America during these two extreme cases and consequently they have potential to predict climate anomalies. [ABSTRACT FROM AUTHOR]

The precipitation variability over South America south of 20° S (5A205) has been investigated at a decadal (DD) and non-DD time scales. The results suggest that the space-time particularities of the ENSO-related precipitation anomalous patterns depend on the time scales considered. The precipitation patterns in the 5A205 associated with the non-DD episodes exhibit a space-time coherent characteristics during ONDJ (0)-JJAS (+1) period such that a prominent area of positive (negative) anomalies is observed in the central 5A205 and displaced northeastward with the time for the non-DD El Niños (La Niñas). On the other hand, the precipitation anomalous patterns associated with the DD episodes feature more complex horizontal structures and larger anomalies than those of the non-decadal episodes. It is also worthwhile noting that the 5A205 climate experiences the strongest and more extensive effects of the DD episode during the austral summer of the year following the onset of the DD episodes. [ABSTRACT FROM AUTHOR]