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The Choco low-level jet is among the main regional circulation mechanisms related to the advection of water vapor from the eastern Pacific to northwestern South America. Variations in the intensity of position of the jet core are identified as determinant for regional moisture transport and associated rainfall. This paper analyzes the annual cycle of intensity and latitudinal location of this jet according to different reanalysis and observational datasets. Moreover, we compare possible changes in the Choco jet occurred during past climates, like the little ice age (LIA), with those associated with future scenarios of greenhouse gas concentrations (RCP8.5), using simulations from the Paleoclimate Modelling Intercomparison Project Phase 3 (PMIP3) and the Coupled Model Intercomparison Project Phase 5 (CMIP5). Our results suggest that according to reanalysis/observational data, as well as the CMIP5 models with the best representation of the Choco jet in present climate, there is a positive correlation between the jet intensity and its latitudinal location, and such relationship is associated with the sea level pressure (SLP) difference between the eastern tropical Pacific and the northwestern South American landmass. Hence, stronger (weaker) SLP differences favor a stronger (weaker) intensity and a northward (southward) location of the Choco jet. PMIP3 simulations suggest a stronger and northward Choco jet during LIA due to a stronger SLP difference in comparison to present climate. However, under the RCP8.5 scenario, there is not robust agreement among CMIP5 models although the best models suggest a southward jet at the end of the 21st century. This suggests that the mechanisms influencing the Choco jet may play different roles during past natural climate changes with respect to anthropogenically-forced climate changes. [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]

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]

Recent studies have shown that global warming and associated sea-surface temperature (SST) changes may trigger an important rainfall increase in southeastern South America (SESA) during the austral summer (December-January-February, DJF). The goal of this paper is to provide some insight into processes which may link global and SESA changes. For this purpose, a 'two-way nesting' system coupling interactively the regional and global versions of the LMDZ4 atmospheric model is used to study the response to prescribed SST changes. The regional model is a variable-grid version of the global model, with a zoom focused over South America. An ensemble of simulations forced by distinct patterns of DJF SST changes has been carried out using a decomposition of full SST changes into their longitudinal and latitudinal components. The full SST changes are based on projections for the end of the twenty-first century from a multi-model ensemble of WCRP/CMIP3. Results confirm the presence of a major rainfall dipole structure, characterized by an increase in SESA and a decrease in the South Atlantic Convergence Zone region. Rainfall changes found in the WCRP/CMIP3 models are largely explained as a response of this dipole structure to the zonally-asymmetric (or longitudinal) component of SST changes. The rainfall response to the zonal-mean (or latitudinal) SST changes (including the global warming signal itself) shows an opposite contribution. The processes explaining the role of zonally-asymmetric SST changes involve remote effects of SST warming over the equatorial Indian and Pacific oceans inducing an atmospheric wave-train extended across the South Pacific into South America. [ABSTRACT FROM AUTHOR]

The objective of this work is to evaluate climate simulations over South America using the regional Eta Model driven by four members of an ensemble of the UK Met Office Hadley Centre HadCM3 global model. The Eta Model has been modified with the purpose of performing long-term decadal integrations and has shown to reproduce 'present climate'-the period 1961-1990-reasonably well when forced by HadCM3. The global model lateral conditions with a resolution of 2.5° latitude × 3.75° longitude were provided at a frequency of 6 h. Each member of the global model ensemble has a different climate sensitivity, and the four members were selected to span the range of uncertainty encompassed by the ensemble. The Eta Model nested in the HadCM3 global model was configured with 40-km horizontal resolution and 38 layers in the vertical. No large-scale internal nudging was applied. Results are shown for austral summer and winter at present climate defined as 1961-90. The upper and low-level circulation patterns produced by the Eta-CPTEC/HadCM3 experiment set-up show good agreement with reanalysis data and the mean precipitation and temperature with CRU observation data. The spread in the downscaled mean precipitation and temperature is small when compared against model errors. On the other hand, the benefits in using an ensemble is clear in the improved representation of the seasonal cycle by the ensemble mean over any one realization. El Niño and La Niña years were identified in the HadCM3 member runs based on the NOAA Climate Prediction Center criterion of sea surface temperature anomalies in the Niño 3.4 area. The frequency of the El Niño and La Niña events in the studied period is underestimated by HadCM3. The precipitation and temperature anomalies typical of these events are reproduced by most of the Eta-CPTEC/HadCM3 ensemble, although small displacements of the positions of the anomalies occur. This experiment configuration is the first step on the implementation of Eta-CPTEC/HadCM3 upcoming experiments on climate change studies that are discussed in a companion paper. [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]

Heat waves in Amazonia have become more frequent, longer, and more intense according to observational records. Climate change and deforestation are two significant drivers of such trends. In the Amazon rainforest, heat waves are still an understudied issue, in part due to limited surface observations. To date, heat waves in central Amazon have been associated with the ITCZ northward migration in austral winter, weakening moisture influx through the South American Monsoon System. This study contributes to this topic by being the first Amazon-specific analysis of heat extremes and the first in South America to jointly explore extreme heat wave events and associated synoptic atmospheric and land surface conditions. Ten of the most extreme heat waves are identified in the Southeast of Amazonia, from Era-Interim (1979 to 2018) maximum daily temperature records. Dry conditions are measured from relative humidity and evaporative fraction anomalies at surface and vertically also using the Era-Interim data. In all 10 events an extreme drying signal co-occurs with extreme heat waves. Wind patterns and anomalies revealed a consistent easterly dry advection anomalously extending to Southeast Amazonia. In addition, an intensification of the northerly South Atlantic Anticyclone wind circulation reduced the influx of moisture to Southeast Amazon, namely linked to the South American Low Level Jet. These, together, contributed to a compound effect on the extreme heat waves under near-surface drying conditions, which escalated hot temperatures to extreme heat. [ABSTRACT FROM AUTHOR]

Studies that evaluate climate change projections over the whole of South America (SA) and including different seasons and models are scarce. In this context, the objective of this work is to assess climate projections for SA through the use of climatic indices, considering the entire continent, distinct seasons, and ensembles of models. Projections performed with the Eta regional climate model and its driving global climate models (GCMs) are analysed. From these projections, 19 climate indices based on daily precipitation and maximum and minimum temperature are computed. The results focus on two ensembles (GCMs and Eta), time slices (1980–2005 and 2050–2080), and scenarios (RCP4.5 and RCP8.5). In the validation of the present climate, it is shown that Eta adds value to GCMs. Future projections indicate, for both austral summer (DJF) and winter (JJA), an increase in the frequency and intensity of extreme events of daily rainfall over southeastern and extreme north of SA. Over the Amazon, during DJF, there is a statistically significant increase in the number of consecutive dry days and a decrease in the consecutive wet days. For northeastern Brazil, these features are more intense in JJA. The frequency of cold (warm) nights and days is projected to decrease (increase) over the whole continent and seasons. The climate change signal for the 19 climate indices is more intense under RCP8.5, and the regions more vulnerable to climate change are the Amazon, northeastern Brazil, and southeastern SA. Considering Brazil, the projections of precipitation and air temperature are also shown by biomes. [ABSTRACT FROM AUTHOR]

Future projections in austral winter characteristics of explosive extratropical cyclones (EECs) in three CORDEX Southern Hemisphere domains (Africa-AFR, Australia-AUS and South America-SAM) are investigated. The projections are obtained with a fine resolution (25 km) Regional Climate Model (RegCM4) within the CORDEX-CORE framework driven by three Global Climate Models (GCMs: HadGEM2-ES, MPI-ESM-MR and NorESM-1 M) under the RCP8.5 scenario. The cyclone database was obtained using a tracking scheme applied to 6-hourly mean sea level pressure fields and EECs are selected using the Sanders and Gyakum criterion. EECs represent ~ 13–17% of the total number of extratropical cyclones during austral winter in the ERA-Interim reanalysis (1995–2014), while both GCMs and RegCM4 ensembles underestimate this percentage. The frequency of EECs is projected to increase in AFR and in SAM domains at the end of the twenty-first century. However, the magnitude of the projected changes needs to be considered with caution because it is smaller than the underestimations in the frequency of EECs of both ensembles in the present climate. EECs in the future will be deeper and faster but with a shorter lifetime. Eady Growth Rate composites, when EECs reach the explosive phase, indicate a less baroclinic large-scale environment in the future. On the other hand, the intensification of precipitation associated with EECs in the future indicates an increase in the contribution of the diabatic processes acting to strengthen the local baroclinicity of the EECs. [ABSTRACT FROM AUTHOR]

Southwestern South America (SWSA) has undergone frequent and persistent droughts in recent decades with severe impacts on water resources, and consequently, on socio-economic activities at a sub-continental scale. The local drying trend in this region has been associated with the expansion of the subtropical drylands over the last decades. It has been shown that SWSA precipitation is linked to large-scale dynamics modulated by internal climate variability and external forcing. This work aims at unravelling the causes of this long-term trend toward dryness in the context of the emerging climate change relying on a large set simulations of the state-of-the-art IPSL-CM6A-LR climate model from the 6th phase of the Coupled Model Intercomparison Project. Our results identify the leading role of dynamical changes induced by external forcings, over the local thermodynamical effects and teleconnections with internal global modes of sea surface temperature. Our findings show that the simulated long-term changes of SWSA precipitation are dominated by externally forced anomalous expansion of the Southern Hemisphere Hadley Cell (HC) and a persistent positive Southern Annular Mode (SAM) trend since the late 1970s. Long-term changes in the HC extent and the SAM show strong co-linearity. They are attributable to stratospheric ozone depletion in austral spring-summer and increased atmospheric greenhouse gases all year round. Future ssp585 and ssp126 scenarios project a dominant role of anthropogenic forcings on the HC expansion and the subsequent SWSA drying, exceeding the threshold of extreme drought due to internal variability as soon as the 2040s, and suggest that these effects will persist until the end of the twenty-first century. [ABSTRACT FROM AUTHOR]

Hazardous weather related to the occurrence of severe thunderstorms including tornadoes, high-winds, and hail cause significant damage globally to life and property every year. Yet the impact on these storms from a warming climate remains a difficult task due to their transient nature. In this study we investigate the change in large-scale environments in which severe thunderstorms form during twenty-first century warming (RCP2.6 and RCP8.5) in a group of RegCM CORDEX-CORE simulations. Severe potential is measured in terms of Convective Available Potential Energy (CAPE) and vertical wind-shear during the severe seasons in three regions which are known to currently be prone to severe hazards: North America, subtropical South America, and eastern India and Bangladesh. In every region, environments supportive for severe thunderstorms are projected to increase during the warm season months in both the RCP2.6 and RCP8.5 scenarios during the twenty-first century. The number of days supportive for severe thunderstorms increases by several days per season over the vast majority of each region by the end of the century. Analyzing the CAPE and shear trends during the twenty-first century, we find seasonally and regionally specific changes driving the increased severe potential. Twenty-first century surface warming is clearly driving a robust increase in CAPE in all regions, however poleward displacement of vertical shear in the future leads to the displacement of severe environments over North America and South America. The results found here relate that severe impacts in the future cannot be generalized globally, and that regionally specific changes in vertical shear may drive future movement of regions prone to severe weather. [ABSTRACT FROM AUTHOR]

The precipitation behaviour at different timescales (interannual, intraseasonal and synoptic) and extreme events in a warmer scenario over South America is analysed. This study is based on a set of Regional Climate Models (RCM) from the CORDEX database and their driving Global Climate Models (GCM) from the CMIP5 Project. Historical simulations for 1979–2005 and from the RCP4.5 scenario for 2071–2100 are used. The projected changes in the precipitation behaviour are evaluated in terms of the consistency between the pairs RCM-GCM aiming to explore the added value of RCMs. The agreement between projected changes from RCMs is also evaluated as a measure of confidence of the regional climate change signal. The analysis is carried out for two extended seasons (April to September and October to March). The projected change in the mean precipitation over subtropical latitudes is associated with both changes in the frequency of rainy days and in the intensity of extreme events, while for the tropics the changes are mainly associated with changes in the wet day frequency. The increase of extreme precipitation events over the subtropics arises as a robust signal among models, while for tropical latitudes the dispersion among models is high, which reduces the confidence of the projections. In general, the consistency of the projections in the pairs RCM-GCM and the agreement among models are higher for the low frequency variability patterns during winter, while for summertime a better agreement in the projected changes of the precipitation behaviour at different timescales among RCMs is found. [ABSTRACT FROM AUTHOR]

Changes in temperature, precipitation, and other variables simulated by 40 current climate models for the 21st century are approximated as the product of the global mean warming and a spatial pattern of scaled changes. These fields of standardized change contain consistent features of simulated change, such as larger warming over land and increased high-latitude precipitation. However, they also differ across the ensemble, with standard deviations exceeding 0.2 for temperature over most continents, and 6% per degree for tropical precipitation. These variations are found to correlate, often strongly, with indices based on those of modes of interannual variability. Annular mode indices correlate, across the 40 models, with regional pressure changes and seasonal rainfall changes, particularly in South America and Europe. Equatorial ocean warming rates link to widespread anomalies, similarly to ENSO. A Pacific-Indian Dipole (PID) index representing the gradient in warming across the maritime continent is correlated with Australian rainfall with coefficient r of − 0.8. The component of equatorial warming orthogonal to this index, denoted EQN, has strong links to temperature and rainfall in Africa and the Americas. It is proposed that these indices and their associated patterns might be termed "modes of climate change". This is supported by an analysis of empirical orthogonal functions for the ensemble of standardized fields. Can such indices be used to help constrain projections? The relative similarity of the PID and EQN values of change, from models that have more skilful simulation of the present climate tropical pressure fields, provides a basis for this. [ABSTRACT FROM AUTHOR]

The intraseasonal variability of the frontal activity and its connection with the variability of the atmospheric circulation and precipitation in the Southern Hemisphere is studied. The frontal activity is defined as the relative vorticity times the local temperature gradient. A band-pass filter was applied to retain the intraseasonal timescales. An empirical orthogonal function analysis was applied to the filtered frontal activity anomalies. The two main modes show positive and negative centers located mainly over the southern Pacific Ocean and South American sector and are in quadrature with each other. A similar pattern was found when the main modes of intraseasonal variability of the 500 hPa geopotential height were projected on the frontal activity, suggesting that the variability of fronts are influenced by the variability of the large scale atmospheric circulation. Moreover, the precipitation anomalies projected on the main modes of both frontal activity and 500 hPa geopotential height show similar structures, especially over the southern Pacific Ocean and South America, which may indicate that the variability of fronts controls the variability of precipitation. The lagged regression of the time series of the frontal activity areally-averaged over one of the centers of action against the frontal activity anomaly field shows at lags −8 and 8 a similar pattern, suggesting a period of around 17 days for each mode. Moreover, lagged regression between times series of frontal activity and precipitation anomalies reveals an opposite pattern between southeastern South America and southern Chile, being precipitation anomalies over these two regions anti-correlated due to the frontal activity. [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]

The simulation of the climate over South America by a coupled ocean-atmosphere model with embedded cloud resolving model is studied on different time scales. The mean climate and the variability over South America as simulated by the superparameterized Community Climate System Model version 3 (SP-CCSM) are compared with those in the observation and in the control simulation of the CCSM3 (CT-CCSM) which employs conventional scheme of convection parameterization. The CT-CCSM is able to simulate only the longer period seasonal oscillation (SO) while the SP-CCSM is successful in simulating both the SO and the intraseasonal oscillation (ISO). The spatial structure and the propagation of the oscillations are better in the SP-CCSM. Both models are able to simulate the observed low-frequency modes of variability related to El Niño-Southern oscillation (ENSO) and Pacific decadal oscillation (PDO). While the ENSO mode in the CT-CCSM has more regular variability with a biennial time scale, the SP-CCSM simulates the ENSO mode with more irregular variability and time scale closer to the observation. The spatial structure, the relation with the Pacific and the regional variations of the observed PDO mode are better simulated by the SP-CCSM than the CT-CCSM. [ABSTRACT FROM AUTHOR]

In this study we introduce two new node-weighted difference measures on complex networks as a tool for climate model evaluation. The approach facilitates the quantification of a model's ability to reproduce the spatial covariability structure of climatological time series. We apply our methodology to compare the performance of a statistical and a dynamical regional climate model simulating the South American climate, as represented by the variables 2 m temperature, precipitation, sea level pressure, and geopotential height field at 500 hPa. For each variable, networks are constructed from the model outputs and evaluated against a reference network, derived from the ERA-Interim reanalysis, which also drives the models. We compare two network characteristics, the (linear) adjacency structure and the (nonlinear) clustering structure, and relate our findings to conventional methods of model evaluation. To set a benchmark, we construct different types of random networks and compare them alongside the climate model networks. Our main findings are: (1) The linear network structure is better reproduced by the statistical model statistical analogue resampling scheme (STARS) in summer and winter for all variables except the geopotential height field, where the dynamical model CCLM prevails. (2) For the nonlinear comparison, the seasonal differences are more pronounced and CCLM performs almost as well as STARS in summer (except for sea level pressure), while STARS performs better in winter for all variables. [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]

The performance of seven regional climate models in simulating the radiation and heat fluxes at the surface over South America (SA) is evaluated. Sources of uncertainty and errors are identified. All simulations have been performed in the context of the CLARIS-LPB Project for the period 1990-2008 and are compared with the GEWEX-SRB, CRU, and GLDAS2 dataset and NCEP-NOAA reanalysis. Results showed that most of the models overestimate the net surface short-wave radiation over tropical SA and La Plata Basin and underestimate it over oceanic regions. Errors in the short-wave radiation are mainly associated with uncertainties in the representation of surface albedo and cloud fraction. For the net surface long-wave radiation, model biases are diverse. However, the ensemble mean showed a good agreement with the GEWEX-SRB dataset due to the compensation of individual model biases. Errors in the net surface long-wave radiation can be explained, in a large proportion, by errors in cloud fraction. For some particular models, errors in temperature also contribute to errors in the net long-wave radiation. Analysis of the annual cycle of each component of the energy budget indicates that the RCMs reproduce generally well the main characteristics of the short- and long-wave radiations in terms of timing and amplitude. However, a large spread among models over tropical SA is apparent. The annual cycle of the sensible heat flux showed a strong overestimation in comparison with the reanalysis and GLDAS2 dataset. For the latent heat flux, strong differences between the reanalysis and GLDAS2 are calculated particularly over tropical SA. [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]

December-January-February (DJF) rainfall variability in southeastern South America (SESA) is studied in 18 coupled general circulation models from the WCRP/CMIP3 dataset, for present climate and the SRES-A1B climate change scenario. The analysis is made in terms of properties of the first leading pattern of rainfall variability in the region, characterized by a dipole-like structure with centers of action in the SESA and South Atlantic Convergence Zone (SACZ) regions. The study was performed to address two issues: how rainfall variability in SESA would change in a future climate and how much of that change explains the projected increasing trends in the summer mean rainfall in SESA identified in previous works. Positive (negative) dipole events were identified as those DJF seasons with above (below) normal rainfall in SESA and below (above) normal rainfall in the SACZ region. Results obtained from the multi-model ensemble confirm that future rainfall variability in SESA has a strong projection on the changes of seasonal dipole pattern activity, associated with an increase of the frequency of the positive phase. In addition, the frequency increase of positive dipole phase in the twenty first century seems to be associated with an increase of both frequency and intensity of positive SST anomalies in the equatorial Pacific, and with a Rossby wave train-like anomaly pattern linking that ocean basin to South America, which regionally induces favorable conditions for moisture transport convergence and rainfall increase in SESA. [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]

The influence of the intraseasonal variability on heat wave development over subtropical South America during austral summer is analyzed. The role of the South Atlantic Convergence Zone (SACZ) on this development is documented. Results show that intraseasonal variability can explain on average at least 32% of summer temperature variance. Moreover, 73% of the heat waves in subtropical South America develop in association with an active SACZ. The analysis of pentad maps shows that warm conditions in the region under study develop in association with the strengthening of an anticyclonic anomaly, which is discernible over the subtropical regions at least 15 days before temperature peak occurrence. That circulation anomaly is embedded in a large-scale Rossby wave train extending along the South Pacific Ocean that is linked to convection anomalies at the equatorial western and central Pacific Ocean. In addition, the development of the anticyclonic circulation over subtropical South America appears to be strengthened by the subsidence conditions promoted by the active SACZ, which result in temperature rise in the subtropical region under relatively dry conditions. On the other hand, during the last 2 days of evolution, SACZ activity weakens and the progressive temperature rise in the region is dominated by warmer and moister air being anomalously advected from the north. Results confirm the important role that SACZ activity on intraseasonal time scales has in inducing persistent circulation anomalies at the subtropical regions that can result in the development of persistent heat waves, and very extreme daily temperature. [ABSTRACT FROM AUTHOR]

Regional climate change projections for the last half of the twenty-first century have been produced for South America, as part of the CREAS (Cenarios REgionalizados de Clima Futuro da America do Sul) regional project. Three regional climate models RCMs (Eta CCS, RegCM3 and HadRM3P) were nested within the HadAM3P global model. The simulations cover a 30-year period representing present climate (1961-1990) and projections for the IPCC A2 high emission scenario for 2071-2100. The focus was on the changes in the mean circulation and surface variables, in particular, surface air temperature and precipitation. There is a consistent pattern of changes in circulation, rainfall and temperatures as depicted by the three models. The HadRM3P shows intensification and a more southward position of the subtropical Pacific high, while a pattern of intensification/weakening during summer/winter is projected by the Eta CCS/RegCM3. There is a tendency for a weakening of the subtropical westerly jet from the Eta CCS and HadRM3P, consistent with other studies. There are indications that regions such of Northeast Brazil and central-eastern and southern Amazonia may experience rainfall deficiency in the future, while the Northwest coast of Peru-Ecuador and northern Argentina may experience rainfall excesses in a warmer future, and these changes may vary with the seasons. The three models show warming in the A2 scenario stronger in the tropical region, especially in the 5°N-15°S band, both in summer and especially in winter, reaching up to 6-8°C warmer than in the present. In southern South America, the warming in summer varies between 2 and 4°C and in winter between 3 and 5°C in the same region from the 3 models. These changes are consistent with changes in low level circulation from the models, and they are comparable with changes in rainfall and temperature extremes reported elsewhere. In summary, some aspects of projected future climate change are quite robust across this set of model runs for some regions, as the Northwest coast of Peru-Ecuador, northern Argentina, Eastern Amazonia and Northeast Brazil, whereas for other regions they are less robust as in Pantanal region of West Central and southeastern Brazil. [ABSTRACT FROM AUTHOR]

We present an analysis of climate change over southern South America as simulated by a regional climate model. The regional model MM5 was nested within time-slice global atmospheric model experiments conducted by the HadAM3H model. The simulations cover a 10-year period representing present-day climate (1981–1990) and two future scenarios for the SRESA2 and B2 emission scenarios for the period 2081–2090. There are a few quantitative differences between the two regional scenarios. The simulated changes are larger for the A2 than the B2 scenario, although with few qualitative differences. For the two regional scenarios, the warming in southern Brazil, Paraguay, Bolivia and northeastern Argentina is particularly large in spring. Over the western coast of South America both scenarios project a general decrease in precipitation. Both the A2 and B2 simulations show a general increase in precipitation in northern and central Argentina especially in summer and fall and a general decrease in precipitation in winter and spring. In fall the simulations agree on a general decrease in precipitation in southern Brazil. This reflects changes in the atmospheric circulation during winter and spring. Changes in mean sea level pressure show a cell of increasing pressure centered somewhere in the southern Atlantic Ocean and southern Pacific Ocean, mainly during summer and fall in the Atlantic and in spring in the Pacific. In relation to the pressure distribution in the control run, this indicates a southward extension of the summer mean Atlantic and Pacific subtropical highs. [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]

We present an analysis of a regional simulation of present-day climate (1981–1990) over southern South America. The regional model MM5 was nested within time-slice global atmospheric model experiments conducted by the HadAM3H model. We evaluate the capability of the model in simulating the observed climate with emphasis on low-level circulation patterns and surface variables, such as precipitation and surface air mean, maximum and minimum temperatures. The regional model performance was evaluated in terms of seasonal means, seasonal cycles, interannual variability and extreme events. Overall, the regional model is able to capture the main features of the observed mean surface climate over South America, its seasonal evolution and the regional detail due to topographic forcing. The observed regional patterns of surface air temperatures (mean, maxima and minima) are well reproduced. Biases are mostly within 3°C, temperature being overestimated over central Argentina and underestimated in mountainous regions during all seasons. Biases in northeastern Argentina and southeastern Brazil are positive during austral spring season and negative in other seasons. In general, maximum temperatures are better represented than minimum temperatures. Warm bias is larger during austral summer for maximum temperature and during austral winter for minimum temperature, mainly over central Argentina. The broad spatial pattern of precipitation and its seasonal evolution are well captured; however, the regional model overestimates the precipitation over the Andes region in all seasons and in southern Brazil during summer. Precipitation amounts are underestimated over the La Plata basin from fall to spring. Extremes of precipitation are better reproduced by the regional model compared with the driving model. Interannual variability is well reproduced too, but strongly regulated by boundary conditions, particularly during summer months. Overall, taking into account the quality of the simulation, we can conclude that the regional model is capable in reproducing the main regional patterns and seasonal cycle of surface variables. The present reference simulation constitutes the basis to examine the climate change simulations resulting from the A2 and B2 forcing scenarios which are being reported in a separate study. [ABSTRACT FROM AUTHOR]

The simulated low-frequency variability patterns of the atmospheric circulation, ranging from interannual to interdecadal timescales, are studied in an area encompassing southern South America. The experiment is a transient simulation performed with the IPSL CCM2 coupled global model, in which the greenhouse forcing is continuously increasing. The main modes of low-frequency variability are found to remain stationary throughout the simulation, suggesting they depend more on the internal dynamics of the atmospheric flow than on its external forcing. Inspection of the circulation regimes that represent the more recurrent patterns at interannual and interdecadal timescales showed that climate change manifests itself as a change in regime population, suggesting that the negative phase of the Antarctic Oscillation-like pattern becomes more frequented in a climate change scenario. Changes of regime occurrence are superimposed to a positive trend whose spatial pattern is reminiscent of the structure of the Antarctic Oscillation-mode of variability. Moreover, it resembles the spatial patterns of those regimes that show a significant change in population. The change in regime frequencies of the circulation patterns of low-frequency variability are in opposite phase with respect to the trend, thus, the behaviour of these patterns of variability, superimposed to a changing mean state, modulates the climate change signal. The analysis of the high frequencies, in terms of recurrent patterns representing intraseasonal and synoptic-scale of variability, shows no significant changes in regime characteristics, concerning both spatial and temporal behaviour. [ABSTRACT FROM AUTHOR]