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This paper presents an evaluation of climate simulations produced by the Brazilian Global Atmospheric Model version 1.2 (BAM-1.2) of the Center for Weather Forecast and Climate Studies (CPTEC). The model was run over the 1975–2017 period at two spatial resolutions, corresponding to ~ 180 and ~ 100 km, both with 42 vertical levels, following most of the Atmospheric Model Intercomparison Project (AMIP) protocol. In this protocol, observed sea surface temperatures (SSTs) are used as boundary conditions for the atmospheric model. Four ensemble members were run for each of the two resolutions. A series of diagnostics was computed for assessing the model's ability to represent the top of the atmosphere (TOA) radiation, atmospheric temperature, circulation and precipitation climatological features. The representation of precipitation interannual variability, El Niño-Southern Oscillation (ENSO) precipitation teleconnections, the Madden and Julian Oscillation (MJO) and daily precipitation characteristics was also assessed. The model at both resolutions reproduced many observed temperature, atmospheric circulation and precipitation climatological features, despite several identified biases. The model atmosphere was found to be more transparent than the observations, leading to misrepresentation of cloud-radiation interactions. The net cloud radiative forcing, which produces a cooling effect on the global mean climate at the TOA, was well represented by the model. This was found to be due to the compensation between both weaker longwave cloud radiative forcing (LWCRF) and shortwave cloud radiative forcing (SWCRF) in the model compared to the observations. The model capability to represent inter-annual precipitation variability at both resolutions was found to be linked to the adequate representation of ENSO teleconnections. However, the model produced weaker than observed convective activity associated with the MJO. Light daily precipitation over the southeast of South America and other climatologically similar regions was diagnosed to be overestimated, and heavy daily precipitation underestimated by the model. Increasing spatial resolution helped to slightly reduce some of the diagnosed biases. The performed evaluation identified model aspects that need to be improved. These include the representation of polar continental surface and sea ice albedo, stratospheric ozone, low marine clouds, and daily precipitation features, which were found to be larger and last longer than the observed features. [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]

This paper examines moisture transport on intraseasonal timescales over the continent and over the South Atlantic convergence zone (SACZ) during the South America (SA) summer monsoon. Combined Empirical Orthogonal Function analysis (EOFc) of Global Precipitation Climatology Project pentad precipitation, specific humidity, air temperature, zonal and meridional winds at 850 hPa (NCEP/NCAR reanalysis) are performed to identify the large-scale variability of the South America monsoon system and the SACZ. The first EOFc was used as a large-scale index for the South American monsoon (LISAM), whereas the second EOFc characterized the SACZ. LISAM (SACZ) index showed spectral variance on 30-90 (15-20) days and were both band filtered (10-100 days). Intraseasonal wet anomalies were defined when LISAM and SACZ anomalies were above the 75th percentile of their respective distribution. LISAM and SACZ wet events were examined independently of each other and when they occur simultaneously. LISAM wet events were observed with the amplification of wave activity in the Northern Hemisphere and the enhancement of northwesterly cross-equatorial moisture transport over tropical continental SA. Enhanced SACZ was observed with moisture transport from the extratropics of the Southern Hemisphere. Simultaneous LISAM and SACZ wet events are associated with cross-equatorial moisture transport along with moisture transport from Subtropical Southwestern Atlantic. [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 seasonal cycle of the intraseasonal (IS) variability of precipitation in South America is described through the analysis of bandpass filtered outgoing longwave radiation (OLR) anomalies. The analysis is discriminated between short (10-30 days) and long (30-90 days) intraseasonal timescales. The seasonal cycle of the 30-90-day IS variability can be well described by the activity of first leading pattern (EOF1) computed separately for the wet season (October-April) and the dry season (May-September). In agreement with previous works, the EOF1 spatial distribution during the wet season is that of a dipole with centers of actions in the South Atlantic Convergence Zone (SACZ) and southeastern South America (SESA), while during the dry season, only the last center is discernible. In both seasons, the pattern is highly influenced by the activity of the Madden-Julian Oscillation (MJO). Moreover, EOF1 is related with a tropical zonal-wavenumber-1 structure superposed with coherent wave trains extended along the South Pacific during the wet season, while during the dry season the wavenumber-1 structure is not observed. The 10-30-day IS variability of OLR in South America can be well represented by the activity of the EOF1 computed through considering all seasons together, a dipole but with the stronger center located over SESA. While the convection activity at the tropical band does not seem to influence its activity, there are evidences that the atmospheric variability at subtropical-extratropical regions might have a role. Subpolar wavetrains are observed in the Pacific throughout the year and less intense during DJF, while a path of wave energy dispersion along a subtropical wavetrain also characterizes the other seasons. Further work is needed to identify the sources of the 10-30-day-IS variability in South America. [ABSTRACT FROM AUTHOR]

Previous study showed that the interaction of synoptic disturbances with intraseasonal anomalies is important for heavy rainfall in the South Atlantic Convergence Zone and the La Plata basin during the austral summer. Here, we conduct similar analysis to study the evolution of rainfall extremes during austral spring (SON), fall (MAM) and winter (JJA). A relatively homogeneous region over southeastern South America, whose limits change little from season to season, is heavily affected by extreme precipitation events, as indicated by the value of the 95th percentile of daily rainfall, higher during the spring season (16.94 mm day) and lower in winter (13.79 mm day). From 1979 to 2013, extreme rainfall events are more frequent in spring (131 events) and less frequent in fall (112 events). Similar to summertime extreme events, synoptic-scale waves continue to be the main drivers of extreme precipitation over the region. The interaction between these waves and intraseasonal anomalies during the development of rainfall extremes over southeastern South America is observed especially during neutral ENSO and La Niña conditions. Warm ENSO phases tend to favor more frequent extremes in all three seasons and extreme events during El Niños are associated with synoptic waves, with no significant interaction with intraseasonal anomalies. [ABSTRACT FROM AUTHOR]

Combining individual forecasts is one of the practices used to improve weather prediction results. Identifying which combination of techniques results in a more accurate forecast is the subject of many comparative studies as well proposals for combined methods. Here we compare three combination techniques: (1) principal component regression (PCR), (2) convex combination by mean squared errors (MSE) and (3) ensemble average to combine six regional climate models of the Regional Climate Change Assessment for the La Plata Basin Project (CLARIS-LPB) for variable rainfall in three regions: Amazon (AMZ), Northeastern Brazil (NEB) and La Plata Basin (LPB), for the past (1961-1990) and future (2071-2100) climates. The results indicate that the average RMSE values showed improved representation of climate for LPB in some months, which is an important advance in climate studies. On the other hand, PCR presented greater accuracy (lower RMSE) than MSE in the AMZ and NEB regions. In winter months, both combinations presented lower RMSE results, mainly PCR in the three study regions. The correlation coefficient supports the results already found, namely, PCR obtained moderate to strong correlations, which were statistically significant at 5 % in both regions for all months, while MSE presented low to moderate correlations, which were statically significant at 5 % only in some months. Based on that, PCR achieved the best corrected forecast, as it was superior in forecasting precipitation due to the lower RMSE value. It is noteworthy that the PCR data were first subjected to principal component analysis (PCA) and the scores were used to perform the prediction. [ABSTRACT FROM AUTHOR]

Warm-season precipitation variability over subtropical South America is characterized by an inverse relationship between the South Atlantic convergence zone (SACZ) and precipitation over the central and western La Plata basin of southeastern South America. This study extends the analysis of this 'South American Seesaw' precipitation dipole to relationships between the SACZ and large, long-lived mesoscale convective systems (LLCSs) over the La Plata basin. By classifying SACZ events into distinct continental and oceanic categories and building a logistic regression model that relates LLCS activity across the region to continental and oceanic SACZ precipitation, a detailed account of spatial variability in the out-of-phase coupling between the SACZ and large-scale organized convection over the La Plata basin is provided. Enhanced precipitation in the continental SACZ is found to result in increased LLCS activity over northern, northeastern, and western sections of the La Plata basin, in association with poleward atmospheric moisture flux from the Amazon basin toward these regions, and a decrease in the probability of LLCS occurrence over the southeastern La Plata basin. Increased oceanic SACZ precipitation, however, was strongly related to reduced atmospheric moisture and decreased probability of LLCS occurrence over nearly the entire La Plata basin. These results suggest that continental SACZ activity and large-scale organized convection over the northern and eastern sections of the La Plata basin are closely tied to atmospheric moisture transport from the Amazon basin, while the warm coastal Brazil Current may also play an important role as an evaporative moisture source for LLCSs over the central and western La Plata basin. [ABSTRACT FROM AUTHOR]

The Atlantic Intertropical Convergence Zone (A-ITCZ) exhibits variations on several time-scales and plays a crucial role in precipitation regimes of northern South America and western Africa. Here we investigate the variability of the A-ITCZ on intraseasonal time-scales during austral summer (November-March) and winter (May-September) based on a multivariate index that describes the main atmospheric features of the A-ITCZ and retains its variability on interannual, semiannual, and intraseasonal time-scales. This index is the time coefficient of the first combined empirical orthogonal function mode of anomalies (annual cycle removed) of precipitation, and zonal and meridional wind components at 850 hPa from the climate forecast system reanalysis (1979-2010). We examine associations between the intraseasonal variability of the A-ITCZ and the activity of the Madden-Julian oscillation (MJO). We show that during austral summer intraseasonal variability of the A-ITCZ is associated with a Rossby wave train in the Northern Hemisphere. In austral winter this variability is associated with the propagation of a Rossby wave in the Southern Hemisphere consistent with the Pacific-South American pattern. Moreover, we show that intense A-ITCZ events on intraseasonal time-scales are more frequent during the phase of MJO characterized by convection over western Pacific and suppression over the Indian Ocean. These teleconnection patterns induce anomalies in the trade winds and upper level divergence over the equatorial Atlantic that modulate the intensity of the A-ITCZ. [ABSTRACT FROM AUTHOR]

Impacts of the main South American orographic structures (the Andes, the Brazilian Plateau and the Guiana shield) on the regional climate and associated global teleconnection are investigated through numerical experiments in which some of these features are suppressed. Simulations are performed with a ''two-way nesting'' system coupling interactively the regional and global versions of the LMDZ4 atmospheric general circulation model. At regional scale, the simulations confirm previous studies, showing that both the Andes and the Brazilian Plateau exert a control on the position and strength of the South Atlantic convergence zone (SACZ), mainly through their impact on the low-level jet and the coastal branch of the subtropical anticyclones. The northern topography of South America appears to be crucial to determine the leading mode of rainfall variability in eastern South America, which manifests itself as a dipole-like pattern between Southeastern South America and the SACZ region. The suppression of South America orography also shows global-scale effects, corresponding to an adjustment of the global circulation system. Changes in atmospheric circulation and precipitation are found in remote areas on the globe, being the consequences of various teleconnection mechanisms. When the Brazilian Plateau and the Andes are suppressed, there is a decrease of precipitation in the SACZ region, associated with a weakening of the large-scale ascendance. Changes are described in terms of anomalies in the Walker circulation, meridional displacements of the mid-latitude jet stream, Southern annular mode anomalies and modifications of Rossby wave train teleconnection processes. [ABSTRACT FROM AUTHOR]

The regional influence of the Madden-Julian oscillation (MJO) on South America is described. Maps of probability of weekly-averaged rainfall exceeding the upper tercile were computed for all seasons and related statistically with the phase of the MJO as characterized by the Wheeler-Hendon real-time multivariate MJO (RMM) index and with the OLR MJO Index. The accompanying surface air temperature and circulation anomalies were also calculated. The influence of the MJO on regional scales along with their marked seasonal variations was documented. During December-February when the South American monsoon system is active, chances of enhanced rainfall are observed in southeastern South America (SESA) region mainly during RMM phases 3 and 4, accompanied by cold anomalies in the extratropics, while enhanced rainfall in the South Atlantic Convergence Zone (SACZ) region is observed in phases 8 and 1. The SESA (SACZ) signal is characterized by upper-level convergence (divergence) over tropical South America and a cyclonic (anticyclonic) anomaly near the southern tip of the continent. Impacts during March-May are similar, but attenuated in the extratropics. Conversely, in June-November, reduced rainfall and cold anomalies are observed near the coast of the SACZ region during phases 4 and 5, favored by upper-level convergence over tropical South America and an anticyclonic anomaly over southern South America. In September-November, enhanced rainfall and upper-level divergence are observed in the SACZ region during phases 7 and 8. These signals are generated primarily through the propagation of Rossby wave energy generated in the region of anomalous heating associated with the MJO. [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]

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]

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 dominant mode of coupled variability over the South Atlantic Ocean is known as 'South Atlantic Dipole' (SAD) and is characterized by a dipole in sea surface temperature (SST) anomalies with centers over the tropical and the extratropical South Atlantic. Previous studies have shown that variations in SST related to SAD modulate large-scale patterns of precipitation over the Atlantic Ocean. Here we show that variations in the South Atlantic SST are associated with changes in daily precipitation over eastern South America. Rain gauge precipitation, satellite derived sea surface temperature and reanalysis data are used to investigate the variability of the subtropical and tropical South Atlantic and impacts on precipitation. SAD phases are assessed by performing Singular value decomposition analysis of sea level pressure and SST anomalies. We show that during neutral El Niño Southern Oscillation events, SAD plays an important role in modulating cyclogenesis and the characteristics of the South Atlantic Convergence Zone. Positive SST anomalies over the extratropical South Atlantic (SAD negative phase) are related to increased cyclogenesis near southeast Brazil as well as the migration of extratropical cyclones further north. As a consequence, these systems organize convection and increase precipitation over eastern South America. [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]

This work focuses on the evaluation of different sources of uncertainty affecting regional climate simulations over South America at the seasonal scale, using the MM5 model. The simulations cover a 3-month period for the austral spring season. Several four-member ensembles were performed in order to quantify the uncertainty due to: the internal variability; the definition of the regional model domain; the choice of physical parameterizations and the selection of physical parameters within a particular cumulus scheme. The uncertainty was measured by means of the spread among individual members of each ensemble during the integration period. Results show that the internal variability, triggered by differences in the initial conditions, represents the lowest level of uncertainty for every variable analyzed. The geographic distribution of the spread among ensemble members depends on the variable: for precipitation and temperature the largest spread is found over tropical South America while for the mean sea level pressure the largest spread is located over the southeastern Atlantic Ocean, where large synoptic-scale activity occurs. Using nudging techniques to ingest the boundary conditions reduces dramatically the internal variability. The uncertainty due to the domain choice displays a similar spatial pattern compared with the internal variability, except for the mean sea level pressure field, though its magnitude is larger all over the model domain for every variable. The largest spread among ensemble members is found for the ensemble in which different combinations of physical parameterizations are selected. The perturbed physics ensemble produces a level of uncertainty slightly larger than the internal variability. This study suggests that no matter what the source of uncertainty is, the geographical distribution of the spread among members of the ensembles is invariant, particularly for precipitation and temperature. [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 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]

Daily precipitation data from three stations in subtropical Argentina are used to describe intraseasonal variability (20–90 days) during the austral summer. This variability is compared locally and regionally with that present in outgoing longwave radiation (OLR) data, in order to evaluate the performance of this variable as a proxy for convection in the region. The influence of the intraseasonal activity of the South American Seesaw (SASS) leading convection pattern on precipitation is also explored. Results show that intraseasonal variability explains a significant portion of summer precipitation variance, with a clear maximum in the vicinity of the SASS subtropical center. Correlation analysis reveals that OLR can explain only a small portion of daily precipitation variability, implying that it does not constitute a proper proxy for precipitation on daily timescales. On intraseasonal timescales, though, OLR is able to reproduce the main features of precipitation variability. The dynamical conditions that promote the development of intraseasonal variability in the region are further analyzed for selected summers. Seasons associated with a strong intraseasonal signal in precipitation variability show distinctive wet/dry intraseasonal periods in daily raw data, and are associated with a well defined SASS-like spatial pattern of convection. During these summers, strong large-scale forcing (such as warm El Niño/Southern Oscillation (ENSO) events and/or tropical intraseasonal convective activity), and Rossby-wave-like circulation anomalies extending across the Pacific Ocean, are also observed. [ABSTRACT FROM AUTHOR]

The Paraná-Plata basin is the second largest hydrological basin in South America and is of great importance for the countries of the region (Argentina, Bolivia, Brazil, Paraguay and Uruguay). The present study focuses on the long-term trends in basin-scale precipitation with special emphasis on the role of distribution changes in extreme large-scale precipitation events and on the characteristics and evolution of ENSO teleconnections over the last 50 years. First, we defined a Paraná-Plata basin total precipitation index (PTPI) as the precipitations spatially averaged over the hydrological basin. On interannual time scales, such an index is mainly representative of anomalous monsoon precipitations in the northern part of the basin and large convective precipitation anomalies in the center of the basin (Paraguay-southern Brazil-Uruguay-northern Argentina) typical of the canonical ENSO teleconnection pattern. Our major findings clearly highlight a positive trend in yearly averaged PTPI mainly from the late 1960s to the early 1980s with a strong dependence from month-to-month. The largest precipitation increase is observed from November to May in southern Brazil and Argentina. A close examination of PTPI distributions during the two halves of the period 1950-2001 shows that the changes in the mean state from 1950-1975 to 1976-2001 result from significant changes in each calendar month mean state and in the tails of the PTPI anomaly distributions in May with lesser and weaker large-scale dry events and stronger large-scale wet events. Further studies will be needed to assess whether the observed trend in large-scale extreme precipitation conditions can be related to natural climate variability or anthropogenic activities and whether it is associated to changes in local/regional extreme events. The stronger wet conditions in different months seem to be associated to changes in ENSO characteristics (amplitude, propagation, spatial structure, ...) since the 1982-1983 El Niño. Indeed, spatial ENSO teleconnections (stronger in November and April-May) have greatly evolved from 1950-1975 to 1976-2001. Moreover, we demonstrate that there is a strong modulation and displacement of the teleconnection patterns from one event to another, impeding the definition of robust statistical relationship between ENSO and precipitation in the Paraná-Plata basin (except maybe over a very limited area near the common border between Paraguay, Argentina and Brazil). Finally, the non-antisymmetrical patterns of precipitation between El Niño and La Niña conditions and the non-linear relationship between precipitation and either Niño3.4 or Niño1+2 sea surface temperature indices show that linear statistical forecast systems are actually of very limited use for impact predictions on society on a local or regional scale. [ABSTRACT FROM AUTHOR]

We classified 34 years of winter daily 500 hPa geopotential height patterns over the eastern South Pacific-South America-South Atlantic region using the K-means clustering method. We found a significant classification into five weather regimes (WRs) defined as the most frequent large-scale circulation anomalies: WR1 (trough centred downstream of the Drake Passage), WR2 (trough over the SW Pacific and ridge downstream), WR3 (ridge over the SE Pacific and NW–SE trough downstream), WR4 (trough over the SE Pacific and NW–SE ridge downstream) and WR5 (weak ridge to the west of southern South America). We also analysed their persistence and temporal evolution, including transitions between them and development around onsets and breaks of each regime. The preferred transitions, WR1→WR3→WR2→WR4→WR1 and also WR1→WR3→WR2→WR1, suggest the progression of a Rossby wave-like pattern in which each of the regimes resemble the Pacific-South America modes. Significant influence of the WRs on local climate over Argentina was found. The preferred transitions WR1→WR3 and WR3→WR2 induce sustained cold conditions over Patagonia and over northern Argentina, respectively. The most significant change in precipitation frequency is found for WR3, with wetter conditions over all the analysed regions. Finally, the interannual to interdecadal significant variations in the occurrence of these regimes were discussed. WR1 and WR3 are more frequent and WR2 is less frequent during El Niño, and WR2 and WR5 are more frequent and WR1 is less frequent during La Niña. A significant decrease in WR2 and increase of WR4 and WR5 during the 1970s and early 1980s were found. [ABSTRACT FROM AUTHOR]