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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]

A characterization of the diurnal cycle of precipitation (DCP) over the whole South America is still lacking in the literature and the scarcity of sub‐daily rain ground measurements limits the data available for analysis and forbids a correct validation of alternative datasets. In this paper we analyse the climatological mean DCP during the monsoon active season using five gridded datasets: two satellite precipitation estimates, two regional climate models and one reanalysis. Amazonia, the Brazilian Highlands, the northeastern South American coast, the Andes and the western Colombian coast are identified as the areas with most prominent DCPs. The afternoon convection triggered by solar heating over land and the coastal and topographic effects are the main modes of sub‐daily variability, based on an EOF decomposition of the 3 hourly mean precipitation fields. We explore the contribution of mean frequency and intensity to amount of precipitation and nighttime–daytime differences. In general, both models precipitate earlier and more frequently than the satellite products and do not reproduce correctly areas of observed predominant nighttime precipitation where mesoscale convective systems are active, like La Plata Basin or Amazonia. Over the analysed areas, the high frequency of precipitation is the driving mechanism of total amount in the models, whereas in the satellite products there is also considerable contribution from intensity. Overall, the reanalysis shows features in between the models and the satellite estimates, sharing characteristics with both types of data. The results presented here point at the diversity of sub‐daily precipitation characteristics in South America, the issues with conventional climate models and the uncertainty in satellite products and reanalyses. The growing interest in the DCP by the scientific community and the development of new techniques like convection permitting modelling will hopefully continue to improve our knowledge of the precipitation dynamics and its influence on climate. [ABSTRACT FROM AUTHOR]

The Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset was conceived as a tool for monitoring drought and environmental change over land. Recent validation efforts along South America have assessed its suitability for reproducing the main spatial and temporal features of precipitation. Nevertheless, little has been done regarding the ability of CHIRPS for the assessment of wet and dry conditions, particularly in areas where in situ precipitation records are scarce. In this paper, we investigated the performance of CHIRPS for monitoring wet and dry events along the semiarid Central-Western Argentina. Using the Standardized Precipitation Index (SPI), we compared the CHIRPS database with records from 49 meteorological stations along the study area for the period 1987–2016. Results indicate that the CHIRPS dataset adequately reproduced the temporal variability of SPI on multiple timescales (1 month, 3 months, and 6 months), particularly in the region dominated by warm season precipitation. The large overestimation of the seasonal precipitation in the region dominated by cold season precipitation can introduce errors that are reflected in the performance of CHIRPS over the western portion of the domain. The frequency of wet and dry classes was accurately reproduced by CHIRPS on timescales larger than 1 month (SPI1), given the existence of a wet bias that produces an underestimation of the frequency of zero values. This bias is further translated to the evaluation of the SPI1 during the spatial and temporal assessment of historical dry (1998) and wet (2016) events, especially for the classification of extreme dry/wet months. The results from the evaluation indicate that CHIRPS is a suitable tool for assessing dry and wet conditions for timescales longer than 1 month and can support decision-making process within the hydrometeorological agencies over the region. [ABSTRACT FROM AUTHOR]

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

ABSTRACT It is known that the El Niño - Southern Oscillation ( ENSO) episodes have a great influence on South American precipitation and its extreme events during austral autumn (from March until May, MAM) and winter (from June until August, JJA) that occur after the ENSO peak (normally this happens on austral summer). Recent papers have studied the two types of ENSO and their influence on atmosphere-ocean system. This study analysed the influence of Central and East equatorial Pacific ENSO on South American seasonal/monthly mean precipitation and its extreme events during MAM and JJA. The composites of precipitation anomalies, during these two types of ENSO, show that there are different, even opposite patterns over South America. In MAM, there is an increased precipitation in southeastern South America and a decrease in the northeast South America during East El Niño ( EEN) and an increased precipitation in central Brazil during Central El Niño ( CEN). In JJA, the signs of anomaly precipitation are opposite between CEN (less precipitation) and EEN (more precipitation) over southeastern South America. The extreme precipitation events show patterns consistent with the precipitation anomaly patterns, but, normally, the changes in the frequency of extremes precipitation events affect more extensive areas than the total precipitation. If monthly or seasonal atmospheric anomalies in a certain region during one of the types of ENSO are similar (opposite) to the atmospheric anomalies associated with extreme precipitation events in this region, then there is enhancement (suppression) of the frequency of extreme events in this region during this type of ENSO. [ABSTRACT FROM AUTHOR]

This paper describes a comprehensive assessment of a new high-resolution, gauge–satellite-based analysis of daily precipitation over continental South America during 2004. This methodology is based on a combination of additive and multiplicative bias correction schemes to get the lowest bias when compared with the observed values (rain gauges). Intercomparisons and cross-validation tests have been carried out between independent rain gauges and different merging techniques. This validation process was done for the control algorithm [Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis real-time algorithm] and five different merging schemes: additive bias correction; ratio bias correction; TRMM Multisatellite Precipitation Analysis, research version; and the combined scheme proposed in this paper. These methodologies were tested for different months belonging to different seasons and for different network densities. All compared, merging schemes produce better results than the control algorithm; however, when finer temporal (daily) and spatial scale (regional networks) gauge datasets are included in the analysis, the improvement is remarkable. The combined scheme consistently presents the best performance among the five techniques tested in this paper. This is also true when a degraded daily gauge network is used instead of a full dataset. This technique appears to be a suitable tool to produce real-time, high-resolution, gauge- and satellite-based analyses of daily precipitation over land in regional domains. [ABSTRACT FROM AUTHOR]

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

The physical mechanisms and predictability associated with extreme daily rainfall in southeastern South America (SESA) are investigated for the December-February season in a two-part study. Through a k-mean analysis, this first paper identifies a robust set of daily circulation regimes that are used to link the frequency of rainfall extreme events with large-scale potential predictors at subseasonal-to-seasonal scales. This represents a basic set of daily circulation regimes related to the continental and oceanic phases of the South Atlantic convergence zone (SACZ) and wave train patterns superimposed on the Southern Hemisphere polar jet. Some of these recurrent synoptic circulation types are conducive to extreme rainfall events in the region through synoptic control of different mesoscale physical features and, at the same time, are influenced by climate phenomena that could be used as sources of potential predictability. Extremely high rainfall (as measured by the 95th and 99th percentiles) is associated with two of these weather types (WTs), which are characterized by moisture advection intrusions from lower latitudes and the Pacific Ocean; another three WTs, characterized by above-normal moisture advection toward lower latitudes or the Andes, are associated with dry days (days with no rain). The analysis permits the identification of several subseasonal-to-seasonal scale potential predictors that modulate the occurrence of circulation regimes conducive to extreme rainfall events in SESA. It is conjectured that a cross-time scale interaction between the different climate drivers improves the predictive skill of extreme precipitation in the region. [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]

Abstract: The prevailing view in the palaeoclimate literature of the last 20 years is that the Southern Westerly Winds (SWW) were intensified over southern Australia and Tasmania during the warmer-than-present early Holocene (11–8ka). At similar latitudes on the opposite side of the southern mid-latitudes, palaeoclimate studies have suggested a poleward shift of the northern edge of the westerlies and focusing at 49°S in southern South America. This zonal asymmetry contrasts with the modern day zonal symmetry displayed by the SWW and poses a formidable challenge to an understanding of the modes of climatic variability of the southern extra-tropics. This paper presents an updated synthesis of continuous, radiocarbon-dated palaeoenvironmental data from the westerlies zone of influence in all Southern Hemisphere continents. Synchronous multi-millennial trends in moisture, vegetation, fire, and hydrologic balance are remarkably consistent with the way the SWW changes impact upon the climate in Southern Hemisphere landmasses in the modern climate. Considering the modern relationships between local precipitation and zonal wind speeds, it is suggested that the SWW changed in a zonally symmetric manner at multi-millennial scale between 14 and 5ka. Regional asymmetry develops after 5ka across the Southern Hemisphere, with a pattern of precipitation anomalies akin to the modern functioning of El Niño – Southern Oscillation, which started ∼6200 years ago. [Copyright &y& Elsevier]

Abstract: Conventional surface data and quantitative estimations of precipitation are used to document the occurrence and spatial distribution of severe weather phenomena associated with deep moist convection over southeastern South America. Data used in this paper are 24-hour rainfall, maximum hourly gusts and present weather reports from the surface station network for Argentina to the north of 40°S and cover the period 2000–2005. Hourly rainfall estimated with the CMORPH technique (CPC MORPHing technique, R. J. Joyce et al., 2004) is included in the analysis in order to increase the density of the precipitation database from January 2003 to December 2005. Extreme events are detected by means of a 95th-percentile analysis of the 24-hour rainfall and wind; values greater than 30mm and 25ms−1 respectively are considered extreme in the study area. These results are related to the presence of deep convection by considering the 235K and 218K cloud shield evolution in Geostationary Operational Environmental Satellite-12 Infrared (GOES-IR) imagery evaluated by the Forecasting and Tracking of Cloud Cluster (FORTRACC) technique. Rainfall above 30mmday−1 and present convection-related weather events tend to occur in the northeast of the country. Finally, an analysis is made of the relationship between severe phenomena and the location and lifecycle of Mesoscale Convective Systems (MCSs) defined by the 218K or 235K levels. According to the reports, favorable locations for severe weather concentrate to the northeast of the cloud shield anvil centroid although most of the cases are found in the northwest. This feature can be seen in systems with anvil areas larger than 250,000km2 in association to the predominant mid-level wind shear direction from the northwest over the area. Moreover, systems with centers located north of 30°S present a more circular shape while those to the south are more elongated with a NW–SE main axis clearly related to the presence and interaction with frontal zones over the area. Most of the events occur previous to the moment when the systems reach their maximum extension, between 2 and 10h after the initiation of the system depending on the size of the MCSs. [Copyright &y& Elsevier]

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]

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

The objective of this research is to explore the relationship between maximum and minimum temperatures, daily precipitation, and the Madden–Julian oscillation (MJO). It was found that the different phases of the MJO show a consistent signal on winter temperature variability and precipitation in southeastern South America. Additionally, this paper explores the spatial–temporal variations of mutual information and joint entropy between temperature and the MJO. A defined spatial pattern was observed with an increased signal in northeastern Argentina and southern Brazil. In the local mutual information analysis, periods in which the mutual information doubled the average values were observed over the entire region. These results indicate that these connections can be used to forecast winter temperatures with a better skill score in situations where both variables covary. [ABSTRACT FROM AUTHOR]

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

A simulation of the stable water isotope cycle over South America by the regional circulation model REMOiso is discussed. The performance of the regional model, with a resolution of 0.5° (∼55 km), is compared to simulations by the global circulation model ECHAMiso at two coarser resolutions and evaluated against observations of precipitation and δ18O. Here REMOiso is demonstrated to reproduce reasonably well climatic and isotopic features across South America. This paper explores further insights of δ18O as a climate proxy, based on REMOiso’s improvements as compared to ECHAMiso. In particular, the authors focus on the seasonal variation of the amount effect (δ18O decrease with precipitation amounts) and the anomalous δ18O continental gradient across the Amazon basin, as inferred from the REMOiso, ECHAMiso, and GNIP datasets. The finer resolution of topography in REMOiso enables a detailed analysis of the altitude effect: not only the first, but also the second derivative of δ18O with altitude is considered. It appears that high-altitude grid cells show an isotopic signature similar to Rayleigh distillation, in accordance with experimental studies. Finally, a Lagrangian reference frame is adopted to describe the evolution of δ18O in precipitation along its trajectory, in order to relate the simulation analysis to the fractionation mechanisms. This confirms that the amount effect, via Rayleigh distillation processes, is dominant during the wet season. During the dry season, the δ18O in precipitation is controlled by isotopic reequilibration of rain droplets with surrounding vapor, reflecting the impact of nonfractionating transpiration by the vegetation. [ABSTRACT FROM AUTHOR]

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

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

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

Deep convection in the Tunuyán Valley region (33°–34°S, 69°–70°W) on the eastern side of the highest peaks of the Andes Mountains is sometimes associated with damaging hail. Understanding the physical mechanisms responsible for the occurrence of deep convection in that region is therefore a central part of the development of hail suppression projects. In this paper, a case of deep convection that occurred on 22 January 2001 is studied in detail through a combined analysis of radar, satellite, and radiosonde data and numerical simulations using a nonhydrostatic mesoscale atmospheric (Meso-NH) model. The time evolution and stability characteristics are first documented using the data. In order to get insight into the main causes for the deep convection event, numerical simulations of that day were performed. These results are compared with the results corresponding to conditions of 4 January 2001 when no deep convection occurred. The comparison between the 2 days strongly suggests that the deep convection event occurred because of the simultaneous presence of anabatic winds, accumulation of moist enthalpy, and the stability conditions. The present results should be helpful in designing future observational programs in the region. [ABSTRACT FROM AUTHOR]

Transient incursions of midlatitude air to the east of the Andes Mountains into subtropical and tropical latitudes are a distinctive feature of the synoptic climatology over South America. The mean synoptic-scale structure of these incursions is documented in this paper on the basis of a compositing analysis of NCEP--NCAR reanalyzed meteorological fields and satellite-based outgoing longwave radiation measurements. Although these incursions are a year-round phenomenon, with relatively modest seasonal changes in their structure, this analysis is focused on the austral summer, when they have their largest impact in the precipitation field. The summertime incursions move equatorward at a mean speed of 10 m s 21 and retain their identities over intervals of about 5 days. The upper-level circulation is characterized by a midlatitude trough--ridge couplet that provides the quasigeostrophic forcing of the system. Before the onset of the incursions of midlatitude air, the approaching upper-level trough tends to deepen the semipermanent area of low pressure over the central plains of the continent (25°--10°S). The strong southward advection of warm, humid air creates favorable conditions for the development of deep convection over central and southern Argentina. During the next two days, a migratory cold anticyclone, steered by the ridge aloft, moves onto the southern plains of South America (40°-- 35°S), establishing a large-scale, southward-directed pressure gradient. Due to the blocking effect of the Andes, the induced low-level circulation assumes the form of an agesotrophic southerly flow that produces the equa-torward advection of the cold air. In this stage, enhanced convection occurs in a well-defined band of the intensified low-level convergence at the leading edge of the cold surge. This synoptic-scale banded structure in the convective cloudiness also emerges as the dominant mode of the day-to-day variability of the deep... [ABSTRACT FROM AUTHOR]

Thunderstorms in southeastern South America (SESA) stand out in satellite observations as being among the strongest on Earth in terms of satellite-based convective proxies, such as lightning flash rate per storm, the prevalence for extremely tall, wide convective cores and broad stratiform regions. Accurately quantifying when and where strong convection is initiated presents great interest in operational forecasting and convective system process studies due to the relationship between convective storms and severe weather phenomena. This paper generates a novel methodology to determine convective initiation (CI) signatures associated with extreme convective systems, including extreme events. Based on the well-established area-overlapping technique, an adaptive brightness temperature threshold for identification and backward tracking with infrared data is introduced in order to better identify areas of deep convection associated with and embedded within larger cloud clusters. This is particularly important over SESA because ground-based weather radar observations are currently limited to particular areas. Extreme rain precipitation features (ERPFs) from Tropical Rainfall Measurement Mission are examined to quantify the full satellite-observed life cycle of extreme convective events, although this technique allows examination of other intense convection proxies such as the identification of overshooting tops. CI annual and diurnal cycles are analyzed and distinctive behaviors are observed for different regions over SESA. It is found that near principal mountain barriers, a bimodal diurnal CI distribution is observed denoting the existence of multiple CI triggers, while convective initiation over flat terrain has a maximum frequency in the afternoon. [ABSTRACT FROM AUTHOR]