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

The rise in the Earth's global average surface temperature and the increase of extreme weather events have been the focus of scientific discussion in the last decades. Extreme heat combined with other environmental extremes, like high concentrations of air pollution, may induce health problems—especially in socioeconomically vulnerable populations. Spring in South America requires particular attention due to its association with hot, dry weather and air pollution in most parts of the continent. This paper intends to better comprehend the behaviour of heatwaves during the austral winter–spring transition. We propose identifying the spatial coverage, frequency and intensity of heatwaves in homogeneous areas of maximum air temperature near the surface (Tmax). We employed cluster analyses during the period between July and October for 41 years (1979–2019) through the ERA5 reanalysis. Homogeneous Tmax areas in South America were defined by cluster analyses that indicated three homogeneous Tmax regions, as follows: a larger area of the continent including the tropical region (Area 1), eastern and southeastern South America (Area 2) and southernmost and steep areas in the Andes (Area 3). The heatwave events identified via ERA5 reanalysis were classified according to their intensity (intense, moderate and weak events). Spatial frequency and trend analyses were also performed regarding the intensity and persistence of heatwave episodes. These methods allowed the identification of the behavioural aspect of heatwaves spanning the last four decades. The Mann–Kendall statistical test (MK) was applied in order to analyse the heatwave trend with a statistical significance level of 5%. A total of 191 heatwave episodes were identified. Of this total, 47.12, 35.60 and 17.28% of episodes occurred in Areas 2, 3 and 1, respectively. The hotter area extending from northeast to southwest in central South America stood out by its largest frequencies of intense heatwave episodes. Across the continent there was a significant increase in the intensity and persistence of heatwaves over the period of 1979 through to 2019. [ABSTRACT FROM AUTHOR]

Climate change impacts are already happening through the world, and it is now clear that there is the need for an adaptive response from global institutions down to the local level. Reducing vulnerability to cope with climate variability might be more challenging in tropical countries than in North America or Europe. The ten papers of this special issue were presented during the Adaptclim conference that was held by the Sinergia Project, the CLARIS LPB project, and the GeoData Institute in Asunción, Paraguay, in 2010. All papers, except one regarding the Brahmaputra Basin in South Asia, present studies from South America. These studies are first contextualized geographically and then are related one to another by a simplified vulnerability concept linking climate stress to sensitivity and adaptive capacity of natural and human systems. One half of the papers focus on actual or future climate change and the present-day causes of the vulnerability of natural and agrosystems. Droughts are and will be the main source of stress for agriculture in South America. Increasing fragmentation of forest of the center of this continent is aggravating their vulnerability to dry spells. Another half of the studies of this special issue deal with the adaptive capacity human populations to system perturbations produced or enhanced by climate change. The studies point out inclusion of traditional knowledge and involvement of local actors in their own vulnerability assessment to increase adaptive capacity. These elements of climate justice, giving voice to those less responsible for carbon emissions but bearing their most severe consequences, allow the particular needs of a community to be considered and can direct adaptation policy toward preserving or rebuilding their specific capabilities under threat from climate change. The special issue also made clear that a basin analysis of the climate change problem could provide information, results, and methods more readily of use for the local population and decision makers. [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]

Copyright of Anuario do Instituto de Geociencias is the property of Universidade Federal do Rio de Janeiro, Instituto de Geociencias and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Andes as mountain regions worldwide, provide fundamental resources, not only for the local population. Due to the topographic characteristics, the potential for natural hazards is higher than elsewhere. In these areas, assessments of climate change impacts and the development of adequate adaptation strategies therefore become particular important. The data basis, however, is often scarce. Moreover, perceptions of changes and needs are often divergent between national and local levels, which make the implementation of adaptation measures a challenge. Taking the Peruvian Andes as an example, this paper aims at initiating a discussion about scientific baseline and integrative concepts needed to deal with the adverse effects of climate change in mountain regions. [ABSTRACT FROM AUTHOR]

Abstract: Several regions of the world have developed capability in providing services on climate information for risk management, but there are still gaps in service delivery due to inadequate information regarding the needs within the regions. This paper highlights the role of Regional Climate Outlook Forums, assesses the needs for some regions and extracts examples of how regional associations could benefit through the provision of better climate services. Problems are given for Africa, South-East Asia, South America, the Pacific and Europe. Different geographical climate features lead to different climate phenomena and in turn determine the type of climate delivery needs for risk management. Short discussions of regional socio-economic factors that shape the needs for climate information provide further context for the unique character of delivery services. Recommendations and future plans follow this assessment. [ABSTRACT FROM AUTHOR]

The purpose of this study is to assess the ability of a set of large ensembles (LE) of Global Climate Model (GCM) simulations from the Multi‐Model Large Ensemble Archive, Coupled Model Intercomparison Project Phase 6 (CMIP6) and database for Policy Decision making for Future climate change in reproducing the variability and change of the austral summer precipitation observed in South America along the second part of the 20th century and beginning of the 21st. LE show similar biases in the mean austral summer rainfall and interannual variability than those detected in previous model sets, such as the Coupled Model Intercomparison Project Phase 5 (CMIP5). The positive trends in south‐eastern South America (SESA) and negative ones in the southern Andes (SAn), that are the most significant observed regional features, are identified to some extent in LE simulations. The negative trend in SAn is a feature consistently shown among different models. For all models, mean trend is negative in that particular region and larger than the inter‐member dispersion for each large ensemble. Trend magnitudes in the SESA region show a larger dispersion between models than the SAn region. While the mean trend among models is consistent with the observations, models underestimate the observed trend. The multi‐model ensemble of selected models that best reproduce both mean and interannual variability features of rainfall in South America shows an 18% larger positive mean trend in SESA rainfall than those that have the worst performance. However, internal variability uncertainty is still higher than the mean trend for both sets of multi‐model ensembles [5% (18%) for selected (non‐selected) models]. Improvements in the representation of the main features of mean rainfall and variability are needed in order to better describe and reduce the uncertainties associated with the main climate change related signals in the continent. [ABSTRACT FROM AUTHOR]

The Cenozoic climate of tropical South America was fundamental to the development of its biota, the most biodiverse on Earth. No previous studies have explicitly addressed how the very different atmospheric composition and Atlantic geometry during the early Eocene (approximately 55 million years ago) may have affected South American climate. At that time, the Atlantic Ocean was approximately half of its current width and the CO2 concentration of Earth's atmosphere ranged from ~550 to ~1500 ppm or even higher. Climate model simulations were performed to examine the effects of these major state changes on the climate of tropical South America. Reducing the width of the Atlantic by approximately half produces significant drying relative to modern climate. Drying is only partly offset by an enhancement of precipitation due to the higher CO2 of the early Eocene. The main mechanism for drier conditions is simple. Low-level air crosses the tropical Atlantic from North Africa in much less time for a narrower Atlantic (2 days) than for the modern Atlantic (~6 days); as a result, much less water is evaporated into the air and thus there is far lower moisture imported to the continent in the Eocene simulation than in the modern control. The progressive wetting (during the mid- to late Cenozoic) of the Amazon due to the widening Atlantic and the rising Andes, only partly offset by decreasing CO2 values, may have been partly responsible for the accumulating biodiversity of this region. [ABSTRACT FROM AUTHOR]

The South Pacific Subtropical High (SPSH) is a predominant feature of the South American climate. The variability of this high-pressure center induces changes in the intensity of coastal alongshore winds and precipitation, among others, over southwestern South America. In recent decades, strengthening and expansion of the SPSH have been observed and attributed to the current global warming. These changes have led to an intensification of the southerly winds along the coast of northern to central Chile and a decrease in precipitation from central to southern Chile. Motivated by improving our understanding about the regional impacts of climate change in this part of the Southern Hemisphere, we analyzed SPSH changes during the two most extreme climate events of the last millennium, the Little Ice Age (LIA) and the Current Warm Period (CWP: 1970–2000), based on paleoclimate records and CMIP5/PMIP3 model simulations. In order to assess the level of agreement of general circulation models, we also compare them with ERA-Interim reanalysis data for the 1979–2009 period as a complementary analysis. Finally, with the aim of evaluating future SPSH behavior, we include 21st century projections under a Representative Concentration Pathway (RCP8.5) scenario in our analyses. Our results indicate that during the relative warm (cold) period, the SPSH expands (contracts). Together with this change, alongshore winds intensify (weaken) south (north) of ∼35 ∘ S; also, southern westerly winds become stronger (weaker) and shift southward (northward). Model results generally underestimate reanalysis data. These changes are in good agreement with paleoclimate records, which suggest that these variations could be related to tropical climate dynamics but also to extratropical phenomena. However, although models adequately represent most of the South American climate changes, they fail to represent the Intertropical Convergence Zone–Hadley cell system dynamics, emphasizing the importance of improving tropical system dynamics in simulations for a better understanding of its effects on South America. Climate model projections indicate that changes recently observed will continue during the next decades, highlighting the need to establish effective mitigation and adaptation strategies against their environmental and socioeconomic impacts. [ABSTRACT FROM AUTHOR]

In this work we analyze potential environmental drivers of malaria cases in Northwestern Argentina. We inspect causal links between malaria and climatic variables by means of the convergent cross mapping technique, which provides a causality criterion from the theory of dynamic systems. Analysis is based on 12 years of weekly malaria P. vivax cases in Tartagal, Salta, Argentina—at the southern fringe of malaria incidence in the Americas—together with humidity and temperature time-series spanning the same period. Our results show that there are causal links between malaria cases and both maximum temperature, with a delay of five weeks, and minimum temperature, with delays of zero and twenty two weeks. Humidity is also a driver of malaria cases, with thirteen weeks delay between cause and effect. Furthermore we also determined the sign and strength of the effects. Temperature has always a positive non-linear effect on cases, with maximum temperature effects more pronounced above 25°C and minimum above 17°C, while effects of humidity are more intricate: maximum humidity above 85% has a negative effect, whereas minimum humidity has a positive effect on cases. These results might be signaling processes operating at short (below 5 weeks) and long (over 12 weeks) time delays, corresponding to effects related to parasite cycle and mosquito population dynamics respectively. The non-linearities found for the strength of the effect of temperature on malaria cases make warmer areas more prone to higher increases in the disease incidence. Moreover, our results indicate that an increase of extreme weather events could enhance the risks of malaria spreading and re-emergence beyond the current distribution. Both situations, warmer climate and increase of extreme events, will be remarkably increased by the end of the century in this hot spot of climate change. [ABSTRACT FROM AUTHOR]

Global climate change alters the dynamic of natural ecosystems and directly affects species distributions, persistence and diversity. The impacts of climate change may lead to dramatic changes in biotic interactions, such as pollination and seed dispersal. Life history traits are extremely important to consider the vulnerability of a species to climate change, producing more robust models than those based primarily on species distributions. Here, we hypothesized that rising temperatures and aridity will reduce suitable habitats for the endemic flora of the Caatinga, the most diverse dry tropical forest on Earth. Specifically, species with specialized reproductive traits (e.g. vertebrate pollination, biotic dispersal, obligatory cross-pollination) should be more affected by climate change than those with generalist traits. We performed two ecological niche models (current and future) to simulate the effects of climate change on the distribution area of endemic species in relation to life-history traits. We used the MIROC-ESM and CCSM4 models for both intermediate (RCP4.5) and highest predicted (RCP8.5) GHG emission scenarios, with a resolution of 30' (~1 km2). Habitat with high occurrence probability (>80%) of endemic species will be reduced (up to ~10% for trees, ~13% for non-arboreous, 10–28% for species with any pollination/reproductive system), with the greatest reductions for species with specialized reproductive traits. In addition, the likely concentration of endemic plants in the extreme northeastern portion of the Caatinga, in more mesic areas, coincides with the currently most human-modified areas of the ecosystem, which combined with climate change will further contract suitable habitats of endemic species. In conclusion, plant species endemic to the Caatinga are highly vulnerable to even conservative scenarios of future climate change and may lose much of their climatic envelopes. New protected areas should be located in the northeastern portion of the Caatinga, which hosts a more favorable climate, but is currently exposed to escalating agricultural intensification. [ABSTRACT FROM AUTHOR]

The bias correction of the General Circulation Model (GCM) outputs has become a routine step that is taken in climate change impact assessments. To responsibly support the decision‐making processes, the climate‐modeling community has been debating about the conceptual requirements that bias‐correction methods should fulfill. Bearing in mind these requirements, we propose to decompose atmospheric variables into three temporal elements that represent the climate mean state, the interannual variability, and the daily variability. This decomposition is aimed at correcting the biases at one time scale without affecting the simulated climate (mean state) trend or the distributional properties at other time scales. The novelty of the proposed approach is, nevertheless, marked by the adjustment of interannual and daily variability that is made by replacing the GCM‐simulated data with synthetic samples drawn from Stable Distributions (SDs) that are fitted to the observed variability. The replacement prevents the transfer of the sampling variability of the calibration period and gives the corrected data the distributional properties of the observed climate. The employment of SDs was motivated by the fact that the climate‐change‐induced changes in the scale, the symmetry, and the frequency of extremes can be measured and applied to the SDs of the observed data. We correct the biases in the GCM‐simulated temperature and precipitation over northern South America using our proposed approach and two other existing ones. Our proposed method is capable of not only preserving the simulated climate trends but also reproducing the observed extremes as well as a more flexible method based on nonparametric distributions. Key Points: We decompose GCM's daily time series into terms that represent the climate mean state, the interannual variability, and the daily variabilityWe replace the modeled daily variability using trend‐preserving synthetic samples that are drawn from stable distributionsThe mathematical properties of stable distributions allow the inclusion of simulated climate change in the correction process [ABSTRACT FROM AUTHOR]

When assessing the more pressing challenges of the Paris Agreement, four aspects become relevant. First, the lack of reliable sources and resources of climate finances-related information. Second, only developed countries' contributions are being accounted and disseminated. The omission of the resources invested by the developing world to combat climate change skews theoretical analysis, limits accuracy in policy, and has the potential to alienate the Global South against adopting climate policies. Third, loans represent a majority share of the climate finances and are swelling the debt of developing countries, especially in Latin America. Finally, Kyoto's leaves as legacy a governance model predominantly hierarchical both at general climate finances as well as in REDD+ in the three regions. The goal of this article is to draw a baseline on the quantity and quality of climate finances and specifically those of REDD+, a mechanism targeted at developing countries. There were three distinct stages to this review: (1) the assessment of 13,000 projects implemented in Asia, Africa, and Latin America between 2008 and 2015; (2) the assessment of 312 REDD+ initiatives implemented in the three regions in this period; and (3) the analysis of the governance model propelled by these transactions. Policy implications of the results presented in this article conclude this analysis. [ABSTRACT FROM AUTHOR]

Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Climatically similar native landcovers were aggregated using a decision tree, generating a reclassified landcover map, from which 25% of the map’s coverage was randomly selected to fuel distribution models. We selected the best geographical distribution models among twelve techniques, validating the predicted distribution for current climate with the landcover map and used the best technique to predict the future distribution. All landcover categories showed changes in area and displacement of the latitudinal/longitudinal centroid. Closed vegetation was the only landcover type predicted to expand its distributional range. The range contractions predicted for other categories were intense, even suggesting extirpation of the sparse vegetation category. The landcover refuges under future climate change represent a small proportion of the South American area and they are disproportionately represented and unevenly distributed, predominantly occupying five of 26 South American countries. The predicted changes, regardless of their direction and intensity, can put biodiversity at risk because they are expected to occur in the near future in terms of the temporal scales of ecological and evolutionary processes. Recognition of the threat of climate change allows more efficient conservation actions. [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]

An appraisal of Paleogene floral and land mammal faunal dynamics in South America suggests that both biotic elements responded at rate and extent generally comparable to that portrayed by the global climate pattern of the interval. A major difference in the South American record is the initial as well as subsequent much greater diversity of both Neotropical and Austral floras relative to North American counterparts. Conversely, the concurrent mammal faunas in South America did not match, much less exceed, the diversity seen to the north. It appears unlikely that this difference is solely due to the virtual absence of immigrants subsequent to the initial dispersal of mammals to South America, and cannot be explained solely by the different collecting histories of the two regions. Possible roles played by non-mammalian vertebrates in niche exploitation remain to be explored. The Paleogene floras of Patagonia and Chile show a climatic pattern that approximates that of North America, with an increase in both Mean Annual Temperature (MAT) and Mean Annual Precipitation (MAP) from the Paleocene into the Early Eocene Climatic Optimum (EECO), although the Paleocene-Eocene Thermal Maximum (PETM) is not recognized in the available data set. Post-EECO temperatures declined in both regions, but more so in the north than the south, which also retained a higher rate of precipitation. The South American Paleogene mammal faunas developed gradual, but distinct, changes in composition and diversity as the EECO was approached, but actually declined somewhat during its peak, contrary to the record in North America. At about 40 Ma, a post-EECO decline was recovered in both hemispheres, but the South American record achieved its greatest diversity then, rather than at the peak of the EECO as in the north. This post-EECO faunal turnover apparently was a response to the changing conditions when global climate was deteriorating toward the Oligocene. Under the progressively more temperate to seasonally arid conditions in South America, this turnover reflected a major change from the more archaic, and more tropical to subtropical-adapted mammals, to the beginning of the ultimately modern South American fauna, achieved completely by the Eocene-Oligocene transition. Interestingly, hypsodonty was achieved by South American cursorial mammals about 15-20 m.y. earlier than in North America. In addition to being composed of essentially different groups of mammals, those of the South American continent seem to have responded to the climatic changes associated with the ECCO and subsequent conditions in a pattern that was initially comparable to, but subsequently different from, their North American counterparts. [ABSTRACT FROM AUTHOR]

Copyright of Revista Iberoamericana de Ciencia, Tecnologia y Sociedad is the property of Centro de Estudios sobre Ciencia, Desarrollo y Educacion Superior and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

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]

BACKGROUND: Climate change is expected to have large impacts on health at low latitudes where droughts and malnutrition, diarrhea, and malaria are projected to increase OBJECTIVES: The main objective of this study was to indicate a method to assess a range of plausible health impacts of climate change while handling uncertainties in a unambiguous manner. We illustrate this method by quantifying the impacts of projected regional warming on diarrhea in this century. METHODS: We combined a range of linear regression coefficients to compute projections of future climate change-induced increases in diarrhea using the results from five empirical studies and a 19-member climate model ensemble for which future greenhouse gas emissions were prescribed. Six geographical regions were analyzed. RESULTS: The model ensemble projected temperature increases of up to 4°C over land in the tropics and subtropics by the end of this century. The associated mean projected increases of relative risk of diarrhea in the six study regions were 8-11% (with SDs of 3-5%) by 2010-2039 and 22-29% (SDs of 9-12%) by 2070-2099. CONCLUSIONS: Even our most conservative estimates indicate substantial impacts from climate change on the incidence of diarrhea. Nevertheless, our main conclusion is that large uncertainties are associated with future projections of diarrhea and climate change. We believe that these uncertainties can be attributed primarily to the sparsity of empirical climate-health data. Our results therefore highlight the need for empirical data in the cross section between climate and human health. [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]

The goal of the CLARIS project was to build an integrated European–South American network dedicated to promote common research strategies to observe and predict climate changes and their consequent socio-economic impacts taking into account the climate and societal peculiarities of South America. Reaching that goal placed the present network as a privileged advisor to contribute to the design of adaptation strategies in a region strongly affected by and dependent on climate variability (e.g. agriculture, health, hydro-electricity). Building the CLARIS network required fulfilling the following three objectives: (1) The first objective of CLARIS was to set up and favour the technical transfer and expertise in earth system and regional climate modelling between Europe and South America together with the providing of a list of climate data (observed and simulated) required for model validations; (2) The second objective of CLARIS was to facilitate the exchange of observed and simulated climate data between the climate research groups and to create a South American high-quality climate database for studies in extreme events and long-term climate trends; (3) Finally, the third objective of CLARIS was to strengthen the communication between climate researchers and stakeholders, and to demonstrate the feasibility of using climate information in the decision-making process. [ABSTRACT FROM AUTHOR]

A new version of ETA WS (workstation) forecast model destined for long-term climate change simulation (ETA CCS) was designed. Numerous modifications and corrections have been made in the original code of the ETA WS forecast model. As a first step in the ETA CCS validation program, we have integrated the model over South America with a horizontal resolution of 40 km for the period 1960–1990. We forced it at its lateral boundaries by the outputs of HadAM3P, which provides a simulation of modern climate with a resolution of about 150 km. The climate ETA model was run on the supercomputer SX-6. Here, we present and compare the output fields of the ETA model and HadAM3P and analyze the geopotential, temperature, and wind fields of both models. For evaluating the similarities of the model outputs, we used a Fourier analysis of time series, the consistency index from linear regression coefficients, the time mean and space mean models’ arithmetic difference and root mean square difference. The results of the study demonstrate that there are no significant differences in behavior and spatial arrangement of large-scale structures of the two models. In addition, the regional model characteristics do not have major positive or negative trends during the integration in relation to the global model. Our analysis shows that the descriptions of large-scale climate structures by these two models are consistent. This means that the ETA CCS model can be used for downscaling HadAM3P output fields. Our proposed technique can be used to evaluate the consistency of any regional model and its driving global model. [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 Northern Patagonia Icefield (NPI), covering 3953 km2, is the second largest temperate ice body in South America. Despite its importance as a climate change indicator because of its location and size, data on ground-based mass balance and meteorological records for the analysis of glacier (snout) variations are still lacking. The use of multitemporal satellite images to estimate equilibrium line altitude variations could be a surrogate for such analyses. Since late-summer snowlines of temperate glaciers coincide with the equilibrium line, we analyzed live Landsat images spanning 1979-2003 and an ASTER-derived digital elevation model to reveal oscillations in the equilibrium line altitude (ΔZELA). The average ELAs range between 870 m and 1529 (± 29 m), with lower altitudes on the west side. Winter snow cover accumulation indicates higher elevations (relative to the glacier snout) of the transient snowlines in the west. Thus, one of the reasons for the higher retreating rates observed on the west side is that the lower part of the ablation area is likely exposed to year-round ablation. Glacier sensitivity to ΔZELA oscillations would depend upon the topographic condition of the accumulation area (gentle or steep). In outlet glaciers with gentle accumulation areas such as San Rafael and San Quintin, ΔZELA of up to 65 and 70 m at the central flow part and bare ice area variations > 5 km2 and > 13 (± 0.6 km2) were observed, respectively. [ABSTRACT FROM AUTHOR]

At times when attention on climate issues is strongly focused on the assessment of potential impacts of future climate change due to the intensification of the planetary greenhouse effect, it is perhaps pertinent to look back and explore the consequences of past climate variability. In this article we examine a large disruption in global climate that occurred during 1877–1878, when human influence was negligible. The mechanisms explaining this global disturbance are not well established, but there is considerable evidence that the major El Niño episode that started by the end of 1876 and peaked during the 1877–1878 boreal winter contributed significantly to it. The associated regional climate anomalies were extremely destructive, particularly in the Northern Hemisphere, where starvation due to intense droughts in Asia, South-East Asia and Africa took the lives of more than 20 million people. In South America regional precipitation anomalies were typical of El Niño events, with rainfall deficit and droughts in the northern portion of the continent as well as in northeast Brazil and the highlands of the central Andes (Altiplano). In contrast, anomalously intense rainfall and flooding episodes were reported for the coastal areas of southern Ecuador and Northern Perú, as well as along the extratropical West coast of the continent (central Chile, 30° S–40° S), and in the Paraná basin in the southeast region. By far the most devastating impacts in terms of suffering and loss of life occurred in the semiarid region of northeast Brazil where several hundreds of thousands of people died from starvation and diseases during the drought that started in 1877. [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]

Aim This study analyses long-term responses to climate changes in Podocarpus parlatorei, a cold-tolerant tree species from the subtropics in South America, using distribution patterns of isozyme variation. Location Podocarpus parlatorei characterizes montane forests within the Yungas, a cloud forest of the subtropics of north-western Argentina and southern Bolivia. Podocarpus parlatorei consists of disjunct populations ecologically subdivided into northern, central, and southern sectors that we predict will be genetically divergent from one another as a result of historical isolation. Methods We collected fresh leaves from a maximum of 30 randomly selected individuals from each of 18 populations. We resolved 25 isozyme loci, and scored the most consistent 14, 57% of which were polymorphic. Within-population variation was tested against latitude, longitude, and elevation using multiple regressions. Genetic structure across populations was analysed using diversity parameters. The relationship between genetic and geographic distances was explored with reference to Pearson correlation coefficients. Results The effective number of alleles and observed heterozygosity increase latitudinally. Southern populations tend to be the most variable and genetically distinct. This result suggests that they could represent the location of a long-term refuge for P. parlatorei. The mean number of alleles per locus decreases with elevation. The total genetic diversity is HT = 0.163, 10% of which is distributed among populations. A positive association between genetic and geographic distances was detected. Main conclusions Reductions in genetic diversity towards the north and high-elevation mountains are consistent with evidence of patterns of forest migration resulting from climate change during the Late Quaternary, northern expansion during episodes of cooling, and range contraction towards the highlands during warming trends. Naturally disjunct populations of P. parlatorei are genetically divergent from one another, indicating that local genetic stocks should be used for restoration of degraded habitats. [ABSTRACT FROM AUTHOR]

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

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

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]

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

A regional climate model driven by reanalyzed atmospheric forcing is used to investigate 1) the large-scale circulation anomalies that were driven by sea surface temperatures (SSTs), which resulted in extreme rainfall anomalies during January-May 1983 (dry) and 1985 (wet) in tropical South America; 2) the effects of vegetation and soil moisture in the interior Amazon basin on regional circulations, moisture transport, and rainfall; and 3) the sensitivity of regional model results to domain size. Seasonal integrations demonstrated that by prescribing observed SSTs and applying reanalyses-derived forcing along the boundaries of the control domain, the regional climate model (RegCM) was able to simulate the dramatically different large-scale circulations in the two years, as well as the resulting rainfall differences. Thus, the large-scale forcing apparently has a first-order effect on the region. The regional model shows reduced rainfall in the western Amazon compared with observed estimates that are associated with weak low-level moisture transport from the Atlantic. The sensitivity experiments to surface forcing in the Amazon, employing a large (10.8 × 10[SUP7]km[SUP2]) and a small (5.7 × 10[SUP7]km[SUP2]) domain, show that both simulation and sensitivity are a function of domain size in the Tropics. However, the spatial scales and hence the domains required are larger in the Tropics than in the midlatitudes. The perturbations employed in this study influence the large-scale tropical circulation. This feedback is damped by the lateral boundary conditions of the control (smaller) domain. [ABSTRACT FROM AUTHOR]

A regional climate model driven at the lateral boundaries by ensemble integrations of a general circulation model (GCM) is used to investigate 1) the large-scale circulation anomalies associated with tropical sea surface temperatures (SSTs) that lead to extreme rainfall anomalies during January-May of 1983 (dry) and 1985 (wet) in tropical South America, and 2) the sensitivity of the nested model results to the choice of domain. The nested model is composed of the Regional Climate Model (RegCM) and the Community Climate Model version 3 (CCM3), both developed at the National Center for Atmospheric Research. In Part I of this study, the RegCM's ability to simulate circulation and rainfall observed in the two extreme seasons was demonstrated when driven at the lateral boundaries by reanalyzed forcing. Seasonal integrations with the RegCM driven by GCM ensemble-derived lateral boundary forcing demonstrate that the nested model responds well to the SST forcing, by capturing the major features of the circulation and rainfall differences between the two years. The GCM-driven model also improves upon the monthly evolution of rainfall compared with that from the GCM. However, the nested model rainfall simulations for the two seasons are degraded compared with those from the reanalyses-driven RegCM integrations. The poor location of the Atlantic inter-tropical convergence zone (ITCZ) in the GCM leads to excess rainfall in Nordeste in the nested model. An expanded domain was tested, wherein the RegCM was permitted more internal freedom to respond to SST and regional orographic forcing. Results show that the RegCM is able to improve the location of the ITCZ, and the seasonal evolution of rainfall in Nordeste, the Amazon region, and the southeastern region of Brazil. However, it remains that the limiting factor in the skill of the nested modeling system is the quality of the lateral boundary forcing provided by the global model. [ABSTRACT FROM AUTHOR]