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Climate change has been unequivocally linked to human impact. Human actions have affected the environment and its inhabitants in a variety of ways around the globe and the response of various species can provide insight to what the future holds if we do not begin to mitigate the impacts of climate change. Monkeys are especially important as they function as ecosystem engineers, having a significant impact on plants and other animals in their habitats. Despite their importance, primates in South America and Africa remain understudied, yet are especially at risk as these regions have already undergone significant habitat loss. These regions are also Biodiversity Hotspots with the highest numbers of primate species on Earth. This systematic literature review assesses the current state of knowledge on how monkeys have changed their behavior in response to anthropogenic climate change. For this review, we scanned 3,461 titles, and 100 papers were read in full; seven of 100 papers provided relevant data. These studies primarily reported fertility changes and food substitutions when species were exposed to harsh conditions. The paucity of results from this review demonstrates that more research is needed on this topic. The effects of climate change on primates and their habitats must also be studied in conjunction with other anthropogenic stressors. As humans encroach on wildlife habitats, policies must be implemented to protect the habitats that are still viable. [ABSTRACT FROM AUTHOR]

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]

This paper assesses the state of knowledge of climate change and tourism in South and Central America, with a special focus on the characteristics of the tourism sector, the particularities of climate risks of the region and the sectoral GHG contribution. We conducted a scientific literature review (by region and by country) in Spanish, Portuguese and English using publications in the Scopus and Google databases to the end of 2021. In parallel, we performed a search for institutional publications, programs, and strategies on climate change and tourism in South and Central American countries. This analysis identified the main challenges and potentialities between tourism and climate change in the region. Among the main findings is the limited number of studies and lack of primary data to inform policy formulation and tourism planning. Likewise, national, and regional public policies specific to tourism are scarce, while multisectoral climate plans have only recently been developed and, consequently, are difficult to evaluate. [ABSTRACT FROM AUTHOR]

Purpose: Offshoring of pulpwood production outside Europe is more and more common, which increases transport distances and also changes production technologies, raw material supply and energy production profiles. In this paper, we aim to compare the life cycle greenhouse gas emissions of pulp production from Finnish boreal hardwood and from South American eucalyptus. Special emphasis was placed on analysing the contribution of transport to overall climate impacts. Materials and methods: A life cycle assessment (LCA) was used as the system modelling tool. The impact assessment was limited to climate change. Finnish and South American industrial data were combined with data from LCA databases in the life cycle inventory (LCI). Results and discussion: Based on the results, offshoring of pulp production would decrease the global greenhouse gas emissions of pulp production itself. However, transport to Europe outweighs the benefit even if transported by energy efficient ships. In this case study, transportation accounted for 27% of the life cycle greenhouse gas emissions of South American pulp shipped to Europe. Conclusions: Outsourcing of biomass production offers opportunities for emission reductions. Such a conclusion may be valid if the distances between biomass production and upgrading processes were relatively short. However, this study reveals that the offshoring of biomass production contributes to a significant growth of transport emissions. The trend of offshoring provides challenges for the implementation of emission trading since the responsibility of countries to transoceanic transport is still unclear. [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]

Global warming is causing an intensification of extreme climate events with significant changes in frequency, duration, and intensity over many regions. Understanding the current and future influence of this warming in northeastern Brazil (NEB) is important due to the region's greater vulnerability to natural disasters, as historical records show. In this paper, characteristics of climate change projections (precipitation and air temperature) over NEB are analyzed using 15 models of Coupled Model Intercomparison Project Phase 6 (CMIP6) under four Shared Socioeconomic Pathways (SSPs: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) scenarios. By using the Taylor diagram, we observed that the HadGEM3-GC31-MM model simulates the seasonal behavior of climate variables more efficiently. Projections for NEB indicate an irreversible increase in average air temperature of at least 1 °C throughout the 21st century, with a reduction of up to 30% in annual rainfall, as present in scenarios of regional rivalry (SSP3-7.0) and high emissions (SSP5-8.5). This means that a higher concentration of greenhouse gases (GHG) will increase air temperature, evaporation, and evapotranspiration, reducing rainfall and increasing drought events. The results obtained in this work are essential for the elaboration of effective strategies for adapting to and mitigating climate change for the NEB. [ABSTRACT FROM AUTHOR]

This paper presents a novel methodology in which an individual's optimization decisions are statistically decomposed into choices of systems, system-specific outcomes, and the overall outcome in an integrative framework. The methodology is applied to individuals' decisions on natural resource enterprises given climatic changes. This paper finds that when the Goddard Institute scenario comes to pass by the middle of this century, adoption of a crops-only enterprise will fall, so will adoption of a crops-forests enterprise. Instead, people will increase adoption of a livestock-only as well as a crops-livestock-forests enterprise. The impacts of climate change on the six enterprises are varied, which are calculated from the estimated models by altering climate variables. The crops-only enterprise will lose the value of land by 8.3 %. However, the livestock-only enterprise will gain by 8.9 %. The crops-livestock-forests enterprise also will gain largely by 7.8 %. The impacts on the other enterprises are muted, e.g., 1 % gain for the crops-livestock enterprise. The total damage under the scenario is expected to be a loss of 1.9 % of land value. Under a severer UK Met Office scenario, the damage is predicted to increase to 6.2 %. [ABSTRACT FROM AUTHOR]

This paper evaluates behavioral adaptation models to climate change using South American agricultural data. This paper finds that the Ricardian model with spatial effects leads to 20 % loss of land value under the UK Hadley center (UKMO hereafter) model and 11 % loss under the milder US Goddard Institute (GISS hereafter) model by the middle of the century. The micro portfolio adaptation model (G-MAP hereafter), on the other hand, results in a much smaller damage estimate: 1 % loss of land value under the GISS model and 3.4 % loss under the UKMO model. Even with the G-MAP model, however, the land value of the crops-only system falls sharply by as much as 9.5 % under the GISS scenario. In contrast to the Ricardian model, the G-MAP model can explicitly explain the decisions to choose one of the agricultural systems as well as the conditional land value function for each system of agriculture. Under the GISS model, the choice of a crops-only farm declines by 3.3 % which is offset by an increase in the mixed system by 2.1 % and an increase in the livestock-only system by 1.2 %. Although the land value of the crops-only system falls by 9.5 %, the land value of the mixed system falls only by 3.5 % while that of the livestock-only system increases by a large percentage. This paper finds that the differences in the impact estimates between the two models result from the treatment of sunk cost. The result from the Ricardian model would deviate from that from the G-MAP model if sunk cost is significantly large. [ABSTRACT FROM AUTHOR]

Although econometric models have been widely used to measure the impact of climate change on agriculture, there exist differences among the modelers on which specification should be preferred. To help explain the discrepancies, this paper assesses four different econometric models, i.e. OLS, panel, and two spatial models using a South American agricultural household data. The relationship among the econometric specifications is examined in terms of the freedom given to a spatial autoregressive parameter. In spatial models, the spatial parameter is free within the model, but is fixed a priori in the aspatial models. Empirical results show a high correlation of the land values across South America. Spatial models result in somewhat lower climate change impact estimates than those from the aspatial models. [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]

Background: climate change is a reality, and more and more people are becoming aware of this global problem, which has generated anxiety in some populations. To validate a short survey to assess eco-anxiety in adults in South America. Methods: It is an instrumental study, and the validation was based on a previous survey, which had six questions and was generated by 217 respondents in the USA in 2021. These questions were subjected to a validation process with expert judgment, pilot and application, and then statistics were obtained. It was validated with 1907 people in six countries in South America, where the mean, standard deviation, skewness and kurtosis were adequate. Results: The initial confirmatory factorial model obtained unsatisfactory goodness-of-fit indices, so the indices were modified through a re-specification, where two items were eliminated, after which adequate values were obtained (χ2 = 22.34, df = 2, p = 0.00; RMR = 0.020; GFI = 0.990; CFI = 0.990; TLI = 0.990; and RMSEA = 0.070). Finally, the overall Cronbach's α was calculated to be 0.88 (95% CI = 0.86–0.89). Conclusions: The test was validated in a large South American population and found that only four questions can efficiently measure anxiety about the effects of climate change. The instrument can be used with other tests to screen different age groups, ethnicities and realities. [ABSTRACT FROM AUTHOR]

The vast diversity of present vegetation and environments that occur throughout South America (12°N to 56°S) is the result of diverse processes that have been operating and interacting at different spatial and temporal scales. Global factors, such as the concentration of CO2 in the atmosphere, may have been significant for high altitude vegetation during times of lower abundance, while lower sea levels of glacial stages potentially opened areas of continental shelf for colonisation during a substantial portion of the Quaternary. Latitudinal variation in orbital forcing has operated on a regional scale. The pace of climate change in the tropics is dominated by precessional oscillations of c. 20 kyr, while the high latitudes of the south are dominated by obliquity oscillations of c. 40 kyr. In particular, seasonal insolation changes forced by precessional oscillations must have had important consequences for the distribution limits of species, with potentially different effects depending on the latitude. The availability of taxa, altitude and human impact, among other events, have locally influenced the environments. Disentangling the different forcing factors of environmental change that operate on different timescales, and understanding the underlying mechanisms leads to considerable challenges for palaeoecologists. The papers in this Special Issue present a selection of palaeoecological studies throughout South America on vegetation changes and other aspects of the environment, providing a window on the possible complexity of the nature of transitions and timings that are potentially available. [ABSTRACT FROM AUTHOR]

General circulation models (GCMs) forced under different greenhouse gases emission and socioeconomic scenarios are currently the most extended tool throughout the scientific community that is used to infer the future climate on Earth. However, these models still have problems in capturing several aspects of regional climate variability in many parts of the globe. In this paper, the hydrological cycle of the La Plata Basin is simulated using the variable infiltration capacity (VIC) distributed hydrology model and forced with atmospheric data from different GCMs to determine to what extent errors in temperature and precipitation fields impact the hydrology of the basin. The skill assessment is performed in terms of simulated runoff at different closing points. Simulated hydrographs show that all of the GCMs present deficiencies in simulating the regional climatology of southern South America, and this leads to a very poor representation of the hydrological cycle of the main rivers across the basin. Two unbiasing schemes are then proposed as a means of correcting the GCM outputs before forcing the hydrology model, and comparisons between biased and unbiased simulations are also performed. Results indicate that both schemes, though methodologically different, reduce the water cycle simulation bias. Finally, VIC is forced with bias-corrected data from the GCMs for future decades (2030 and 2070) under different socioeconomic scenarios [e.g., the Intergovernmental Panel on Climate Change's (IPCC) Special Report on Emissions Scenarios (SRES) scenarios A1B, A2, and B1] to determine the potential changes in streamflow due to climate change for the rest of the present century. [ABSTRACT FROM AUTHOR]

This paper develops a microeconometric analysis of adapting portfolios in response to climate change using information on South American farmers' adoption of agricultural systems taken from approximately 2,000 household surveys. The results show that farmers in a hotter climate prefer a mixed system over specialized systems either in crops or livestock. Under a hot and dry scenario, the land values of all three systems would fall, but the damage would be much smaller in the mixed system (−10%) than for the farms specializing in crops (−20%). Farmers are predicted to lose 8% of their land's value under the Canadian Climatic Center (CCC) scenario, but only 2% under the Parallel Climate Model (PCM). Losses would increase to 18% if they do not adapt. [ABSTRACT FROM PUBLISHER]

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

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

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

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

This paper provides an analysis of public adaptation to climate change using agricultural water schemes in South American farms. Unlike other studies of adaptation, this paper examines the differences between private irrigation and public irrigation schemes based on around 1400 farm surveys collected across seven countries in South America which recorded detailed water schemes. We analyze the choice of water schemes in the first stage and the land values for each scheme in the second stage. We find that public irrigations do not increase in response to a warmer climate, but private irrigations do. On the other hand, we find that public irrigation schemes are provided primarily as a response to water scarcity. Moreover, we find that private irrigations are taken gradually while public irrigations are provided as a lump sum, resulting in either too much or too little provision. Therefore, public adaptations to climate change will likely involve two inefficiencies. No provision of irrigation in a hotter climate may result from a lack of knowledge. Overprovision of irrigation in dry zones may result from a lump-sum provision of a public good. [Copyright &y& Elsevier]

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]

Oxygen isotope speleothems have been widely used to infer past climate changes over tropical South America (TSA). However, the spatial patterns of the millennial precipitation and precipitation δ18O (δ18Op) response have remained controversial, and their response mechanisms are unclear. In particular, it is not clear whether the regional precipitation represents the intensity of the millennial South American summer monsoon (SASM). Here, we study the TSA hydroclimate variability during the last deglaciation (20–11 ka ago) by combining transient simulations of an isotope-enabled Community Earth System Model (iCESM) and the speleothem records over the lowland TSA. Our model reasonably simulates the deglacial evolution of hydroclimate variables and water isotopes over the TSA, albeit underestimating the amplitude of variability. North Atlantic meltwater discharge is the leading factor driving the TSA’s millennial hydroclimate variability. The spatial pattern of both precipitation and δ18Op show a northwest–southeast dipole associated with the meridional migration of the intertropical convergence zone, instead of a continental-wide coherent change as inferred in many previous works on speleothem records. The dipole response is supported by multisource paleoclimate proxies. In response to increased meltwater forcing, the SASM weakened (characterized by a decreased low-level easterly wind) and consequently reduced rainfall in the western Amazon and increased rainfall in eastern Brazil. A similar dipole response is also generated by insolation, ice sheets, and greenhouse gases, suggesting an inherent stability of the spatial characteristics of the SASM regardless of the external forcing and time scales. Finally, we discuss the potential reasons for the model–proxy discrepancy and pose the necessity to build more paleoclimate proxy data in central-western Amazon. Significance Statement We want to reconcile the controversy on whether there is a coherent or heterogeneous response in millennial hydroclimate over tropical South America and to clearly understand the forcing mechanisms behind it. Our isotope-enabled transient simulations fill the gap in speleothem reconstructions to capture a complete picture of millennial precipitation/δ18Op and monsoon intensity change. We highlight a heterogeneous dipole response in precipitation and δ18Op on millennial and orbital time scales. Increased meltwater discharge shifts ITCZ southward and favors a wet condition in coastal Brazil. Meanwhile, the low-level easterly and the summer monsoon intensity reduced, causing a dry condition in the central-western Amazon. However, the millennial variability of hydroclimate response is underestimated in our model, together with the lack of direct paleoclimate proxies in the central-west Amazon, complicating the interpretation of changes in specific paleoclimate events and posing a challenge to constraining the spatial range of the dipole. Therefore, we emphasize the necessity to increase the source of proxies, enhance proxy interpretations, and improve climate model performance in the future. [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]

A 22-member ensemble from CMIP6 is used to analyze the projected changes and seasonal behavior in surface air temperature over South America during the twenty-first century. In the future projections, CMIP6 models shown a high dependency to the socioeconomic pathway over each country of South America. The multimodel ensemble projects a continuous increase in the annual mean temperature over South America during the twenty-first century under the three future scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5). Besides, it was possible to identify consistent positive trends across all the models, with values between 0.45 ± 0.05 and 2.05 ± 0.31 °C cy−1 under the historical experiment, however largest trends occurs for the projection periods (near, mid and far future), with values between − 0.87 ± 0.84 to 2.88 ± 0.60 °C cy−1 (SSP1-2.6), 1.41 ± 0.88 to 5.32 ± 0.81 °C cy−1 (SSP2-4.5) and 4.75 ± 0.58 to 8.76 ± 0.74 °C cy−1 (SSP5-8.5) with maximum values at Bolivia, Brasil, Paraguay and Venezuela whilst minimum values for Argentina and Uruguay, regardless of the SSP scenario used. From the seasonal behavior analysis was possible to identify maximum values between January and March whilst minimum between June and July, except in Brasil, Venezuela and Guyana–Surinam–French Guayana, with annual range decreasing as the latidude decreases. By the end of the twenty-first century the annual mean temperature over South america is projected to increase between 0.92–2.11 °C, 0.97–3.37 °C and 1.27–6.14 °C under SSP1-2.6, SSP2-4.5 and SSP5-8.5 projection scenarios respectively. This projected increase of temperature across the continent will produce negative repercussions in the social, economic and political spheres. The results obtained in this study provide insights about the CMIP6 performance over this region, which can be used to develop adaptation strategies and might be useful for the adaptation to the climate change. [ABSTRACT FROM AUTHOR]

Climate change is undeniable, and its effects, like droughts and intense precipitation, evidence this reality. However, many questions remain unanswered, such as climate extremes' future frequency and intensity. International collaboration projects such as the Coordinated Regional Climate Downscaling Experiment (CORDEX)-Coordinated Output for Regional Evaluations (CORE) have emerged to address these questions, creating protocols to facilitate the intercomparison among simulations obtained by different regional climate models (RCMs). Given this context, this study aims to describe the projected changes in the extreme precipitation events over the South America domain by using a set of projections of three RCMs (Eta, RegCM, and REMO) under the CORDEX-CORE framework (except Eta). These models were nested in different global climate models (GCMs) from Coupled Model Intercomparison Project phase 5 (CMIP5) under the RCP8.5 scenario and integrated with a grid space of 25 km. In addition, six climate indices (PRCPTOT, SDII, R95p, P95, CDD, and CWD) were computed by season for the historical period (1995–2014) and four future time-slices (2020–2039, 2040–2059, 2060–2079, and 2080–2099). For brevity, this study focuses on the austral summer. RCMs are generally capable of representing the spatial pattern of climate indices but with differences in intensity. The ensemble with all RCMs shows a slightly better spatial correlation with the reference data than the ensemble of each RCM. The signal of the projections is similar between RegCM and REMO and, in general, opposite to Eta (mainly in the South Atlantic Convergence Zone region). Of the six climate indices analyzed, the ensemble performed with the three RCMs projects statistically significant negative (positive) trends for four indices in the Amazon (La Plata Basin), indicating a signal of dry (wet) conditions increasing towards the end of the century. Furthermore, both regions have significant positive (negative) trends of consecutive dry (wet) days. The region with higher uncertainties lies over southeastern Brazil, where Eta projects a dry climate and RegCM and REMO, a wet one. [ABSTRACT FROM AUTHOR]

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

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

Abstract: This invited review paper tends to summarise the results based on the variability of occurrence of temperature extremes in South America. The first thing to note is that there is a geographical imbalance with respect to the number of published studies on temperature extremes. Most of the results come from the southern part of South America, east of the Andes, and a few from the northern part of the continent and for the Altiplano. The workshop organised by the ETCCDMI in Brazil was the first time to have the opportunity to collect information in a regional way and present trends in extreme daily temperatures. A better geographical picture enhanced with more data show significant geographical trends in warm (positive) and cold (negative) nights over Southern South America and over the northern South America coast. All other studies based on smaller regions also agree in finding the most significant trends in the evolution of the minimum temperature, with positive trends in almost all studies on the occurrence of warm nights (or hot extremes of minimum temperature) and negative trend in the cold extremes of the minimum. On the other hand, there is little agreement on the variability of maximum temperature. Generally the maximum temperature in southern South America has decreased, in opposition to the case of northern South America where it has increased. Strong decadal and interannual variability have been found in the occurrence of cold extremes. Reanalysis and climate models underestimate the intensity of extremes, mainly near the Andes. The studies trying to understand the dynamics of the circulation that leads to the occurrence of these extremes are analysed from its occurrence in almost all scales from the synoptic, intraseasonal, seasonal, annual, and multi-year linear trend with different methodologies, also, indentifying the local and remote forcing. A gap was found in studies that relate some specific local forcing (like changes in land use) and compare it with the remote ones. Different aspects of the occurrence of the temperature extremes are still missing in some regions of the continent. [Copyright &y& Elsevier]

This paper examines how South American farmers'' choices of livestock species vary across the range of climate and in turn infer from them as to what would happen under climate changes. We examine the choice of five primary species using a multinomial logit model with and without climate variability measures based on 1300 livestock farm surveys in seven countries. The results indicate that climate variables are highly significant determinants of primary species choice after controlling for soils, geography, household characteristics, and country fixed effects. We find the probability of adopting any livestock increases with warming, but decreases when it becomes too wet. The impacts of climate change would vary by species and climate scenarios. For example, under a hot and dry CCC scenario by 2060, beef cattle decrease by 3.2%, dairy cattle by 2.3%, pigs by 0.5%, and chickens by 0.9%, which is offset by a large increase in sheep by 7%. These adaptive changes vary again by country. Large changes are observed in the Andean countries. Under the hot dry scenario, dairy cattle increase in Uruguay and Argentina, but decrease elsewhere. The increase in sheep occurs mostly in the Andes mountain countries such as Chile, Colombia, Ecuador, and Venezuela. Under a milder and wetter scenario, beef cattle choice declines in Colombia, Ecuador, and Venezuela, but increases in Argentina and Chile. Sheep increase in Colombia and Venezuela, but decrease in the high mountains of Chile where chickens are chosen more frequently. [Copyright &y& Elsevier]

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]

In tropical regions, particularly in Central and South America (CSA), the projections of climate seasonality under climate change are still uncertain. This is especially true for ecologically‐relevant variables such as precipitation and temperature. However, assessments of model‐based projections of seasonal climate for this region are scarce. We analyzed the simulation of seasonal precipitation and air surface temperature in CSA and six sub‐regions within from 49 models included in the Coupled Intercomparison Project Phase 5 (CMIP5) and 33 models from CMIP6. In general, continental patterns and seasonality of both variables are moderately well resembled, while most models show systematic biases over the oceans, producing unrealistic spatial patterns. To quantify how well CMIP5/CMIP6 models simulate these variables, we used Taylor diagrams with respect to TRMM for precipitation and ERA5 for temperature. Precipitation shows the largest spread among models. Conversely, temperature shows a better simulation. CMIP5/CMIP6 models exhibit a better performance simulating both variables during December–January–February and March–April–May than during the other seasons. This is partly due to the reduced model biases in representing the Intertropical Convergence Zone during these two seasons. In general, biases are reduced in the CMIP6 models with respect to CMIP5. Regarding regional evaluations, precipitation patterns for Mesoamerica, Cerrado and Chaco regions are better reproduced compared to TRMM, while the annual cycles for the Andes hotspot, Central Chile and Guianas are not well simulated, mainly during their wet seasons. However, these biases are reduced in CMIP6 models. In regard to precipitation projections, models only agree over most of the regions with decreasing precipitation. Conversely, temperature exhibits a general consensus on persistent warming even during the historical period, with an average increase of 6°C by the end of the century, according to the CMIP6 models. [ABSTRACT FROM AUTHOR]

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

Temperature extreme indices were analyzed for five continental regions of southern South America defined according to their climatic characteristics. Gridded observations, reanalysis, and global‐coupled climate models from CMIP5 were used with the approach of temperature extreme trend attribution analysis on fixed‐threshold and percentile‐based temperature extremes indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). The largest positive trends are exhibited in the tropical nights index, and a clear anthropogenic signal is evident in the subtropical region. In the subtropical central Andes, there is a decrease in the frost days index and increases in the tropical nights and summer days indices, and an anthropogenic signal is evident. In the Patagonian region, all trends from the historical runs were significant, while the ones from the natural experiment were nonsignificant, showing the marked effect of anthropogenic forcing in this region in the extreme temperature events. Projected changes in extreme indices for the 21st century are consistent with a warming climate, and larger changes are expected in the warm nights index. [ABSTRACT FROM AUTHOR]

During the last four decades, the sea level pressure has been decreasing over the Amundsen–Bellingshausen Sea (ABS) region and increasing between 30° and 40°S from New Zealand to Chile, thus forming a pressure trend dipole across the South Pacific. The trends are strongest in austral winter and have influenced the climate of West Antarctica and South America. The pressure trends have been attributed to decadal variability in the tropics, expansion of the Hadley cell, and an associated positive trend of the southern annular mode, but these mechanisms explain only about half of the pressure trend dipole intensity. Experiments conducted with two atmospheric models indicate that upper ocean warming over the subtropical southwest Pacific (SSWP), termed the Southern Blob, accounts for about half of the negative pressure trend in the ABS region and nearly all the ridging/drying over the eastern subtropical South Pacific, thus contributing to the central Chile megadrought. The SSWP warming intensifies the pressure trend dipole through warming the troposphere across the subtropical South Pacific and shifting the midlatitude storm track poleward into the ABS. Multidecadal periods of strong SSWP warming also appear in fully coupled preindustrial simulations, associated with a pressure trend dipole and reduction in rainfall over the central tropical Pacific, thus suggesting a natural origin of the Southern Blob and its teleconnection. However, the current warming rate exceeds the range of natural variability, implying a likely additional anthropogenic contribution. [ABSTRACT FROM AUTHOR]

This study presents results from an assessment of climate change projections over South America using fifth phase of the Coupled Model Intercomparison Project models. Change in near‐surface temperature, precipitation, evapotranspiration, integrated water vapour transport (IVT), sea level pressure (SLP), and wind at three pressure levels is quantified across the multi‐model suite. Additionally, model agreement for the sign and significance of projected change is assessed within the ensemble. Models are in strong agreement that the highest magnitude of projected warming will be over tropical regions. The CMIP5 models project a decrease in precipitation for all seasons over southern South America, especially along the northern portions of the present‐day mid‐latitude storm track. This is consistent with a robustly projected poleward shift of the Pacific extratropical high‐pressure system and mid‐latitude storm track indicated by a systematic increase in SLP and decrease in westerly wind magnitude over the region. Decreased precipitation for the months of September, October, and November is also projected, with strong model agreement, over portions of northern and northeastern Brazil, coincident with decreases in SLP and increases in evapotranspiration. IVT is broadly projected to decrease over southern South America, coincident with the projected poleward shift of the mid‐latitude storm track, with increases projected in the vicinity of the South Atlantic Convergence Zone in spring and summer. Results provide a comprehensive picture of climate change across South America and highlight where model consensus on change is most robust. [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]

Analyses of biota at lower latitudes may presage impacts of climate change on biota at higher latitudes. Macroinvertebrate assemblages in depressional wetlands may be especially sensitive to climate change because weather‐related precipitation and evapotranspiration are dominant ecological controls on habitats, and organisms of depressional wetlands are temperature‐sensitive ectotherms. We aimed to better understand how wetland macroinvertebrate assemblages were structured according to geography and climate. To do so, we contrasted aquatic‐macroinvertebrate assemblage structure (family level) between subtropical and temperate depressional wetlands of North and South America using presence–absence data from 264 of these habitats across the continents and more‐detailed relative‐abundance data from 56 depressional wetlands from four case‐study locations (North Dakota and Georgia in North America; southern Brazil and Argentinian Patagonia in South America). Both data sets roughly partitioned wetland numbers equally between the two climatic zones and between the continents. We used ordination methods (PCA and NMDS) and tests of multivariate dispersion (PERMDISP) to assess the distribution and the homogeneity in variation in the composition of macroinvertebrate assemblages across climates and continents, respectively. We found that macroinvertebrate assemblage structures in the subtropical depressional wetlands of North and South America were similar to each other (at the family level), while assemblages in the North and South American temperate wetlands were unique from the subtropics, and from each other. Tests of homogeneity of multivariate dispersion indicated that family‐level assemblage structures were more homogeneous in wetlands from the subtropical than the temperate zones. Our study suggests that ongoing climate change may result in the homogenization of macroinvertebrate assemblage structures in temperate zones of North and South America, with those assemblages becoming enveloped by assemblages from the subtropics. Biotic homogenization, more typically associated with other kinds of anthropogenic factors, may also be affected by climate change. [ABSTRACT FROM AUTHOR]

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

Phytolith analysis is conventionally an archeo-botanical tool used to study past human activity using material from excavations or soil pits. However, phytolith analysis also has potential as a paleoecological tool, to reconstruct vegetation changes through periods of climatic change and human influence. To study phytoliths from lake sediment alongside pollen requires an understanding of phytolith taphonomy in lakes. Theoretical models suggest phytoliths represent more local vegetation at smaller spatial scales than pollen from lake sediments, but this has not been tested empirically in the Neotropics. This paper compares pollen and phytolith assemblages from the same lake sediment surface sample, from a suite of lakes of different sizes across different vegetation types of lowland tropical Bolivia. We find three factors driving phytolith composition in lakes: taphonomy, lake size and phytolith productivity. By comparing phytolith assemblages with pollen assemblages, we find that they provide different taxonomic information and generally complement each other as paleo-vegetation proxies. We also demonstrate empirically that pollen assemblages in lake samples represent a larger catchment area than phytolith assemblages. Our findings suggest that phytoliths can be particularly useful in providing local-scale vegetation histories from large lakes, to complement the regional-scale vegetation histories provided by pollen data. • Phytoliths can differentiate evergreen from semi-deciduous forest and savannah. • Phytolith assemblages from lakes are most strongly influenced by local vegetation. • Phytolith assemblages from lakes represent a smaller catchment area than pollen. • Phytolith assemblages across large lakes are more variable than pollen assemblages. [ABSTRACT FROM AUTHOR]

South America contributes to roughly 30% of global runoff to the oceans. Because the regional economy and biodiversity depend significantly on its water resources, assessing potential climate change impacts on the continental water balance is crucial to support water management planning. Here we evaluate the mean alterations of water balance variables and river discharge in South America by the end of this century using two different GHG scenarios (RCP4.5 and RCP8.5). An ensemble comprising 25 global climate models (GCM) from CMIP5 is used to force a continental-scale hydrologic-hydrodynamic model developed for that region. A negative signal with respect to changes in precipitation, evapotranspiration, and runoff is observed on most of the continent. Major decreases in the annual mean discharge are expected for the Orinoco, Tocantins, and Amazon basins, which would be around 8–14% at least (statistically significant – RCP4.5 and RCP8.5, respectively). Only the Uruguay Basin presents a positive trend for the mean discharge. [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]

Background: Before 1996 the phlebotomine sand fly Lutzomyia neivai was usually treated as a synonym of the morphologically similar Lutzomyia intermedia, which has long been considered a vector of Leishmania braziliensis, the causative agent of much cutaneous leishmaniasis in South America. This report investigates the likely range changes of both sand fly species in response to a stabilisation climate change scenario (RCP4.5) and a high greenhouse gas emissions one (RCP8.5). Methods: Ecological niche modelling was used to identify areas of South America with climates currently suitable for each species, and then the future distributions of these climates were predicted based on climate change scenarios. Compared with the previous ecological niche model of L. intermedia (sensu lato) produced using the GARP algorithm in 2003, the current investigation modelled the two species separately, making use of verified presence records and additional records after 2001. Also, the new ensemble approach employed ecological niche modelling algorithms (including Maximum Entropy, Random Forests and Support Vector Machines) that have been widely adopted since 2003 and perform better than GARP, as well as using a more recent climate change model (HadGEM2) considered to have better performance at higher resolution than the earlier one (HadCM2). Results: Lutzomyia intermedia was shown to be the more tropical of the two species, with its climatic niche defined by higher annual mean temperatures and lower temperature seasonality, in contrast to the more subtropical L. neivai. These different latitudinal ranges explain the two species' predicted responses to climate change by 2050, with L. intermedia mostly contracting its range (except perhaps in northeast Brazil) and L. neivai mostly shifting its range southwards in Brazil and Argentina. This contradicts the findings of the 2003 report, which predicted more range expansion. The different findings can be explained by the improved data sets and modelling methods. Conclusions: Our findings indicate that climate change will not always lead to range expansion of disease vectors such as sand flies. Ecological niche models should be species specific, carefully selected and combined in an ensemble approach. [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]

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

ABSTRACT The 1976-1977 cold-to-warm sea surface temperature ( SST) shift in the tropical Pacific Ocean, which has been associated with a phase change of the Pacific Decadal Oscillation ( PDO) index, separated a 'La Niña-like' decadal regime from an 'El Niño-like' one. In this article, we analyse the differences of mean of annual and austral-summer ( DJF) temperature, precipitation, and sea-level pressure ( SLP) over South America ( SA) between 1961-1973 and 1978-1990, and explore the occurrence of significant shifts in their time series. Our sources are instrumental records, gridded interpolated data, and reanalyses. Although major regional differences in the intensity of the signal are detected, the climate shift is identified in all variables. In the mid-1970s at annual level, reanalysis SLP data reveal the onset of a step-like anticyclonic circulation anomaly in the southern tip of SA and an abrupt weakening of the Southeast Pacific Subtropical Anticyclone ( SEPA). This latter feature may have partly induced the rapid warming observed along the tropical-extratropical west coast of the continent through the weakening of the cold Humboldt current system. An abrupt warming was also detected in surface air temperature ( SAT) composites located along the coast of the northern part of SA and in Southeastern SA ( SESA). During summer, we found a particularly conspicuous shift-like warming over Southern South America ( SSA, comprising Patagonia). Besides, a shift-like increase (decrease) in annual mean precipitation is observed over Central Argentina and in the tropics, to the south (north) of 10°S. In line with previous studies, we conclude that both the interannual (El Niño-Southern Oscillation, ENSO) and the interdecadal ( PDO) variability modes seem to have had an incidence in the manifestation of the 1970s climate shift, and that its magnitude appears to be unprecedented during the 20th century, as shown in particular by century-long SAT composites from northern Chile and SSA. [ABSTRACT FROM AUTHOR]

Bees ensure 35 % of global food production, but this service is endangered due to several threats. Declines in bumblebee populations (genus Bombus) have been reported worldwide. Bombus bellicosus is one of the rare cases of reported threatened bumblebees in South America. It was once widespread in southern Brazil's grasslands until the 1960s. During that time, that area underwent increasing land use which led to a decrease in bee abundance and richness, and to local disappearance of B. bellicosus. Climate change is also believed to cause declines in the abundance of B. bellicosus. Here we used species distribution models to assess potential effects of climate changes on the distribution of B. bellicosus in southern Brazil, considering both current and future climate scenarios. Our results show that the suitable climatic conditions for B. bellicosus will retreat southwards. A wax cover inside its nests is usually related to Bombus species inhabiting cooler climates. This cover enables the maintenance of higher temperatures inside the nest and may be deleterious for the species under future warmer climates. Continuously growing land use is the second major threat to this pollinator. The results presented here may eventually provide theoretical grounds and enable practical conservation actions for B. bellicosus protection in South America, especially given the potential adverse effects of climate changes for this species. [ABSTRACT FROM AUTHOR]

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

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

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

Satellite precipitation estimates are increasingly available at temporal and spatial scales of interest to hydrological applications and with the potential for improving flood forecasts in data-sparse regions. This study evaluates the effect of sampling error on simulated large flood events. Synthetic precipitation fields were generated in Monte Carlo fashion by perturbing observed precipitation fields with sampling errors based on 1, 2 and 6 h intervals. The variable infiltration capacity hydrological model was used to assess the impact of these errors on simulated high flow events in the Iguazu basin, a rain-dominated, subtropical basin in southeastern South America. Results showed that unbiased errors in daily error-corrupted precipitation fields introduced bias in the simulated hydrologic fluxes and states. The overall bias for error-corrupted daily streamflows was positive and its magnitude increased with larger sampling intervals. However, for high flow events, the bias was negative as a result of an increase in simulated infiltration and changes in precipitation variability. Errors in precipitation also affected the magnitude and volume of the peak events but did not change the first two statistical moments of the peaks indicating that non-linearities in the hydrological system preserve the statistical properties of high flows in the basin. Caution is needed when using satellite products for hydrological applications that require the estimation of large peaks and volumes. [ABSTRACT FROM PUBLISHER]