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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]

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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 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]

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]

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.)

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]

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]

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]

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]

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]