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The South Atlantic Ocean (SAO) is characterized by the development of different types of synoptic scale cyclones, which affect the weather and climate of South America. For the first time, we obtained the long term trend of subtropical cyclones (SCs) climatology over the SAO through two ensembles under RCP8.5 scenario. Regional Climate Model version 4 (RegCM4) projections were driven by three global climate models (GCMs) from CMIP5. SCs are obtained by applying three algorithms: (1) for tracking all cyclones based on relative vorticity; (2) to describe the thermal structure of the cyclones; and (3) for selecting only the SCs. Ensemble means are able to capture the main SCs characteristics shown by ERA-Interim reanalysis in the present climate (1979–2005), such as the main region of formation (near the southeastern Brazilian coast), track density, seasonality (higher frequency in austral summer) and lifetime (~ 3 days). The RegCM4 and GCMs ensembles project a negative and statistically significant trend in the frequency of SCs in the future climate (2050–2080) near the southeastern coast of Brazil. The projections also indicate a greater negative trend of SCs than for all cyclones. This would be a response to the future increase in the mean sea level pressure (expansion of South Atlantic subtropical anticyclone), which in turn leads to a change in the low-level circulation acting to decrease the moisture transport to the main region of SCs development. Though the SCs frequency will decrease in the future, they are projected to be more intense due to stronger convective forcing. [ABSTRACT FROM AUTHOR]

An essential step for improving climate change models' performance is to evaluate their ability to represent the current climate conditions, especially extreme events. On such background, this study aims at evaluating the performance of the Quantile Delta Mapping (QDM) as a bias correction method for annual maximum daily precipitation series (bmax) generated from downscaled climate change models under tropical–subtropical conditions of Brazil. We selected the QDM due to its ability to correct bias in extreme quantile of wet days. Climate projections obtained from 20 NASA Earth Exchange Daily Downscaled Projections models (NEX‐GDDP) from 1950 to 2005 were subjected to validation processes based on the QDM method. Two climate change scenarios (RCP 4.5 and RCP 8.5 W m−2) have also been considered. Several goodness‐of‐fit measures, such as root‐mean‐square‐error (RMSE), SD, percentual bias (pbias), mean absolute error (MAE), Pearson correlation test, modified Willmott test (dm), have been calculated from the outcomes of the models and their corresponding observed data (obtained from rain gauges). These goodness‐of‐fit measures were calculated before and after applying the QDM method. The QDM was able to correct virtually all biases. More specifically, the QDM successfully adjusted the empirical cumulative distribution of climate change projections, removing the systematic error of raw data. The QDM also presented a suitable performance when applied to future projections (2020–2095). This statement holds for all NEX‐GDDP models, except for the ACCESS1‐0 model in RCP 8.5. In such a scenario, this latter model presented unrealistic rainfall values. Finally, with the improvement resulting from applying the bias correction method QDM, there was an increase in the number of climate projections suitable for end‐users in the study region. [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]

In this study, multi-model ensembles are used to understand regional features of future climate trends of cyclones and associated winds in eastern South America. For this, we consider three cyclogenetic hot-spot regions located in south-southeastern Brazil, extreme southern Brazil-Uruguay, and southern Argentina, named, respectively, RG1, RG2 and RG3. The multi-model ensembles consist of four RegCM4 downscalings (RegCM4s) nested in three different global circulation models (GCMs) from CMIP5 under RCP8.5 for the period 1979–2100. ERA-Interim, and CFSR provide the reanalyses ensemble. For the present climate (1979–2005), RegCM4s and GCMs simulate the main characteristics of the cyclone's genesis and propagation. There is greater agreement between RegCM4s and reanalyses regarding the magnitude and location of stronger winds associated with intense cyclones starting in RG1 and RG2. An important added value is the greater ability of RegCM4s to capture the observed features (phase and amplitude of the annual cycle, intensity, and near surface winds) of cyclogenesis starting in regions away from the boundary domain, such as in RG1 and RG2. In these regions, RegCM4s present smaller (higher) error (correlation) for the frequency of cyclones than GCMs, which improves the representation of cyclones for the whole southwestern South Atlantic domain. RegCM4s are able to simulate in greater agreement with reanalysis than GCMs, the initially stronger cyclones and associated low level winds. For these intense cyclones in the future climate, an intensification of low-level winds off the coast (south-southeast Brazil and south Argentina) and a shift to the south of the upper-level polar jet are projected. Furthermore, there is a clear trend towards decrease in the number of cyclogeneses in each hot-spot region, indicating that each intense cyclone will be associated with stronger low level winds near the eastern South America coast at the end of the twenty-first century. [ABSTRACT FROM AUTHOR]

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There is an urgent need for more information about the climate change impact on health in order to strengthen the commitment to tackle climate change. However, few studies have quantified the health impact of climate change in Brazil and in the Latin America region. In this paper, we projected the impacts of temperature on cardiovascular (CVD) mortality according to two climate change scenarios and two regionalized climate model simulations in Brazilian cities. We estimated the temperature-CVD mortality relationship in 21 Brazilian cities, using distributed lag non-linear models in a two-stage time-series analysis. We combined the observed exposure-response functions with the daily temperature projected under two representative concentration pathways (RCP), RCP8.5 and RCP4.5, and two regionalized climate model simulations, Eta-HadGEM2-ES and Eta-MIROC5. We observed a trend of reduction in mortality related to low temperatures and a trend of increase in mortality related to high temperatures, according to all the investigated models and scenarios. In most places, the increase in mortality related to high temperatures outweighed the reduction in mortality related to low temperatures, causing a net increase in the excess temperature-related mortality. These trends were steeper according to the higher emission scenario, RCP8.5, and to the Eta-HadGEM2-ES model. According to RCP8.5, our projections suggested that the temperature-related mortality fractions in 2090-99 compared to 2010–2019 would increase by 8.6% and 1.7%, under Eta-HadGEM2-ES and Eta-MIROC5, respectively. According to RCP4.5, these values would be 0.7% and −0.6%. For the same climate model, we observed a greater increase trend in temperature-CVD mortality according to RCP8.5, highlighting a greater health impact associated with the higher emission scenario. Our results may be useful to support public policies and strategies for mitigation of and adaptation to climate change, particularly in the health sector. • We estimated climate change impacts on temperature-CVD mortality in Brazil. • The projections showed a reduction in CVD mortality related to low temperatures. • The projections showed an increase in CVD mortality related to high temperatures. • We found a net increase in temperature-related mortality in most cities. • A greater health impact was associated with the higher emission scenario. [ABSTRACT FROM AUTHOR]