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This study evaluates the ability of 19 models of CMIP phase 6 (CMIP6) to simulate Paraguay’s climate features. Historical multi-member simulations of single models and their multi-model ensembles are bias-corrected and evaluated with statistical metrics. Future projections of precipitation and temperature are generated with the ensembles for three integrated scenarios of socio-economic development and greenhouse gas emissions (SSP1–2.6, SSP2–4.5, and SSP5–8.5). The 19 models simulate well the observed mean temperature. The bias-corrected multi-model ensemble reaches the highest skill scores and accurately reproduces the mean spatial field and annual cycle. The bias-corrected multi-model ensemble of precipitation represents the annual cycle weakly, missing the sharp onset and decay of the South American Monsoon. Some individual models and the multi-model ensemble correctly reproduce the west-east gradient, although they underestimate its pronounced spatial variability. Ensembles of future simulations project that by 2100, the annual mean temperature will increase for the three scenarios. On average, the increases are almost 1.7 °C in the sustainable development and low emissions scenario (SSP1–2.6), 3 °C in the middle-of-the-road development and medium emissions scenario (SSP2–4.5), and 5.5 °C in the fossil-fueled development and high emissions scenario (SSP5–8.5). Models project a slight decrease in annual precipitation towards the northwest (less than 50 mm) and an increase towards the southeast (more than 200 mm). Paraguay’s humid eastern part is projected to have a small growth in temperature and an increase in precipitation. In contrast, the western arid Chaco region would experience a substantial increase in temperature, while rainfall would slightly decrease.

This work examines the characteristics and prevalent life cycle of agricultural flash droughts globally. Using ERA5 data, the study introduces a flash drought indicator based on soil water availability. This approach integrates root-zone soil moisture and hydraulic soil properties, such as field capacity and wilting point, to couple the rapid soil moisture depletion and plant water stress. Our findings reveal that agricultural flash droughts present their higher frequency predominantly during the critical growth periods of crops. Notably, these droughts exhibit a similar life cycle regardless of the location or climatic regime. The primary cause of the rapid soil moisture depletion is the precipitation deficit, but evapotranspiration also plays a significant role. In an energy-limited environment, evapotranspiration rapidly increases before the onset and decreases rapidly during the intensification period as the system becomes water-limited. Upon concluding the intensification period, most crops experience water stress, diminishing their yields.

This study investigates the characteristics of agricultural flash droughts (AFDs) and their impacts on critical growth periods of soybean and corn in southeastern South America (SESA). Using ERA5 data from 1960 to 2022, we examine AFD frequency, duration, intensity, trends, seasonality, life cycle, and the influence of land–atmosphere interactions. Historical crop data, spanning different time periods across SESA countries, are analyzed to assess how the spatiotemporal evolution and varying life cycles of AFDs affect crop yields. The highest AFD frequencies (3–8 events per decade) occur in the central portion of SESA. These rapidly intensifying events often evolve into seasonal droughts lasting 1.5–3 months. Although area-averaged AFD frequency shows no significant change in central SESA, positive trends are noticeable in southern Brazil and Uruguay. Towards the north of SESA, AFDs are less frequent, with 1–3 episodes per decade, although the frequency has significantly increased since 1970. AFDs tend to last over 3 months and reach higher intensity. Land–atmosphere feedback mechanisms are reflected in high positive vapor pressure deficit and temperature anomalies that exacerbate soil moisture deficits despite a relatively stable precipitation deficit, accelerating AFD intensification periods. AFDs typically impact smaller areas, while slow-evolving droughts affect larger regions. However, AFDs’ timing during the critical growth periods of the crops can lead to substantial yield losses. In central SESA, AFDs mainly occur between November and January, affecting both crops during their flowering and grain filling in December and January. In northern SESA, AFDs occur later, from February to April, primarily impacting second-season corn. The overall impact on crop yields depends on the duration, spatial extent, and intensity of the drought after its intensification.

The observed continuous rise in the frequency of extreme heat events in South America (SA) poses a serious challenge for public health. However, there is a lack on the understanding of the large-scale and long-term variability and trends of thermal stress in this continent. Accordingly, here we developed the first comprehensive bioclimatology of thermal stress over SA during the past four decades. Consecutive heat stress hours were analyzed using the Universal Thermal Climate Index (UTCI) from ERA5-HEAT reanalysis according to the Köppen–Geiger climate classification and also focusing on the 31 most populated cities of SA. Results show an inland/coastline contrast and a marked latitudinal northward increase in the number of hours under heat stress. Heat stress hotspots are located mostly around the Amazon, northern and central parts of SA with 26–35% of the hours between 1979 and 2020 under strong heat stress. The annual number of hours within heat stress increased significantly between 1979 and 2020, varying from + 1.16 h/year to + 8.25 h/year depending on the Köppen–Geiger class. The past 20 years (2000 forward) presented not only more consecutive hours under heat stress than the previous two decades in all the analyzed cities, but also a higher persistence of such conditions. The bioclimatology of thermal stress developed here may provide important guidelines to decision-makers for exploring adaptation strategies to increase societal resilience.

Generalized frosts have a significant impact on the Pampa Húmeda of Argentina, particularly those without persistence (0DP), defined as events that do not last more than one day, and are the most frequent generalized frosts. This study investigates the dynamical and physical mechanisms that sustain these events, emphasizing the nonlinear interactions represented by the Rossby Wave Source (RWS) equation. Composite analysis of pressure, temperature, wind and geopotential height fields were performed, showing that 0DP events are related to abrupt cold air intrusion linked to the enhancement of upper levels troughs over the eastern Pacific Ocean and transient surface anticyclones over South America. This linear analysis only showed a lack of persistent upper-level maintenance and did not explain the dynamics of the rapid weakening of the circulation. For this reason, a nonlinear analysis based on the decomposition of the RWS equation into its advective and divergent terms is performed. The advective term only acts as an initial trigger, deepening troughs and favoring meridional cold air advection, while the divergent term dominates the events, representing 63–67% of the affected area. This term reinforces ridges, promotes subsidence and favors clear sky conditions that enhance nocturnal radiative cooling and frost formation. Positive anomalies of the divergent RWS term strengthen the ridge and advect cold air over the Pampa Húmeda, whereas subsequent negative anomalies over the southwestern Atlantic act as sinks of wave activity, leading to the rapid dissipation of the synoptic configuration. Consequently, the same mechanism that generates favorable conditions for frost development also determines their lack of persistence. These findings demonstrate that the short-lived nature of 0DP frosts is not due to the absence of dynamical forcing, but rather to nonlinear processes that both enable and constrain frost occurrence. This highlights the importance of incorporating nonlinear diagnostics, such as the RWS, to improve the understanding of short-lived atmospheric extremes.

This study advances the understanding and impacts of dry episodes on wheat, corn, and soybean yields over Argentina's core crop region. The production of these major crops is intense and is the main contribution to the country's gross domestic product. Our analysis focuses on the droughts' properties, including their magnitude, frequency at different timescales, duration, and severity. We analyzed 40 years of precipitation and soil moisture anomalies and their corresponding nonparametric standardized indices at timescales of 1, 3, and 6 months. The climate variables were complemented with 40 years of the crops' yield data. The percentage of drought occurrence in northeastern Argentina ranges between 12 % and 18 %, with the larger values located towards the core crop region's eastern–northeastern sector. An analysis of drought duration suggests that most cases tend to occur for periods shorter than 3 months, while a few can extend up to 1 year, and even fewer can last longer. More importantly, regardless of the duration, droughts have larger impacts during the crops' critical growth period. Corn and soybean have their critical growth periods during summer and are more sensitive to precipitation and soil moisture deficits than wheat, which has its critical growth period during spring. Quantification of the relation between the droughts' indicators during the crops' critical periods and detrended annual crop yields was performed. Large drought severity values during the crop-sensitive months result in significant crop yield losses. Results suggest that shorter-scale indicators during sensitive periods are more appropriate for predicting crop yield losses than the longer-scale indicators. This new approach can be helpful for regional decision-making systems that support planning by water managers and agricultural stakeholders.

This study assesses the capability of ten Coordinated Regional Climate Downscaling Experiment regional climate models to simulate the components of the Canadian fire weather index (FWI) system across South America. Model performance for the historical period (1951–2005) is evaluated against the Copernicus Emergency Management Service ERA5 reanalysis using correlation, root mean square error, bias, and inter-model variability as validation metrics. Future projections are analyzed using the time of emergence and global temperature of emergence frameworks under two representative concentration pathways (RCP4.5 and RCP8.5), to identify when and under which global warming levels fire-conducive conditions emerge beyond natural variability. Results show that FWI and the fine fuel moisture code reproduce observed variability most accurately (r > 0.70), while cumulative indices such as the drought code and Duff moisture code exhibit larger uncertainties linked to precipitation biases and long-term moisture processes. Projections indicate that extreme fire weather conditions (represented by the frequency of days exceeding the 95th percentile of FWI, FWI95d) emerge earliest and most extensively, particularly under the high-emission RCP8.5 scenario, with large areas of northern and central South America crossing emergence thresholds during the early years of the 2030s decade. In contrast, indices related to fire-season length (FWIfwsl) and seasonal severity (FWIfs) show delayed and spatially fragmented emergence patterns, reflecting their stronger dependence on persistent warming trends. A critical finding is that several regions, including southern Brazil, Paraguay, northern Argentina, and Bolivia, have already exceeded emergence thresholds during the historical period, signaling that shifts in fire-weather regimes are already underway. These results highlight the urgent need to strengthen fire management and adaptation strategies across South America, while emphasizing that limiting global warming below 2 °C would significantly delay and reduce the extent of emerging fire danger in the region.

This study evaluates the suitability of the European Space Agency Climate Change Initiative Combined Root-Zone Soil Moisture product (ESA CCI COM RZSM) for detecting agricultural flash droughts (AFDs) across southeastern South America (SESA) and assesses how satellite-based indicators capture their evolution and agricultural impacts. We identify AFDs using two complementary approaches based on RZSM percentiles and the Soil Water Deficit Index (SWDI). We compare AFD detection from ESA CCI COM RZSM against the fifth-generation European Centre for Medium-Range Weather Forecasts (ERA5) reanalysis RZSM over 1979–2022. To assess satellite-based representations of AFD evolution and impacts, we analyze satellite-derived RZSM, evapotranspiration (EVT), and three vegetation indicators—land surface water index, fraction of absorbed photosynthetically active radiation, and gross primary productivity—for two representative events. ESA CCI COM RZSM reproduces the main spatial patterns and seasonal cycles of AFD depicted by ERA5. However, it shows smoother temporal variability, delayed drying, and lower absolute RZSM, which may stem from its climatological rescaling and exponential filtering that propagates surface signals into deeper layers. Detection outcomes are highly sensitive to both methodology and dataset choice. The percentile-based approach tends to over-detect events in persistently wet or dry regimes. The SWDI-based method preserves regional hydroclimatic patterns and provides a more physically constrained representation of plant water stress. Satellite indicators capture the AFD progression, linking rapid RZSM depletion and reduced EVT to declines in vegetation productivity. The intensity and extent of impacts depend on antecedent SM and land cover, confirming the causal propagation of stress through the soil–plant–atmosphere system. Overall, the results demonstrate that ESA CCI COM RZSM, when combined with physically based indices and vegetation metrics, provides a robust, process-oriented foundation for AFD monitoring and early warning in SESA, where in situ observations are scarce.

Leptospirosis, the infectious disease caused by a spirochete bacteria, is a major public health problem worldwide. In Argentina, some regions have climatic and geographical characteristics that favor the habitat of bacteria of the Leptospira genus, whose survival strongly depends on climatic factors, enhanced by climate change, which increase the problems associated with people’s health. In order to have a method to predict leptospirosis cases, in this paper, five time series forecasting methods are compared: two parametric (autoregressive integrated moving average and an alternative one that allows covariates, ARIMA and ARIMAX, respectively), two nonparametric (Nadaraya-Watson Kernel estimator, one and two kernels versions, NW-1 K and NW-2 K), and one semiparametric (semi-functional partial linear regression, SFPLR) method. For this, the number of cases of leptospirosis registered from 2009 to 2020 in three important cities of northeastern Argentina is used, as well as hydroclimatic covariates related to the presence of cases. According to the obtained results, there is no method that improves considerably the rest and can be recommended as a unique tool for leptospirosis prediction. However, in general, the NW-2 K method gets a better performance. This work, in addition to using a long-term high-quality time series, enriches the area of applications of statistical models to epidemiological leptospirosis data by the incorporation of hydroclimatic variables, and it is recommended directing further efforts in this line of research, under the context of current climate change.

Droughts that occurred in selected areas located in homogeneous regions of South America during the austral springs (SON) and summers (DJF) from 1982 to 2019 are identified using the Standard Precipitation Index (SPI). Four areas were analyzed for droughts in SON, and three areas were analyzed for droughts in DJF. The areas in the Amazon suffered from the majority of their droughts during El Niño years, while most of the droughts in the areas of southern Brazil, Uruguay, and North Argentina occurred during La Niña years. In southeastern and central-western parts of Brazil, droughts occurred during both phases of El Niño-Southern Oscillation (ENSO) and also during neutral years. Thus, other processes besides ENSO are likely related to the observed droughts. The droughts were investigated for each area and month, and composites of atmospheric and oceanic variables during both seasons were analyzed for the selected cases. Regional and large-scale field composites were examined to identify the main processes associated with dry conditions in the different areas. Regional features were related to the influence of high pressure over southern and southeastern areas and the divergence of moisture flux in all areas. Meridional circulations contributed to subsidence over the dry regions. The large-scale influential features include SST anomalies, wavetrains over the South Pacific Ocean with centers of action over South America that produced subsidence in the study areas, and convection anomalies in the Maritime continent and surrounding areas. Therefore, the droughts were associated with a combination of regional and large-scale features that produced subsidence over the analyzed regions.