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We analyze the variability and changes in mean temperature, annual precipitation, and snow water equivalent (SWE) in the Desaguadero-Salado-Chadileuvú-Curacó (DSCC) basin, observed in a recent period, and their projected future values. The current climate and observed changes are studied based on the scarce observation records available in the region. Simulations from the High-Resolution Model Intercomparison Project (HighResMIP v1.0) are used for the analysis of future climate projections. The mean annual temperature presents a major rise between 1 and 2 °C throughout the region in the 1961–2020 period. The annual precipitation has nonlinear positive trends of varied importance. The SWE has decreased noticeably since 2010. Interannual variability also plays a key role, with dominant cycles between 2.8 and 4 years and between 7.5 and 10 years. The projected changes, computed as the difference between the 1985–2014 and 2021–2050 averages, reveal a rise in mean annual temperature in the entire basin, with an eastward magnitude increase from 1 to more than 2 °C. The annual precipitation is projected to increase up to 10% over most of the basin, except in the Andes, where it will decrease. The maximum annual SWE will also continue to decrease, in agreement with the trend observed in recent years. [ABSTRACT FROM AUTHOR]

This study reassesses the spatiotemporal variability of and changes in extreme precipitation events (EPEs) and examines the response of soil moisture and water table depth to EPEs in Argentina's core crop region. Standardized nonparametric indices are applied to precipitation, soil moisture, and groundwater. The temporal variability of EPEs exhibits a decadal cycle and inter-annual modes with dominant frequencies between 2.5 and 4 years related to El Niño Southern Oscillation periodicities. The soil moisture and water table depth respond to precipitation variability replicating both decadal and inter-annual EPE variability. The response of soil moisture to EPEs attenuates in time as soil depth increases. Water table depth responds to EPEs with an average delay of 10 months. In recent decades, soil moisture increases (water table depth becomes shallower) rapidly when reacting to excess precipitation, while soil moisture decreases (water table depth deepens) slowly during and after drought events. [ABSTRACT FROM AUTHOR]

This study assesses the intensity, spatial distribution and temporal variability of extreme precipitation events (EPEs) on different time scales relevant to agriculture and water resources during the 1901–2016 period over Argentina's Austral Chaco (ACh). EPEs were identified using a nonparametric approach for the Standardized Precipitation Index (SPI). The leading modes of SPI's variability were detected using the Singular Spectrum Analysis. We also compile and control the quality of precipitation observations in a scarcely monitored region. The limited number of stations conditions the interpolation of the GPCC v2018 database here used, mainly during the early twentieth century. The EPEs characterized by SPI at a 24‐month time scale, which favour long‐lasting water excesses or deficits with hydrological impacts, underwent two differentiated long‐term periods: a dry one before 1960 and a wet one from 1960 to 2005. Consistently, seasonal wet EPEs were more frequent during the wet period while seasonal droughts were more frequent and with larger spatial extent during the dry period. Seasonal EPEs, represented by the SPI at 3‐month time scale, can impact agriculture during the crops' critical growth period. Since 2006, the long‐term wetting trend has been reversed. If this behaviour continues into the coming decades, more droughts and less wetness might be expected. The EPEs present a large interannual variability with 6.3‐ and 9‐year significant cycles that, combined with long‐term trends, favoured extremely wet/dry EPEs. Most of the wet/dry EPEs occurred during El Niño/La Niña events. Although this relationship is not straightforward, we found a discriminant ENSO signal between October of the year when an ENSO event starts and February of the next year. Finally, severely dry/wet EPEs tend to have large spatial extent in the ACh region. The central‐eastern ACh region experiences the most extreme wet and dry conditions, which makes this area more prone to extreme EPEs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Changes in climate extremes affect socioeconomics and natural systems in northeastern Argentina (NEA) and may increase its vulnerability leading to unprecedented disasters. This study investigates the long-term changes and interannual variability of daily temperature and precipitation climate extremes and assesses to what extent global reanalyses reproduce the observed variability in the recent past. Datasets include quality-controlled observations (1963–2013) and ERA-Interim and NCEP2 reanalyses (1979–2011). Climate extremes are characterized spatially and temporally by 15 indices proposed by the Expert Team on Climate Change Detection and Indices. The leading modes of the area-averaged index time series were obtained by means of a Singular Spectrum Analysis, while the spatial distribution of mean changes was estimated by fitting nonparametric linear trends to each index time series. The results show that temperature extremes are changing towards warmer conditions. The number of warm days has been increasing since 1990 while the number of cold days has been decreasing. Warm and cold nights show a significant signal of warming that seems to be stabilizing in recent decades. Heat waves almost double the frequency and duration of cold waves, and the duration of heat waves increased while cold spells decreased in last decades. Longer heat waves are related to longer dry spells. On the other hand, the number of frost days remained stable although they exhibit high interannual and decadal variability. As well, intense precipitation events in most of the region increased steadily since 1970. The annual maximum amount of 1-day and 5-day precipitation events increased from the 1970s to the 2000s, stabilizing in recent years. The ERA-Interim and NCEP2 reanalyses represent climate extremes with different success. ERA-Interim can recognize temperature extremes in time and space, while the older NCEP2 presents systematic positive errors and has some difficult to replicate the interannual variability of the number of summer days. Both reanalyses reproduce dry spells and the annual maximum 5-day precipitation with large biases, which are particularly noticeable at each observation station. Although reanalyses would be expected to add information for climate extremes in areas of scarce observations like northeastern Argentina, they still need to be used with great caution and only as a complement to observations, especially in studies focusing on precipitation extremes. [ABSTRACT FROM AUTHOR]

ABSTRACT: It is generally agreed that models that better simulate historical and current features of climate should also be the ones that more reliably simulate future climate. This article describes the ability of a selection of global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) to represent the historical and current mean climate and its variability over northeastern Argentina, a region that exhibits frequent extreme events. Two types of simulations are considered: Long‐term simulations for 1901–2005 in which the models respond to climate forcing (e.g. changes in atmospheric composition and land use) and decadal simulations for 1961–2010 that are initialized from observed climate states. Monthly simulations of precipitation and temperature are statistically evaluated for individual models and their ensembles. Subsets of models that best represent the region's climate are further examined. First, models that have a Nash–Sutcliffe efficiency of at least 0.8 are taken as a subset that best represents the observed temperature fields and the mean annual cycle. Their temperature time series are in phase with observations (r > 0.92), despite systematic errors that if desired can be corrected by statistical methods. Likewise, models that have a precipitation Pearson correlation coefficient of at least 0.6 are considered that best represent regional precipitation features. GCMs are able to reproduce the annual precipitation cycle, although they underestimate precipitation amounts during the austral warm season (September through April) and slightly overestimate the cold season rainfall amounts. The ensembles for the subsets of models achieve the best evaluation metrics, exceeding the performance of the overall ensembles as well as those of the individual models. [ABSTRACT FROM AUTHOR]

The core crop region of the Humid Pampa is one of the most productive agricultural lands around the world and depends highly on climate conditions. This study assesses climate variability, climate extremes, and observed and projected climate changes there, using 1911–2019 observations and CMIP5 model simulations. Since 1970, the annual mean temperature has risen by 1 °C and the mean annual minimum and maximum temperatures by 2 and 0.5 °C, respectively. The frequency of warm days and nights increased, and cold days and nights decreased. Heatwaves became longer and more intense, and cold waves decreased with less frost events. Annual precipitation increased by 10% from 1911, mainly in summer, and years with excess precipitation outnumbered those with a deficit. Both intense precipitation events and consecutive dry days grew, suggesting more annual precipitation falling on fewer days. Projections show a warming of 1 °C by 2035, regardless of the scenario. From then on until 2100, mean temperature will increase by 2 and 3–3.5 °C in the RCP4.5 and RCP8.5 scenarios, respectively. Annual precipitation will grow 8 and 16% from current values by 2100 in the RCP4.5 and RCP8.5 scenarios, respectively. No major precipitation changes are projected in the RCP2.6 scenario. [ABSTRACT FROM AUTHOR]

Climate in northeastern Argentina poses great challenges to the population that needs to cope with extreme events. Climate variability and changes are leading to an increased vulnerability which in turn can produce unprecedented disasters. This study investigates the long-term changes and interannual variability of daily temperature and precipitation extremes, discusses their impacts on agriculture and human settlements, and assesses to what extent global reanalyses reproduce the observed variability. Climate extremes are characterized in space and time by relevant indices, like those proposed by the Expert Team on Climate Change Detection and Indices. The leading modes of variability were detected with spectral analysis, and their spatial distribution was assessed through nonparametric trends. The results confirm that temperature extremes are changing towards warmer conditions. Since 1990 the number of warm days has been increasing, while the number of cold days has been decreasing. Likewise, warm and cold nights show a significant signal of warming, although the trend seems to be stabilizing in recent decades. The duration of heat spells increased while cold spells decreased in recent decades. At present, heat spells almost double the frequency and duration of cold spells. Longer heat spells are associated with longer dry spells impacting a region where intense agricultural activity is rainfed. Changes in temperature regimes are important for agriculture when the spells agree with the crops' critical periods. The growth periods of maize and sunflower are sensitive to the increase of warm days, leading to a reduction of their yields. On the other hand, the decrease in cold nights shortens crops' critical growth periods reducing wheat and barley yields. Likewise, the decrease of cold days may reduce the flowering and yield of winter wheat. More relevant for health, the longer duration of heat waves may increase the population mortality risk by heat strokes and produce more frequent collapses of energy systems. Intense precipitation events in most of the region increased steadily since 1970. The intensity and frequency of annual maximum 1-day and 5-day precipitation events increased from the 1970s to the 2000s, stabilizing in recent years. The increased intensity of heavy precipitation events constitutes a growing risk for urban settlements where heavy rainfall may exceed the capacity of drainage systems, causing significant infrastructure losses and, in the most extreme cases, deaths. Intense precipitation events in the predominantly flat agricultural plains lead to extensive waterlogging with significant economic impacts due to loss of crops and decreased livestock productivity. A similar analysis based on reanalysis data (ERA-Interim and NCEP2 reanalysis) reveals mixed results. ERA-Interim can recognize temperature extremes in time and space, while the older NCEP2 presents systematic biases. Both reanalyses reproduce dry spells and the annual maximum 5-day precipitation with large biases, which are particularly noticeable at each observation station. Although reanalyses would be expected to add information for climate extremes in areas of scarce observations, they still need to be used with great caution and only as a complement to observations. [ABSTRACT FROM AUTHOR]