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This work proposes a probabilistic forecast of seasonal precipitation in the basins of the Limay, Neuquén, and Negro rivers in the north of Argentine Patagonia. The Comahue region is particularly important because part of the country's hydroelectric energy is generated there. The amount of winter precipitation modulates the flow of rivers, and therefore, prior knowledge of possible precipitation thresholds is very useful for decision-makers. Ensembles made up of statistical models that explain more than 50% of the precipitation were used and were generated with multiple techniques such as linear regression, generalized additive models, support vector regression, and artificial neural networks. The result showed that the forecasts are better in Limay and Neuquén river basins in winter than in Negro River basin. Brier Skill Score values indicate that the probabilistic forecast is better than the climatology in winter, in Neuquén and Limay basins for below and above normal categories. [ABSTRACT FROM AUTHOR]

This study provides a regional assessment of mean and extreme temperature and precipitation over South America south of 20°S under global warming of 1.5 °C, 2 °C, and 3 °C above pre-industrial level. A particular analysis is performed over four sub-regions: southeastern South America (SESA), Pampa, southern Patagonia (SPat), and northern Patagonia (NPat), where special interest is given to the differences in impacts between the global warming targets under analysis. Results indicate that the ongoing global warming will maintain and even stress the observed trends in the region. SESA is the region projected to experience the largest increases in both mean and extreme temperature and precipitation, and the magnitude of change becomes larger under the warmer global warming targets. The Patagonian regions are expected to suffer robust reductions in the frequency of frost days (fd) and ice days (id), and there appears to be a relationship between the target and the magnitude of decrease in fd and id over these regions. The present study shows that the degree of global warming will play a key role in determining the intensity and frequency of the climate extremes which could significantly affect the socio-economic activities in the selected climatic sensitive regions over southern South America. [ABSTRACT FROM AUTHOR]

Changes in thermal and hydric patterns affect crop growth. This research is aimed to assess temporal and spatial trends of 18 climatic and agro-climatic thermal and hydric indices in the north of Argentine Patagonia (39°–44°, south latitude), to establish the current and potential suitability of this region for agriculture in a context of climate change. The period of study was 1970–2016, and it was focused on the last 20 years. Regional warming was indicated by the average increases of annual mean temperature (+ 0.2 °C decade−1), mean maximum temperature of the warm trimester (+ 0.3 °C decade−1), and extreme maximum temperature of the warmest month (+ 0.6 °C decade−1) during 1970–2016. This trend was also found in the 1996–2017 period. Mean minimum temperature of the cold trimester showed an uneven spatial and temporal trend, with increasing temperatures during 1970–2016 (+ 0.1 °C decade−1), but a negative trend (− 0.1 °C decade−1) over the last 20 years, which leads to an increasing regional trend in temperature amplitude. Negative trends in extreme minimum temperatures of April (− 0.3 °C decade−1), July and October (− 0.2 °C decade−1) imply more significant risks of cold damage for crops that exhibit sensitive phenological stages during this time. Thermal agro-climatic indices showed negative trends in winter chill (− 15.8 chill hours decade−1 considering the Weinberger method and − 20.8 chill hours decade−1 using Sharpe method) and higher accumulation of warm semester growing degree days (+ 38.8 GDD5 °C and + 32.3 GDD10 °C decade−1). Climatic and agro-climatic water indices showed that most of the region experienced decreasing water availability, mainly in the central-south and Andean subregions, showing annual precipitation trends of − 11.5 and − 31.2 mm decade−1, respectively). If these thermal and hydric trends are maintained in the future, the region will evolve into an area of greater energetic availability but with some restrictions: lower winter chill that would affect very high-chill cultivars cultivated in the warmest regions, higher risk of extreme thermal events during crucial phenological periods of specific crops, and decreasing water availability that would mainly affect dryland farming and river basin recharge. [ABSTRACT FROM AUTHOR]

The current study presents an assessment of the impact of climate change on water yield, one of the main hydrological ecosystem services, in northern Patagonia. The outputs of regional climate models from the CORDEX Project for South America were used to drive the InVEST water yield model. CORDEX regional climate models project for the far future (2071–2100) an increase in temperature higher than 1.5 °C and a precipitation decrease ranging from − 10 to − 30% for the study area. The projected warmer and dryer climate emerges as a robust signal based on model agreement and on consistent physical drivers of these changes. Moreover, both the projected increase in evapotranspiration and the decrease in precipitation contribute to a strong decrease in water yield of around − 20 to − 40% in the headwaters of northern Patagonian watersheds. Comparison of the results in the two basins reveals that the land cover may be considered a buffer of water yield changes and highlights the key role of protected areas in reducing the vulnerability of water resources to climate change. [ABSTRACT FROM AUTHOR]

The persistence and long-term memories in daily maximum and minimum temperature series during the instrumental period in southern South America were analysed. Here, we found a markedly seasonal pattern both for short- and long-term memories that can lead to enhanced predictability on intraseasonal timescales. In addition, well-defined spatial patterns of these properties were found in the region. Throughout the entire region, the strongest dependence was observed in autumn and early winter. In the Patagonia region only, the temperatures exhibited more memory during the spring. In general, these elements indicate that nonlinear interactions exist between the annual cycles of temperature and its anomalies. Knowledge of the spatiotemporal behaviour of these long-term memories can be used in the building of stochastic models that only use persistence. It is possible to propose two objective forecast models based on linear interactions associated with persistence and one that allows for the use of information from nonlinear interactions that are manifested in the form of forerunners. [ABSTRACT FROM AUTHOR]