Central Chile, home to more than 10 million inhabitants, has experienced an uninterrupted sequence of dry years since 2010 with mean rainfall deficits of 20–40%. The so‐called Mega Drought (MD) is the longest event on record and with few analogues in the last millennia. It encompasses a broad area, with detrimental effects on water availability, vegetation and forest fires that have scaled into social and economical impacts. Observations and reanalysis data reveal that the exceptional length of the MD results from the prevalence of a circulation dipole‐hindering the passage of extratropical storms over central Chile—characterized by deep tropospheric anticyclonic anomalies over the subtropical Pacific and cyclonic anomalies over the Amundsen–Bellingshausen Sea. El Niño Southern Oscillation (ENSO) is a major modulator of such dipole, but the MD has occurred mostly under ENSO‐neutral conditions, except for the winters of 2010 (La Niña) and 2015 (strong El Niño). Climate model simulations driven both with historical forcing (natural and anthropogenic) and observed global SST replicate the south Pacific dipole and capture part of the rainfall anomalies. Idealized numerical experiments suggest that most of the atmospheric anomalies emanate from the subtropical southwest Pacific, a region that has experienced a marked surface warming over the last decade. Such warming may excite atmospheric Rossby waves whose propagation intensifies the circulation pattern leading to dry conditions in central Chile. On the other hand, anthropogenic forcing (greenhouse gases concentration increase and stratospheric ozone depletion) and the associated positive trend of the Southern Annular Mode also contribute to the strength of the south Pacific dipole and hence to the intensity and longevity of the MD. Given the concomitance of the seemingly natural (ocean sourced) and anthropogenic forcing, we anticipate only a partial recovery of central Chile precipitation in the decades to come.

An important goal of the Climate Variability and Predictability (CLIVAR) research on the American monsoon systems is to determine the sources and limits of predictability of warm season precipitation, with emphasis on weekly to interannual time scales. This paper reviews recent progress in the understanding of the American monsoon systems and identifies some of the future challenges that remain to improve warm season climate prediction. Much of the recent progress is derived from complementary international programs in North and South America, namely, the North American Monsoon Experiment (NAME) and the Monsoon Experiment South America (MESA), with the following common objectives: 1) to understand the key components of the American monsoon systems and their variability, 2) to determine the role of these systems in the global water cycle, 3) to improve observational datasets, and 4) to improve simulation and monthly-to-seasonal prediction of the monsoons and regional water resources. Among the recent observational advances highlighted in this paper are new insights into moisture transport processes, description of the structure and variability of the South American low-level jet, and resolution of the diurnal cycle of precipitation in the core monsoon regions. NAME and MESA are also driving major efforts in model development and hydrologic applications. Incorporated into the postfield phases of these projects are assessments of atmosphere–land surface interactions and model-based climate predictability experiments. As CLIVAR research on American monsoon systems evolves, a unified view of the climatic processes modulating continental warm season precipitation is beginning to emerge.

Since 2010 an uninterrupted sequence of dry years, with annual rainfall deficits ranging from 25 to 45 %, has prevailed in central Chile (western South America, 30–38° S). Although intense 1- or 2-year droughts are recurrent in this Mediterranean-like region, the ongoing event stands out because of its longevity and large extent. The extraordinary character of the so-called central Chile megadrought (MD) was established against century long historical records and a millennial tree-ring reconstruction of regional precipitation. The largest MD-averaged rainfall relative anomalies occurred in the northern, semi-arid sector of central Chile, but the event was unprecedented to the south of 35° S. ENSO-neutral conditions have prevailed since 2011 (except for the strong El Niño in 2015), contrasting with La Niña conditions that often accompanied past droughts. The precipitation deficit diminished the Andean snowpack and resulted in amplified declines (up to 90 %) of river flow, reservoir volumes and groundwater levels along central Chile and westernmost Argentina. In some semi-arid basins we found a decrease in the runoff-to-rainfall coefficient. A substantial decrease in vegetation productivity occurred in the shrubland-dominated, northern sector, but a mix of greening and browning patches occurred farther south, where irrigated croplands and exotic forest plantations dominate. The ongoing warming in central Chile, making the MD one of the warmest 6-year periods on record, may have also contributed to such complex vegetation changes by increasing potential evapotranspiration. We also report some of the measures taken by the central government to relieve the MD effects and the public perception of this event. The understanding of the nature and biophysical impacts of the MD helps as a foundation for preparedness efforts to confront a dry, warm future regional climate scenario.

We introduce the first catchment dataset for large sample studies in Chile. This dataset includes 516 catchments; it covers particularly wide latitude (17.8 to 55.0° S) and elevation (0 to 6993 m a.s.l.) ranges, and it relies on multiple data sources (including ground data, remote-sensed products and reanalyses) to characterise the hydroclimatic conditions and landscape of a region where in situ measurements are scarce. For each catchment, the dataset provides boundaries, daily streamflow records and basin-averaged daily time series of precipitation (from one national and three global datasets), maximum, minimum and mean temperatures, potential evapotranspiration (PET; from two datasets), and snow water equivalent. We calculated hydro-climatological indices using these time series, and leveraged diverse data sources to extract topographic, geological and land cover features. Relying on publicly available reservoirs and water rights data for the country, we estimated the degree of anthropic intervention within the catchments. To facilitate the use of this dataset and promote common standards in large sample studies, we computed most catchment attributes introduced by Addor et al. (2017) in their Catchment Attributes and MEteorology for Large-sample Studies (CAMELS) dataset, and added several others. We used the dataset presented here (named CAMELS-CL) to characterise regional variations in hydroclimatic conditions over Chile and to explore how basin behaviour is influenced by catchment attributes and water extractions. Further, CAMELS-CL enabled us to analyse biases and uncertainties in basin-wide precipitation and PET. The characterisation of catchment water balances revealed large discrepancies between precipitation products in arid regions and a systematic precipitation underestimation in headwater mountain catchments (high elevations and steep slopes) over humid regions. We evaluated PET products based on ground data and found a fairly good performance of both products in humid regions (r > 0.91) and lower correlation (r < 0.76) in hyper-arid regions. Further, the satellite-based PET showed a consistent overestimation of observation-based PET. Finally, we explored local anomalies in catchment response by analysing the relationship between hydrological signatures and an attribute characterising the level of anthropic interventions. We showed that larger anthropic interventions are correlated with lower than normal annual flows, runoff ratios, elasticity of runoff with respect to precipitation, and flashiness of runoff, especially in arid catchments. CAMELS-CL provides unprecedented information on catchments in a region largely underrepresented in large sample studies. This effort is part of an international initiative to create multi-national large sample datasets freely available for the community. CAMELS-CL can be visualised from http://camels.cr2.cl and downloaded from https://doi.pangaea.de/10.1594/PANGAEA.894885.