Unprecedented wet conditions are reported in the 2014 summer (December-March) in Southwestern Amazon, with rainfall about 100% above normal. Discharge in the Madeira River (the main southern Amazon tributary) has been 74% higher than normal (58 000 m 3 s −1 ) at Porto Velho and 380% (25 000 m 3 s −1 ) at Rurrenabaque, at the exit of the Andes in summer, while levels of the Rio Negro at Manaus were 29.47 m in June 2014, corresponding to the fifth highest record during the 113 years record of the Rio Negro. While previous floods in Amazonia have been related to La Niña and/or warmer than normal tropical South Atlantic, the 2014 rainfall and flood anomalies are associated with warm condition in the western Pacific-Indian Ocean and with an exceptionally warm Subtropical South Atlantic. Our results suggest that the tropical and subtropical South Atlantic SST gradient is a main driver for moisture transport from the Atlantic toward south-western Amazon, and this became exceptionally intense during summer of 2014.

The Andes is the longest cordillera in the world and extends from northern South America to the southern extreme of the continent (from 11 • N to 53 • S). The Andes runs through seven countries and is characterized by a wide variety of ecosystems strongly related to the contrasting climate over its eastern and western sides, as well as along its latitudinal extension. This region faces very high potential impacts of climate change, which could affect food and water security for about 90 million people. In addition, climate change represents an important threat on biodiversity, particularly in the tropical Andes, which is the most biodiverse region on Earth. From a scientific and societal view, the Andes exhibits specific challenges because of its unique landscape and the fragile equilibrium between the growing population and its environment. In this manuscript, we provide an updated review of the most relevant scientific literature regarding the hydroclimate of the Andes with an integrated view of the entire Andes range. This review paper is presented in two parts. Part I is dedicated to summarize the scientific knowledge about the main climatic features of the Andes, with emphasis on mean large-scale atmospheric circulation, the Andes-Amazon hydroclimate interconnections and the most distinctive diurnal and annual cycles of precipitation. Part II, which is also included in the research topic "Connecting Mountain Hydroclimate Through the American Cordilleras," focuses on the hydroclimate variability of the Andes at the sub-continental scale, including the effects of El Niño-Southern Oscillation.

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Abstract. This paper proposes a protocol to assess the space–time consistency of 12 satellite-based precipitation products (SPPs) according to various indicators, including (i) direct comparison of SPPs with 72 precipitation gauges; (ii) sensitivity of streamflow modelling to SPPs at the outlet of four basins; and (iii) the sensitivity of distributed snow models to SPPs using a MODIS snow product as reference in an unmonitored mountainous area. The protocol was applied successively to four different time windows (2000–2004, 2004–2008, 2008–2012 and 2000–2012) to account for the space–time variability of the SPPs and to a large dataset composed of 12 SPPs (CMORPH–RAW v.1, CMORPH–CRT v.1, CMORPH–BLD v.1, CHIRP v.2, CHIRPS v.2, GSMaP v.6, MSWEP v.2.1, PERSIANN, PERSIANN–CDR, TMPA–RT v.7, TMPA–Adj v.7 and SM2Rain–CCI v.2), an unprecedented comparison. The aim of using different space scales and timescales and indicators was to evaluate whether the efficiency of SPPs varies with the method of assessment, time window and location. Results revealed very high discrepancies between SPPs. Compared to precipitation gauge observations, some SPPs (CMORPH–RAW v.1, CMORPH–CRT v.1, GSMaP v.6, PERSIANN, and TMPA–RT v.7) are unable to estimate regional precipitation, whereas the others (CHIRP v.2, CHIRPS v.2, CMORPH–BLD v.1, MSWEP v.2.1, PERSIANN–CDR, and TMPA–Adj v.7) produce a realistic representation despite recurrent spatial limitation over regions with contrasted emissivity, temperature and orography. In 9 out of 10 of the cases studied, streamflow was more realistically simulated when SPPs were used as forcing precipitation data rather than precipitation derived from the available precipitation gauge networks, whereas the SPP's ability to reproduce the duration of MODIS-based snow cover resulted in poorer simulations than simulation using available precipitation gauges. Interestingly, the potential of the SPPs varied significantly when they were used to reproduce gauge precipitation estimates, streamflow observations or snow cover duration and depending on the time window considered. SPPs thus produce space–time errors that cannot be assessed when a single indicator and/or time window is used, underlining the importance of carefully considering their space–time consistency before using them for hydro-climatic studies. Among all the SPPs assessed, MSWEP v.2.1 showed the highest space–time accuracy and consistency in reproducing gauge precipitation estimates, streamflow and snow cover duration.