Seasonal predictions have a great socioeconomic potential if they are reliable and skillful. In this study, we assess the prediction performance of SEAS5, version 5 of the seasonal prediction system of the European Centre for Medium-Range Weather Forecasts (ECMWF), over South America against homogenized station data. For temperature, we find the highest prediction performances in the tropics during austral summer, where the probability that the predictions correctly discriminate different observed outcomes is 70%. In regions lying to the east of the Andes, the predictions of maximum and minimum temperature still exhibit considerable performance, while farther to the south in Chile and Argentina the temperature prediction performance is low. Generally, the prediction performance of minimum temperature is slightly lower than for maximum temperature. The prediction performance of precipitation is generally lower and spatially and temporally more variable than for temperature. The highest prediction performance is observed at the coast and over the highlands of Colombia and Ecuador, over the northeastern part of Brazil, and over an isolated region to the north of Uruguay during DJF. In general, Niño-3.4 has a strong influence on both air temperature and precipitation in the regions where ECMWF SEAS5 shows high performance, in some regions through teleconnections (e.g., to the north of Uruguay). However, we show that SEAS5 outperforms a simple empirical prediction based on Niño-3.4 in most regions where the prediction performance of the dynamical model is high, thereby supporting the potential benefit of using a dynamical model instead of statistical relationships for predictions at the seasonal scale.

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In the southern Peruvian Andes, communities are highly dependent on climatic conditions due to the mainly rain-fed agriculture and the importance of glaciers and snow melt as a freshwater resource. Longer-term trends and yearto-year variability of precipitation or temperature severely affect living conditions. This study evaluates seasonal precipitation and temperature climatologies and trends in the period 1965/66-2017/18 for the southern Peruvian Andes using quality-controlled and homogenized station data and new observational gridded data. In this region, precipitation exhibits a strong annual cycle with very dry winter months and most of the precipitation falling from spring to autumn. Spatially, a northeast-southwest gradient in austral spring is observed, related to an earlier start of the rainy season in the northeastern part of the study area. Seasonal variations of maximum temperature are weak with an annual maximum in austral spring, which is related to reduced cloud cover in austral spring compared to summer. On the contrary, minimum temperatures show larger seasonal variations, possibly enhanced through changes in longwave incoming radiation following the precipitation cycle. Precipitation trends since 1965 exhibit low spatial consistency except for austral summer, when in most of the study area increasing precipitation is observed, and in austral spring, when stations in the central-western region of the study area register decreasing precipitation. All seasonal and annual trends in maximum