This study describes the performance of five gridded data sets in reproducing precipitation and/or temperature over the complex terrain in the high Chilean Andes. The relationship of instrumental observations and the gridded data sets with climate modes of variability and the trends of indices of climate extremes are also explored between the period 1980-2015. The mismatches between gridded data sets are larger in northern and southern regions in relation to precipitation, while for temperature, disagreement is higher in central region. However, better results are delivered by the Climatic Research Unit and Global Precipitation Climatology Centre followed by Re-Analysis Interim Project. The El Niño Southern Oscillation and Pacific Decadal Oscillation indices are well correlated with precipitation in North and South Chile. Additional, trend analyses reveal a significant downward (upward) tendency for precipitation (temperature), especially in central region, delivered by observed and the majority of gridded data sets. Furthermore, the consecutive number of dry days is increasing in all regions at the annual scale. This study allows a better understanding of the capacity of global data sets and thus contributes to further climate research within this Andean region.

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This study evaluates the skill of the Weather Research and Forecasting (WRF) model to reproduce the variability of precipitation over the Central Andes of Chile and Argentina, a region characterized by complex topography. The simulation corresponds to a dynamical downscaling of ERA-Interim, in the period between 1996 and 2015, performed with two nested grids, at 9 and 3 km horizontal resolution. Precipitation data from 62 rain gauges from Chile and Argentina were used to evaluate the performance of WRF simulations carried out at the annual and warm-cold season analysis. The results of this study indicate that WRF at 9 and 3 km is able to reproduce the main characteristics of seasonal and interannual precipitation variability along the study area. On the windwards slopes of the Andes, however, WRF at 9 km presents a wet bias in relation to observation and WRF at 3 km. Additionally, WRF at 3 km achieves better performance of precipitation as elevation increases, most likely due to the better-resolved topography. To our knowledge, this is the first study that compares performance between nested domains on mountain areas that found a better match between the model and observations, as elevations increased.

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