Silvia Terzago focuses her research on climate system processes, with particular interest on the hydrological cycle and its representation in global and regional climate models. She is involved in modeling snowpack dynamics in mountain areas. The mismatch between the large scales at which the climate model information is available and the scales at which the information is desired led her to study downscaling methods. Beyond the study of dynamical downscaling techniques, she also contributed to develop a stochastic downscaling tool for precipitation data (RainFARM). She is interested in exploring climate variability and change over long time scales, both from in-situ, satellite and simulation datasets, with the aim of relating past and projected changes to possible impacts relevant to the society. She has recently expanded her interests to ecosystems and their vulnerability to climate change. In the frame of the H2020 ECOPOTENTIAL project she studied the impact of climate change in several protected areas in Europe and contributed to develop tools for predicting ecosystem behavior under different climate change scenarios. She is currently working on climate predictability at the seasonal scale and she develops climate services tools to predict snow depth evolution in Alpine areas for applications in the water management, energy and touristic sectors.