My research deals with creating forecasting models to predict the power production from variable renewable sources, such as solar and wind. As these resources become more integrated in power grids, grid managers need to know ahead of time how much energy those renewables will produce so that electric supply and demand can be properly balanced. This research is very interdisciplinary. For some projects, the models are mostly based on machine learning tools that treat the underlying physics as a black box. In other projects, we model atmospheric dynamics and predict wind and cloud patterns. In these cases, the research deals with some of the most complex and chaotic phenomena in nature, such as turbulence.