Research scientist
SMHI
Ramón is a climate researcher at the Swedish Meteorological and Hydrological Institute since 2016. Before, his current position he was a postdoctoral fellow at the International Centre for Theoretical Physics in Trieste, Italy where he carried out several regional and global studies using mainly the Regional Climate Model RegCM. He did his PhD at the Ensenada Center for Advanced Studies and Higher Education in Baja California, Mexico. His current lines of research are related to global climate variability and change, particularly on how global modes of variability impact the regional climate. Lately, he has started to work on implementing machine learning methods to climate science, particularly focusing on applying and developing ML methods for downscaling coarse resolution global model data to high resolution, which provides more detailed climate information for regional studies. He is also working on algorithms to detect extreme events from climate variables, using as predictors the current and previous states of the atmosphere. He is currently leading two work packages in the Horizon projects OptimESM and AI4PEX, applying ML methods for climate studies.