Numerical atmospheric modeling and simulation with both simplified models (e.g. barotropic) and state-of-the-art regional (WRF) and global (CAM) models
Development and deployment of earth science applications (e.g., global and regional climate models) to run in geographically distributed data and computing environments (GRID computing).
Analysis of nonlinear spatiotemporal dynamics in the atmosphere using simplified models (Lorenz96, barotropic, etc.), including theoretical aspects of error growth, predictability and ensemble forecasting, control and synchronization.
Técnicas de Minería de Datos, incluyendo redes Bayesianas y neuronales, y aplicaciones en meteorología y clima en problemas de diagnóstico y predicción
Statistical and machine learning techniques applied to local weather forecast by adapting the prediction of numerical models using statistical relationships obtained from historical records
Análisis de tendencias en el clima, escenarios de cambio climático, estimación de incertidumbres, proyección regional usando técnicas estadísticas y dinámicas