Dr. Mejia's research makes strong emphasis on areas associated with observing, understanding, modeling, and predicting weather and climate at different spatial and temporal scales. He works on developing methods for representing uncertainty in regional models, and tailoring simulated output for impact applications. Dr. Mejia's focus involves the development of a regional climate modeling framework for the Western U.S. using Weather Research Forecasting Model (WRF) and the NCAR's Community Earth System Model to study the impacts of the global and regional aspects of climate change over the complex terrain, and source identification related to systematic errors in climate models. He has extensive experience in development and operation of multi-dimensional and ensemble forecasting models, observational and model data processing, data assimilation, and in the research areas of improvement in atmospheric modeling. Experience operating atmospheric models of different generations to investigate atmospheric dynamics and moist processes; real-time weather forecasting; atmospheric flows over complex terrain and air quality and dispersion m

climate modeling, weather forecasting, north american monsoon, interannual and intraseasonal variability, atmospheric dynamics, dynamical downscaling, hydroclimate, hydrometeorology, urban canopy modeling, air dispersion modeling, energy and water.