MSc in Atmospheric Science - Computational Geosciences in Davis United States | University of California Davis

Atmospheric science explores the physics, chemistry, and behavior of Earth's atmosphere and its interactions with water systems and living organisms. Students develop expertise in areas like air quality, weather patterns, atmospheric chemistry, microclimate processes, biological weather interactions, climate systems, regional meteorology, global atmospheric movements, and computer-based weather forecasting. Graduates acquire both theoretical and practical skills needed for academic and research careers focused on atmospheric chemistry and dynamics, including their connections to aquatic and biological systems. The Atmospheric Science Graduate Group provides Master's and Doctoral programs, allowing students to specialize in disciplines such as air quality meteorology, atmospheric chemistry, cloud physics, biological meteorology, microclimate studies, weather prediction modeling, remote sensing, climate systems, global atmospheric patterns, regional and boundary-layer meteorology, computational earth sciences, severe weather events, and climate change effects. Faculty members' broad expertise enables cross-disciplinary education and investigation.

UC Davis's Computational Geosciences program concentrates on creating and applying regional and global climate and weather models, along with related simulation tools, to enhance comprehension of atmospheric events and refine forecasting methods. With computing capabilities growing dramatically in recent years, substantial research efforts now focus on developing software that leverages these technological advances. A key priority involves designing atmospheric models that can efficiently utilize systems with tens or hundreds of thousands of processors. Consequently, researchers dedicate considerable attention to implementing contemporary numerical methods for atmospheric simulation, creating systems to integrate observational data into predictive models, and developing techniques for handling massive climate datasets.