The inherent variability of marine and atmospheric systems is due in part to the complexity of nonlinear interactions that occur in a coupled ocean/atmosphere system. Analytical and numerical models, particularly those that use multi-dimensional numerical simulations, have become powerful tools for analysis of such systems. Applications of such models range from optimizing environmental remediation and restoration, to coastal and watershed development, to fisheries management. Models of marine systems have traditionally emphasized physical components including fluid motions; energy, heat and salinity budgets; interactions with atmospheric forcing; and paleoclimatic changes. More modern state-of-the-art models now also include primary and secondary production, biomass distribution, hydrological cycling, air/sea gas exchange, and nutrient and contaminant distributions. Global scale models are used to understand past, present, and future global changes in the ocean-atmosphere system. Data assimilation has become an essential element of state-of -the-art models that are used for system forecasting. Observational data are used for establishing initial and boundary conditions and updating model fields in many cases in real time. Historical and real-time data is obtained from remote and in situ sensors that are deployed in operational and experimental configurations.

The MASMA Option will provide a framework in which students can learn the skills required to develop and implement interdisciplinary models, as well as use them for the analysis of marine and/or atmospheric systems. MASMA students will be expected to become familiar with basic concepts in physical, biological, and chemical oceanography; atmospheric sciences, and measurements. MASMA student research will focus in one or more of the following areas: Atmosphere-Ocean coupling, oceanic modeling, atmospheric modeling, weather/climate variability, ecosystem modeling/analysis, environmental modeling/analysis, spatial/temporal variability in marine and/or atmospheric systems, realistic simulation and prediction, chemical, biological, and physical process modeling, data assimilation techniques, model/data synthesis, numerical/analytical synthesis, theoretical/numerical synthesis, interdisciplinary/integrative modeling, data acquisition and modeling, data systems development, and information management systems development.