Hamlington-Milliff Research Group
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Earth-observing satellite data provide multi-scale perspectives on atmosphere-ocean systems in both global and regional contexts. Our research exploits the volume and precision of multi-platform data in conjunction with in-situ data and process models for particular phenomena in the earth system. Using methodologies like Bayesian Hierarchical Models (BHMs) and Cyclostationary Empirical Orthogonal Functions (CSEOFs), we test the limits of satellite and in-situ measurements of the atmosphere and ocean. In particular, we seek to develop and implement techniques that use satellite data in novel and innovative ways to obtain a better understanding of the earth system. Sample research includes sea-level reconstructions based on multi-variate historical datasets, regional and global ensemble surface wind dataset construction, ocean forecast model error analyses, Madden-Julian Oscillation studies, and tsunami detection and monitoring using satellite remote sensing.