Morphodynamic data assimilation used to understand changing coasts
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Abstract
Morphodynamic data assimilation blends observations with model predictions and comes in many forms, including linear regression, Kalman filter, brute-force parameter estimation, variational assimilation, and Bayesian analysis. Importantly, data assimilation can be used to identify sources of prediction errors that lead to improved fundamental understanding. Overall, models incorporating data assimilation yield better information to the people who must make decisions impacting safety and wellbeing in coastal regions that experience hazards due to storms, sea-level rise, and erosion. We present examples of data assimilation associated with morphologic change. We conclude that enough morphodynamic predictive capability is available now to be useful to people, and that we will increase our understanding and the level of detail of our predictions through assimilation of observations and numerical-statistical models.
Publication type | Conference Paper |
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Publication Subtype | Conference Paper |
Title | Morphodynamic data assimilation used to understand changing coasts |
DOI | 10.1142/9789814689977_0244 |
Year Published | 2015 |
Language | English |
Publisher | World Scientific Publishing Company |
Contributing office(s) | St. Petersburg Coastal and Marine Science Center |
Conference Title | Coastal Sediments 2015 |
Conference Location | San Diego, CA |
Conference Date | May 11-15, 2015 |
Google Analytic Metrics | Metrics page |