Uncertainty Quantification and Assimilation for Efficient Coastal Ocean Forecasting

Uncertainty Quantification and Assimilation for Efficient Coastal Ocean Forecasting

Bayesian inference is commonly used to quantify and reduce modeling uncertainties in coastal ocean models by computing the posterior probability distribution function (pdf) of some uncertain quantities to be estimated conditioned on available observations. The posterior can be computed either direct...

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Bibliographic Details
Main Author: Siripatana, Adil
Other Authors: Hoteit, Ibrahim
Language:en
Published: 2019
Subjects:
Uncertainty Quantification
Data Assimilation
Coastal Ocean Forecast
Bayesian Inference
Manning’s n coefficients
Adaptive Mesh Refinement
Online Access:http://hdl.handle.net/10754/652463

Internet

http://hdl.handle.net/10754/652463

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