@article{
 title = {Proposing a Hydrodynamic Forecast System for San Quintin Bay Via Data Assimilation Scheme},
 type = {article},
 year = {2017},
 keywords = {bay via data assimilation,corresponding author,proposing a hydrodynamic forecast,system for san quintin},
 id = {3b42e8c9-68f6-34ed-8387-2a1808b0acc6},
 created = {2016-04-28T20:06:59.000Z},
 file_attached = {false},
 profile_id = {ef52f833-b61a-3930-8f4c-9bf1e2e805d7},
 group_id = {21e763bb-7c4c-325f-8f40-0dcc50aa6eda},
 last_modified = {2017-06-30T18:45:12.849Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Garcia2015c},
 private_publication = {false},
 abstract = {A Delft3D model was implemented for the study of the hydrodynamics of San Quintin Bay. Calibration and validation have been successfully executed in previous research, but uncertainties propagated through simulation of future conditions are mostly unknown, and have not been tested in this region. Data Assimilation (DA) techniques play an important role, as their mathematical methods depict algorithms for combining dynamical system observations, implement computational models describing their evolution, and any relevant prior information. The aim of this study was to make a comparative analysis of calibration methods versus DA, as well as evaluate the predictive capability of a model using sea surface height and current measurements taken within the bay. Delft3D-OpenDA is considered an effective a tool for delivering real-time forecasting via employment of the ensemble Kalman filter algorithm, and this automatic procedure is expected to obtain an improved model forecast. We anticipate an ensemble size of between 40 and 60 will provide the optimal and most accurately predicted water levels for San Quintin Bay by assimilating a few observations located at the bay's entry. New computational challenges will also be addressed, as well as means of reducing the computational costs of these implementations.},
 bibtype = {article},
 author = {Garcia, Mariangel and Ramirez, I. and Verlaan, Martin and Blanco, Rafael and Castillo, Jose E.},
 journal = {To be submitted}
}

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We anticipate an ensemble size of between 40 and 60 will provide the optimal and most accurately predicted water levels for San Quintin Bay by assimilating a few observations located at the bay's entry. New computational challenges will also be addressed, as well as means of reducing the computational costs of these implementations.","bibtype":"article","author":"Garcia, Mariangel and Ramirez, I. and Verlaan, Martin and Blanco, Rafael and Castillo, Jose E.","journal":"To be submitted","bibtex":"@article{\n title = {Proposing a Hydrodynamic Forecast System for San Quintin Bay Via Data Assimilation Scheme},\n type = {article},\n year = {2017},\n keywords = {bay via data assimilation,corresponding author,proposing a hydrodynamic forecast,system for san quintin},\n id = {3b42e8c9-68f6-34ed-8387-2a1808b0acc6},\n created = {2016-04-28T20:06:59.000Z},\n file_attached = {false},\n profile_id = {ef52f833-b61a-3930-8f4c-9bf1e2e805d7},\n group_id = {21e763bb-7c4c-325f-8f40-0dcc50aa6eda},\n last_modified = {2017-06-30T18:45:12.849Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Garcia2015c},\n private_publication = {false},\n abstract = {A Delft3D model was implemented for the study of the hydrodynamics of San Quintin Bay. 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