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The Application of Uncertainty Quantification Techniques and Information Theory to Oil Spill and Ocean Forecasting.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	The Application of Uncertainty Quantification Techniques and Information Theory to Oil Spill and Ocean Forecasting./
Author:	Wang, Shitao.
Description:	1 online resource (117 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.
Subject:	Physical oceanography. -
Online resource:	click for full text (PQDT)
ISBN:	9780355241624

The Application of Uncertainty Quantification Techniques and Information Theory to Oil Spill and Ocean Forecasting.
Wang, Shitao.

The Application of Uncertainty Quantification Techniques and Information Theory to Oil Spill and Ocean Forecasting. - 1 online resource (117 pages)

Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.

Thesis (Ph.D.)--University of Miami, 2017.

Includes bibliographical references

Quantifying uncertainties in ocean current forecasts is an important component of formulating a response to an oil spill, e.g. to compute the anticipated oil trajectories. Polynomial Chaos (PC) methods have recently been used to quantify uncertainties in the circulation forecast of the Gulf of Mexico caused by uncertain initial conditions and wind forcing data. The input uncertainties consisted of the amplitudes of perturbation modes whose space-time structure was obtained from Empirical Orthogonal Functions (EOF) decompositions. These efforts were the first to rely on a PC approach to efficiently quantify uncertainties in an ocean model, and as such have raised a number of issues that we wish to address, namely the realism of the perturbations, the effective choices in choosing the uncertain variables, the information trade-offs of the different uncertain input choices, and the ability to reduce these uncertainties if observational data is available.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355241624Subjects--Topical Terms:

1178843
Physical oceanography.
Index Terms--Genre/Form:

554714
Electronic books.

The Application of Uncertainty Quantification Techniques and Information Theory to Oil Spill and Ocean Forecasting.
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245 1 4 $a The Application of Uncertainty Quantification Techniques and Information Theory to Oil Spill and Ocean Forecasting.
264 0 $c 2017
300 $a 1 online resource (117 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.
500 $a Adviser: Mohamed Iskandarani.
502 $a Thesis (Ph.D.)--University of Miami, 2017.
504 $a Includes bibliographical references
520 $a Quantifying uncertainties in ocean current forecasts is an important component of formulating a response to an oil spill, e.g. to compute the anticipated oil trajectories. Polynomial Chaos (PC) methods have recently been used to quantify uncertainties in the circulation forecast of the Gulf of Mexico caused by uncertain initial conditions and wind forcing data. The input uncertainties consisted of the amplitudes of perturbation modes whose space-time structure was obtained from Empirical Orthogonal Functions (EOF) decompositions. These efforts were the first to rely on a PC approach to efficiently quantify uncertainties in an ocean model, and as such have raised a number of issues that we wish to address, namely the realism of the perturbations, the effective choices in choosing the uncertain variables, the information trade-offs of the different uncertain input choices, and the ability to reduce these uncertainties if observational data is available.
520 $a We explore whether these EOF-based perturbations lead to realistic representation of the uncertainties in the circulation forecast of the Gulf of Mexico. We also use information theoretic metrics to quantify the information gain and the computational trade-offs between different wind forcing and initial condition EOF modes. Surface and subsurface model data comparisons show that the observational data falls within the envelope of the ensemble simulations and that the EOF decompositions deliver "realistic'' perturbations in the Loop Current region. The result of the computational trade-offs indicate that two initial condition EOF modes are enough to represent the uncertainties in the Loop Current region; while wind forcing EOF modes are necessary in order to capture uncertainties in the coastal zone. This result is consistent with the global sensitivity analysis.
520 $a The ensemble statistics are then explored using the PC approach and the newly developed contour boxplot method. Specifically, the contour boxplot is used to identify the most representative ensemble member and the outliers. The full probability density functions of sea surface height are estimated using the PC method. With 20 years of satellite observations, the predictability in the circulation forecast of the Gulf of Mexico is investigated using information theory.
520 $a Finally, we update our knowledge about the uncertain inputs using along track satellite observations. The best initial perturbations are found using the Bayesian optimization approach and the full posterior distributions of the uncertain inputs are estimated using the Bayesian inference framework.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Physical oceanography. $3 1178843
655 7 $a Electronic books. $2 local $3 554714
690 $a 0415
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of Miami. $b Meteorology and Physical Oceanography - Marine. $3 1186122
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10618559 $z click for full text (PQDT)