Quasi-3D Statistical Inversion of Oceanographic Tracer Data

We perform a quasi-3D Bayesian inversion of oceanographic tracer data from the South Atlantic Ocean. Initially we are considering one active neutral density layer with an upper and lower boundary. The available hydrographic data is linked to model parameters (water velocities, diffusion coefficients...

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Other Authors: Herbei, Radu (authoraut)
Format: Others
Language:English
English
Published: Florida State University
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Online Access:http://purl.flvc.org/fsu/fd/FSU_migr_etd-4101
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spelling ndltd-fsu.edu-oai-fsu.digital.flvc.org-fsu_1822962020-06-13T03:07:12Z Quasi-3D Statistical Inversion of Oceanographic Tracer Data Herbei, Radu (authoraut) Speer, Kevin (professor co-directing dissertation) Wegkamp, Marten (professor co-directing dissertation) Laurent, Louis St. (outside committee member) Huffer, Fred (committee member) Niu, Xufeng (committee member) Department of Statistics (degree granting department) Florida State University (degree granting institution) Text text Florida State University Florida State University English eng 1 online resource computer application/pdf We perform a quasi-3D Bayesian inversion of oceanographic tracer data from the South Atlantic Ocean. Initially we are considering one active neutral density layer with an upper and lower boundary. The available hydrographic data is linked to model parameters (water velocities, diffusion coefficients) via a 3D advection-diffusion equation. A robust solution to the inverse problem considered can be attained by introducing prior information about parameters and modeling the observation error. This approach estimates both horizontal and vertical flow as well as diffusion coefficients. We find a system of alternating zonal jets at the depths of the North Atlantic Deep Water, consistent with direct measurements of flow and concentration maps. A uniqueness analysis of our model is performed in terms of the oxygen consumption rate. The vertical mixing coefficient bears some relation to the bottom topography even though we do not incorporate that into our model. We extend the method to a multi-layer model, using thermal wind relations weakly in a local fashion (as opposed to integrating the entire water column) to connect layers vertically. Results suggest that the estimated deep zonal jets extend vertically, with a clear depth dependent structure. The vertical structure of the flow field is modified by the tracer fields over that set a priori by thermal wind. Our estimates are consistent with observed flow at the depths of the Antarctic Intermediate Water; at still shallower depths, above the layers considered here, the subtropical gyre is a significant feature of the horizontal flow. A Dissertation submitted to the Department of Statistics in partial fulfillment of the requirements for the degree of Doctor of Philosophy. Summer Semester, 2006. May 12, 2006. Inverse Problem, Bayesian Approach, Advection-Diffusion, Thermal Wind Includes bibliographical references. Kevin Speer, Professor Co-Directing Dissertation; Marten Wegkamp, Professor Co-Directing Dissertation; Louis St. Laurent, Outside Committee Member; Fred Huffer, Committee Member; Xufeng Niu, Committee Member. Statistics Probabilities FSU_migr_etd-4101 http://purl.flvc.org/fsu/fd/FSU_migr_etd-4101 This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). The copyright in theses and dissertations completed at Florida State University is held by the students who author them. http://diginole.lib.fsu.edu/islandora/object/fsu%3A182296/datastream/TN/view/Quasi-3D%20Statistical%20Inversion%20of%20Oceanographic%20Tracer%20Data.jpg
collection NDLTD
language English
English
format Others
sources NDLTD
topic Statistics
Probabilities
spellingShingle Statistics
Probabilities
Quasi-3D Statistical Inversion of Oceanographic Tracer Data
description We perform a quasi-3D Bayesian inversion of oceanographic tracer data from the South Atlantic Ocean. Initially we are considering one active neutral density layer with an upper and lower boundary. The available hydrographic data is linked to model parameters (water velocities, diffusion coefficients) via a 3D advection-diffusion equation. A robust solution to the inverse problem considered can be attained by introducing prior information about parameters and modeling the observation error. This approach estimates both horizontal and vertical flow as well as diffusion coefficients. We find a system of alternating zonal jets at the depths of the North Atlantic Deep Water, consistent with direct measurements of flow and concentration maps. A uniqueness analysis of our model is performed in terms of the oxygen consumption rate. The vertical mixing coefficient bears some relation to the bottom topography even though we do not incorporate that into our model. We extend the method to a multi-layer model, using thermal wind relations weakly in a local fashion (as opposed to integrating the entire water column) to connect layers vertically. Results suggest that the estimated deep zonal jets extend vertically, with a clear depth dependent structure. The vertical structure of the flow field is modified by the tracer fields over that set a priori by thermal wind. Our estimates are consistent with observed flow at the depths of the Antarctic Intermediate Water; at still shallower depths, above the layers considered here, the subtropical gyre is a significant feature of the horizontal flow. === A Dissertation submitted to the Department of Statistics in partial fulfillment of the requirements for the degree of Doctor of Philosophy. === Summer Semester, 2006. === May 12, 2006. === Inverse Problem, Bayesian Approach, Advection-Diffusion, Thermal Wind === Includes bibliographical references. === Kevin Speer, Professor Co-Directing Dissertation; Marten Wegkamp, Professor Co-Directing Dissertation; Louis St. Laurent, Outside Committee Member; Fred Huffer, Committee Member; Xufeng Niu, Committee Member.
author2 Herbei, Radu (authoraut)
author_facet Herbei, Radu (authoraut)
title Quasi-3D Statistical Inversion of Oceanographic Tracer Data
title_short Quasi-3D Statistical Inversion of Oceanographic Tracer Data
title_full Quasi-3D Statistical Inversion of Oceanographic Tracer Data
title_fullStr Quasi-3D Statistical Inversion of Oceanographic Tracer Data
title_full_unstemmed Quasi-3D Statistical Inversion of Oceanographic Tracer Data
title_sort quasi-3d statistical inversion of oceanographic tracer data
publisher Florida State University
url http://purl.flvc.org/fsu/fd/FSU_migr_etd-4101
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