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Journal article 1167 views

Statistical prediction of coastal and estuarine evolution

Magar, V.,, S Gross, M, Probert, G.,, Reeve, D.E, Yuzhi Cai Orcid Logo

'International Conference of Coastal Engineering 2012, USA, Volume: 1, Issue: 33

Swansea University Author: Yuzhi Cai Orcid Logo

Abstract

This paper presents a novel data-driven methodology based on empirical orthogonal teleconnections (EOTs) to analyse and forecast the evolution of coastal navigational channels near the mouth of the Exe estuary, UK. This is the first time EOTs are used in coastal morphodynamics. Therefore, particular...

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Published in: 'International Conference of Coastal Engineering 2012, USA
Published: 2012
URI: https://cronfa.swan.ac.uk/Record/cronfa15292
first_indexed 2013-08-22T01:57:37Z
last_indexed 2018-02-09T04:47:08Z
id cronfa15292
recordtype SURis
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spelling 2014-12-21T16:17:24.0169154 v2 15292 2013-07-30 Statistical prediction of coastal and estuarine evolution eff7b8626ab4cc6428eef52516fda7d6 0000-0003-3509-9787 Yuzhi Cai Yuzhi Cai true false 2013-07-30 CBAE This paper presents a novel data-driven methodology based on empirical orthogonal teleconnections (EOTs) to analyse and forecast the evolution of coastal navigational channels near the mouth of the Exe estuary, UK. This is the first time EOTs are used in coastal morphodynamics. Therefore, particular emphasis is placed on the comparison of EOTs with the well established empirical orthogonal functions (EOFs) method. EOTs and EOFs are used with a series of 14 surveys, taken approximately every 8 months, covering the period between January 2001 and February 2010. The skill of the methods in producing accurate bathymetric one-step forecasts for February 2010 is analyzed and compared with one-step forecasts based on the raw data. It is found that, provided the order of the autoregressive forecast method is chosen appropriately, EOTs and EOFs are better than the raw data and EOTs outperforms than EOFs. This is attributed to the fact that EOTs, without the orthonormality restriction for the temporal eigenfunctions required in EOFs, capturing the temporal patterns within the data more accurately than EOFs. Journal Article 'International Conference of Coastal Engineering 2012, USA 1 33 133 empirical orthogonal functions; empirical orthogonal teleconnections; forecasting skill 30 9 2012 2012-09-30 COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University 2014-12-21T16:17:24.0169154 2013-07-30T10:42:47.9929909 Faculty of Humanities and Social Sciences School of Management - Accounting and Finance Magar, V., 1 S Gross, M 2 Probert, G., 3 Reeve, D.E 4 Yuzhi Cai 0000-0003-3509-9787 5
title Statistical prediction of coastal and estuarine evolution
spellingShingle Statistical prediction of coastal and estuarine evolution
Yuzhi Cai
title_short Statistical prediction of coastal and estuarine evolution
title_full Statistical prediction of coastal and estuarine evolution
title_fullStr Statistical prediction of coastal and estuarine evolution
title_full_unstemmed Statistical prediction of coastal and estuarine evolution
title_sort Statistical prediction of coastal and estuarine evolution
author_id_str_mv eff7b8626ab4cc6428eef52516fda7d6
author_id_fullname_str_mv eff7b8626ab4cc6428eef52516fda7d6_***_Yuzhi Cai
author Yuzhi Cai
author2 Magar, V.,
S Gross, M
Probert, G.,
Reeve, D.E
Yuzhi Cai
format Journal article
container_title 'International Conference of Coastal Engineering 2012, USA
container_volume 1
container_issue 33
publishDate 2012
institution Swansea University
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Accounting and Finance{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Accounting and Finance
document_store_str 0
active_str 0
description This paper presents a novel data-driven methodology based on empirical orthogonal teleconnections (EOTs) to analyse and forecast the evolution of coastal navigational channels near the mouth of the Exe estuary, UK. This is the first time EOTs are used in coastal morphodynamics. Therefore, particular emphasis is placed on the comparison of EOTs with the well established empirical orthogonal functions (EOFs) method. EOTs and EOFs are used with a series of 14 surveys, taken approximately every 8 months, covering the period between January 2001 and February 2010. The skill of the methods in producing accurate bathymetric one-step forecasts for February 2010 is analyzed and compared with one-step forecasts based on the raw data. It is found that, provided the order of the autoregressive forecast method is chosen appropriately, EOTs and EOFs are better than the raw data and EOTs outperforms than EOFs. This is attributed to the fact that EOTs, without the orthonormality restriction for the temporal eigenfunctions required in EOFs, capturing the temporal patterns within the data more accurately than EOFs.
published_date 2012-09-30T06:28:23Z
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score 10.890605

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