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Development of an automatic tide gauge processing system

Development of an automatic tide gauge processing system
Development of an automatic tide gauge processing system
There are many tide gauges around the world for which research quality data is not available for sea-level studies, including gauges that are maintained primarily for tsunami monitoring. In some cases high-frequency data is available for download through the Intergovernmental Oceanographic Commission (IOC) http://www.iocsealevelmonitoring.org, but manual QC has been too labour intensive.
In this report we describe Matlab software for automatic quality control (QC) for tide gauges, including generalised comparison of instrument channels, fitting and predicting tides using irregular high-frequency data. We include details of the implementation, testing, and known capability and weaknesses.
National Oceanography Centre
Williams, Joanne
82ccfacf-2ec2-4f91-b35c-e199753b5cb8
Matthews, Andrew
8b218390-cb36-4f73-ae8d-e4d0e2d222fa
Jevrejeva, Svetlana
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Williams, Joanne
82ccfacf-2ec2-4f91-b35c-e199753b5cb8
Matthews, Andrew
8b218390-cb36-4f73-ae8d-e4d0e2d222fa
Jevrejeva, Svetlana
237423c0-e564-442f-9a85-0cadf056a32d

Williams, Joanne, Matthews, Andrew and Jevrejeva, Svetlana (2019) Development of an automatic tide gauge processing system (National Oceanography Centre Research and Consultancy Report, 64) Southampton. National Oceanography Centre 26pp.

Record type: Monograph (Project Report)

Abstract

There are many tide gauges around the world for which research quality data is not available for sea-level studies, including gauges that are maintained primarily for tsunami monitoring. In some cases high-frequency data is available for download through the Intergovernmental Oceanographic Commission (IOC) http://www.iocsealevelmonitoring.org, but manual QC has been too labour intensive.
In this report we describe Matlab software for automatic quality control (QC) for tide gauges, including generalised comparison of instrument channels, fitting and predicting tides using irregular high-frequency data. We include details of the implementation, testing, and known capability and weaknesses.

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NOC_R&C_64_Final - Version of Record
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Published date: 2019

Identifiers

Local EPrints ID: 431968
URI: https://eprints.soton.ac.uk/id/eprint/431968
PURE UUID: 120736cc-438c-4d04-957e-fa8a13f1e99b

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Date deposited: 25 Jun 2019 16:30
Last modified: 25 Jun 2019 16:30

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Contributors

Author: Joanne Williams
Author: Andrew Matthews
Author: Svetlana Jevrejeva

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