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
39447123-69ab-40ce-9815-7fea3e98d597
Matthews, Andrew
8b218390-cb36-4f73-ae8d-e4d0e2d222fa
Jevrejeva, Svetlana
237423c0-e564-442f-9a85-0cadf056a32d
2019
Williams, Joanne
39447123-69ab-40ce-9815-7fea3e98d597
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.
Text
NOC_R&C_64_Final
- Version of Record
More information
Published date: 2019
Identifiers
Local EPrints ID: 431968
URI: http://eprints.soton.ac.uk/id/eprint/431968
PURE UUID: 120736cc-438c-4d04-957e-fa8a13f1e99b
Catalogue record
Date deposited: 25 Jun 2019 16:30
Last modified: 16 Mar 2024 02:25
Export record
Contributors
Author:
Joanne Williams
Author:
Andrew Matthews
Author:
Svetlana Jevrejeva
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics