Towards realistic dynamic topography from coast to offshore by incorporating hydrodynamic and geoid models. (December 2022)
- Record Type:
- Journal Article
- Title:
- Towards realistic dynamic topography from coast to offshore by incorporating hydrodynamic and geoid models. (December 2022)
- Main Title:
- Towards realistic dynamic topography from coast to offshore by incorporating hydrodynamic and geoid models
- Authors:
- Jahanmard, Vahidreza
Delpeche-Ellmann, Nicole
Ellmann, Artu - Abstract:
- Abstract: One of the major factors preventing utilization of realistic sea-level data is that various sources are referred to inconsistent vertical reference datum (VRD). This study presents a methodology for deriving instantaneous and realistic sea level data from the coastal to offshore areas of the Baltic Sea, by synergizing different sources of sea level data (tide-gauge (TG), hydrodynamic model (HDM) and satellite altimetry (SA)). The key component being the geoid that links the VRD of these different sources. HDMs are known to be a representable source of sea level data, however their VRD is often undisclosed. Therefore, they are often spatially and temporally biased with respect to in-situ data. This study demonstrates that by using geoid-referenced TG data that represents 'realistic' sea level it is possible to correct HDM, by deriving and applying a spatial bias correction. Three interpolation methods (linear, thin plate spline regression, and inverse distance weighted) are examined to derive the corrected HDM. The results showed an improvement with respect to TG data, and the annual mean dynamic topography of corrected HDM was improved by a factor of almost 1.5. Examination of the Sentinel-3A satellite along-track data also confirms the corrected HDM data to be more accurate. The methodology applied also identified problematic locations of HDM, SA and geoid data along with unreliable TG. This accuracy and conformity in sea level data are urgently required for aAbstract: One of the major factors preventing utilization of realistic sea-level data is that various sources are referred to inconsistent vertical reference datum (VRD). This study presents a methodology for deriving instantaneous and realistic sea level data from the coastal to offshore areas of the Baltic Sea, by synergizing different sources of sea level data (tide-gauge (TG), hydrodynamic model (HDM) and satellite altimetry (SA)). The key component being the geoid that links the VRD of these different sources. HDMs are known to be a representable source of sea level data, however their VRD is often undisclosed. Therefore, they are often spatially and temporally biased with respect to in-situ data. This study demonstrates that by using geoid-referenced TG data that represents 'realistic' sea level it is possible to correct HDM, by deriving and applying a spatial bias correction. Three interpolation methods (linear, thin plate spline regression, and inverse distance weighted) are examined to derive the corrected HDM. The results showed an improvement with respect to TG data, and the annual mean dynamic topography of corrected HDM was improved by a factor of almost 1.5. Examination of the Sentinel-3A satellite along-track data also confirms the corrected HDM data to be more accurate. The methodology applied also identified problematic locations of HDM, SA and geoid data along with unreliable TG. This accuracy and conformity in sea level data are urgently required for a comprehensive understanding of climate change, marine engineering and navigation applications, which can be achieved by adapting the uniquely defined geoid for the vertical reference datum. Highlights: Sea level data from hydrodynamic models tend to be biased due to undisclosed vertical reference system. A spatial bias correction can be derived using geoid referred tide gauges and interpolation methods. The developed method improves instantaneous and mean dynamic topography within 5 cm of accuracy. Satellite altimetry confirms the corrected HDM data to be more accurate. Comparison of datasets reveals inconsistency between data sources and identifies areas of model deficiencies. … (more)
- Is Part Of:
- Ocean modelling. Volume 180(2022)
- Journal:
- Ocean modelling
- Issue:
- Volume 180(2022)
- Issue Display:
- Volume 180, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 180
- Issue:
- 2022
- Issue Sort Value:
- 2022-0180-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-12
- Subjects:
- Sea level -- Geoid -- Hydrodynamic modelling -- Vertical reference datum -- Hydrogeodesy -- Baltic sea
Oceanography -- Periodicals
Océanographie -- Périodiques
Oceanography
Periodicals
551.46 - Journal URLs:
- http://www.sciencedirect.com/science/journal/14635003 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ocemod.2022.102124 ↗
- Languages:
- English
- ISSNs:
- 1463-5003
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6231.315760
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24324.xml