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Development and exploitation of a high-resolution sea level product in the coastal ocean

Scientific Background and Motivation

As oceans respond to local, regional and global changes a key parameter to monitor is sea level particularly along the coasts, as this is where changes impact on populations and a better understanding of measurable values is required. Currently, tide gauges provide point measurements with high temporal resolution whereas satellite altimeters can provide synoptic information but with poor temporal resolution. The quality of measuring sea level from satellite altimeters has improved markedly over recent years in particular in the critical zone close to the coast. For example,  through coastal retracking ( or the introduction of SAR altimetry (CryoSat-2 and Sentinel 3).

This is a CASE studentship, the student will be based at NOC, Liverpool and registered at University of Edinburgh.

Aims and objectives

In order to address some key issues in the coastal zone it is proposed to develop a methodology for a gridded coastal sea level product (for 2011 onwards). By building a statistical model linking sea level data (altimetry and tide gauges) with satellite sea surface temperature and/or ocean colour products as a proxy for changes in sea level the student will be able to create a high-resolution product for scientific analyses.  Associated case studies could be global or regional in nature, with a number of key areas of interest already identified (e.g. Severn Estuary).


Conventional geostatistical methods will face several challenges when applied to reconstructing coastal sea level. One challenge is that the correlation length scales of sea level are much longer along the coast than across the shelf and so isotropic covariance functions, which are predominantly used in geostatistics, will not work well. New geostatistical models based on Gaussian processes with local anisotropy will be investigated to address this problem.

The approach would incorporate multiple satellite altimeters (with different sampling so simple methods result in aliasing), tide gauges and other satellite/in situ/model parameters (e.g. surface temperature and/or ocean colour) via some form of spatio-temporal model . There is the potential in the latter part of the studentship for comparison of results with results from the innovative SWOT mission that will provide the same information we are looking to produce.

Data sources

The key data sources to be exploited in this PhD are:

  • satellite altimetry sea level data (e.g. CryoSat-2, Jason series, Sentinel 3, possibly SWOT and Sentinel 6),
  • satellite sea surface temperature and ocean colour
  • tide gauge data