We offer 4-year PhD position at Tallinn University of Technology, in collaboration with Research group of Geodesy and Road Engineering (Dept. of Civil Engineering and Architecture) and Lab of Wave Engineering (Dept. Of Cybernetics).
Proposed doctoral thesis topic: Identification and improved modelling of marine dynamics by utilizing the Marine Geoid.
Supervisors: Professor Artu Ellmann, Dr. Nicole Delpeche-Ellmann
Hydrodynamic models are often used to simulate water levels, currents, sediment transport and chemical properties (e.g. salinity, temperature, etc.) of marine environment. Thus they are quite effective in understanding and predicting trends and persistent dynamical features in the marine area. In many circumstances however, the accuracy and representation of the dynamical characteristics especially on the (sub)mesoscale have not been adequate enough for various reasons (e.g. parameterization used, model resolution, forcing data etc.). This often results in the under- or overestimated of marine dynamics, that in effect has drastic consequences for engineering, shipping and scientific applications.
This study now proposes a unique methodology that shall improve the accuracy and representation of oceanographic dynamics by utilizing the data assimilation of hydrodynamic and geoid model along with space-borne and in-situ (laser scanning, tide gauges, etc.). The basic concept stems from utilization of a geoid model. Recalling that the geoid represents the equipotential surface (i.e. it defines sea level shape that the ocean surface would take under the influence of the gravity and rotation of Earth alone). In reality however the ocean is influenced by other influences such as winds, tides etc. which is often captured by hydrodynamic models and in situ data with respect to their sea surface heights (SSH). Thus it is expected that due to dynamic processes present in the ocean and atmosphere, the SSH are expected to depart from the geoid. This separation is known as the ocean’s dynamic topography (SSH-geoid=DT). DT represents the mean and time varying currents. Thus intuitively, by including SSH (determined from satellite or airborne laser scanning (ALS) missions) in conjunction with DT estimates (e.g. HDMs and in-situ measurements) we can validate and iteratively improve hydrodynamic and marine geoid models. Examining the abnormalities between the models and reference data allows possible identification of marine dynamical features. As a result creative methods can be developed for adjusting the hydrodynamic models.
- The PhD candidate shall develop a methodology that utilizes a synergy of hydrodynamic and geoid modelling complemented by in-situ data (tide gauges, satellite altimetry etc), to obtain accurate and reliable SSH results and marine geoid model.
- The first stage of this project requires compilation and statistical analyses of all relevant data whereby the candidate is expected to refer these to a common reference datum, correcting the temporal/spatial mismatch between data sets, performance of statistical analysis between different data sets.
- The second stage requires detailed understanding on the operations of the hydrodynamic model to be used. This phase essentially involves a statistical approach to data assimilation (training shall be provided), whereby all the in-situ data are combined with the HDM to improve the model.
- An iterative approach is employed, whereby once results (SSH and inversely geoidal heights) are calculated, they are checked for accuracy and reliability. Inter-comparisons of the two reference models (geoid and SSH) are conducted for detecting abnormalities. Identifying reasons for the detected discrepancies enables to determine whether these are due to poor hydrodynamic representation or/and geoid model errors. Both models can be improved iteratively, e.g. by acquiring new data over suspicious areas and iterative modelling.
- The candidate is expected to assist in project related field campaigns.
- This study is part of the Estonian Research Council supported research for developing an iterative approach for near-coast marine geoid modelling by using re-tracked satellite altimetry, in-situ and modelled data.
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