Investigating Thermohaline Patterns: A Study of Spatial and Temporal Variability in the Mediterranean

University of Split

Flexible

20h / week

English B2

Physical oceanography reanalysis models produce a vast amount of highly reliable data. Reducing their dimensionality helps to identify characteristic spatial patterns and their temporal variability, enabling the distinction between climate change and natural oscillations. Neural network techniques allow for the extraction of nonlinear processes. The bimodal oscillation system found in the Ionian Sea serves as one notable example.

Tasks and duties entrusted to the student:
Physical oceanography reanalysis models produce a vast amount of highly reliable data. Reducing their dimensionality helps to identify characteristic spatial patterns and their temporal variability, enabling the distinction between climate change and natural oscillations. Neural network techniques allow for the extraction of nonlinear processes. The bimodal oscillation system found in the Ionian Sea serves as one notable example.

Skills to be acquired or developed:
The student will acquire and develop foundational skills in data mining techniques, specifically applied to analyzing thermohaline properties within the context of the Mediterranean Sea.

Frano Matić
frano.matic@unist.hr

https://more.unist.hr/en/