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Oceanic Submesoscale and Autonomous Observation Systems

Code: EGEO4024     Acronym: EGEO4024

Keywords
Classification Keyword
OFICIAL Surveying Engineering

Instance: 2021/2022 - 2S

Active? Yes
Responsible unit: Department of Geosciences, Environment and Spatial Plannings
Course/CS Responsible: Master's degree in Remote Sensing

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
M:DR 3 The study plan from 2018 1 - 6 42 162

Teaching Staff - Responsibilities

Teacher Responsibility
Jose Carlos Pinto Bastos Teixeira Silva

Teaching - Hours

Theoretical and practical : 2,00
Other: 1,00
Type Teacher Classes Hour
Theoretical and practical Totals 1 2,00
Jose Carlos Pinto Bastos Teixeira Silva 2,00
Other Totals 1 1,00
Jose Carlos Pinto Bastos Teixeira Silva 1,00

Teaching language

Suitable for English-speaking students

Objectives

Students should comprehend in what sense new autonomous vehicles and instrumentation, through their environmental measurements, can contribute to understanding the oceanic submesoscale and its dynamics. The students should develop skills to select various sampling strategies, including simultaneously autonomous vehicles and satellite measurements, for an effective observation of submesoscale processes. The students should be able to describe in mathematical language some basic dynamics of the submesoscale, grasping some basic understanding of the physics of the involved phenomena. The foundations of control associated to autonomous vehicles should be understood in a collaborative and optimized form.

Learning outcomes and competences








Understanding physical dynamics in the ocean that occur between scales of a meter and a few tens of kilometers requires, as the first step, collecting data, which are required to have the spatial coverage as broad as possible and repeat observation period as short as possible. New technologies and autonomous vehicles (underwater, surface and airborne), configurations and state of the art sensors, are ideal for Lagrangian-based field experiments and consequently contribute to understanding ocean dynamics at these scales. This curricular unit intends to address the physical dynamics of sub-mesoscale processes and demonstrate how new measuring technologies can contribute to a better understanding of these phenomena. It also provides a basis to comprehend SAR Ocean observations, hence being essential to this other curricular unit (Ocean SAR).


Working method

Presencial

Program

Description of oceanic phenomena observed by satellite remote sensing, space-time scales of those phenomena and some techniques and sensors for observing them; Fundamental properties of ocean water; Geofluid dynamics (equations of inviscid motion with Earth rotation); Surface waves (deep and shallow water approximations; dispersion relations); Internal gravity waves (Boussinesq approximation; two-layer model; propagation in continuous stratification; wave modes and ray propagation); Nonlinear waves (Kortweg-deVries equation; internal solitons); Sub-mesoscale vortices; Estuarine coastal dynamics (river plumes and environmental conditions: wind speed and direction, tides, flow); near-inertial oscillations; Bathymetry effects on surface gravity-capillary waves (weak hydrodynamic modulation theory); Friction effects (some notions of ocean turbulence associated to waves and fronts); Autonomous vehicles and measurement techniques; Instrumentation onboard autonomous vehicles and hydrographic measurements (measurements of other variables); Synchronous measurements with swarms of autonomous vehicles and strategies for measuring different phenomena.

Mandatory literature

Kundu Pijush K.; Fluid mechanics. ISBN: 0-12-178253-0
Carter N.; Autonomous Underwater Vehicles: Technology and Applications, Carter N. , 2015. ISBN: ISBN-13: 978-1632400741

Complementary Bibliography

LeBlond, P.H., Mysak, L.A. ; Waves in the Ocean, Elsevier, 1981. ISBN: ISBN-13: 978-0133533019
Zheng, Q.; Satellite SAR detection of sub-mesoscale Ocean Dynamic Processes, Advanced Series on Ocean Engineering , Volume 44; 300pp, 2017

Teaching methods and learning activities

The teaching method is based on theoretical exposition and analysis of the equations of motion that govern some of the sub-mesoscale, followed by detailed discussions of the implications in the ocean dynamics. The analysis is made with aid of numerical model results (e.g. animations of MITgcm output) and in situ measurements obtained with the autonomous vehicles. Whenever possible and desirable, some numerical simulations will be proposed to illustrate the processes addressed in class. Satellite observations are the preferential form to illustrate some characteristics of the sub-mesoscale phenomena, and a way to gain insight into those processes. A visit to the Underwater Systems and Technology Laboratory (LSTS) of the Faculty of Engineering of the University of Porto (FEUP) ) (http://lsts.fe.up.pt/) will allow acquaintance with those autonomous vehicles, and whenever possible planning of operational missions with these vehicles will take place in class, as well as analysis of data collected by the vehicles. In the lectures of type “O” possible doubts about the various topics of the syllabus will be clarified and support to the execution of the proposed practical exercises will be given

Software

MATLAB
SNAP

keywords

Physical sciences > Physics > Classical mechanics > Fluid dynamics
Natural sciences > Environmental science > Earth science > Marine sciences

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation Weight (%)
Trabalho prático ou de projeto 50,00
Trabalho escrito 50,00
Total: 100,00

Amount of time allocated to each course unit

designation Time (hours)
Estudo autónomo 40,00
Frequência das aulas 42,00
Trabalho escrito 22,00
Total: 104,00

Eligibility for exams

Evaluation shall include a written manuscript (50%) and a proposal for a project with the aim to sample a given submesoscale ocean phenomenon through the use of autonomous vehicles and satellite remote sensing. Minimum average mark for successful conclusion of the U.C. is 9.5/20.

Calculation formula of final grade

Final=0.5*Manuscript+0.5*Assignment

Examinations or Special Assignments

NA

Internship work/project

NA

Special assessment (TE, DA, ...)

NA

Classification improvement

Improvement of marks may be achieved by the realization of an additional Exam and/or an additional Assignment.

Observations

NA
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