Master’s degree1,500 h · Online · 11 modules

Master's in Ocean Current and Tide Observation

This master's gives you an in-depth understanding of ocean dynamics. You will learn to observe, analyze and model currents and tides with the latest technologies, from satellites and radar to in situ sensors, ADCPs and tide gauges, and to turn those observations into reliable forecasts. The program prepares you to support sustainable coastal management, safe navigation, port and offshore operations and the prediction of extreme events.

Duration1,500 h

ModeOnline

Start1 December

Modules11

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About the program

What is the Master's in Ocean Current and Tide Observation?

This master's covers the full chain of current and tide observation and forecasting. You will study the physics of ocean currents and tides, Coriolis and pressure gradients, harmonic constituents and spectral analysis; 2D and 3D hydrodynamic modeling with finite difference, finite volume and finite element schemes; remote sensing with satellite altimetry, SAR, HF radar and LIDAR; oceanographic campaigns, ADCPs, tide gauges, buoys, drifters and AUVs, with calibration and data quality control under GOOS and IOOS practices; real-time observation networks and data transmission over satellite, cellular and LoRaWAN links; big data, machine learning and data assimilation with variational methods and Kalman filters; coastal and estuarine dynamics and sediment transport; early warning systems; and the use of predictions in navigation, port entry, tidal energy, offshore work windows and search and rescue drift.

What sets this master's apart: it integrates observation, modeling and operational forecasting instead of treating them as separate disciplines, so you learn how a measurement from an ADCP or a radar station ends up improving a forecast and an alert; it gives real weight to computing, high-performance simulation and AI alongside classical harmonic analysis; it connects the science with concrete applications such as tide tables, under-keel clearance, port works and offshore operations; and it closes with a Final Project in which you develop an integrated real-time prediction system combining numerical modeling, remote sensing and big data.

Program typeMaster’s degree

ModeOnline

Duration1,500 hours

Modules11

Start1 December

Program highlights

Physics and analysis of currents and tides: harmonic constituents, spectral analysis and tide-current interaction.
2D and 3D hydrodynamic modeling, calibration, sensitivity analysis and high-performance computing.
Observation technologies: ADCP, tide gauges, HF radar, satellite altimetry, SAR, LIDAR, buoys, drifters and AUVs.
Real-time networks, data quality control, assimilation with Kalman filters and machine learning forecasting.
Applications: tide tables, port entry and under-keel clearance, tidal energy, offshore windows and SAR drift.
Final Project: an integrated real-time current and tide prediction system.

Syllabus

Syllabus of the Master's in Ocean Current and Tide Observation

11 modules. Select a module to see its content.

Module 1

Advanced analysis of ocean currents and tides: numerical modeling and prediction

1.1. Physical and mathematical foundations of ocean currents: fluid dynamics, Coriolis forces and pressure gradients
1.2. Tidal theory and analysis: harmonic constituents, frequency spectra and multicomponent tidal analysis
1.3. Numerical hydrodynamic modeling: Navier-Stokes equations and 2D and 3D hydrodynamic tide models
1.4. Implementation of numerical models: numerical methods, discretization schemes and stabilization
1.5. Integration of observational data: assimilation of data from buoys, tide gauge stations and altimetry satellites
1.6. Prediction and simulation models: short- and medium-term forecasting techniques based on digital models and machine learning
1.7. Analysis of tide-current interaction and its impact on coastal processes: sedimentation, erosion and beach dynamics
1.8. Applied case studies: modeling of currents in estuaries, bays and continental shelves
1.9. Uncertainty assessment and model validation: metrics, calibration and verification with experimental data
1.10. Optimization and automation of observation and prediction systems: integration into oceanographic networks and early warning systems

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 2

Advanced remote sensing techniques and sensors for the dynamic monitoring of currents and tides

2.1. Foundations of remote sensing applied to oceanography: physical and technological principles
2.2. Active and passive remote sensors: characteristics, types and specific applications in detecting currents and tides
2.3. Satellite signal processing: advanced algorithms for extracting oceanographic data
2.4. Spectral interpretation and multiband analysis: techniques to improve the accuracy of dynamic monitoring
2.5. Integration of LIDAR and radar systems for detailed mapping of coastal strips and recording of tidal variations
2.6. Numerical models coupled with sensor data for real-time simulation of current and tidal patterns
2.7. Field calibration and validation of sensors: operating protocols and data quality control
2.8. In situ monitoring with complementary technologies: instrumented buoys, ADCPs (Acoustic Doppler Current Profilers) and coastal stations
2.9. GIS tools and specialized software for three-dimensional visualization and time analysis of oceanographic data
2.10. Practical applications and case studies: coastal risk management, current prediction for navigation and environmental and port planning

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 3

Numerical modeling and advanced prediction techniques for currents and tides

3.1. Foundations of numerical modeling: Navier-Stokes equations, hydrodynamic approximations and boundary conditions in coastal and ocean settings
3.2. Hydrodynamic models for currents and tides: one-, two- and three-dimensional types, input parameters and technical limitations
3.3. Processes and methods for tide simulation: harmonic analysis, tidal spectrum and advanced time decomposition techniques
3.4. Modeling of complex ocean currents: interaction between wind-driven flows, density gradients and seabed topography
3.5. Integration of observational data: assimilation of satellite, buoy and remote sensor data to improve forecasts
3.6. Optimization and calibration of numerical models: parameter tuning, validation against real data and sensitivity analysis
3.7. Advanced prediction with coupled models: hydrodynamics and meteorology, incorporating atmospheric forecasts for changing scenarios
3.8. Machine learning and artificial intelligence algorithms applied to current and tide prediction
3.9. Operational systems for running models: computing performance, parallelization and use of HPC (High Performance Computing)
3.10. Advanced interpretation and visualization of results: dynamic maps, time series charts and decision tools for maritime planning

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 4

Oceanographic campaigns and real-time observation networks: instrumentation, calibration, quality assurance and data transmission

4.1. Design and planning of oceanographic campaigns: scientific objectives, selection of study areas and timing
4.2. Advanced instrumentation for measuring currents and tides: ADCPs, tide gauges, pressure and temperature sensors, HF radar and LIDAR systems
4.3. Calibration and validation of sensors: metrological procedures, inter-instrument comparison and field adjustments
4.4. Quality assurance and control of oceanographic data: anomaly detection, digital filtering, bias correction and international standard protocols (IOOS, GOOS)
4.5. Real-time observation networks: design, architecture and communication protocols (TCP/IP, UDP, MQTT) for efficient and secure data transmission
4.6. Integration of autonomous and remote platforms: smart buoys, drifters, AUVs (autonomous underwater vehicles) and fixed coastal stations
4.7. Maritime data acquisition and management systems: SCADA software, georeferenced databases and standardization with ISO 19115
4.8. Operational processing and numerical modeling: data assimilation in hydrodynamic models for real-time prediction of currents and tidal variation
4.9. Satellite and terrestrial communication for real-time transmission: GPRS, VSAT, Iridium and LoRaWAN networks
4.10. Practical applications in maritime operations: safe navigation, port planning, mitigation of coastal impacts and management of tide and current risks

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 5

Integration of oceanographic systems and big data to optimize current and tide prediction models

5.1. Foundations of physical oceanography: dynamics of ocean currents, tidal cycles and hydrodynamic forces
5.2. Principles and architecture of oceanographic systems: in situ sensors, buoys, HF radar and autonomous platforms
5.3. Advanced acquisition and processing of oceanographic data: calibration, validation and correction of time series
5.4. Introduction to big data in marine science: volume, variety and velocity of oceanographic data
5.5. Integration of heterogeneous sources: fusion of satellite data, numerical models and coastal stations
5.6. Predictive models of currents and tides: numerical analysis, hydrodynamic models and statistical validation
5.7. Machine learning methods applied to oceanography: supervised and unsupervised algorithms and deep neural networks
5.8. Model optimization with artificial intelligence: parameter tuning, error reduction and generalization
5.9. Data management and visualization platforms: GIS, interactive dashboards and early warning systems
5.10. Practical applications: prediction of extreme tides, modeling of pollutant transport and support for maritime operations

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 6

Advanced numerical modeling and innovative technologies for real-time monitoring of currents and tides

6.1. Foundations of numerical modeling applied to current and tide dynamics: Navier-Stokes equations, hydrodynamic approximations and time scales
6.2. Advanced hydrodynamic models: 2D and 3D models, fluid-sediment coupling and multiscale approaches
6.3. Implementation of numerical schemes: finite differences, finite volumes and finite elements in coastal simulations
6.4. Optimization and calibration of numerical models with observational data: statistical methods and data assimilation techniques
6.5. Integration of in situ and remote sensors for real-time monitoring: ADCPs, tide buoys, coastal radar and observation satellites
6.6. Real-time data transmission protocols and systems: IoT architecture, satellite communications and wireless sensor networks
6.7. Dynamic processing and visualization platforms: specialized software for real-time analysis, automated alerts and operational decision-making
6.8. Advanced prediction and simulation of extreme scenarios: storm surges, tsunamis and critical coastal flows
6.9. Artificial intelligence and machine learning in the predictive analysis of tidal patterns and coastal currents
6.10. Case studies and practical applications in international projects: evaluation of results, continuous improvement and technology standards

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 7

Numerical modeling, remote sensing and real-time monitoring for accurate current and tide prediction

7.1. Foundations of numerical modeling for currents and tides: Navier-Stokes equations, governing hydrodynamic equations and conservation of mass and energy
7.2. Implementation of two- and three-dimensional hydrodynamic models: spatial and temporal discretization, advanced numerical schemes and stabilization techniques
7.3. Dynamics of ocean currents and tides: harmonic analysis, tidal interaction and meteorological effects on coastal circulation
7.4. Remote sensing data for monitoring ocean parameters: optical sensors, long-wave radar, satellite altimetry and advanced processing
7.5. Digital processing of satellite and aerial images to detect and track current fronts, upwelling and oceanographic parameters
7.6. Integration and fusion of data from satellite platforms, buoys and in situ systems to validate and calibrate numerical models
7.7. Development and optimization of real-time monitoring with sensor networks integrated with IoT and big data platforms
7.8. Machine learning and predictive algorithms for continuously improving the accuracy of current and tide estimates
7.9. Advanced data assimilation strategies: variational methods and Kalman filters for dynamically updating ocean models
7.10. Design and configuration of early warnings for coastal risk management based on real-time current and tide forecasts

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 8

Integrated analysis of coastal and estuarine dynamics: advanced modeling, real-time monitoring and applications in environmental management and maritime safety

8.1. Physical and mathematical foundations of coastal dynamics: Navier-Stokes equations, conservation of mass and momentum and their application in coastal and estuarine settings
8.2. Advanced hydrodynamic modeling: finite element, finite difference and finite volume techniques for simulating currents, tides and freshwater and saltwater flows
8.3. Integration of atmospheric and oceanographic forcing: wind, barometric pressure and extreme weather events in coastal dynamics models
8.4. Real-time monitoring systems: in situ and remote sensors (ADCPs, tide gauges, weather stations and satellites) and data acquisition and processing
8.5. Spectral and harmonic analysis of tides: harmonic decomposition, tidal prediction and model validation with historical time series and observations
8.6. Sediment dynamics and transport: modeling particle movement, erosion and deposition processes and their impact on coastal geomorphology
8.7. Interaction between ocean and river currents in estuaries: hydrodynamic configuration, stratification, mixing and transport of nutrients and pollutants
8.8. Applications in environmental management: assessing the impact of coastal infrastructure, designing mitigation measures based on predictive modeling and sustainable management of marine resources
8.9. Maritime safety and coastal navigation: integrating hydrodynamic models with decision support systems for safe route planning and emergency management
8.10. Case studies and applied simulations: critical areas, response to pollutant spills and monitoring protocols for early warning and rapid response

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 9

Foundations and advanced technologies for real-time monitoring and prediction of ocean currents and tides

9.1. Fundamental physical principles: fluid dynamics applied to currents and tides, Coriolis forces, pressure gradients and their influence on water movement
9.2. Advanced mathematical and numerical models: Navier-Stokes equations, 2D and 3D hydrodynamic models, parameterization and simulation techniques
9.3. Real-time monitoring systems: in situ sensors (ADCPs, tide gauges, buoys), telemetry and data transmission technologies, sensor integrity and calibration
9.4. Advanced signal processing and data analysis: digital filters, statistical methods and harmonic and spectral analysis of current and sea level time series
9.5. Applied remote sensing technologies: altimetry satellites, synthetic aperture radar (SAR) and coastal radar for detecting surface currents and tidal variability
9.6. Systems and platform integration: integrated sensor networks, SCADA systems for control and supervision and data interoperability with GIS
9.7. Predictive algorithms and artificial intelligence: machine learning, neural networks and adaptive models for improving the prediction of tidal events and current changes
9.8. Implementation of early warning systems: operating protocols, effective communication and mitigation strategies based on real-time data and probabilistic forecasts
9.9. Regulatory aspects and international standards: IMO guidelines, ISO, data quality standards and requirements for ocean monitoring systems
9.10. Case studies and professional applications: design and implementation of monitoring projects, real cases in complex coastal and marine areas and coastal risk management

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 10

Applications of current and tide prediction to navigation and engineering

10.1. Tide tables and nautical almanacs
10.2. Current prediction for navigation
10.3. Planning port entries
10.4. Tides and available depth
10.5. Currents in channels and straits
10.6. Applications in tidal energy
10.7. Design of port works
10.8. Offshore operations and weather windows
10.9. Search and rescue and drift of objects
10.10. Oceanographic information services

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 11

Final Project

11.1. Advanced foundations of numerical modeling applied to currents and tides: coastal and ocean hydrodynamics, scalability and spatial and temporal resolution
11.2. Remote sensing in operational oceanography: physical principles, active and passive sensors, satellite image processing, spectral interpretation and radiometric calibration
11.3. Integration of in situ and remote data: multisource data fusion, cross-validation, time series correction and adaptive hybrid models in real time
11.4. Big data applied to oceanography: data architecture, management of large volumes of hydrographic and oceanographic information and machine learning for pattern detection and forecasting
11.5. Development of the integrated system: modular design, human-machine interface (HMI), communication protocols and synchronization between sensors, observation stations and data processing centers
11.6. Implementation of real-time predictive models: data assimilation, dynamic parameter adjustment, uncertainty analysis and automated operational alerts
11.7. Computational optimization and use of HPC: parallel computing, latency reduction and load balancing for simulations in complex coastal settings
11.8. Practical applications and case studies: prediction of extreme tides, current tracking for safe navigation, port planning and coastal environmental management
11.9. Performance evaluation and system validation: accuracy, sensitivity, temporal and spatial consistency and procedures for iterative post-implementation adjustment
11.10. Future outlook and technology trends: artificial intelligence in oceanography, IoT in marine observatories and sustainable development based on real-time ocean data

At this stage

136 hestimated workload

11 wkweeks at your pace

Plan your pace

Duration and format of the Master's in Ocean Current and Tide Observation

It is 1,500 hours. Tell us how many you can study each week and we will tell you when you will really finish.

Hours per week

4 h30 h

With 12 h per week

months to finish

125 weeks

weeks in total

This is the pace at which most students finish. It fits well with the installment plan.

Faculty

Academic leadership and faculty

The Navalis teaching team: working professionals who teach and supervise the programs.

Dr. Marina AlcoverAcademic Director and Head of Quality Assurance

Eng. Diego CifuentesSenior Lecturer in Naval Welding and Non-Destructive Testing; Head of QA/QC for Welded Joints

Capt. Javier Abaroa (MCA)Senior Lecturer in Ship Handling, Electronic Navigation (ECDIS/Radar/ARPA) and GMDSS; STCW Compliance and Bridge Resource Management Coordinator

Dr. Pau FerrerSenior Lecturer in Naval Architecture and Simulation; Director of the Hydrodynamics and CFD Laboratory

Dr. Nuria LlobregatSenior Lecturer in Marine Meteorology, SAR and Operational Safety; Navigation Risk Management Coordinator

Eng. Javier BañulsSenior Lecturer in Electrical Engineering, Automation and ETO Engineering; Electronic Integration and Engine Alarms Coordinator

Eng. Sofía MarquinaSenior Lecturer in Materials, Composites and Corrosion Protection; Coordinator of the Advanced Paints and Coatings Line

Eng. Tomás RieraSenior Lecturer in Propulsion, Alternative Energy and Hybrid Systems; Energy Performance and Vibration Coordinator

Objectives

Objectives of the Master's in Ocean Current and Tide Observation

01Optimize the use of marine resources and maritime operations, planning navigation around tides, currents, wind and draft or air draft restrictions.

02Predict and mitigate coastal risks by analyzing oceanographic and meteorological data to anticipate extreme events, protect infrastructure and support coordination with local authorities.

03Design and implement early warning systems for extreme ocean events, integrating satellite, buoy and model data and applying machine learning to detect anomalous patterns.

04Model ocean dynamics accurately, implementing advanced numerical models, calibrating key parameters such as wind, tide and density and validating results against observations.

05Advise on the planning of resilient coastal infrastructure, taking climate variability and sea level rise into account in long-term design.

06Lead innovative oceanographic projects, fostering multidisciplinary collaboration and managing resources and risks to achieve high-impact scientific and technical results.

Careers

Career opportunities after the Master's in Ocean Current and Tide Observation

01Oceanographer or researcheranalysis of oceanographic data, modeling of currents and tides and study of climate change impacts on coastal areas.

02Environmental consultantimpact assessments, pollutant dispersion modeling and design of early warning systems for extreme events.

03Coastal engineer or coastal resource managerdesign of maritime infrastructure, optimization of ports and channels, coastal protection and risk assessment.

04Marine data analystprocessing of satellite and buoy data and development of visualization and prediction tools for currents and tides.

05Marine renewable energy specialistassessment of tidal and current energy potential and support to the design and operation of marine energy plants.

06Hydrographer or marine cartographercurrent maps, hydrographic surveys and management of marine geographic information.

Frequently asked questions

Questions about the Master's in Ocean Current and Tide Observation

Ocean currents and tides: how they are measured, analyzed, modeled and predicted, and how those predictions are used in navigation, coastal engineering, environmental management and maritime operations.

Both. The program combines observation technologies such as ADCPs, tide gauges, HF radar and satellite altimetry with data processing, numerical modeling, data assimilation and machine learning.

Basic knowledge of Python or MATLAB is recommended, since much of the work involves processing time series and running or interpreting models. The admission interview helps assess your starting point.

Yes. A dedicated module covers tide tables, current prediction for navigation, port entry planning, available depth, currents in channels and straits, offshore weather windows and search and rescue drift.

Yes. The program is aimed at oceanographers, physicists, coastal and port engineers, environmental consultants and marine energy professionals, as well as maritime professionals.

Online, with practical projects and case studies throughout the modules, and a Final Project in which you develop an integrated real-time current and tide prediction system.

A Navalis Institute master's certificate and a Final Project that documents a complete observation and prediction system, useful as a professional portfolio.

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Online admission

Admission process

No waiting for a call back. If your documents are in order, you can enroll in the same session.

Entry requirements

Profile: a degree in marine science, oceanography, physics, mathematics or maritime-oriented engineering, or demonstrable professional experience in marine meteorology, hydrography or numerical modeling; basic knowledge of fluid dynamics, statistics, Python or MATLAB and GIS is recommended.
Language: sufficient command of English to follow the classes and the technical documentation.
Technical resources: a computer with data analysis software (for example Python with scientific libraries), a high-speed internet connection and the capacity to run and visualize simulations.
Admission: online application, review of your profile and a short interview with the academic team.

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