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

Master's in Climatology and Satellite Weather Forecasting

This master's gives you an in-depth understanding of climate processes and forecasting techniques, with a specialized focus on satellite data. You will learn to analyze and interpret information from weather satellites to model the climate, forecast weather patterns and understand the impact of climate change, working with observation networks, data assimilation, numerical weather prediction models, ensembles and artificial intelligence, and applying them to strategic sectors such as navigation, aviation, agriculture, energy and natural hazard management.

Duration1,500 h
ModeOnline
Start1 December
Modules11
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About the program

What is the Master's in Climatology and Satellite Weather Forecasting?

This master's moves from the physics of the atmosphere to an operational forecasting service. You will begin with the climate system, the radiation balance, atmospheric structure and thermodynamics and the general circulation; study atmospheric dynamics, stability, convection, clouds, fronts and pressure systems; learn the principles of meteorological remote sensing with geostationary and polar-orbiting satellites and active and passive sensors; work with observation networks, data quality control, data assimilation and big data; run global and regional numerical weather prediction models, parameterizations and ensembles; process and classify satellite images; analyze climate variability, El Niño, teleconnections and climate change scenarios; apply forecasting to aviation, navigation, agriculture, renewable energy and early warning systems; use AI and hybrid physical-statistical models; and finish with marine and aviation meteorology and climate services.

What sets this master's apart: it joins two disciplines that are often taught separately, short- and medium-range weather forecasting and long-term climatology, through a common thread of satellite observation; it pays specific attention to marine weather, waves and storms at sea alongside aviation and other strategic sectors; and it ends with the design of a weather service and a Final Project in which you build a complete forecasting case study from satellite and meteorological data.

Program typeMaster’s degree
ModeOnline
Duration1,500 hours
Modules11
Start1 December

Program highlights

  • Climate system, radiation balance, atmospheric thermodynamics and general circulation of the atmosphere.
  • Weather satellites: geostationary and polar orbits, active and passive sensors and derived atmospheric variables.
  • Observation networks, quality control, data assimilation and big data for weather and climate.
  • Global and regional numerical weather prediction, parameterization, ensembles and forecast verification.
  • Climate variability, El Niño and La Niña, teleconnections, climate projections and regional scenarios.
  • Marine and aviation meteorology, early warning, seasonal forecasting, reanalysis and AI-based forecasting.
Syllabus

Syllabus of the Master's in Climatology and Satellite Weather Forecasting

11 modules. Select a module to see its content.

Module 1

Advanced foundations of climatology, the Earth's climate system and the physical basis of the atmosphere

  • 1.1. The concept of climate and the differences between climate, weather and climate variability
  • 1.2. Components of the climate system: atmosphere, oceans, cryosphere, biosphere and lithosphere
  • 1.3. Earth's radiation balance, the greenhouse effect and energy transfer in the climate system
  • 1.4. Vertical structure of the atmosphere and thermodynamic properties of air
  • 1.5. General circulation of the atmosphere and global patterns of energy and mass transport
  • 1.6. Ocean-atmosphere interactions and their influence on climate variability
  • 1.7. The global hydrological cycle and its relationship with climate and weather
  • 1.8. Natural climate variability and external forcings of the climate system
  • 1.9. Spatial and temporal scales of climate, from local to global
  • 1.10. A systems approach to climatology as the basis for advanced weather forecasting
At this stage
136 hestimated workload
11 wkweeks at your pace
Module 2

Atmospheric dynamics and the physical processes behind weather

  • 2.1. Fundamental equations of atmospheric dynamics and their physical interpretation
  • 2.2. Air motion, acting forces and geostrophic balance
  • 2.3. Thermodynamic processes in the atmosphere: stability, convection and advection
  • 2.4. Formation of clouds and precipitation and associated weather phenomena
  • 2.5. Atmospheric waves, fronts and low- and high-pressure systems
  • 2.6. Turbulence, vertical mixing and atmospheric boundary layer processes
  • 2.7. Extreme weather phenomena and their dynamics
  • 2.8. Interaction between topography, the land surface and atmospheric dynamics
  • 2.9. Scales of atmospheric motion, from mesoscale to synoptic scale
  • 2.10. Integration of physical processes in weather forecasting
At this stage
136 hestimated workload
11 wkweeks at your pace
Module 3

Meteorological remote sensing, fundamentals of satellite observation and remote sensors applied to the atmosphere

  • 3.1. Principles of remote sensing and acquisition of atmospheric data from satellite platforms
  • 3.2. Types of weather satellites: geostationary and polar-orbiting
  • 3.3. Active and passive sensors for observing the atmosphere
  • 3.4. Radiometry, electromagnetic spectra and signals captured by meteorological sensors
  • 3.5. Satellite-derived atmospheric variables: temperature, humidity, cloud cover and aerosols
  • 3.6. Spatial, temporal and spectral resolution in satellite observation
  • 3.7. Initial processing of satellite data and radiometric corrections
  • 3.8. Limitations and errors in the remote observation of the atmosphere
  • 3.9. Integration of satellite data with in situ observations
  • 3.10. Applications of remote sensing in operational meteorology
At this stage
136 hestimated workload
11 wkweeks at your pace
Module 4

Meteorological observation systems, data networks and assimilation of atmospheric information

  • 4.1. Land, marine and airborne meteorological observation networks
  • 4.2. Meteorological instrumentation and measurement of atmospheric variables
  • 4.3. Radiosondes, automatic weather stations and continuous observation platforms
  • 4.4. Integration of satellite and ground data in global monitoring systems
  • 4.5. Data quality, validation and error control in meteorological observations
  • 4.6. Systems for the storage, transmission and management of meteorological data
  • 4.7. Fundamentals of data assimilation in numerical models
  • 4.8. Interpolation methods and reconstruction of atmospheric fields
  • 4.9. Big data and the management of large volumes of climate information
  • 4.10. Building integrated observation systems for weather forecasting
At this stage
136 hestimated workload
11 wkweeks at your pace
Module 5

Numerical weather prediction models and simulation of the climate system

  • 5.1. Fundamentals of numerical modeling of the atmosphere
  • 5.2. Discretization of equations and numerical methods applied to meteorology
  • 5.3. Global and regional weather prediction models
  • 5.4. Parameterization of subgrid-scale physical processes
  • 5.5. Model initialization with observational data
  • 5.6. Short-, medium- and long-range forecasting
  • 5.7. Uncertainty assessment and ensembles in weather forecasting
  • 5.8. Model validation and forecast verification
  • 5.9. Simulation of future climate scenarios
  • 5.10. Integration of models into operational forecasting systems
At this stage
136 hestimated workload
11 wkweeks at your pace
Module 6

Advanced satellite data processing and analysis of meteorological imagery

  • 6.1. Digital processing of meteorological satellite images
  • 6.2. Classification of clouds and atmospheric systems from imagery
  • 6.3. Detection of weather phenomena through remote sensing
  • 6.4. Multispectral and multitemporal analysis of satellite data
  • 6.5. Extraction of atmospheric variables from images
  • 6.6. Correction and enhancement algorithms for meteorological images
  • 6.7. Integration of satellite data with numerical models
  • 6.8. Automation of analysis with artificial intelligence
  • 6.9. Advanced visualization of meteorological data
  • 6.10. Operational applications of satellite processing
At this stage
136 hestimated workload
11 wkweeks at your pace
Module 7

Climate variability, climate change and analysis of global trends

  • 7.1. Climate variability phenomena such as El Niño and La Niña
  • 7.2. Climate oscillations and teleconnection patterns
  • 7.3. Evidence of climate change and trend analysis
  • 7.4. Impact of climate change on weather systems
  • 7.5. Climate models and future projections
  • 7.6. Interaction between climate change and extreme events
  • 7.7. Climate risk assessment
  • 7.8. Adaptation to and mitigation of climate change
  • 7.9. Integration of satellite data into climate studies
  • 7.10. Building regional climate scenarios
At this stage
136 hestimated workload
11 wkweeks at your pace
Module 8

Operational applications of weather forecasting in strategic sectors

  • 8.1. Weather forecasting for aviation and navigation
  • 8.2. Applications in agriculture and water resource management
  • 8.3. Meteorology applied to renewable energy
  • 8.4. Risk and natural disaster management
  • 8.5. Early warning systems
  • 8.6. Applications in urban and spatial planning
  • 8.7. Weather forecasting for transportation
  • 8.8. Economic impact of weather forecasting
  • 8.9. Operational weather services
  • 8.10. Integration of forecasts into decision-making
At this stage
136 hestimated workload
11 wkweeks at your pace
Module 9

Artificial intelligence, big data and new technologies in climatology and weather forecasting

  • 9.1. Applying artificial intelligence to weather analysis
  • 9.2. Machine learning for weather forecasting
  • 9.3. Big data in climatology
  • 9.4. Integration of heterogeneous data
  • 9.5. Hybrid physical-statistical models
  • 9.6. Forecast automation
  • 9.7. Decision support systems
  • 9.8. Advanced visualization of climate data
  • 9.9. Technological innovation in meteorology
  • 9.10. The future of weather forecasting
At this stage
136 hestimated workload
11 wkweeks at your pace
Module 10

Marine and aviation meteorology and climate services

  • 10.1. Marine weather forecasting
  • 10.2. Waves and storms at sea
  • 10.3. Aviation meteorology
  • 10.4. Hazardous weather and warnings
  • 10.5. Climate services for economic sectors
  • 10.6. Seasonal forecasting
  • 10.7. Climate reanalyses
  • 10.8. Communicating forecasts
  • 10.9. Forecast verification
  • 10.10. Designing a weather service
At this stage
136 hestimated workload
11 wkweeks at your pace
Module 11

Final Project

  • 11.1. Definition of the case study
  • 11.2. Collection of meteorological and satellite data
  • 11.3. Processing and analysis of information
  • 11.4. Application of forecasting models
  • 11.5. Data integration and simulation
  • 11.6. Evaluation of results
  • 11.7. Drawing conclusions
  • 11.8. Practical application of the project
  • 11.9. Writing of the technical report
  • 11.10. Presentation and defense of the final project
At this stage
136 hestimated workload
11 wkweeks at your pace
Plan your pace

Duration and format of the Master's in Climatology and Satellite Weather Forecasting

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

4 h30 h
With 12 h per week
29
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.

Dra. Marina AlcoverDr. Marina AlcoverAcademic Director and Head of Quality Assurance
Ing. Diego CifuentesEng. Diego CifuentesSenior Lecturer in Naval Welding and Non-Destructive Testing; Head of QA/QC for Welded Joints
Cap. Javier Abaroa (MCA)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 FerrerDr. Pau FerrerSenior Lecturer in Naval Architecture and Simulation; Director of the Hydrodynamics and CFD Laboratory
Dra. Nuria LlobregatDr. Nuria LlobregatSenior Lecturer in Marine Meteorology, SAR and Operational Safety; Navigation Risk Management Coordinator
Ing. Javier BañulsEng. Javier BañulsSenior Lecturer in Electrical Engineering, Automation and ETO Engineering; Electronic Integration and Engine Alarms Coordinator
Ing. Sofía MarquinaEng. Sofía MarquinaSenior Lecturer in Materials, Composites and Corrosion Protection; Coordinator of the Advanced Paints and Coatings Line
Ing. Tomás RieraEng. Tomás RieraSenior Lecturer in Propulsion, Alternative Energy and Hybrid Systems; Energy Performance and Vibration Coordinator
Objectives

Objectives of the Master's in Climatology and Satellite Weather Forecasting

01Develop advanced predictive models, using machine learning algorithms such as regression, classification and neural networks together with numerical model output and satellite observations, to forecast temperature, precipitation and high-impact weather events.
02Interpret satellite data to improve water resource management, analyzing spectral and geospatial information to assess water availability, quality and use and to identify patterns and anomalies that support informed decisions.
03Assess the impact of climate change on regional weather patterns, analyzing historical records and predictive models to identify trends in temperature, precipitation and extreme events while considering the vulnerability of ecosystems and local communities.
04Design mitigation strategies for extreme weather events, assessing the specific risks of each type of hazard, such as waves, wind, ice or heavy rain, and adapting operational plans for navigation, transportation and other exposed activities.
05Communicate weather and climate information effectively to different audiences, adapting language and format to the knowledge level and needs of each one, from the public and businesses to the media.
06Lead weather and climate research projects based on satellite technology, designing, carrying out and communicating robust studies that ensure satellite data quality and its integration with climate models, working with experts and managing resources efficiently.
Careers

Career opportunities after the Master's in Climatology and Satellite Weather Forecasting

01Meteorologist or climatologist in national or regional weather servicesforecasting, monitoring and analysis of weather and climate.
02Consultant for the energy, agriculture, tourism, insurance or shipping sectorsclimate risk assessment and optimization of weather-sensitive activities.
03Researcher in research centersdevelopment of climate models, satellite data analysis and impact studies.
04Climate data analystprocessing and analysis of large volumes of weather and climate data.
05Remote sensing specialist or technologistsatellite image analysis for environmental monitoring and development of observation and forecasting software and instruments.
06Climate adaptation project manager or science communicatorrisk management projects for NGOs and public bodies, and outreach on weather and climate topics.
Frequently asked questions

Questions about the Master's in Climatology and Satellite Weather Forecasting

The application of satellite data and imagery to climatology and weather forecasting, from atmospheric physics and observation to numerical models, climate scenarios and operational services.

Both. It covers short-, medium- and long-range forecasting with numerical models and ensembles, as well as climate variability, climate change projections, seasonal forecasting and reanalyses.

Yes. A specific module deals with marine weather forecasting, waves and storms at sea, alongside aviation meteorology, hazardous weather warnings and climate services.

Data from geostationary and polar-orbiting weather satellites, combined with radiosondes, automatic stations and other observation networks, processed and assimilated into numerical models.

You will apply machine learning to image classification, forecasting and forecast automation, and compare hybrid physical-statistical models with traditional numerical weather prediction.

Online in a flexible format, with practical case studies based on real data, designed for both professionals and students.

Through practical work in each module, such as satellite image analysis, model runs, forecast verification and climate trend studies, together with the Final Project.

A Final Project in which you define a case study, collect and process meteorological and satellite data, apply forecasting models, evaluate the results and present and defend a technical report.

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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: aimed at graduates in physics, mathematics, environmental science, geography or engineering, meteorology and climatology professionals, researchers, environmental consultants and natural resource and spatial planning managers who want to apply satellite technology to climate analysis and weather forecasting; a solid grounding in calculus, physics (especially thermodynamics and fluid mechanics), statistics and programming is recommended, or demonstrable professional experience in meteorology, climatology or related fields.
  • Language: sufficient command of English to follow the classes and the technical documentation.
  • Technical resources: a computer with a camera and microphone, a stable broadband internet connection and software for meteorological data visualization and modeling.
  • Admission: online application, review of your profile and a short interview with the academic team.
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