2025
Atmospheric Modeling
Name: Atmospheric Modeling
Code: EME13174D
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Mechanical Engineering
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Sustainable Development Goals
Learning Goals
To provide an up-to-date overview on the atmospheric processes, numerical methods, and computational techniques required for advanced students and scientists to study meteorology, climate and air pollution.
Contents
Scales of motions and types of atmospheric models: LES, mesoscale, weather forecast and general circulation models.
The governing equations. Coordinate systems and projections.
Numerical methods and computational concepts. Discretization of the dynamic equations and parameterization of subgrid-scale physical processes.
Atmosphere-surface interactions and Boundary Layer representations. turbulence
Radiative transfer schemes. Clouds and precipitation. Shallow and deep convection. Atmospheric chemistry and aerosols parameterizations.
Data assimilation and model initialization.
Performing numerical simulations with atmospheric models: case studies.
The governing equations. Coordinate systems and projections.
Numerical methods and computational concepts. Discretization of the dynamic equations and parameterization of subgrid-scale physical processes.
Atmosphere-surface interactions and Boundary Layer representations. turbulence
Radiative transfer schemes. Clouds and precipitation. Shallow and deep convection. Atmospheric chemistry and aerosols parameterizations.
Data assimilation and model initialization.
Performing numerical simulations with atmospheric models: case studies.
Teaching Methods
Theoretical lectures
Practice in atmospheric modeling (case studies)
Evaluation: Realization of two works, one or them based on the realization of a simulation of a real case with an atmospheric model.
Practice in atmospheric modeling (case studies)
Evaluation: Realization of two works, one or them based on the realization of a simulation of a real case with an atmospheric model.
Teaching Staff (2024/2025 )
- Rui Paulo Vasco Salgado [responsible]