- Docente: Antonio Navarra
- Crediti formativi: 9
- SSD: GEO/12
- Lingua di insegnamento: Inglese
- Modalità didattica: Convenzionale - Lezioni in presenza
- Campus: Bologna
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Corso:
Laurea Magistrale in
Science of Climate (cod. 5895)
Valido anche per Laurea Magistrale in Physics (cod. 9245)
Laurea Magistrale in Scienze e gestione della natura (cod. 9257)
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dal 16/09/2024 al 20/12/2024
Conoscenze e abilità da conseguire
The student will learn the conceptual basis of earth system modelling and its major components . The student will learn how the atmospheric, oceanic, cryogenic and ecosystems components can be modelled separately and how they can be coupled using examples from state-of-the-art models. The student will be exposed to strategies to design numerical experiments, verification and validation procedures using both ensemble techniques and probabilistic approaches. At the end of the course, the student will have a grasp of logic and rationale framing of earth system modelling, and will develop a capacity to design numerical experiments and a critical understanding of the verification and validation procedures.
Contenuti
- Introduction and Historical Developments
- Physical Description of the climate system
- Basic Numerical methods for constructing the Earth System Model
- Numerical Grids
- Finite Differences
- Spectral Methods
- Lagrangian Methods
- Spectral Elements
- Finite Volume
- Components of the Climate system
- Atmosphere General Circulation Model: adiabatic component
- Atmosphere General Circulation Model: diabatic processes
- Atmosphere General Circulation Model: convection
- Ocean General Circulation Model
- Sea-ice models
- Land
- Terrestrial ecosystems models (II
- Marine biogeochemistry
- Atmosphere chemistry
- The concept of climate system simulations
- Hierarchy of global coupled models
- The General Circulation Model as a Numerical Laboratory
- Strategies for the design of numerical experiments
- Verification, diagnostics and fidelity of global models.
- Sensitivity to small perturbations
- Probability Distributions
- The rise of AI in weather and climate sciences.
- Dynamical modeling and Statistical Modeling
- Modeling with Deep Learning methods
- Prospects of global climate modelling
Testi/Bibliografia
Warren,M.W. and C.L. Parkinson, Three-dimensional Climate Modeling, University Science Books, CA.
Trenberth, K, Climate System Modeling (selected Chapters)
Notes and other readings may be provided during the course
Metodi didattici
Lectures
Modalità di verifica e valutazione dell'apprendimento
Written test and oral exam
Orario di ricevimento
Consulta il sito web di Antonio Navarra
SDGs




L'insegnamento contribuisce al perseguimento degli Obiettivi di Sviluppo Sostenibile dell'Agenda 2030 dell'ONU.