Search result: Catalogue data in Spring Semester 2018
Environmental Sciences Master | ||||||
Major in Atmosphere and Climate | ||||||
Climate Processes and Feedbacks | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
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701-1216-00L | Numerical Modelling of Weather and Climate | W | 4 credits | 3G | C. Schär, U. Lohmann | |
Abstract | The guiding principle of this lecture is that students can understand how weather and climate models are formulated from the governing physical principles and how they are used for climate and weather prediction purposes. | |||||
Learning objective | The guiding principle of this lecture is that students can understand how weather and climate models are formulated from the governing physical principles and how they are used for climate and weather prediction purposes. | |||||
Content | The course provides an introduction into the following themes: numerical methods (finite differences and spectral methods); adiabatic formulation of atmospheric models (vertical coordinates, hydrostatic approximation); parameterization of physical processes (e.g. clouds, convection, boundary layer, radiation); atmospheric data assimilation and weather prediction; predictability (chaos-theory, ensemble methods); climate models (coupled atmospheric, oceanic and biogeochemical models); climate prediction. Hands-on experience with simple models will be acquired in the tutorials. | |||||
Lecture notes | Slides and lecture notes will be made available at Link | |||||
Literature | List of literature will be provided. | |||||
Prerequisites / Notice | Prerequisites: to follow this course, you need some basic background in atmospheric science, numerical methods (e.g., "Numerische Methoden in der Umweltphysik", 701-0461-00L) as well as experience in programming | |||||
701-1232-00L | Radiation and Climate Change | W | 3 credits | 2G | M. Wild, W. Ball | |
Abstract | This lecture focuses on the prominent role of radiation in the energy balance of the Earth and in the context of past and future climate change. | |||||
Learning objective | The aim of this course is to develop a thorough understanding of the fundamental role of radiation in the context of climate change. | |||||
Content | The course will cover the following topics: Basic radiation laws; sun-earth relations; the sun as driver of climate change (faint sun paradox, Milankovic ice age theory, solar cycles); radiative forcings in the atmosphere: aerosol, water vapour, clouds; radiation balance of the Earth (satellite and surface observations, modeling approaches); anthropogenic perturbation of the Earth radiation balance: greenhouse gases and enhanced greenhouse effect, air pollution and global dimming; radiation-induced feedbacks in the climate system (water vapour feedback, snow albedo feedback); climate model scenarios under various radiative forcings. | |||||
Lecture notes | Slides will be made available, lecture notes for part of the course | |||||
Literature | As announced in the course | |||||
701-1252-00L | Climate Change Uncertainty and Risk: From Probabilistic Forecasts to Economics of Climate Adaptation | W | 3 credits | 2V + 1U | D. N. Bresch, R. Knutti | |
Abstract | The course introduces the concepts of predictability, probability, uncertainty and probabilistic risk modelling and their application to climate modeling and the economics of climate adaptation. | |||||
Learning objective | Students will acquire knowledge in uncertainty and risk quantification (probabilistic modelling) and an understanding of the economics of climate adaptation. They will become able to construct their own uncertainty and risk assessment models (MATLAB), hence basic understanding of scientific programming forms a prerequisite of the course. | |||||
Content | The first part of the course covers methods to quantify uncertainty in detecting and attributing human influence on climate change and to generate probabilistic climate change projections on global to regional scales. Model evaluation, calibration and structural error are discussed. In the second part, quantification of risks associated with local climate impacts and the economics of different baskets of climate adaptation options are assessed – leading to informed decisions to optimally allocate resources. Such pre-emptive risk management allows evaluating a mix of prevention, preparation, response, recovery, and (financial) risk transfer actions, resulting in an optimal balance of public and private contributions to risk management, aiming at a more resilient society. The course provides an introduction to the following themes: 1) basics of probabilistic modelling and quantification of uncertainty from global climate change to local impacts of extreme events 2) methods to optimize and constrain model parameters using observations 3) risk management from identification (perception) and understanding (assessment, modelling) to actions (prevention, preparation, response, recovery, risk transfer) 4) basics of economic evaluation, economic decision making in the presence of climate risks and pre-emptive risk management to optimally allocate resources | |||||
Lecture notes | Powerpoint slides will be made available | |||||
Literature | - | |||||
Prerequisites / Notice | Hands-on experience with probabilistic climate models and risk models will be acquired in the tutorials; hence basic understanding of scientific programming forms a prerequisite of the course. Basic understanding of the climate system, e.g. as covered in the course 'Klimasysteme' is required. Examination: graded tutorials during the semester (benotete Semesterleistung) |
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