Course: Monday 8-10 CHN E42
Exercise: Monday 10-12 NO D39
Assistants: Markus Huber (markus.huber[at]env.ethz.ch), Omar Bellprat (omar.bellprat[at]env.ethz.ch).
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.
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.
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
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.
Exercises every two weeks approximately. Powerpoint slides will be provided here.
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) and short presentations
Presentations April 12, 2010
Presentations May 31, 2010
Topics and rules
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