Overordnede kursusmål:

The aim of this course is to enable students to use climate projections from global and regional climate models in impact analyses, while realizing the models' strengths and limitations. Additionally, the course aims to to provide an overview of observations of past and recent instrumental climate variations and to give an overview of future climate changes as projected with state-of-the art climate models.

Læringsmål:

En studerende, der fuldt ud har opfyldt kursets mål, vil kunne:

• Understand the general structure, functionality and the fundamental mathematical, physical, chemical and biological components in a climate model
• Describe the observed changes in the climate in the past and at present, and be able to attribute these variations to different drivers and mechanisms in the climate system
• Know how ocean and ocean heat content and sea level have risen over the recent past and what methods have been applied to obtain these measures
• Analyze and discuss results and data from state-of-the-art global and regional climate models and be able to use these in analyses using e.g. detailed hydrological, ecological or socio-economic models
• Evaluate and estimate the quantitative uncertainties on climate model projections and to identify the limitations of climate models
• Describe the general future climate changes (including sea level rise) as simulated with state- of-the-art climate models
• Describe the differences between different downscaling techniques: dynamical downscaling (regional climate models) and empirical-statistical downscaling. Know how to downscale results from global and regional climate models
• Extract and process climate model data from international database, e.g. ENSEMBLES, CORDEX, CMIP3 and CMIP5, etc.
• Extract and process reanalysis data from e.g. ECMWF (e.g. ERA-Interim)
• Use dedicated software to process and analyze climate model data
• Use select statistical ensemble techniques

Kursusindhold:

Complex numerical experiments using coupled atmosphere-ocean global circulation models (AOGCM), Earth System Models and regional climate models (RCM) are important tools for understanding the climate system. Climate models are also essential for evaluating the impacts of climate change to human and natural systems and often constitute the initial link in a detailed modeling chain, involving physical, ecological or socio-economic models.

The course provides a comprehensive introduction to climate modeling and climate model analysis, including their general structure and functionality and the use of multi-model ensembles. The course also provides an overview of observations of past (proxy) as well as recent and present day instrumental climate variations based on remote sensing techniques, ground observations, etc. It is discussed how these variations may be attributed to different climate drivers using, e.g. 20th century "hindcasts", and how future climate conditions are simulated by state-of-the-art climate models. Lastly, the course provides an extensive introduction and hands-on experience in using climate model data for different kinds of analyses.

Litteraturhenvisninger:

Kursusnoter, udvalgte dele af Working Group 1s bidrag til den 5. Vurderingsrapport fra FNs Klimapanel, videnskabelige artikler

Bemærkninger:

The course comprises a mix of lectures and exercises, where the students will extract, process and analyze climate data from international data centers like the CORDEX and CMIP5 archives and work with them using, e.g. Matlab. The last 3 weeks of the course (corresponding to the normal 3-week period in June) students from DTU only will work additionally on group projects, which concludes in a project report corresponding to 2.5 ECTS.

Mulighed for GRØN DYST deltagelse:

Dette kursus giver den studerende en mulighed for at lave eller forberede et projekt som kan deltage i DTUs studenterkonference om bæredygtighed, klimateknologi og miljø (GRØN DYST). Se mere på http://www.groendyst.dtu.dk

Kursusansvarlig:

Martin Drews , Risø Campus, Bygning 142, Tlf. (+45) 4677 5155 , mard@dtu.dk
Eigil Kaas , kaas@gfy.ku.dk
Jens Hesselbjerg Christensen , jhc@dmi.dk