The objective of this course is to enable students to use climate projections from global and regional climate models broadly in impact analyses, while accounting, e.g, for their strengths and limitations. This includes understanding the role of observations of past and recent climate variations in climate modelling. For this aim students are comprehensively introduced to the fundamentals of climate modelling and climate model analysis and develop associated skills through a number of numerical exercises. En studerende, der fuldt ud har opfyldt kursets mål, vil kunne:

• 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
• 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
• 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
• Process climate model data from international database, e.g. CORDEX and CMIP5.
• Process reanalysis data from e.g. ECMWF (e.g. ERA-Interim)
• Use dedicated software to process and analyze climate model data
• Use select statistical techniques

Complex numerical experiments using both regional and global climate models are important tools for understanding the climate system. Climate models are also essential for projecting and evaluating the impacts of climate change to human and natural systems and are in this context often used as part of detailed modeling chain involving, e.g., physical, ecological and/or socio-economic models. Such results frequently serve as input to decision-making on, e.g., adaptation.

This course provides a comprehensive introduction to the fundamentals of climate modeling and climate model analysis. The course is aimed at students from different backgrounds and master programmes, who will use climate model data to assess for example the potential climate change impacts on, e.g., energy and water systems, urban, terrestrial as well as marine environments, including as means to facilitate adaptation decision-making.

The course introduces the general structure and functionality of state-of-the-art climate models as well as a number of key analyses techniques like the use of multi-model ensembles for climate change assessments. The course reviews 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 observations may be used to validate climate models and variations 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. Kursusnoter, udvalgte dele af "The Physical Science Basis - The Working Group 1 contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC)", videnskabelige artikler The course comprises a mix of lectures and numerical exercises, where the students will 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 roughly to the normal 3-week period in June) students from DTU will work additionally on group projects, which concludes in a project report corresponding to 2.5 ECTS. 25. april, 2019