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Lund University
Computational Science: Introduction to Modelling of Climate System
<p>Mathematical modelling is an essential tool within earth system sciences to understand processes and test hypotheses. For example, hypotheses related to ongoing climate changes are tested with models, and the estimated impacts of future global warming are based on model scenarios. On longer timescales, the comple…
- Higher education
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- 2 November 2026
- Information unavailable
- Information unavailable
- 50 %
Overview
<p>Mathematical modelling is an essential tool within earth system sciences to understand processes and test hypotheses. For example, hypotheses related to ongoing climate changes are tested with models, and the estimated impacts of future global warming are based on model scenarios. On longer timescales, the complex dynamics of climate changes during the last glacial cycle have been reproduced in climate models, adding to our understanding of the natural variability of the climate system. In this course you will learn how earth system models work, how they are constructed, how to handle large amounts of data, and how to analyse complex systems.</p> <p>In the first half of the course different components of contemporary climate models (ocean/land/atmosphere) and interactions between them are introduced and discussed. This includes handling of typical data formats associated with climate models and the analysis of model output with varying resolution and/or complexity. The second half of the course focuses on applications in palaeoclimate reconstructions and impact models as well as the use of ensembles to assess model uncertainties. This includes an individual project where you solve tasks using programming. There will be exercises in the use of simplified climate models and analysis tools as well as information retrieval, and you will do oral and written presentations.</p> <p>This course covers the basics of how to become a confident model user, how to understand the strengths and limitations of modelling. You will also learn how to carry out the necessary analysis of data for interpretation of model outputs and for comparison with observations and more long-term time series from geological archives.</p>
Admission scores
Entry requirements
For admission to the course 90 credits in natural science or engineering, including knowledge equivalent to BERN01, Modelling in Computational Science, 7.5 credits and English 6/B are required.
The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.
Source, measure and data quality
- Source
- Skolverket Susa-navet
- Period
- 2026-11-02
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.lu.bern03.14550.20262
- Last checked
- 2026-09-23T10:38:26.989764+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
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About the provider
Sources and data quality
Education facts for the selected offering come from Skolverket Susa-navet.
Retrieved . Published . Times are shown in Swedish local time.
Source identity and publication version
- Publication version
- 8e217193-f5fa-4778-b085-a4521fd03e8d
- Education identity in the source
- i.uoh.lu.bern03.14550.20262
- Offering identity in the source
- e.uoh.lu.bern03.14550.20262
- Education-form source code
- HS
- Education code in the source
- BERN03
- Change time according to the source
- 2026-02-03T11:46:07
The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.