Contents
63-953 Climate and Satellite Data Analysis
MS Integrated Climate System Sciences
Date: 3.2.2014-7.2.2014
Place: Geom 1536c
Course objectives
The participants will learn to practically work with climate model, reanalysis, in-situ station and satellite data. Organized as a group project, the participants will further learn the principles of project management and shared software development.
Schedule
Monday
General Introduction
Stochastic analysis of time series.ipynb Monte carlo.ipynb GISSTEMP netcdf.ipynb datetimeobjects.ipynb Station data seasonal cycle.ipynb
Group work: develop a project plan and write a short technical proposal for your project.
Final report due by 15. March 2014
Obtain data and do preliminary analysis (e.g. data coverage).
Tuesday
Morning: Group presentations of project plan and preliminary analysis. Afternoon: implementation and project work
Wednesday
Morning: Group presentations of methods and code implementations Afternoon: Project work
Thursday
Morning: Group presentations of preliminary results Afternoon: Project work
Friday
Morning: final presenation of results and discussion Afternoon: evaluation and preparation of final report
Topics for group work
Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends
Kevin Cowtan and Robert Way fill the gaps of the HadCRUT temperature data set by using satellite data. Compare their new reconstruction of surface temperature data compares to independent in-situ observations!
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TODOs
Data
prepare sea ice data (Lars)
(CMIP5 data available) prepare CMIP5 data (Alex)
ERA-Interim
NCEP
Stations
Final report
Template structure:
- Abstract
- Introduction: state of the art (literature), statement of the problem
- Methods and data
- Results
- Discussion
- Conlcusion
References
- Python Scripting for Computational Science, Hans Petter Langtangen, Springer (available in the ZMAW library)