Preparing data for climate change analysis using MATLAB
Alexandre Martinez, University of California-Irvine, Civil Engineering Author Profile
This activity was selected for the Teaching Computation in the Sciences Using MATLAB Peer Reviewed Teaching Collection
This activity has received positive reviews in a peer review process involving five review categories. The five categories included in the process are
- Computational, Quantitative, and Scientific Accuracy
- Alignment of Learning Goals, Activities, and Assessments
- Pedagogic Effectiveness
- Robustness (usability and dependability of all components)
- Completeness of the ActivitySheet web page
For more information about the peer review process itself, please see https://serc.carleton.edu/teaching_computation/materials/activity_review.html.
This page first made public: Aug 23, 2019
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In this activity, we mainly learn the importance of analyzing data format before applying models to it, with the examples of drought. We use monthly precipitation from the Climate Research Unit (gridded data) and assess if it is suitable for extreme events or climate change analysis. We learn how to be critical with the initial data provided, about the results calculated, and how to ensure the quality of the calculations performed and to put the results calculated with model in perspective to the empirical results.
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Grade LevelCollege Upper (15-16), Graduate/Professional
The principal obective of this activity is to be critical when using data and be able to quickly indentify a dataset with low consistency. In this activity, the student will learn
- to inspect different key characteristics of a dataset (space uniformity, time variation).
- different strategies data providers are using for filling missing data and how to reveal them.
Context for Use
This activity is designed for the people who wants to learn how to be critical with climate data analysis and for the students who are working on data analysis, at any academic level (undergraduate or graduate). Students with limited coding experiences will be able to successfully complete this activity since it involves more thinking than coding. However basic experience in Matlab syntax is preferred. Basic knowledge of data analysis is also preferred but not required.
Description and Teaching Materials
In the handout
Proposal (Acrobat (PDF) 88kB Aug19 19)
Handout (Acrobat (PDF) 551kB Aug19 19)
dataset (Matlab .MAT File 23.2MB Aug19 19)
Code (Zip Archive 3kB Aug19 19)
livescript.mlx (MATLAB Live Script 741kB Nov5 19)
livescript.pdf (Acrobat (PDF) 4.8MB Nov5 19)
Teaching Notes and Tips
This activity can be performed with other climatic variables: temperature, moisture, etc... Students should make simple calculations (such as average in space or time) and be critical with the physical meaning of the results. Randomly selected a pixel to make a point analysis and look at each steps in details prior going to a global analysis is very common and students should not be afraid (i.e. they should be grade-rewarded) to make extra analysis.
At the end of the activity, the student should have a global map of the length of record of precipitation using CRU data.
References and Resources
AghaKouchak, A., et al. "Remote sensing of drought: Progress, challenges and opportunities." Reviews of Geophysics 53.2 (2015): 452-480.
Martinez, A. "Climate change and extreme values analysis", Teaching Computation in the Sciences Using MATLAB Exemplary Teaching Activities collection (2018). https://serc.carleton.edu/teaching_computation/workshop_2019/activities/231095.html