Working with Scientific Data Sets in Matlab: Intra-annual variability of Sea Surface Temperature and Data Interpolation
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Sea surface temperature is a critical variable that determines biogeographic and distribution patterns of marine organisms. Changes in temperature influence species reproduction and survival and can affect the spread of invasive species spread and marine diseases. As a result SST is a vital indicator of changes in ecosystem health and understand patterns and causes of change are necessary for conservation decisions. . In a previous activity (Working with Scientific Data Sets in Matlab: An Exploration of Ocean Color and Sea Surface Temperature), you downloaded and sub-scened global, annually averaged SST data. In addition to understanding the year-to-year variability in SST patterns, it is important to understand the SST variability over shorter time scales e.g. daily, seasonal). In this activity we will work with a daily imagery to understand intra-annual variability of SST and interpolate values for where data has not been collected.
In this activity, student will learn to work with scientific data files (e.g. NetCDF) to extract, using Matlab, sea surface temperature data, plot this data and interpolate for missing values.
Context for Use
This is a computer lab activity that caters to a class size of 15-30 students. It is an introductory activity that requires not prior Matlab instruction, but students are expected to completed introductory GIS and a quantitative methods class. The activity forms part of a semester long ecosystem-based management project. The results of this activity are included student final reports.
Description and Teaching Materials
A full description of this activity is included in the attached file, "Working with Scientific Data Sets in Matlab: Intra-annual variability of Sea Surface Temperature and Data Interpolation" In this activity, students are guided through a series of steps including (1) accessing online sea surface temperature data, (2) reading and georeferencing the (NetCDF) data with MATLAB, (3) plotting the data, (4) interpolating missing data (interp function) and (5) creating a batch script with loops to repeat the above steps on multiple files. With each step, students are asked specific questions to help them understand the data sets they are working with and the purpose of the MATLAB commands and functions they are implementing. The student performs the set of steps for a particular region and year identified in the activity, Working with Scientific Data Sets in Matlab: An Exploration of Ocean Color and Sea Surface Temperature set of steps for a particular area of interest . The activity assumes that the College or University has a Matlab license that students can access. Data for this activity are freely available and easy to download from the supplied websites. This exercise is not posted anywhere else and has not yet been thoroughly evaluated and tested. This activity requires a computer lab with a Matlab license as well as sufficient disk storage (~2 GB) for students to download and store data.
Working with Scientific Data Sets in Matlab: Intra-annual variability of Sea Surface Temperature and Data Interpolation (Microsoft Word 2007 (.docx) 24kB Sep21 15)
Teaching Notes and Tips
Most students have problems converting the digital numbers of the sea surface data set into actual geophysical values. The students also need to be careful with adjusting the matrix size, the color scale values (very different for temperature) and pointing Matlab to the correct directory for loading the appropriate files. To overcome many of the above difficulties the activity is run for small groups (<15) allowing the instructor to give the students individual attention. Students are also encouraged to work with one another but are required to submit their own work.
This activity forms part of a larger, term-long project, conducting an ecosystem assessment for a particular marine environment. For this exercise, students are required to submit one plot of annual, daily SST and interpolate missing data. This task is assessed with the attached grading rubric. Grading Rubric (Microsoft Word 2007 (.docx) 45kB Oct11 15)
References and Resources