Contents

Week 9 overview

Week 9 overview

Learning Objectives:

  1. Cloud-served gridded data in Zarr format

  2. Rasters, shapefiles, and cloud-served background imagery

Learning and Participation Activities with Due Dates (Mon. Oct. 24, Noon EDT):

  1. Xarray data analysis and visualization notebooks

    a. cd to your /spare11/atm533/<NetID> directory

    b. Clone Kevin’s week9 folder: git clone /spare11/atm533/ktyle/week9

    c. Open up a JupyterLab session on Turing

    d. Browse to your atm533/week9 directory

    e. Work through the notebooks


  2. Team assignments:

Continued work on your ERA-5 case study:

Please follow these steps … confer among fellow teammates to decide who does what:

a. cd to your team folder

b. Set your repository’s remote URL:      git remote add origin git@github.com:DAES433533/<yourTeamName>    

c. Push your work to that URL, using git push

d. In your testing directory: - Each team member should create or upload a sample file, which could be a notebook, text file, graphics file … whatever you want (you can use the Jupyterlab interface to upload a file)

e. cd back to your team directory, and then stage, commit, and push your changes to GitHub

f. (Once the RDA THREDDS server comes back online, hopefully by Thursday 10/20) - Each team member should create a couple of notebooks for your case - You can do your development work either in your testing or midterm folder - Be sure to stage and commit whenever you have made changes worth saving. You can push to GitHub as well.

  • The due date of the project is now Monday, November 7, 2022.


  1. Post any questions you have on the Week 9 Blackboard Class Community Forum.

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Week 9: 10/17

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Plotting HRRR 2-meter temperatures