This repo intends to provide curated set of Jupyter Python notebooks for the IGAC Short Course.
The notebooks feature the following capabilities:
- Data search/discovery
- Data access/subset/extraction
- Data plotting/analysis/visualization
- See the environment.yml file for a list of dependencies.
- If you not familiar with managing your own dependencies, we suggest utilizing the provided environment.yml file, as follows:
Step 1: Create a new conda environment called tropess-igac-env:
-> Download the environment.yml file.
-> Install the free "mini" conda package: https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html
-> Run the following from your commandline: conda env create --file environment.yml
Step 2: Initialize your new "tropess-igac-env" environemnt:
-> Run the following from your commandline: conda activate tropess-igac-env
| Notebook Title | Summary | Link | Features/Capabilities |
|---|---|---|---|
| TROPESS Demonstration of Ozone Data from CrIS and OMI Satellite Instruments - Integrated Data Download | A Jupyter Notebook coded in Python which demonstrates how to open TROPESS CrIS and OMI Ozone data, manipulate the data, and make figures including time series, maps, and atmospheric profiles over a 2-week analysis period. | Notebook  |
Data access/subset/extraction/plotting/analysis/visualization |
| Study of the 2020 COVID Lockdown (February-July) using the TROPESS Chemical Reanalysis (TCR) Version 2 Download and Analysis Notebook - Integrated Data Download | A Jupyter Notebook coded in Python which reads the TROPESS Chemical Reanalysis Surface Total NOx emissions Monthly 2-dimensional Product V1 (TRPSCRENOXTM2D) data products for February to July 2020 directly using HTTPS-based download from NASA Earthdata (GES DISC) and makes a monthly data plots for monthly comparison. | Notebook |
Data access/subset/extraction/plotting/analysis/visualization |
| Study 2023 Canadian Wildfires using TROPESS CrIS JPSS-1 Carbon Monoxide (CO) data products - Integrated Data Download | A Jupyter Notebook coded in Python which reads TROPESS CrIS JPSS-1 CO data products for June 2023 and June 2022 and makes a monthly averaged data product and plots and compare them with fully integrated download of the input data files. | Notebook |
Data access/subset/extraction/plotting/analysis/visualization |
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