This repo intends to provide a combination of snippet-based tutorials referencing open-source utilities as well as full functioning Jupyter notebooks.
Tutorials are a work in progress, and will range from any of the following features/capabilities:
- Data search/discovery
- Data access/subset/extraction
- Data plotting/analysis/visualization
- Direct S3 (Cloud) Access
- Cloud-based operation
- 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-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-env" environemnt:
-> Run the following from your commandline: conda activate tropess-env
| Tutorial Title | Summary | Link | Features/Capabilities |
|---|---|---|---|
| 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 |
| Study 2023 Canadian Wildfires using TROPESS CrIS JPSS-1 Carbon Monoxide (CO) data products - Direct S3 (Cloud) Access | A Jupyter Notebook coded in Python which reads TROPESS CrIS JPSS-1 CO data products for June 2023 and June 2022 directly from S3 on NASA Earthdata Cloud and makes a monthly averaged data product and plots and compare them. | Notebook | Data access/subset/extraction/plotting/analysis/visualization/direct s3 (cloud) access/cloud-based operation |
| Study 2023 Canadian Wildfires using TROPESS CrIS JPSS-1 Carbon Monoxide (CO) data products | 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. | Notebook | Data plotting/analysis/visualization |
| Bullk Download of Megacities Data by Species | Demonstrates the utilization of the open-source earthaccess Python library which allows users to query the CMR API for data granule metadata that can then be used for targetted download and extraction via a user-defined temporal bounding box and the gas species. | Notebook | Data search/access/extraction |
| Bulk Data Subscriber and Download Service | Demonstrates the utilization of a commandline-based tool known as the podaac-data-subscriber[downloader] which allows users to either subscribe to datasets (for periodic, continuous updating featuring the latest available data) or one-time "bulk" downloading of one or more data files with a single request. | Tutorial | Data search/access/extraction |
| TROPESS netCDF Primer Notebook | A Jupyter Notebook coded in Python which fully extracts all data and metadata, then produces a 2-D map plot of the CrIS-JPSS1 L2 Total Column Carbon Monoxide | Notebook | Data extraction/plotting/visualization |
| Canadian Fires - Carbon Monoxide (CO) - CrIS JPSS-1 | A Jupyter Notebook coded in Python which produces 14x14 km gridded map plots of the Carbon Monoxide (CO) total column for each day from 01-Jun-2023 to 08-Jun-2023. | Notebook | Data plotting/analysis/visualization |
| Bash Script for Data Download for Canadian Fires - Carbon Monoxide (CO) - CrIS JPSS-1 | Bash script tutorial provides data download for the period from 01-Jun-2023 to 08-Jun-2023. | Tutorial/Script | Data search/access/extraction |
| Brazilian Fires - Ammonia (NH3) - CrIS JPSS-1 | A Jupyter Notebook coded in Python which produces 14x14 km gridded map plots of the Ammonia (NH3) total column for each day from from 01-Aug-2022 to 31-Aug-2022. | Notebook | Data plotting/analysis/visualization |
| Brazilian Fires - Carbon Monoxide (CO) - CrIS JPSS-1 | A Jupyter Notebook coded in Python which produces 14x14 km gridded map plots of the Carbon Monoxide (CO) total column for each day from from 01-Aug-2022 to 31-Aug-2022. | Notebook | Data plotting/analysis/visualization |
| Brazilian Fires - PeroxyAcetyl Nitrate (PAN) - CrIS JPSS-1 | A Jupyter Notebook coded in Python which produces 14x14 km gridded map plots of the PeroxyAcetyl Nitrate (PAN) free tropospheric column for each day from from 01-Aug-2022 to 31-Aug-2022. | Notebook | Data plotting/analysis/visualization |
| Bash Script for Data Download for Brazilian Fires - NH3/CO/PAN - CrIS JPSS-1 | Bash script tutorial provides data download for the period from 01-Aug-2022 to 31-Aug-2022. | Tutorial/Script | Data search/access/extraction |
| Methane (CH4) Partial Column - Scatter Plot | A Jupyter Notebook coded in Python which produces a scatter plot of the Methane (CH4) Partial Column retrieved from the Cross-track Infrared Sounder (CrIS JPSS-1) global observations. | Notebook | Data plotting/analysis/visualization |
| Methane (CH4) Partial Column - Gridded Plot (1° x 1°) | A Jupyter Notebook coded in Python which produces a 1° x 1° gridded mapped plot of the Methane (CH4) partial column retrieved from the Cross-track Infrared Sounder (CrIS JPSS-1) global observations. | Notebook | Data plotting/analysis/visualization |
| Methane (CH4) Profiles - Scatter Plots | A Jupyter Notebook coded in Python which produces scatter plots at different pressure levels of Methane (CH4) retrieved from the Cross-track Infrared Sounder (CrIS JPSS-1) global observations. | Notebook | Data plotting/analysis/visualization |
| Carbon Monoxide Column (XCO) | A Jupyter Notebook coded in Python which column variable x_col a.k.a. XCO, in ppbv. The XCO is a pre-calculated vertically averaged dry air mixing ratio of carbon monoxide from the surface to Top of Atmosphere (TOA). CO concentrations are retrieved from CrIS JPSS-1 global observations. | Notebook | Data plotting/analysis/visualization |
| Bash Script for Data Download for Methane (CH4) from CrIS JPSS-1 | Bash script tutorial provides data download for CH4 retrievals on 16-May-2023. | Tutorial/Script | Data search/access/extraction |
| Running in Google Colab | Google Colaboratory (Colab) is an alternate cloud-based environment to run Jupyter notebooks, with lots of additional features, like GPUs, storage in Github or Google Drive, and access to Google Cloud. | Tutorial/Script | cloud-based operation |
| Homepage for TROPESS Tutorials and Notebooks | Assorted Jupyter notebooks for TROPESS data access and analysis. | Notebooks/Tutorials | Data access/subset/extraction/plotting/analysis/cloud-based operation |
| Python-based Repository for TROPESS Tutorials and Notebooks | Assorted Jupyter notebooks for TROPESS data access and analysis. | Notebooks/Tutorials | Data access/extraction/plotting/analysis/cloud-based operation |
| GES DISC Tutorials | GitHub Repo with Jupyter Notebooks and Tutorials | External Tutorials and Notebooks | Data search/discovery/access/subset/extraction/plotting/analysis/visualization |
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