NASA ARSET Training Repository

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This repository provides materials and code for NASA ARSET training on assessing extreme weather statistics using NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6). It includes:

• Intake catalog for NEX-GDDP-CMIP6 climate data
• ETCCDI indices calculation scripts and notebooks
• Country-level analysis using Natural Earth shapefiles
• Interactive Jupyter notebooks for data exploration and visualization

• cmip6_catalog.yml — Intake catalog for NEX-GDDP-CMIP6 data
• requirements.txt — Python dependencies
• scripts/ — Python scripts and Jupyter notebooks:
  • ETCCDI indices drivers and calculators (ETCCDI_*)
  • Data download and streaming (download_nex_gddp.py, Streaming_Via_Intake.ipynb)
  • Plotting and country stats (Plot_NEX-GDDP.ipynb, ETCCDI_country_stats.ipynb)
  • Country boundaries (Natural Earth shapefiles)

For a full description of each script and file, see details.md.

Clone the repository and install dependencies:

git clone https://github.com/aashishpanta0/nasa-arset-training.git
cd nasa-arset-training
pip install -r requirements.txt

import intake
cat = intake.open_catalog("cmip6_catalog.yml")
ds = cat.nex_gddp_cmip6(
        model="CMCC-CM2-SR5",
        variable="tas",
        scenario="historical",
        timestamp="2005-06-15",
        quality=0
).read()
ds.plot()

• Use the Jupyter notebooks in scripts/ for step-by-step workflows on climate indices and country-level statistics.
• Shapefiles for country boundaries are provided in scripts/shapefile/ (source: Natural Earth).

• NEX-GDDP-CMIP6: Daily downscaled climate projections
• Natural Earth: Country boundaries shapefiles

Launch a cloud Jupyter environment to browse the catalog, analyze data, and plot interactively.

This work was developed as part of ongoing research at the NASA JPL, National Science Data Fabric(NSDF), and Scientific Computing and Imaging (SCI) Institute at the University of Utah. The library, data and workflow here is managed by National Science Data Fabric(NSDF).

Aashish Panta, Alex Goodman, Kyo Lee, Valerio Pascucci
University of Utah, NASA JPL