What tools and datasets are available to quantify water quantity and availability?
The third module of our open climate-science curriculum focuses on how to begin a reproducible computational science project, using water resources as a thematic example. At the end of this module, you should be able to:
- Describe the major fluxes and pools of the terrestrial water cycle;
- Know where to access remotely sensed or modeled data on water storage anomalies, evapotranspiration, and soil moisture;
- Calculate a water budget.
- Creating a Research Software Environment
- Analyzing a Global Precipitation Data Cube
- Tracking Changes to Research Code
- Creating a Basin-Scale Water Budget
- Documenting our Water Budget Workflow
See our installation guide here.
You can run the notebooks in this repository using Github Codespaces or as a VSCode Dev Container. Once your container is running, launch Jupyter Notebook by:
# Create your own password when prompted
jupyter server password
# Then, launch Jupyter Notebook; enter your password when prompted
jupyter notebook
The Python libraries required for the exercises can be installed using the pip
package manager:
pip install xarray netcdf4 dask
- Chooses meaningful filenames (CC1.3)
- Records relationships between code, results, and metadata (CC1.5)
- Uses a package manager to install and manage software dependencies (CC1.10)
- Understands multi-dimensional arrays (CC2.3)
- Can scale up a computational workflow (CC2.6)
- Chooses variable names that are clear and informative (CC3.8)
- Uses assertions to verify assumptions as runtime (CC4.7)
- Writes short, simple functions that have no side effects (CC4.9)
In addition, learners will see how to:
- Merge multiple HDF files together into an
xarray.Dataset
- Subset an
xarray.Dataset
using an ERSI Shapefile
- Monthly precipitation totals from NASA IMERG-Final
- Terrestrial water storage anomalies from the NASA GRACE and GRACE-FO missions
This curriculum was enabled by a grant from NASA's Transition to Open Science (TOPS) Training program (80NSSC23K0864), part of NASA's TOPS Program