Introduction

1. First, follow instruction in here to run a jupyterlab/jupyter notebook on COMET.

2. Run conda_settings.sh bash script

In jupyterlab, click on + button (called New Launcher) and open a terminal. Then, browse to the code directory and run conda_settings.sh batch script from the terminal. The script creates an environment varibale (called snotel) with python 3.6. The reason for installing this verion (<3.7) is that ulmo library does not come with versions greater than 3.6. I need ulmo when retrieving SNOTEL data from CUAHSI data client. After installing python 3.6, the script installs ipykernel that lets to have the new python as a kernel when running the jupyter lab. Finally, it installs required libraries such as ulmo and matplotlib.

Open the jupyterlab and change the kernel to snotel. This is the name that is defined within conda_settings.sh when installing the new kernel.

3. Run SNOTEL_Download_Retrieve.ipynb notebook

This noteook retrieves Snow Water Equivalent (SWE) and accumulated precipitation (P) data from SNOTEL sites through CUAHSI data client service.

Directory Description

• code: Includes the batch and the jupyter notebook scripts.

• input: Includes a CSV file that shows SNOTEL information such as latitudes, longitudes, associated ecoregions, ...

• output: Includes two large CSV files, i.e. snow water equivalent and precipitation measured at SNOTEL gages for all available days. Not uploaded on GitHub.