WRF-Hydro calibration demo container

Overview

This container is used for WRF-Hydro training sessions and can be run locally.

This container includes the following:

• Ubuntu base image
• All system libraries required by WRF-Hydro
• Text editors - VIM, Nano, Emacs
• git version control system

Requirements

The easiest and recommended way to run the calibration demo is via the wrfhydro/calibdemo Docker container, which has all software dependencies and data pre-installed.

• Docker >= v.17.12
• Web browser (Google Chrome recommended)

Where to get help and/or post issues

If you have general questions about Docker, there are ample online resources including the excellent Docker documentation at https://docs.docker.com/.

If you have questions regarding the lessons please contact us here https://ral.ucar.edu/projects/wrf_hydro/contact.

The best place ask questions or post issues with these lessons is via the Issues page of the GitHub repository at https://github.com/NCAR/wrf_hydro_training/issues.

How to run

Make sure you have Docker installed and that it can access your localhost ports. Most out-of-the-box Docker installations accepting all defaults will have this configuration.

NOTE: THE DEFAULT DOCKER CONFIGURATION IS FOR 2 CPUS, YOU MUST HAVE AT LEAST 2 CPUS AVAILABLE TO THE DOCKER DAEMON FOR THIS TRAINING

Step 1: Open a terminal or PowerShell session

Step 2: Pull the wrfhydro/calibdemo Docker container

docker pull wrfhydro/calibdemo

Step 3: Start the Docker container Issue the following command in your terminal session to start the training Docker container.

docker run --name wrf-hydro-calib -p 8888:8888 -it wrfhydro/calibdemo

Note: Port forwarding is setup with the -p 8888:8888 argument, which maps your localhost port to the container port. If you already have something running on port 8888 on your localhost you will need to change this number

The container will start and perform a number of actions before starting the training.

• First, the container will pull the model code.
• Second, the container will pull an example test case compatible with the model code release.
• Third, the container will pull the training lessons corresponding to the psecified major version.
• Fourth, the container will launch a Jupyter Notebook server and echo the address to your terminal.

Step 4: Open the jupyter notebook lessons All lessons for this training are contained in the ~/wrf-hydro-training/lessons folder. The lessons are interactive and can execute code commands live. For more information on jupyter notebooks visit the jupyter project page at http://jupyter.org/.