MPAS+JEDI Cookbook

This Project Pythia Cookbook focuses on analyzing, visualizing, and interpreting MPAS model output on its native unstructured grid, as well as exploring MPAS-JEDI data assimilation results in both the model and observation spaces.

Disclaimer: This cookbook does not cover how to run MPAS or JEDI. Readers are encourage to visit MPAS or JEDI websites for more details

Motivation

NOAA's next generation Rapid Refresh Forecast System (RRFS) is built on the MPAS (Model for Prediction Accross Scals) Model and the JEDI (Joint Effort for Data assimilation Integration) system. While both MPAS and JEDI are powerful tools, they can also be complex to use and interpret. This cookbook will demonstrate how to explore MPAS output and MPAS-JEDI analyses directly on the unstructed grid using the UXarray package. It also includes examples for examining JEDI analyses in observation space.

Authors

• Guoqing Ge
• Orhan Eroglu
• etc.
  (Acknowledge primary content authors here)

Contributors

Structure

This cookbook is broken into three sections: "Introduction", "MPAS (regional) Analysis and Visualization", "MPAS-JEDI Analysis and Visulization".

Section 1 Introduction

The introduction part will provide a quick overview about MPAS, JEDI and RRFS(v2).

Section 2 MPAS (regional) Analysis and Visualization

This part will demonstrate how to make basic and advanced MPAS analysis and visulazation using UXarray.

Section 3 MPAS-JEDI Analysis and Visualization

This part will demonstrate how to explore MPAS-JEDI data assimilation results in both the model and observation spaces.

Running the Notebooks

You can either run the notebook using Binder or on your local machine.

Running on Binder

The simplest way to interact with a Jupyter Notebook is through Binder, which enables the execution of a Jupyter Book in the cloud. All you need to know is how to launch a Pythia Cookbooks chapter via Binder. Simply navigate your mouse to the top right corner of the book chapter you are viewing and click on the rocket ship icon, (see figure below), and be sure to select “launch Binder”. After a moment you should be presented with a notebook that you can interact with. I.e. you’ll be able to execute and even change the example programs. You’ll see that the code cells have no output at first, until you execute them by pressing {kbd}Shift+{kbd}Enter. Complete details on how to interact with a live Jupyter notebook are described in Getting Started with Jupyter.

Note, not all Cookbook chapters are executable. If you do not see the rocket ship icon, such as on this page, you are not viewing an executable book chapter.

Running on Your Own Machine

If you are interested in running this material locally on your computer, you will need to follow this workflow:

1. Clone the https://github.com/ProjectPythia/mpas-jedi-cookbook repository:

    git clone https://github.com/ProjectPythia/mpas-jedi-cookbook

2. Move into the mpas-jedi-cookbook directory

   cd mpas-jedi-cookbook

3. Create and activate your conda environment from the environment.yml file

   conda env create -f environment.yml
   conda activate mpas-jedi-cookbook

4. Move into the notebooks directory and start up Jupyterlab

   cd notebooks/
   jupyter lab