https://github.com/brian-rose/stage-iv-cookbook

https://github.com/brian-rose/stage-iv-cookbook

Repository

https://github.com/brian-rose/Stage-IV-Cookbook/blob/main/

# Stage IV Precipitation Cookbook

[![nightly-build](https://github.com/ProjectPythia/cookbook-template/actions/workflows/nightly-build.yaml/badge.svg)](https://github.com/ProjectPythia/cookbook-template/actions/workflows/nightly-build.yaml)
[![Binder](https://binder.projectpythia.org/badge_logo.svg)](https://binder.projectpythia.org/v2/gh/ProjectPythia/cookbook-template/main?labpath=notebooks)
[![DOI](https://zenodo.org/badge/475509405.svg)](https://zenodo.org/badge/latestdoi/475509405)

This Project Pythia Cookbook covers Stage IV Precipitation data analysis that can be employed in a variety of applications.

## Motivation

Due to its high-resolution grid spacing, Hourly Stage IV Precipitation is a highly beneficial tool for analyzing precipitation observations throughout the contiguous United States. Stage IV data is plotted on a 4 km by 4 km polar-stereographic grid, allowing for identification of discontinuities as a result of the operational process. Upon completion of the cookbook, one will gain experience with packages such as cartopy, metpy, and numpy as well as the pandas dataframe.

## Authors

[Evan Belkin](http://github.com/evan-belkin), [Marian de Orla-Barile](https://github.com/mariandob), [Selena Ramos](https://github.com/Selenaramoswx), [Kimberly Riek](https://github.com/Kriek21), [Kathryn Rooney](https://github.com/kathrynrooney)

### Contributors


  


## Structure

(State one or more sections that will comprise the notebook. E.g., _This cookbook is broken up into two main sections - "Foundations" and "Example Workflows."_ Then, describe each section below.)

### Section 1 ( Replace with the title of this section, e.g. "Foundations" )

(Add content for this section, e.g., "The foundational content includes ... ")

### Section 2 ( Replace with the title of this section, e.g. "Example workflows" )

(Add content for this section, e.g., "Example workflows include ... ")

## Running the Notebooks

You can either run the notebook using [Binder](https://binder.projectpythia.org/) or on your local machine.

### Running on Binder

The simplest way to interact with a Jupyter Notebook is through
[Binder](https://binder.projectpythia.org/), which enables the execution of a
[Jupyter Book](https://jupyterbook.org) in the cloud. The details of how this works are not
important for now. 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. youll be able to execute
and even change the example programs. Youll 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](https://foundations.projectpythia.org/foundations/getting-started-jupyter.html).

### Running on Your Own Machine

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

(Replace "cookbook-example" with the title of your cookbooks)

1. Clone the `https://github.com/ProjectPythia/cookbook-example` repository:

   ```bash
    git clone https://github.com/ProjectPythia/cookbook-example.git
   ```

1. Move into the `cookbook-example` directory
   ```bash
   cd cookbook-example
   ```
1. Create and activate your conda environment from the `environment.yml` file
   ```bash
   conda env create -f environment.yml
   conda activate cookbook-example
   ```
1. Move into the `notebooks` directory and start up Jupyterlab
   ```bash
   cd notebooks/
   jupyter lab
   ```
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