Stage IV Precipitation Cookbook

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

Motivation

The 13 National Weather Service River Forecast Centers (RFCs) analyze multi-sensor precipitation observations from rain gauges, mesonet observations, and radar estimates to create stage IV precipitation analysis data.

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. Through the creation of several plots, including rainfall distribution maps and time series, those who follow this cookbook will develope a deeper understanding of trends, patterns, and outliers in Stage IV Precipitation data.

Through the creation of several plots, including rainfall distribution maps and time series, those who follow this cookbook will develope a deeper understanding of trends, patterns, and outliers in Stage IV Precipitation data. The chef can expect to gain experience with packages such as cartopy, metpy, and numpy as well as the pandas dataframe.

Authors

Evan Belkin, Marian de Orla-Barile, Selena Ramos, Kimberly Riek, Kathryn Rooney

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 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. 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. 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.

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/Stage-IV-Cookbook repository:

bash git clone https://github.com/ProjectPythia/Stage-IV-Cookbook.git

1. Move into the Stage-IV-Cookbook directory bash cd Stage-IV-Cookbook
2. Create and activate your conda environment from the environment.yml file bash conda env create -f environment.yml conda activate Stage-IV-Cookbook
3. Move into the notebooks directory and start up Jupyterlab bash cd notebooks/ jupyter lab =======