This Project Pythia Cookbook explores the relationship between Sharan dust aerosols (Bodèlè source) and meteorological variables using Self-Organizing Maps (SOM), Principal Component Analysis (PCA), and Random Forest Regression (RF).

Several meteorological and land surface factors have been found to impact Saharan dust emissions and transport. Dust mobilization occurs when surface wind speed of suitable magnitude is above a threshold velocity, often computed based on soil characteristics, vegetation, and solid particles. The purpose of this cookbook is to understand the relationship between dust and some meteorological variables using self-organizing maps (SOM), random forest regression (RF), and principal component analysis (PCA). The question we are really interested in with this cookbook is to know which variables are the most predictive of dust emissions.

For experimenting purpose, we consider PM10 concentration (PM10), 2m temperature (T2), 2m relative humidity (rh2), planetary boundary layer height (PBLH), 10m wind speed (wind_speed_10m), 925hPa wind speed (wind_speed_925hPa), horizontal wind at 10m (U10), meridional wind at 10m (V10), and convective rainfall (RAINC). This cookbook seeks to establish a clear relationship between the meteorological variables and dust (PM10).

Jacob Tindan, Pooja Hari Ambrish, Altug Karakurt, Ali Fallah Acknowledge primary content authors here_

(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.)

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

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

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

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.

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:

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

2. Move into the cookbook-example directory

   cd cookbook-example

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

   conda env create -f environment.yml
   conda activate cookbook-example

4. Move into the notebooks directory and start up Jupyterlab

   cd notebooks/
   jupyter lab