GOES-R-Weather-Hazards

Project Title

Leveraging GEOS observations for near real-time monitoring of weather hazards over the continental United States

Overview

This repository contains all the codes developed as a part of the GOES-R DataJam competition. Our project harnesses the power of GEOS observations to enable near real-time monitoring of weather hazards, specifically tailored for the continental U.S.

Table of Contents

• Project Description
• Features
• Installation and Usage
• Live Website
• Contributors
• Acknowledgements
• License

Project Description

The goal of our project is to effectively utilize the vast datasets from GEOS observations to create an actionable, real-time monitoring system that aids in identifying and responding to weather hazards in the continental U.S. Our approach emphasizes user-friendly visualizations, efficient data processing, and precise alert systems.

Features

• Real-time Data Monitoring: Seamlessly integrates GEOS observational data to provide up-to-the-minute insights.
• Interactive Visualizations: Offers intuitive and interactive charts and maps to represent complex weather data.
• Alert System: Users can set custom thresholds for various weather parameters to receive timely alerts.
• Cloud-based Data Retrieval: Efficiently fetches and processes data from cloud services.
• Open Source: Encourages community contributions and improvements.

Installation and Usage

1. Clone the repo:

git clone https://github.com/your_username/GOES-R-Weather-Hazards.git

2. Navigate to the directory:

cd GOES-R-Weather-Hazards

3. Follow the instructions in the specific code folders for setup and usage details.

Live Website

Experience our project in action! The website is hosted here.

Contributors

Team members:

• Mohamed Abdelkader, Stevens Institute of Technology, USA
• Daniela Montano Bello, National University of Colombia, Colombia
• Jorge Bravo, Stevens Institute of Technology, USA
• Maria Moreno, National University of Colombia, Colombia
• Jessica Souza, Texas Tech University, USA
• Matsane Willem, University of Limpopo, South Africa

Mentors:

• Peter Vanden Bosch, National Weather Service Office, Texas, USA
• Tristan Klintworth, Office of Observations at the National Weather Service, Maryland, USA

Acknowledgements

We'd like to thank the organizers of the GOES-R DataJam competition for providing us with this opportunity and the community for their continuous support.

License

This project is licensed under the MIT License. See the LICENSE file for details.