A proof of concept for a digital twin for the Argonne Testbed for Multiscale Observational Studies. This initial package contains a model that determines the lakebreeze front location from the 0.5 degree scan of the NEXRAD radar.
Project description
ADAM is the ATMOS Analogue Digital Twin, a Python package that provides tools and predictive models for analyzing lake breezes using NEXRAD radar data. This initial package contains a model that determines the lake breeze front location from the 0.5 degree scan of the NEXRAD radar.
Installation
The recommended way to install ADAM is via pip. This will ensure you get the latest stable release and all required dependencies:
pip install adam-atmos
Getting Started
After installation, you can import ADAM in your Python scripts or notebooks:
import adam
ADAM includes a predictive model for detecting and analyzing lake breezes from NEXRAD radar data. See the documentation and example notebooks for usage details.
Links
Documentation: https://rcjackson.github.io/adam/
Source code: https://github.com/rcjackson/adam
Free software: BSD license
Documentation: https://adam.readthedocs.io.
Features
Lake breeze detection from NEXRAD radar data using deep learning models.
Easy-to-use API for loading and processing radar data.
Example notebooks demonstrating functionality.
Credits
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
Project details
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