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TOAD (Tipping and Other Abrupt events Detector) is a Python framework for detecting and clustering spatio-temporal patterns in gridded Earth-system datasets.

Note

For general information, project overview, and the latest updates, visit the TOAD GitHub repository.

If you’re new to TOAD, start with the Installation guide and then follow the Quick Start tutorial.

What’s in this documentation?

This documentation provides comprehensive guides for using TOAD in your research:

• Installation - Installation instructions for different environments

• Quick Start - Get started with TOAD in minutes

• Tutorials - Detailed tutorials covering core concepts and advanced usage

• API Reference - Complete API reference for all classes and functions

• Scientific References - Scientific references and methodology details

• Release Notes - Version history and changelog

The TOAD Pipeline

TOAD provides a structured workflow for analyzing Earth-system data:

1. Shift Detection: Identify abrupt transitions at individual grid cells using configurable detection methods

2. Clustering: Group detected shifts spatially and temporally to reveal cohesive patterns

3. Aggregation & Synthesis: Aggregate results across multiple datasets, models, or methods to produce consensus clusters

Getting Help

• Documentation: Browse the sections above or use the search function

• GitHub Issues: Report bugs or request features on GitHub

• Source Code: View the source code on GitHub