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Climate Data Analysis

Binder

A modular Jupyter-based workflow for accessing, analysing, and visualising regional climate model data, with support for remote data access, spatial processing, regional aggregation, and interactive exploration.

This repository is designed for use both online via Binder and locally for extended analysis.


Overview

This toolkit provides a structured approach to working with regional climate datasets, including:

  • Direct access to remote NetCDF data via THREDDS / OPeNDAP
  • Spatial preparation through subsetting and regridding
  • Regional-scale analysis using WA Natural Resource Management (NRM) boundaries
  • Consistent visualisation workflows
  • Interactive exploration using Jupyter widgets

Each notebook performs a defined function and can be used independently.


Access options

Online (recommended for quick access)

Use Binder to run the notebooks in your browser with no local installation.

Click the Launch Binder badge above to start.

Local execution

Recommended for large datasets and computationally intensive workflows.


Repository structure

The repository is organised by function, not by dependency.
Notebooks can be run independently.

Notebook overview

  • 00_Local_Environment_Setup.ipynb – Step‑by‑step local environment setup using Miniforge + mamba.
  • 01_accessing_data.ipynb – Standardised access to NARCliM climate data via THREDDS / OPeNDAP.
  • 02_regridding.ipynb – Spatial regridding to regular latitude–longitude grids.
  • 03_wa_nrm_region.ipynb – Regional analysis using WA NRM boundaries.
  • 04_mapping_and_visualisation.ipynb – Spatial maps and time‑series visualisation.
  • 05_basic_climate_analysis.ipynb – Core climate statistics and summary routines.
  • 06_interactive_analysis.ipynb – Interactive, widget‑based exploratory analysis.

Getting started with Binder

  1. Open this repository on GitHub.
  2. Click the Launch Binder badge.
  3. Wait for the environment to initialise.
  4. JupyterLab will open in your browser.
  5. Select any notebook and execute cells using Shift + Enter.

Binder sessions are temporary.
Download outputs or commit changes before closing the session.


Local setup

Clone the repository

git clone <repository-url>
cd <repository-folder>

Create and activate a conda environment

conda create -n climate-toolkit python=3.10 conda activate climate-toolkit

Install dependencies

pip install -r requirements.txt

Launch JupyterLab

jupyter lab


Contributors

Contributors


Acknowledgement

This repository contains example workflows, analysis notebooks, and supporting utilities developed as part of a Climate Science Initiative (CSI) project. The material has been informed by established best practices in climate data analysis and by feedback from researchers and practitioners working with regional climate projection datasets.

Regional climate projection data used in these examples are sourced from the NARCliM2.0 project and accessed via National Computational Infrastructure (NCI) THREDDS services. Additional datasets and contextual information may reference material published by the Department of Water and Environmental Regulation (DWER) and Data WA.

Disclaimer and Terms of Use

This repository is provided for demonstration, exploratory analysis, and learning purposes only. It does not represent an official operational product, advice, or service of the Government of Western Australia.

Use of any Government of Western Australia websites, services, or datasets referenced in this repository is subject to the relevant official terms and conditions, including the WA.gov.au Terms of Use: https://www.wa.gov.au/terms-of-use

Users are responsible for ensuring their use of data and outputs complies with all applicable licence conditions and legal requirements. Any interpretations, conclusions, or errors arising from the use of this repository remain the responsibility of the users.

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Jupyter notebooks for climate data analysis

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