---
id: cmweather
version: "0.3.2"
license: MIT license
license_treatment: permissive
maintenance: dormant
---

# cmweather — A library of useful colormaps when visualizing weather and climate data, with numerous color vision deficiency friendly options

License: permissive · Maintenance: dormant · Downloads: 98.0K/mo

## What it is and what it does

cmweather is a lightweight library that extends matplotlib with colormaps designed specifically for weather and climate visualization. It fills a gap left by core matplotlib by providing domain-specific colormaps used across the weather community, including options designed to be friendly to color vision deficiency. The package depends only on numpy and matplotlib, making it easy to integrate into existing scientific Python workflows.

The library is positioned as a community collaboration effort, with contributions from domain-specific packages like MetPy and GeoCAT. While marked as Pre-Alpha in development status and dormant in maintenance (last release January 2024), it remains archived-free and suitable for stable visualization tasks where weather-specific colormaps are needed.

Use it for:

- Visualizing meteorological data (radar, satellite, model output) with colormaps optimized for weather interpretation.
- Creating climate analysis plots where standard matplotlib colormaps are inadequate for domain conventions.
- Building accessible weather visualizations using color vision deficiency friendly colormaps.
- Standardizing colormap choices across multiple weather-focused Python packages in a single project.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

cmweather provides a collection of colormaps optimized for weather and climate visualization, including color vision deficiency friendly options, built on numpy and matplotlib.

Yes, if you are working with weather or climate data visualization in Python. The low install friction, permissive MIT license, and stable dependency set (numpy, matplotlib) make it a safe addition. The dormant maintenance status is acceptable for a specialized, feature-complete library; however, do not expect active development or rapid bug fixes. Verify that the colormaps you need are included in version 0.3.2 before committing.

## Install

pip install cmweather
uv add cmweather
poetry add cmweather

## Installing cmweather

Before you install: Low install friction with a pure Python wheel. Maintenance is dormant—last release was 2024-01-04 and no commits for 953 days—but the repository remains active and the package is stable enough for its narrow purpose.

License in practice: MIT license is permissive; you can use, modify, and distribute cmweather with minimal restrictions, making it suitable for both open and proprietary projects.

Quickstart:

pip install cmweather

import cmweather.cmap as cmap
import matplotlib.pyplot as plt

plt.imshow(data, cmap=cmap.cmap_d['your_colormap_name'])

Requires matplotlib and numpy; colormaps are accessed through matplotlib's colormap interface.

Verify before relying:

- Which specific colormaps are included in version 0.3.2 and their names for programmatic access.
- Whether all colormaps are accessible via matplotlib's standard cmap registry or require direct import.
- Performance characteristics when rendering large datasets with these colormaps.

## Package facts

- License: MIT license (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: dormant
- Downloads: 98.0K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

weather colormaps, climate visualization, matplotlib colormaps, color vision deficiency friendly, weather data visualization, scientific colormaps, domain-specific colormaps, visualization, weather-climate, accessibility

[View on SkillFed](https://skillfed.io/packages/cmweather) · [View on PyPI](https://pypi.org/project/cmweather/)