pyghcn

A Python library providing programmatic access to the NOAA Global Historical Climatology Network (GHCN), enabling researchers and developers to work with global weather and climate data.

Project Overview

pyghcn simplifies access to one of the world’s most comprehensive climate databases, containing temperature, precipitation, and pressure records from thousands of weather stations globally. The library abstracts away the complexity of NOAA’s data formats and provides intuitive Python interfaces.

Key Features

• Station Discovery: Retrieve station lists and metadata
• Data Download: Fetch daily weather observations
• Geographic Search: Find stations near specific coordinates
• Data Extraction: Extract specific series (e.g., maximum temperature)
• Comprehensive Testing: Full unit test coverage

Technical Implementation

The library provides:

• Clean Python 3 API for GHCN data access
• Efficient data parsing and caching
• Geographic utilities for station location
• Data transformation helpers

GHCN Database

The Global Historical Climatology Network includes:

• ~6,000 temperature stations
• ~7,500 precipitation stations
• ~2,000 pressure stations
• Daily observations spanning decades
• Global coverage with quality controls

Use Cases

This library enables:

• Climate research and analysis
• Weather pattern studies
• Historical weather data retrieval
• Environmental monitoring applications
• Educational projects in climatology

Open Source Impact

Released under MIT license to support:

• Open climate science research
• Reproducible weather analysis
• Educational use in data science
• Environmental monitoring projects

The project represents an intersection of data engineering and climate science, making important environmental data more accessible to the Python community.