IGRA Radiosonde Data Analysis Toolkit

Overview

This repository contains a Jupyter notebook for accessing, processing, and visualizing data from the Integrated Global Radiosonde Archive (IGRA). IGRA provides quality-controlled radiosonde observations from around the world, which are valuable for climate research, weather analysis, and atmospheric studies.

The toolkit enables:

• Downloading IGRA radiosonde data for any station
• Processing both raw sounding measurements and derived stability parameters
• Storing data efficiently in NetCDF format
• Visualizing atmospheric profiles, time series, and stability indices

Requirements

• Python 3.7+
• Required packages:
  • numpy
  • pandas
  • xarray
  • matplotlib
  • requests
  • tqdm
• Optional packages for enhanced functionality:
  • metpy (for Skew-T diagrams and atmospheric calculations)

You can install the required packages using:

pip install numpy pandas xarray matplotlib requests tqdm
pip install metpy  # Optional but recommended

Usage

1. Open the Jupyter notebook: IGRA_Data_Analysis.ipynb
2. Set the station ID for the desired location (e.g., USM00072201 for Key West, FL)
3. Run the notebook to download and process the data
4. Use the visualization functions to explore the atmospheric profiles

The notebook includes:

• Functions for downloading and caching data
• Parsers for IGRA data formats (both raw sounding data and derived parameters)
• Conversion to xarray Datasets
• Visualization tools:
  • Vertical profiles
  • Time series
  • Skew-T log-P diagrams (with MetPy)
  • Time-height cross sections

Data Source

The data is sourced from the NOAA Integrated Global Radiosonde Archive (IGRA) Version 2:

• Base URL: https://www.ncei.noaa.gov/data/integrated-global-radiosonde-archive/access/

IGRA contains radiosonde and pilot balloon observations from over 2,700 globally distributed stations. Data records extend as far back as 1905, and in some cases to the present.

Features

• Caching: Data is cached locally to avoid redundant downloads
• Comprehensive Parsing: Correctly handles both raw sounding data and derived stability parameters
• Missing Value Handling: Properly manages missing or invalid data
• Units Conversion: Converts data to standard meteorological units
• NetCDF Storage: Saves processed data in efficient NetCDF format with compression
• Visualization: Creates standard meteorological plots

Citation

If you use this toolkit in your research, please cite both this repository and the IGRA dataset:

Durre, I., X. Yin, R. S. Vose, S. Applequist, and J. Arnfield, 2018: Enhancing the data coverage in the Integrated Global Radiosonde Archive. Journal of Atmospheric and Oceanic Technology, 35, 1753-1770.

License

This project is licensed under the MIT License - see the LICENSE file for details.