Abstract
Terminal Aerodrome Forecasts (TAFs) are essential components of aviation meteorology, providing critical information for flight safety and operational decision-making. This study conducts a comprehensive analysis of TAF for European airports during the years 2022 and 2023, leveraging Python functions accessible via a dedicated GitHub repository. The complexity inherent in TAF, characterized by diverse change groups, header formats, and regional variations, presents challenges for accurate interpretation. The analysis focuses on key parameters within TAF, including the count of corrected messages and the frequency and types of change groups. The count of corrected messages serves as a metric for evaluating the quality of service provided, while the examination of change group utilization reveals distinct patterns and tendencies specific to each airport. The findings underscore the significance of regional regulations, meteorologist decision-making, and adherence to International Civil Aviation Organization (ICAO) standards in shaping TAF. The GitHub repository and associated Python functions presented in this study provide valuable resources for meteorologists, researchers, and aviation personnel to conduct in-depth analyses and derive insights from TAF. Ultimately, this study identifies local differences and inconsistencies in the publication of TAF, laying the groundwork for enhancing their consistency and uniformity.
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