We’re delighted to announce brand new Laminar Data features that improve data visualization and support better decision making for airline operations. We’ve added one brand new Historical METAR API and two exciting new flight data features to our existing Flight Detail by GUFI API. These new features allow users to consume and analyze our flight and weather data in more depth than ever before.

We all know that weather isn’t a static phenomenon! Constantly shifting met systems, fog and wind all have the potential to play havoc with airline operations. Our improved Laminar Data METAR API now provides historical data to enable you to contextualize what’s actually going on at an aerodrome. Is the visibility reducing over time? Is the QNH rising sharply? Historical METARs for a target aerodrome on a single API call helps you and your users to understand the meteorological environment around specific aerodrome operations

Historical METAR API


This brand new API provides user insight into weather trends and changes at a particular aerodrome. Organizations can make decisions such as assigning different runways to incoming scheduled flights or deviating a flight if needed, helping airline operations to run efficiently. Data showing METARs affecting an aerodrome in the past 180 minutes and identifying the previous METARs/SPECIs issued alongside the current one enable users to analyze weather trends compared to typical weather patterns and determine whether or not a meteorological event is deteriorating or improving.


Flight Detail by GUFI API – New Data Features


The green dotted line shows the planned route and the blue line shows the route that has actually been taken.

This supports an effective visual comparison of planned and actual flight paths, which helps airline operations conduct business analysis and interpret their performance. The actual route that a flight has flown can be visualized in real time on common mapping User Interfaces (UI) and compared with original flight planned routes.

This enables aviation industry stakeholders to analyze operational performance, including schedule block time vs actual block time, measuring gate out departure efficiency, taxi-in efficiency and other Key Performance Indicators recommended by CANSO for measuring ANSP operational performance. This valuable operating data allows organizations to maximize airline efficiency and flight scheduling.

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We’re always looking to hear feedback on how we can enhance our APIs and make them work for you. Please get in touch and let us know your thoughts!