This research explores the application of NOAA's Gridded Binary (GRIB) meteorological data in optimizing fuel-efficient Instrument Flight Rules (IFR) routes for Ultra Long Range (ULR) flight operations. Traditional flight planning relies on static wind models and historical averages, often leading to suboptimal fuel consumption on routes exceeding 14 hours. By ingesting real-time GRIB2 data into a custom routing algorithm, this study demonstrates potential fuel savings of 3–7% on transpacific and transatlantic ULR routes. The algorithm processes upper-air wind, temperature, and pressure data at multiple flight levels, dynamically adjusting the route to exploit favorable wind patterns and avoid adverse conditions. A case study using 12 months of historical GRIB data on the Singapore–Newark route validates the approach, showing consistent fuel efficiency gains across seasonal variations.

• H0Real-time GRIB2 meteorological data does not produce significantly different fuel-optimal routes compared to static wind models for ULR flight operations.
• H1Ingesting real-time GRIB2 upper-air wind data into a dynamic routing algorithm yields measurable fuel savings of at least 3% on transpacific ULR routes.
• H2The fuel efficiency gains from GRIB-based dynamic routing exhibit statistically significant variation across seasonal weather patterns on the Singapore–Newark route.

1. 01Introduction
2. 02Background on GRIB Data
3. 03Methodology & Algorithm Design
4. 04Data Collection & Processing Pipeline
5. 05Route Optimization Framework
6. 06Case Study: Singapore–Newark ULR Route
7. 07Results & Validation
8. 08Operational Considerations
9. 09Conclusion & Future Work