A GE Aviation Systems report for a project, conducted under the CLEEN Program to develop the Flight Management System Weather Input Optimizer (FWIO), documents that the National Oceanic and Atmospheric Administration (NOAA) provided weather forecast data has a bias of 15 knots and a standard deviation of 13.3 knots for the 40 flights considered for the research. It also had a 0.47 bias in the temperature with a standard deviation of 0.27. The temperature errors are not as significant as the wind. There is a potential opportunity to reduce the operational cost by improving the weather forecast.
The flight management system (FMS) currently uses the weather forecast, available before takeoff, to identify an optimized flight path with minimum operational costs depending on the selected speed mode. Such a flight plan could be optimum for a shorter flight because these flight path planning algorithms are very less susceptible to the accuracy of the weather forecast. However, the flight plan for longer flights may require changes with the latest weather data since the weather forecast used initially might have become inaccurate. The errors in the weather forecast negatively impact predictions on ground speeds, which increases the time and fuel costs for a flight. The older the weather forecast, the higher the errors.
It is recommended to automate the uplink request to obtain the latest weather forecast and to ensure the availability of highly accurate weather forecasts. Simulations were conducted to estimate the savings using a narrowbody aircraft. The simulation results show an average saving of 10-15 pound of fuel for a 1000Nm flight, which can result in $15,000-$20,000 savings annually per aircraft. The proposed approach helps to achieve more fuel-time savings and eases the pilots’ workload as they do not need to monitor the error in the weather forecast.