Abstract
(1) Background: Flying in instrument meteorological conditions (IMC) carries an elevated risk of fatal outcome for general aviation (GA) pilots. For the typical GA flight, aerodrome-specific forecasts (Terminal Aerodrome Forecast (TAF), Localized Aviation Model Output Statistics Program (LAMP)) assist the airman in pre-determining whether a flight can be safely undertaken. While LAMP forecasts are more prevalent at GA-frequented aerodromes, the Federal Aviation Administration (FAA) recommends that this tool be used as supplementary to the TAF only. Herein, the predictive accuracy of LAMP for ceiling flight categories of visual flight rules (VFR) and instrument flight rules (IFR) was determined. (2) Methods: LAMP accuracy was evaluated for the period of July–December 2018 using aviation-specific probability of detection (PODA), false alarm ratio (FARA) and critical success scores (CSSA). Statistical differences were determined using Chi-Square tests. (3) Results: LAMP forecasts (n = 823) across 39 states were accrued. LAMP PODA for VFR (0.67) and IFR (0.78) exceeded (p < 0.031) the corresponding TAF scores (0.57 and 0.56). For VFR, the LAMP showed a non-significant (p = 0.243) higher FARA (0.25) than the TAF (0.19). For IFR forecasts, the LAMP FARA was lower (p < 0.001) (0.48 and 0.81, respectively). LAMP CSSA scores exceeded the TAF for VFR (p = 0.012) and IFR forecasts (p < 0.001). (4) Conclusion: These findings support the greater integration of LAMP into pre-flight weather briefings.
Highlights
General aviation, comprised mainly of light (
The overarching goal was to determine if LAMP forecasts, which are more common for aerodromes frequented by general aviation, pose an effective alternative to the Terminal Aerodrome Forecasts (TAFs) for ceiling flight category forecasts
Non-convective clouds), we considered the possibility that more robust LAMP forecasting accuracy in LAMP forecasts for visual flight rules (VFR) and instrument flight rule (IFR) were segregated into warm (July–September) and cool
Summary
General aviation, comprised mainly of light (
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