The Pacific-North American Pattern as a Dominant Driver of Trans-Pacific Flight Time Variability

Optimizing flight trajectories against upper-level jet streams is a crucial task for aviation operations. While current daily operations are efficient, with recorded flight times showing only minor deviations from theoretical optima, the modulation of jet streams by low-frequency climate variability provides a potential source of seasonal-to-decadal predictability for flight efficiency relevant to long-term strategic planning. Using optimal flight trajectory simulations based on 44 years (1979–2022) of reanalysis data, this study investigates the variability of flight times and their connection to large-scale climate modes. We identify a distinctly large variance in wintertime round-trip flight times (RFT) for Trans-Pacific routes from East Asia to the US West Coast. In contrast, North Atlantic or Hawaii–US routes exhibit low variance due to the cancellation of anti-correlated eastbound and westbound flight times, resulting in a reduced round-trip residual. Our results reveal that the Pacific-North American (PNA) pattern is the primary driver of this variability, explaining over 70% of the inter-annual RFT variance (increasing to ~80% when combined with the Western Pacific pattern). The mechanism lies in the PNA’s dipole impact on the zonal wind structure. In the positive phase, the westerlies are intensified at low latitudes and weakened at high latitudes over the North Pacific, promoting a meridional separation of optimal routes and a simultaneous reduction of eastbound and westbound flight times, whereas the negative phase induces the opposite response. Consequently, PNA phase transitions generate large variability in RFT through a coherent response of eastbound and westbound routes. This coherent feature is absent in fixed routing schemes (e.g., Great Circle Routes) or in other regions where flight trajectories cannot diverge meridionally enough to fully adapt to the dominant atmospheric anomalies. This PNA-flight time relationship remains robust across timescales, from seasonal averages to daily variations, with decreasing explanatory power as averaging periods shorten. Furthermore, the PNA pattern is also associated with the frequency of extreme delays. Our findings highlight the strong coupling between large-scale teleconnections and flight efficiency, suggesting that seamless prediction of the PNA pattern can be directly applied to risk assessment and decision-making in the aviation sector.

Acknowledgment: This work was funded by the Korea Meteorological Administration Research and Development Program under Grant (KMI2022-00310) and by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2025-24683550).