2026/06/03 by Liangying Liu, Jie Feng, Qingqing Li +1
Earth and Planetary Sciences · Environmental Science · #Tropical and Extratropical Cyclones Research #Meteorological Phenomena and Simulations #Climate variability and models
paper · doi:10.1175/mwr-d-25-0242.1
Abstract A comprehensive understanding of intrinsic error growth mechanisms is essential for improving tropical cyclone (TC) track predictability. To investigate how region-specific initial condition errors influence forecast uncertainty, we employed convection-permitting ensemble forecasts using the Hurricane Weather Research and Forecasting Model (HWRF) with perturbations applied in three spatial domains: 1) the inner core including outer rainbands (0–350 km), 2) the near environment (350–1300 km), and 3) the far environment (1300–3500 km). Two contrasting typhoon cases are analyzed—Chan-hom (2020), which exhibited large track uncertainty, and Maysak (2020), characterized by relatively high predictability. The results demonstrate case-dependent sensitivities: For Chan-hom, perturbations introduced in the inner-core region result in the most substantial track spread and error growth. In contrast, for Maysak, near-environment perturbations dominate uncertainty early in the forecast, with far-environment perturbations becoming more influential at longer lead times. Mechanism diagnostics reveal that in Chan-hom with relatively weak inertial stability, initial vortex perturbations efficiently propagate outward through enhanced advection effect by upper-level outflow and low-level inflow, enabling rapid modulation of the surrounding environment. This energy transmission leads to significant growth in uncertainties of midtropospheric geopotential height and deep-layer steering wind, which, in turn, amplify track divergence. For Maysak, strong inertial stability as the vortex rapidly intensifies and weak vortex–environment coupling suppresses outward perturbation energy transfer, limiting the influence of inner-core errors. Significance Statement Improving tropical cyclone (TC) track forecasts requires understanding how errors in different regions shape prediction. Using high-resolution ensemble simulations, this study examines initial perturbations in the storm core, nearby environment, and distant surroundings for two contrasting typhoons: Chan-hom (low predictability) and Maysak (high predictability). Results show track sensitivity is case dependent and governed by storm–environment interaction. In Chan-hom, inner-core errors spread outward through strong upper-level outflow and disrupt steering winds, creating large uncertainty. In contrast, Maysak’s compact, stable vortex traps errors near the center, limiting their influence, while surrounding environment errors dominate at different forecast times. These findings show TC track predictability depends not only on where errors occur but also on how storm structure controls their interaction with the environment.