Influence of Region-dependent Error Growth on the Predictability of
Tropical Cyclone Track and Intensity in High-resolution HWRF Ensembles
Abstract
Further extension of skillful prediction of tropical cyclones (TCs)
relies on in-depth studies about the intrinsic predictability of TCs. In
this study, convection-resolving ensemble forecasts based on the
Hurricane Weather Research and Forecasting model were adopted with
perturbed initial conditions to study the error growth and intrinsic
predictability of TCs. The new aspect of our study is the focus on the
sensitivity of TC track and intensity predictability to initial errors
in different regions, including (1) the inner core and outer rainbands
(0-350 km), (2) the near environment (350-1300 km), and (3) the far
environment (1300-3500 km).
The results of TC track predictability show that the most sensitive
region of initial errors for TC track forecasts is case-dependent. For
the TC case with striking track forecast errors (e.g., Typhoon Chan-hom,
2020), the initial errors in the combined region of the TC inner core
and outer rainbands produce the largest track uncertainties compared to
those in the near and far environment. However, for the TC case with a
highly predictable track (e.g., Typhoon Maysak, 2020), the most
sensitive region of initial errors is the near environment at early lead
times and the far environment later. By contrast, the most sensitive
region for TC intensity is the inner core for both cases. The surface
wind structure of TC inner core at larger scales (wavenumbers 0-2) can
be predicted for more than 3.5 days, while the structure at smaller
scales can only be predicted for a few hours.