Composite sharpening by vortex symmetrization and normalization of tropical cyclones

Cyclone composites are a powerful tool for investigating the mean characteristics of tropical cyclones (TCs), offering insights into the mechanisms driving storm development. Traditional composite methods align cyclone centers to capture large-scale patterns but they tend to smooth out mesoscale features. We introduce a novel compositing framework, the SYmmetrized-Normalized Cyclone (SyNC) compositing, designed to address the structural variety of TCs. This method symmetrizes storms to axisymmetric vortices and normalizes them according to their eyewall location and the size of the TC (defined by the radius of 17 m s−1 winds). The method is applied to simulated TCs with the weather and climate model ICON run at 5 km horizontal grid length. ICON reveals the ability to simulate even most intense storms, while overestimating the frequency of major hurricanes and underestimating the seasonal TC frequency. By asymmetrically detecting the eyewalls and the horizontal extents of TCs, the SyNC method enables detailed storm structural analysis. A large structural variability and asymmetries are found across all simulated storm intensities, agreeing with observations. The eyewall alignment of the SyNC framework successfully sharpens composite fields, preserving extreme values of mesoscale features such as super-gradient winds, eyewall updrafts, eyewall precipitation, and localized latent heating related to cloud microphysics. It also reduces within-group variance, thereby increasing statistical power and enabling the detection of differences between TC groups that would be missed using traditional center-based compositing. Limitations of the SyNC composites include reduced applicability during early storm stages, when tangential winds have not yet formed a Rankine-like vortex, and potential data extrapolation during normalization in small storms. Nonetheless, the method proves robust for weakly organized storms. SyNC is particularly beneficial for analyzing mesoscale features using high-resolution data (horizontal grid length of ≈ 10–20 km or finer) capable of resolving these features as well as the structural variability of TCs. As numerical models continue to improve in resolution and representation of mesoscale features and vortex variability, TC misalignment in composites will likely become an increasing challenge. Overall, the SyNC compositing method provides a cyclone-relative framework that improves the accuracy of TC composite analysis, thereby facilitating the investigation and understanding of storm development.