Evaluation of Hurricane Analysis and Forecast System (HAFS) Forecast Statistics by Stratifying Environmental and Internal Structure Metrics of Tropical Cyclones

Although tropical cyclone (TC) track and intensity forecasts have continued to improve in recent years, the relative lack of analysis relating both environmental conditions and internal storm characteristics to forecast errors has precluded a better understanding of these relationships, particularly for cases that undergo rapid intensification (RI). Recent studies have shown the importance of vortex alignment for RI; however, exactly how and why certain storms align remains poorly understood. This study builds upon other recent studies that showed forecast error statistic stratifications with environmental metrics such as vertical wind shear by also including internal storm dynamics. In this way, the study uniquely addresses poorly understood aspects of internal storm dynamics like vortex tilt by examining not only their impact on forecast errors but also how they relate to environmental conditions and their cooperative interactions with precipitation processes.

A 3-year retrospective sample of HAFS (-A and -B) forecasts in the Atlantic Basin demonstrates that TCs within low-to-moderate shear environments and with larger tilt magnitudes have the largest forecast errors on average. Smaller tilt magnitudes have larger absolute intensity errors in short range forecasts, whereas larger tilt magnitudes tend to have larger negative intensity biases at medium ranges. TCs with a tilted vortex are shown to have both downshear and downtilt oriented positional track biases. And those cases with larger (upshear) downshear biases tend to have more (less) convection and larger (negative) positive intensity biases, which highlights the importance of better understanding the interplay of forecast errors and tilt, precipitation, and convection.