| description abstract | This study uses ensemble Kalman filter analyses and short-range ensemble forecasts to study factors affecting the predictability of Hurricane Humberto, which made landfall along the Texas coast in 2007. Humberto is known for both its rapid intensification and extreme forecast uncertainty, which makes it an ideal case in which to examine the origins of tropical cyclone strength forecast error. Statistical correlation is used to determine why some ensemble members strengthen the incipient low into a hurricane and others do not. During the analysis period, it is found that variations in midlevel moisture, low-level convective instability, and strength of a front to the north of the cyclone likely lead to differences in net precipitation, which ultimately leads to storm strength spread. Stronger storms are favored when the atmosphere is more moist and unstable and when the front is weaker, possibly because some storms in the ensemble begin entraining cooler and drier postfrontal air during this period. Later during the free forecast, variable entrainment of postfrontal air becomes a leading cause of strength spread. Surface moisture differences are the primary contributor to intensity forecast differences, and convective instability differences play a secondary role. Eventually mature tropical cyclone dynamics and differences in landfall time result in very rapid growth of ensemble spread. These results are very similar to a previous study that investigated a 2004 Gulf of Mexico low with a different model and analysis technique, which gives confidence that they are relevant to tropical cyclone formation and intensification in general. Finally, the rapid increase in forecast uncertainty despite relatively modest differences in initial conditions highlights the need for ensembles and advanced data assimilation techniques. | |
