Concentric eyewall events have been documented numerous times in intense tropical cyclones over the last two decades. During a concentric eyewall event, an outer (secondary) eyewall forms around the inner (primary) eyewall. Improved instrumentation on aircraft and satellites greatly increases the likelihood of detecting an event. Despite the increased ability to detect such events, forecasts of intensity changes during and after these events remain poor. When concentric eyewall events occur near land, accurate intensity change predictions are especially critical to ensure proper emergency preparations and staging of recovery assets.
A nineteen-year (1997-2015) database of concentric eyewall events is developed by analyzing microwave satellite imagery, aircraft- and land-based radar, and other published documents. Events are identified in both the North Atlantic and eastern North Pacific basins. TCs are categorized as single (1 event), serial (>= 2 events) and super-serial (>= 3 events). Key findings here include distinct spatial patterns for single and serial Atlantic TCs, a broad seasonal distribution for eastern North Pacific TCs, and apparent ENSO-related variability in both basins.
The intensity change subsequent to the concentric eyewall event is calculated from the HURDAT2 database at time points relative to the start and to the end of the event. Intensity change is then categorized as Weaken (<= -10 kt), Maintain (+/- 5 kt), and Strengthen (>= 10 kt). Environmental conditions in which each event occurred are analyzed based on the SHIPS diagnostic files. Oceanic, dynamic, thermodynamic, and TC status predictors are selected for testing in a multiple discriminant analysis procedure to determine which variables successfully discriminate the intensity change category and the occurrence of additional concentric eyewall events. Intensity models are created for 12 h, 24 h, 36 h, and 48 h after the concentric eyewall event’s end. Leave-one-out cross validation is performed on each set of discriminators to generate classifications, which are then compared to observations. For each model, the top combinations achieve 80-95% overall accuracy in classifying TCs based on the environmental characteristics, although Maintain systems are frequently misclassified.
The third part of this dissertation employs the Weather Research and Forecasting model to further investigate concentric eyewall events. Two serial Atlantic concentric eyewall cases (Katrina 2005 and Wilma 2005) are selected from the original study set, and WRF simulations performed using several model designs. Despite strong evidence from multiple sources that serial concentric eyewalls formed in both hurricanes, the WRF simulations did not produce identifiable concentric eyewall structures for Katrina, and only transient structures for Wilma. Possible reasons for the lack of concentric eyewall formation are discussed, including model resolution, microphysics, and data sources.