Type of Document Thesis Author Murray, David Andrew Author's Email Address firstname.lastname@example.org URN etd-11092009-005040 Title Improved Short-term Atlantic Hurricane Intensity Forecasts Using Reconnaissance-based Core Measurements Degree Master of Science Department Meteorology, Department of Advisory Committee
Advisor Name Title Robert Hart Committee Chair Carol Anne Clayson Committee Member Philip Sura Committee Member Keywords
- Tropical Cyclone Intensity Forecasting
- Intensity Prediction
- Aircraft Observations
- Forecast Model
- Eye Structure Forecast Tool
- Regression Model
Date of Defense 2009-11-06 Availability unrestricted AbstractWhile tropical cyclone (TC) track forecasting has improved noticeably over the last twenty years, intensity forecasting has remained somewhat of an enigma to forecasters. Despite increased computing capabilities and more sophisticated dynamical models, statistical models, such as the Statistical Hurricane Intensity Prediction Scheme (SHIPS), still often outperform their dynamical counterparts. There has been a great deal of research focused on improving intensity forecasts of TCs during the past two decades. However, the overwhelming majority of this statistical research has focused on the impacts of the storm environment rather than the effects of the TC structure itself or inner-core measurements. More focus has been placed recently on using some of these measurements from within the TC core, such as the structure of the storm and reconnaissance flight data. Still, much work remains to be done to fully utilize the available data from the inner core of TCs. To this end, flight data from Hurricane Hunter reconnaissance missions will be exploited to the fullest extent in this study.
This research seeks to develop a new statistical-climatological forecasting scheme to improve short-term intensity forecasts for well-developed TCs in the Atlantic basin. Well-developed TCs are classified in this study as having a defined eye. Using Vortex Data Messages (VDMs) gathered from the aforementioned reconnaissance flights and stored in the National Hurricane Center's (NHC) Automated Tropical Cyclone Forecast (ATCF) archives, a VDM climatology from 1991-2008 is developed. These VDMs are collected from dropsondes and include various structural and thermodynamic parameters. This climatology includes storm-scale thermodynamic parameters to aid in TC prediction. A new climatological forecast tool is produced which gives the expected rate of intensity change for 12-48 hour periods based on an initial eye diameter and wind speed. This climatological tool also provides insight into the dynamics involved in hurricane intensity change. Other implications based on the climatological forecast tool, such as the ability to produce probabilistic intensity range forecasts, are also discussed.
Finally, stepwise multiple linear regression is performed to create a SHIPS-style intensity forecast model (Atlantic-based Statistical Prediction of Hurricane Intensity using Recon, or ASPIRE). Examination of the regression equations and the change in predictors selected with varying intensity and forecast length offers additional insight into the science of TC intensity forecasting. Cross-validation results show that the ASPIRE technique outperforms SHIPS at nearly every forecast time and initial intensity, indicating that a new benchmark for TC intensity forecasting may have been attained. Two dependent case studies of Hurricane Ivan and Hurricane Katrina are presented for further analysis of the ASPIRE technique. Further work involving the utilization of satellite data to create proxy VDMs may lead to an expanded climatological database of inner-core data for TCs in the Atlantic basin as well as the capability to create similar regression schemes in the East Pacific and West Pacific basins.
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