GPS Dropwindsonde observations of tropical cyclone low-level wind maxima

Over the last decade substantial improvements have been made in one's ability to observe the tropical cyclone boundary layer. Implementation of the Global Positioning System (GPS) dropwindsonde (Hock and Franklin 1999) has provided a wealth of information regarding the kinematic and thermodynamic characteristics of tropical cyclones. Mean wind profiles computed from GPS dropwindsonde data have shown a “jet-like” wind speed maximum located near 500 m above ground level (agl); however the location of the wind speed maximum within individual GPS dropwindsonde profiles exhibited substantial variability (Franklin et al. 2003; Powell et al. 2003). Low-level wind maxima represent a source of momentum available for vertical transport; however little is known regarding their structure and the conditions which govern their height and strength.

Low-level wind maxima were identified based upon specified criteria within individual GPS dropwindsonde profiles and statistics (mean and variance) regarding their height and strength were computed. A group of 1131 GPS sondes were analyzed from the Atlantic and Eastern Pacific basins from 1997-2005 with an emphasis placed on evaluating the characteristics of low-level wind maxima below 200 m agl. Sondes included were released between 5 and 200 km radius. Approximately 11% exhibited a maximum wind speed below 200 m agl, with nearly 45% containing the maximum below 500 m agl. The maximum wind speed height exhibited a radial and storm-relative dependence as nearly all sondes with a wind maximum below 200 m were confined within 60 km radius and favored within the storm-relative right side sector. For this grouping, the ratio of the wind speed maximum to the mean boundary layer wind (MBL; Franklin et al. 2003) revealed that the maximum was only 10-20% greater than the MBL. This paper seeks to provide preliminary results, as well as to preview future efforts to evaluate tropical cyclone low-level wind maxima and the development of a statistical model to predict their height and strength.