Inside Tropical Cyclones With GPS: A New Perspective on Their Morphology and Intensity Estimation

Panagiotis Vergados, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States, Zhengzhao Johnny Luo, City College of New York, CUNY, Earth & Atmospheric Sciences, New York, NY, United States, Kerry Emanuel, Massachusetts Institute of Technology, Cambridge, MA, United States and Anthony J Mannucci, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States

Contact First Author: Panagiotis Vergados; Panagiotis.Vergados@jpl.nasa.gov

Previously Published Material: These findings were published in the Journal of Geophysical Research - Atmosphere in January 2014, and have never been presented before to the AGU or CGU science meetings.

Abstract ID#: 36122

 

English Abstract:
Despite the great progress in trajectory forecasting of tropical cyclones (TCs) in the past few years, little progress has been made to their intensity forecasting. Temperature inversions layers at the outflow inside the eyewall of TCs, superimposed on the background upper troposphere, markedly affect the background thermal structure of the upper-troposphere lower-stratosphere (UTLS) region. The temperature difference between the ocean surface and the outflow region defines a TC’s thermodynamic efficiency, which is a direct analog of its intensity. Global Positioning System radio occultation (GPSRO) observations offer a unique opportunity to sense the vertical thermal and moisture structure of a hurricane – from its center to the outermost closed isobar – with a vertical resolution of ~100 m. Here, we employ collocated vertical temperature and humidity profiles from the European Center for Medium-range Weather Forecasts Re-Analysis Interim (ERA-Interim) to assess the thermodynamic environment of an ensemble of hurricanes and compare them against GPSRO data sets. Combining GPSRO observations, along with ocean surface temperatures from NASA Modern Era-Retrospective Analysis for Research and Applications (MERRA), we demonstrate how to infer TC intensities using a simplified vortex TC model [Wong and Emanuel, 2007]. We analyzed TCs in the time period 2006–2010, and our GPSRO-based TC intensity estimates are found to be quantitatively consistent with best-track values from the Joint Typhoon Warning Center (JTWC) within 1.2–9.0%. This suggests that GPS signals can potentially augment current datasets in TC intensity forecasting, and provide accurate thermal information of a TCs’ morphology and strength.