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Presentation 10B.5 VORTICITY-BASED DETECTION OF TROPICAL CYCLOGENESIS Michelle M. Hite1*, Mark A. Bourassa1,2, Philip Cunningham2, James J. O’Brien1,2, and Paul D. Reasor2 1Center for Ocean-Atmospheric Prediction Studies, Florida State University, Tallahassee, Florida 2Department of Meteorology, Florida State University, Tallahassee, Florida 1. INTRODUCTION (2001) relied upon closed circulations apparent in the scatterometer data. Using a threshold of Tropical cyclogenesis (TCG), although an vorticity over a defined area, Sharp et al. (2002) already well researched area, remains a highly identified numerous tropical disturbances and debatable and unresolved topic. While assessed whether or not they were likely to considerable attention has been paid to tropical develop into tropical cyclones. Detection was cyclone formation, little attention has focused on based on surface structure, requiring sufficiently observational studies of the very early stages of strong vorticity averaged over a large surface TCG, otherwise referred to as the genesis stage. area. Unlike Sharp et al. (2002), Katsaros et al. In the past, the early stages of TCG were (2001) and Liu et al. (2001) concentrated on unverifiable in surface observations, due to the disturbances that would develop into classified paucity of meteorological data over the tropical tropical cyclones. They examined surface wind oceans. The advent of wide swath scatterometers patterns and looked for areas of closed circulation, helped alleviate this issue by affording the successfully detecting tropical disturbances before scientific community with widespread designation as depressions. These studies observational surface data across the tropical illustrated the usefulness of SeaWinds data basins. One such instrument is the SeaWinds towards tropical disturbance detection, with the scatterometer, aboard the QuikSCAT satellite, intent of improving operational activities. The which infers surface wind speed and direction. early identification of surface circulations Launched in 1999, this scatterometer has presented in these studies suggests an encouraged various studies regarding early opportunity to detect the early stages of TCG, identification of tropical disturbances (Liu et al. setting the basis for this paper. 2001; Katsaros et al. 2001; Sharp et al. 2002). The detection technique described herein has These studies, though operational in intent, the potential for applications in the scientific and hypothesized the potential for SeaWinds data to operational communities. In operational be applied towards research applications (i.e., applications, the forecasting community can genesis stage research). The main goal of this implement the detection technique as an study is to develop an objective technique that will additional observational tool. In doing so, the detect the early stages of TCG in the Atlantic technique can enhance the current observing basin using SeaWinds data. system employed to identify and monitor tropical Liu et al. (2001), Katsaros et al. (2001), and weather systems, thereby reducing the time Sharp et al. (2002) demonstrated the ability to forecasters spend examining the tropics for identify tropical disturbances, discrete weather incipient systems. In research applications, systems of apparently organized convection that identification of the early stages of TCG can maintain their identity for 24 hours or more and are enhance understanding in regions where little too weak to be classified as tropical cyclones (i.e., research has been conducted due to the lack of tropical depressions, tropical storms, or surface observations, prior inability to conclusively hurricanes), by the National Hurricane Center locate TC precursor disturbances, and (NHC). Each technique utilized surface wind data consequently the lack of observation studies obtained by the SeaWinds scatterometer. (Reasor et al. 2005) on the establishment of the However, the criteria that defined their initial surface vortex. This study focuses on the identification method differed. Sharp et al. (2002) Atlantic basin, but the detection technique can be employed vorticity in their detection condition, applied to other tropical regions, such as the whereas Liu et al. (2001) and Katsaros et al. Pacific basin, after adjusting the threshold values ____________________________________ to account for regional differences in TCG Corresponding Author address: Mark A. Bourassa mechanisms. Center for Ocean-Atmospheric Prediction Studies, The ability to detect the early stages of TCG Florida State University, Tallahassee, FL 32306- provides an opportunity to classify tropical 2840. Email: [email protected] Phone: disturbances in the Atlantic basin based on the (850) 644-6923 source of initial surface cyclonic vorticity. Following categorization by Bracken and Bosart associated with the surface vorticity signatures to (2000) these sources include disturbances be tracked. The conjunction of QuikSCAT and associated with: (i) monsoon troughs or the GOES is discussed in more detail in section 3.3. intertropical convergence zone (Riehl 1954, 1979), (ii) an easterly wave (Carlson 1969; Burpee 1972, 2.1 Scatterometer Data 1974, 1975; Reed et al. 1977; Thorncroft and The scatterometer data that is used in this Hoskins 1994 ab), (iii) a stagnant frontal zone study is the simplified Ku2001 dataset produced originating in the midlatitudes (Frank 1988; Davis by Florida State University’s Center for Ocean- and Bosart 2001), (iv) mesoscale convective Atmospheric Prediction Studies (COAPS). It systems (MCSs; Bosart and Sanders 1981; contains wind vectors, rain flags, locations, and Ritchie and Holland 1997; Simpson et al. 1997; times. The geophysical model function (GMF) Bister and Emanuel 1997; Montgomery and used to obtain this data is the Ku2001 product Enagonio 1998), and (v) upper-level cut-off lows developed by Remote Sensing Systems (RSS). that penetrate to lower levels (Avila and Rappaport The Ku2001 product is currently the most accurate 1996). Among these, our research in the Atlantic GMF for most meteorological conditions basin affords the possibility to investigate cases (Bourassa et al. 2003). It performs far better near associated with easterly waves. Of great interest nadir, swath edges, and rain than either the is the prospect to examine the connection science quality product from Jet Propulsion between a cold-core wave disturbance in the Laboratory (JPL) or the near real-time product tropical easterlies and a warm-core tropical from NOAA/NESDIS. This improved vector wind cyclone, which remains an unresolved issue in retrieval algorithm provides a fully integrated TCG research. Easterly waves are of great stand-alone rain flag and the capability to retrieve importance since approximately 63% of tropical winds up to 70 m/s (Wentz et al. 2001). The cyclones in the Atlantic basin originate from scatterometer winds are calibrated to equivalent African easterly waves (Avila and Pasch 1992). neutral winds at a height of 10 meters above the Another fundamental issue with TCG involves local mean water surface (Bourassa et al. 2003). the formation of the surface vortex prior to the onset of the Wind Induced Surface Heat Exchange 2.2 GOES Imagery (WISHE) intensification mechanism of Rotunno GOES-8 and GOES-12 infrared images are and Emanuel (1987). The generation of surface obtained from the NOAA/NESDIS Comprehensive vorticity and its interaction within regions of deep Large Array-data Stewardship System (CLASS) cumulonimbus convection has been hypothesized for our 15 tropical cyclone cases during the 1999- in recent numerical (Hendricks et al. 2004; 2004 Atlantic hurricane seasons. Images are Montgomery et al. 2006) and observational acquired approximately every three hours and (Reasor et al. 2005) studies to lead to the compiled into separate animations, with a establishment of the initial surface vortex. The backward and forward-in-time progression. fine details of this surface vorticity organization process cannot be resolved with SeaWinds data. 3. METHODOLOGY However, SeaWinds data may resolve the general evolution of vorticity and provide estimates of 3.1 Detection Technique vorticity available at the surface prior to TCG, The vorticity-based detection technique used which are needed for numerical model initialization in this study is a variation of the method developed and validation. by Sharp et al. (2002). This technique calculates relative vorticity within the SeaWinds swaths and 2. DATA applies a mean vorticity threshold over a specified spatial area (Sharp et al. 2002). Different criteria Ocean wind vectors are obtained from the are utilized than those of Sharp et al. (2002), SeaWinds scatterometer for the Atlantic basin. permitting earlier identification of tropical QuikSCAT has slightly less than twice-daily disturbances. coverage over this area and, hence, provides The spatial scale for averaging vorticity within infrequent temporal sampling. To provide the SeaWinds swaths is a 100 km by 100 km area. continuity of the track and verification of tropical Individual vorticity values are calculated from wind disturbances between the relatively sparse observations, defined by 4 [2 x 2] adjacent QuikSCAT overpasses, GOES infrared images are scatterometer vectors, by determining the acquired and compiled into animations. These circulation around each box and then dividing animations allow cloud features that are through by the area (Sharp et al. 2002). This method enables the vorticity to be calculated at where H is the
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