Volume 36, 2013

Papers in Applied Geography

Editors:Jay LeeDawna L. Cerney

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PAPERS IN APPLIED GEOGRAPHY

VOLUME 36, 2013

TABLE OF CONTENT 2013 APPLIED GEOGRAPHY CONFERENCES Board of Directors ……………….… vi Preliminary Analysis of the Synoptic-Scale Environment Associated with Tropical Cyclone Tornado Clusters, 1995-2010

Todd W. Moore and Richard W. Dixon …………………………………………….. 1 Communicating Kansas Climate and Climate Change: Initial Development of a Web-Based Resource

Ram Raghavan and John Harrington, Jr. ……………………………………………11 Marketing American Microbrews: Promoting Neolocalism One Map at a Time

Matthew T. Pattern and Adam J. Mathews …………….………………………….. 17 Stream Restoration and Hydrochory: Seed Pool Variation in Restored and Degraded Reaches of the Kissimmee River, Florida

Scott H. Markwith ……………………………………………………………….… 27 A Geo-Temporal Analysis of the Conservation Reserve Program: Net vs. Gross Change, 1986-2013

Chris Laingen ……………………………………………………………………… 37 The Impacts of Natural Revegetation of Abandoned Mine Land on Changing Land Use Patterns in Southeast Kansas

Catherine A. Hooey and Timothy J. Bailey ……………………………………..… 47 Considering the Heritage of Place in Consultation with Indigenous Peoples

Roxanne T. Ornelas ……………………………………………………………...… 55 Hazard Characterization of Induced Seismicity in Eastern Ohio: A Scenario Analysis Using Hazus-MH

James Lein ……………………………………………………………………….… 64 Lidar-Based Detection of Shrubland and Forest Land Cover to Improve Identification of Golden-Cheeked Warbler Habitat

Jennifer L. R. Jensen, Sandra Irvin, and Adam Duarte ……………………………. 74 Forest Changes on Pikes Peak, Colorado as Interpreted through Repeat Photography

Steve Jennings …………………………………………………………………...… 83 Historical Channel Change of Vermillion Creek, Kansas, USA between 1937 and 2013

Rhett L. Mohler .…………………………………………………………………… 92 Validation of the Everglades Depth Estimation Network (EDEN) Water-Surface Model

Zhixiao Xie, Zhangwei Liu, and Yingru Li …….………………………………….. 98

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Remote Sensing of Evapotranspiration in Florida Using Dry Pixel Calibration Aaron Evans ……………………………………………………………………… 107

Mapping Geographic Literacy in Texas

Jeff Lash …………………………………..……………………………………… 117 The Economic Importance of Hunting in Southwestern Montana

Ryan D. Bergstrom, Shannon V. Taylor, and Katherine J. Hansen …………….... 127 A Contingent Valuation of Tampa’s Urban Forest

Alec Foster and Graham A. Tobin ……………………………………………….. 137 Applications of Gravity Modeling to Evaluate Dine-In Restaurant Location and Competitiveness Using a Representative Sample, Jefferson County, Kentucky

Joel P. Dock and Wei Song ………………………………………………………. 146 Influence of Long- and Short-Term Climatic Changes on Chernozem Soils: Central Chernozem Region of Russia

Yury G. Chendev, Anthony R. Lupo, Aleksandr N. Petin, and Maria G. Lebedeva … ……………………………………………………………………… 156

The Sunshine State, GDP, and the DMSP-OLS: Time Series Trend Case Study Dolores Jane Forbes ……………………………………………………………… 165

Chinese FDI in the US: A State Level Analysis of the Geography of FDI and FDI Per Capita

Jeremy Bennett and Jay D. Gatrell ……………………………………………….. 174 The Implementation of GIS in Secondary Education in the State of Maryland

Heather Holst and Paporn Thebpanya ……………………………………………. 183 Opportunities for Integrating Geospatial Technology across University Environmental Science Courses

Emariana Taylor, Chris Blackwood and Patrick Lorch …………………………... 192 Investigating Aquatic Invasive Species Propagation within the Adirondack Region of New York: A Lake and Landscape Approach

Richard R. Shaker and Charles J. Rapp …………………………………………... 200 Localism and American Broadcasting in the Age of Satellite Television

Jonathan C. Comer and Thomas A. Wikle ……………………………………….. 210 Deriving Measures and Profiles of Wetland Features from LIDAR LAS Datasets

Janet Gritzner and Bruce V. Millett …………………………………………….... 220 Spatial Statistical Characterization of Differences between Major Respiratory Diseases across Central Appalachia

Timothy S. Hare, Chad Wells, Barbara J. Pridemore, Porsha Smith, and Nicole Johnson ………………………………………………………………………….... 228

Pre-Service Teacher Preparation in Illinois: A Case Study Gillian Acheson ……………………………………………………………….….. 237

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Prototype Global Coding Political Geographies for Library and Data Management – Wikipedia Example

Thomas J. Christoffel ………………………………………………………….…. 246 The Price is Right? Food Availability and Affordability in Oklahoma City, OK, USA

Stacey R. Brown ………………………………………………………………….. 256 The Learning Cluster Model (LCM) as A Means of Extending the Capabilities of An Online Professional Development System in Geography

Carmen P. Brysch and Richard G. Boehm …………………………………….…. 264 Can You Really Walk There from Here? A Case Study of Walkability at Mockingbird Station in Dallas, Texas

Owen Wilson-Chavez and Murray D. Rice …………………………………….… 271 Retail Change and Light Rail: An Exploration of Business Location Changes Accompanying Commuter Rail Development in Denton, Texas

Trevor Yarbrough and Murray D. Rice ………………………………………..…. 281 Estimating Tree Canopy Foliar Volume Using Terrestrial LiDAR

Clint Harper, Nate Currit, and Jennifer Jensen ………………………………...…. 290 The Edwards Aquifer and Changes in the San Antonio, Texas Water Supply, 1993-2013

Richard A. Earl, David A. Parr, and Eddi Wilcut ……………………………..…. 299 Maps and Locals: Using Landsat Image Analysis to Document Eastern Red Cedar Expansion in the Northern Flint Hills

Bryanna Pockrandt, John Harrington, Jr., and Shawn Hutchinson …………….… 309 The Relationship between Land Cover and Temperature in the Auburn – Opelika, Alabama Urban Area

Andrew W. Hug, Chandana Mitra, Yingru Li, Luke J. Marzen …………..……… 316 Influence of Surface Land Cover on the Urban Heat Island Intensity within Metropolitan Jefferson County, Kentucky

Jeremy Sandifer ………………………………………………………………...… 323 Comparative Analysis of Attitudes Towards Water Management Decision-Making in Western North Carolina

Christopher A. Badurek, Robin Hale, and Kristan Cockerill …………………..… 332 Data Fusion of LiDAR and Optical Imagery for Coastal Vegetation Mapping in South Florida Using an Object-Oriented Approach

Georgia H. De Stoppelaire ……………………………………………………..… 339 Analysis of Ground-Level Ozone in Granite City, Illinois

Mark L. Hildebrandt and Alex McBride …………………………….…………… 348 Precipitation Variability Trends in Texas, 1932 – 2011 Rebecca K. Parylak and Richard W. Dixon …………………………………...…. 358 Business Clustering in Knowledge-Based Industries in the Austin-Round Rock, Texas, Metropolitan Statistical Area

Eric Clennon, R. Denise Blanchard, and T. Edwin Chow ……………………..… 367

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Sultry in Charm City: Shifting Probabilities of Hot Days in Baltimore – 1899 to 2012

Kent Barnes ………………………………………………………………………. 377 Area Disparities of Obesity, Non-Fresh Food Outlets, and Fitness Centers

Jay Lee, Mohammad Al Nasralla, Everett Logue, and Heather Beaird ……….…. 385 A Demonstration of ArcGIS Network Analyst for Criterion-Based Bicycle Route Selection on Existing Road Networkd

Kathleen D. Seal …………………………………………………………………. 396 Demographic Changes and Gentrification in Washington, D.C. between 2000 and 2010

Cinthia Josette Arévalo, Bálint Pető, Agustina Suaya and Michael M. Mann …… 406 Taste Paradise: Tropical North Queensland as a Gastronomic Tourism Destination

Deborah Che, Rose Wright, and Robyn Rae ………………………………….….. 415 Coping with Meniere’s Disease: Identification of Places with Fewest Weather Changes

Kent M. McGregor ……………………………………………………………..… 423 The Impacts of School District Spending: Exploring the Connection between School District Expenditures and Graduation Rates in Virginia

Amber Boykin, Michael Gaskins, Sarah Jackson, Christine McDonnell, Michael L. Mann ……………………………………………………………………………… 432

Area Health Disparities Based on Death Certificates: A Case Study of Census Tracts in Summit County, Ohio

Gordon A. Cromley, Mohammad Al Nasrallah, Jay Lee, and Heather Beaird ..…. 441 GIS Analysis of Power Plant Carbon Dioxide Emission Inventory Databases in the Continental US

Maya G. Hutchins and Christopher A. Badurek ……………………………….…. 451 Urban Expansion and Environmental Parameters – A Case Study of Huntsville, Alabama

Mahjabin Rahman, Chandana Mitra, Luke J. Marzen, and Yingru Li ………….... 458 Chinatown, Ethnoburb, or Invisiburb? Settlement Patterns of Chinese Migrants to Texas

Melissa E. Holmes and Sarah A. Blue ………………………………………….... 467 Analysis of Impacts of Removing the Fort Loudoun Dam on Upstream Residential Property Values in Tennessee

Jeffrey C. French and Christopher A. Badurek .………………………………….. 478 Examining the Impact of Spatial Measures on Residential Property Prices in the Toronto Region

Maurice Yeates, Tony Hernandez, and Paul Du …………………………………. 485 A GIScience Approach to Urgent Care Facility Site Selection in Nebraska

Paul Burger, Brett Chloupek, and H. Jason Combs …………………………...…. 495 Measuring Temporal Displacement of Non-Violent Crime

Vijayaprabha Rajendran and Falguni Mukherjee ………………………………… 505 Author Index ……………………………………………………………………………….. 514

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LIST OF REVIEWERS ………………………………………………………………..… 516

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2013 BOARD OF DIRECTORS APPLIED GEOGRAPHY CONFERENCES

Thomas Dwyer, President BBCN Bank Los Angeles, CA

Jay Lee, Executive Director Department of Geography Kent State University

MEMBERS

Dawna Cerney Department of Geography Youngstown University

Philip Chaney Department of Geology and Geography Auburn University

Bradley Cullen Department of Geography University of New Mexico

Michael DeMers Department of Geography New Mexico State University

Richard Earl Department of Geography Texas State University – San Marcos

Tony Hernandez Centre for the Study of Commercial Activity Ryerson University

Mark Hildebrandt Department of Geography Southern Illinois University Edwardsville

Chris Laingen Geography Program Eastern Illinois University

James Lein Department of Geography Ohio University

Rezaul Mahmood Department of Geography and Geology Western Kentucky University

Burrell Montz Department of Geography East Carolina University

Linda Peters ESRI, Inc. Redlands, CA

Michael Ratcliffe Geography Division US Census Bureau

Murray Rice Department of Geography University of North Texas

Richard Shaker Department of Geography Binghamton University

Wei Song Department of Geography and Geosciences University of Louisville

Papers in Applied Geography, Volume 36 (2013): 1-10

PRELIMINARY ANALYSIS OF THE SYNOPTIC-SCALE ENVIRONMENT ASSOCIATED WITH TROPICAL CYCLONE TORNADO CLUSTERS, 1995–2010

Todd W. Moore (tmoore@towson.edu)

Department of Geography and Environmental Planning Towson University

8000 York Road Towson, MD 21252

Richard W. Dixon

Department of Geography Texas State University-San Marcos

601 University Drive San Marcos, TX 78666

1. INTRODUCTION

Tropical cyclones (TCs), including tropical depressions, tropical storms, hurricanes, and their extratropical and remnant stages, are known to produce multiple meteorological hazards, including tornadoes (TCTORs). TCTORs are capable of causing substantial damage to impacted communities. TCTORs were responsible for 328 casualties over the period 1995-2009 (Moore and Dixon, 2012) and some, such as TC Cindy's (2005) TCTORs, have resulted in millions of dollars in economic losses (Stewart, 2006). TCs may produce TCTORs over a several day period, ranging from a day or two before landfall as their outer rainbands move ashore through several days after landfall as they track inland. The number of TCTORs a TC produces, however, varies. Past events illustrate that some TCs produce only a few, if any, TCTORs, whereas others may produce more than 100 (Novlan and Gray, 1974; Verbout et al., 2007; Moore and Dixon, 2011). In addition to this between-TC variability, the rate at which a single TC produces TCTORs throughout its lifespan varies considerably. TC Ivan (2004), for example, produced more than 100 TCTORs, but, rather than producing these TCTORs at an equal rate, Ivan produced somewhat discrete clusters of relatively high TCTOR activity interspersed with regions of low activity (Figure 1). Over a four day period (15−18 September, 2004), Ivan produced three general clusters: one throughout portions of Florida, Alabama, and Georgia, another near the border of Georgia and South Carolina, and a last throughout Virginia, Maryland, and Pennsylvania. Previous studies have noted the tendency for TCTORs to cluster (Orton, 1970; McCaul, 1987; Curtis, 2004; McCaul et al., 2004; Baker et al., 2009), but none have sought to identify and analyze these clusters in a large sample of TCs. TCTOR clusters have the potential to be particularly hazardous to life and property. A better understanding of the environment in which these clusters occur, and the resulting advancements to TCTOR outlooks and watches, may mitigate the negative impact of TCTORs, especially to life. A large portion of the previous research on this topic has focused on the meso- and storm-scale environments associated with TCTORs (e.g., McCaul, 1991; McCaul and Wiseman, 1996; Baker et al., 2009; Edwards, 2010a; Edwards et al., 2010). Fewer studies have focused on larger synoptic-scale patterns associated with TCTORs (e.g., Curtis, 2004; Verbout et al., 2007; Cohen, 2010). Despite the relatively limited application of synoptic pattern recognition to TCTORs, Cohen (2010) recommended that operational forecasters consider synoptic-scale patterns when determining whether a TC will produce a substantial number of TCTORs.

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FIGURE 1 EXAMPLE OF TCTOR CLUSTERS PRODUCED BY TROPICAL CYCLONE IVAN

(SCALE, 1:45,000,000)

Two of the previous efforts to identify generalized synoptic-scale patterns associated with TCTORs have employed the compositing technique, whereby synoptic maps representing certain environment variables are averaged, thus creating one composite map for each variable to represent the environment associated with TCTORs. Verbout et al. (2007) produced 500 hPa geopotential height and wind shear (between the surface and the 850 hPa surface) composites in association with Texas land-falling TCs that produced TCTOR outbreaks. Their composites indicated that TCTOR outbreaks accompanying Texas landfalls are associated with a 500 hPa midlatitude trough over the north-central United States and relatively high low-level wind shear as compared to non-outbreak landfalls. Cohen (2010) produced composites for a suite of atmospheric variables, including 200 hPa flow, 850 hPa flow, mean sea level pressure, 500 hPa geopotential height, 200 hPa temperature, and 600 hPa relative humidity to represent environmental conditions associated with substantially tornadic U.S. Gulf Coast land-falling TCs. These plots showed that substantially tornadic TCs were associated with an enhanced 200 hPa jet streak to the northwest of the TC, an organized and directionally symmetric 850 hPa and mean sea level cyclonic wind field, and a 600 hPa wedge of relatively dry air that cyclonically envelops the TC and intrudes into its eastern half. Composites such as these reveal a general pattern, but the averaging process masks the variability between the individual maps used to create the composite. Furthermore, the synoptic-scale pattern will invariably change as a TC propagates through its ambient environment. This, combined with the idea that TCs produce temporal clusters of TCTORs, suggests that one composite, or a snapshot, is not representative of the synoptic-scale environment in which all TCTOR clusters occur. Curtis (2004) examined synoptic plots of relative humidity at multiple layers in the atmosphere associated with eleven TCs that produced an outbreak (twenty or more TCTORs) to identify the origin of midlevel dry air intrusions. Rather than compositing these plots, Curtis (2004) manually analyzed animated loops illustrating the relative humidity plots every six hours for an extended period prior to landfall. By doing so, he was able to capture variability in the patterns rather than identifying one averaged pattern. His analysis showed that the eleven TCTOR outbreaks were associated with two general patterns: (1) a region of dry air to the north or northwest of the TC that divides into two lobes, one to the northwest and another to the northeast of the TC as it propagates or (2) a region of dry air that is entrained into the eastern half of the TC circulation.

This study builds upon these previous efforts to identify synoptic patterns associated with TCTORs. Unlike previous studies, this study focuses on temporal clusters of TCTORs produced by TCs rather than the total number of TCTORs produced over their life span. This approach was taken because (1) TCs do not produce TCTORs at a uniform rate through their life span (Figure 1) and (2) it is unlikely that the synoptic-scale environment during each TCTOR cluster that a TC produces is the same. By analyzing the synoptic-scale environment

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corresponding to temporal clusters of TCTORs, this study captures synoptic-scale variability among the clusters and may provide insight into key synoptic-scale features that prime the TC environment for TCTOR production. The objectives of this study are to (1) identify temporal clusters of TCTORs and to (2) analyze and describe their corresponding synoptic-scale environments, with emphasis on recurring patterns that likely provide synoptic scale forcing to TCTOR production.

2. DATA AND METHODS

The TCTOR dataset (Edwards, 2010a and 2010b) produced by Roger Edwards of the Storm Prediction Center was used to identify TCTOR clusters. This dataset is a compilation of information from the Storm Prediction Center's ONETOR tornado database and the National Hurricane Center's HURDAT hurricane records. At the time of analysis, this dataset covered the period 1995−2010. Gridded synoptic plots with a resolution of 32 km2 were obtained from the National Centers for Environmental Prediction-North American Regional Reanalysis (NCEP-NARR; Mesinger et al., 2006) to represent the synoptic environments corresponding to the TCTOR clusters. NCEP-NARR plots are available every three hours beginning at 0000 UTC over the period 1979−2012. Six operational variables in the form of synoptic plots were collected for each cluster to represent six conceptual atmospheric variables (Table 1). These specific plots were chosen because the variables they represent have either been hypothesized to promote TCTOR genesis or they have been empirically linked to TCTORs (Table 1).

TABLE 1 ATMOSPHERIC VARIABLES EXAMINED IN THE SYNOPTIC ANALYSIS

Conceptual Variable Operational Variable Supporting Literature Instability 0−180 hPa above surface CAPE1

[J kg-1] McCaul et al. (2004); Edwards et

al. (2010) Rotation 0−3 km above surface SRH2

[m2 s-2] McCaul (1991); Edwards et al.

(2010) Low-level

convergence 900 hPa horizontal convergence

[100,000 s-1] Gentry (1983); Schultz and Cecil

(2009) Mid-tropospheric dry

air entrainment 600 hPa specific humidity

[kg kg-1] Curtis (2004); Cohen (2010)

Mid- tropospheric flow regime

500 hPa geopotential height [m] Verbout et al. (2007); Baker et al. (2009)

Upper-tropospheric jet streak

200 hPa vector wind [m s-1] Cohen (2010)

This study follows the environment-to-circulation approach to synoptic analysis (Yarnal, 1993); therefore, only the synoptic-scale environments corresponding to TCTOR clusters were analyzed. The first step was to identify the TCTOR clusters, which were defined as three or more TCTORs in a six-hour period. The TCTOR frequency threshold of three distinguishes between six-hour periods when an isolated one or two TCTORs occur and those periods when three or more, or a cluster occur. A six-hour period was not only chosen to capture relatively short time periods when TCs are producing a relatively large number of TCTORs, but also to capture variability in the TCs' relative location in their synoptic-scale environment. While the general synoptic-scale environment may not substantially change in a

1 Convective available potential energy (CAPE) is a measure of the amount of energy available for convection. Higher values indicate greater potential for severe weather (NWS, 2009). 2 Storm relative helicity (SRH) is a measure of the potential for helical flow and it is measured relative to storm motion. Higher values favor mid-level rotation (NWS, 2009).

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six-hour period, a TC's relative location within its environment will invariably change with the amount of change depending on TC translational speed. To ensure temporal synchronicity between the TCTORs in a particular cluster and the synoptic plots used to represent the environment during that cluster, the six-hour periods are centered about 0000, 0600, 1200, and 1800 UTC (times when the NCEP-NARR plots are available). The TCTORs in each cluster occur within three hours of their corresponding synoptic plots. To identify clusters, each day within the TCTOR dataset was parsed into six-hour periods centered about 0000, 0600, 1200, and 1800 UTC. The six-hour periods with three or more TCTORs were extracted to create a dataset of TCTOR clusters. Once the clusters were identified, the synoptic plots corresponding to the central hour of each cluster were acquired; e.g., a cluster of 7 TCTORs occurred between 1500 and 2059 UTC on 15 September 2004, therefore synoptic plots for 1800 UTC on this date were obtained to represent the environment during this cluster. The synoptic plots were manually analyzed to explore the environments in which the TCTOR clusters occurred. Features such as the existence and relative location of a 200 hPa jet streak, the overall configuration of the 500 hPa height contours and the existence and relative location of a midlatitude trough, the overall 600 hPa specific humidity pattern and the existence of dry air entrainment, and the patterns and magnitude of CAPE, SRH, and 900 hPa horizontal convergence were noted during the analysis.

3. RESULTS AND DISCUSSION

3.1 CLUSTER FREQUENCY AND SEVERITY Forty-two TCs produced one or more TCTOR clusters, with a total of 133 clusters over the period of record. These clusters account for a total of 930 of the 1,163 TCTORs (eighty percent) in the TCTOR dataset. The clusters ranged in severity (i.e., the number of TCTORs in a cluster) from three to thirty-three TCTORs, but tended to bunch at the lower end of this range (Figure 2). The most common cluster severity was three, followed by clusters with four and then five TCTORs. Mean and median cluster severity were seven and five, respectively. Although most tend to involve relatively few TCTORs, several clusters highlight the capability for TCs to produce a staggering number of TCTORs over a short period of time. The ten most severe clusters had between sixteen and thirty-three TCTORs (Figure 3). These clusters were produced by TCs Lili (2002), Frances (2004), Ivan (2004), Katrina (2005), Rita (2005), and Ike (2008).

FIGURE 2 FREQUENCY DISTRIBUTION OF TCTOR CLUSTERS BY SEVERITY. DASHED

VERTICAL LINES REPRESENT THE 25TH, 50TH, AND 75TH PERCENTILES

05

101520253035

3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33

Num

ber

of C

lust

ers

Number of TCTORs in Cluster

TCTOR Cluster Severity, 1995−2010 Number of clusters = 133 Mean cluster severity = 7.0 Median cluster severity = 5.0 Standard deviation of frequency distribution = 5.6 Skewness of frequency distribution = 2.4

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FIGURE 3 PLOTS OF THE TOUCHDOWN LOCATION OF THE TCTORS IN THE TEN MOST

SEVERE CLUSTERS, 1995−2010 (SCALE, 1:45,000,000)

3.2 SYNOPTIC-SCALE ENVIRONMENTS OF CLUSTERS The preliminary manual analysis provided insight into possible synoptic-scale forcings that may prime the TC environment for TCTORs. The CAPE, SRH, and 900 hPa horizontal convergence plots were not useful in identifying generalized synoptic patterns. While the variables that these plots represent − instability, rotation, and lift, respectively − are known to be linked to tornadogenesis (e.g., McCaul, 1991; Schneider and Sharp, 2007; Edwards et al., 2010), they were deemed to vary too much over relatively small areas to be considered in the identification of synoptic patterns. This echoes previous studies that also have found thermodynamic and wind shear parameters to be highly variable over small spatial areas (Markowski et al., 1998; French and Parker, 2008). Analysis of the 600 hPa specific humidity plots illustrated that the humidity field is highly varied in the environment surrounding TCs (Figure 4A-D). Figures 4A and 4B illustrate a pattern that was prevalent among many of the most severe clusters − advection of dry air into the southeast quadrant of the TC environment by low- and mid-tropospheric TC inflow, with the dry air typically originating from a region to the southwest of the TC. The evidence of dry air entrainment found in this study is in agreement with the results of Curtis (2004) and Cohen (2010). The importance of dry air entrainment is that it may enhance local lapse rates through evaporative cooling aloft, in effect increasing convective instability (McCaul 1987; Vescio et al., 1996). Convective instability may be further increased by enhanced surface heating as more solar radiation is allowed to reach the surface when cloud cover is reduced in the entrainment region (Curtis 2004). As shown in Figures 4C and 4D, however, southwesterly dry air entrainment into the southeast quadrant of the TC is not always as prevalent as seen with TCs Ivan and Rita, and is sometimes not evident at all. Therefore, while dry air entrainment likely primes certain sections of the TC environment for TCTORs by enhancing convective instability, it is not a requirement.

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FIGURE 4 600 HPA ISOHUMES OF SPECIFIC HUMIDITY CORRESPONDING TO FOUR OF THE

IDENTIFIED CLUSTERS (UNIT=KG KG-1; INTERVAL=0.001). PLOTS WERE OBTAINED FROM NOAA (2012) AND MODIFIED BY THE AUTHORS

Analysis of the 500 hPa geopotential height plots revealed that both open- and closed-circulation TCs have produced TCTOR clusters in various positions of their track from the tropics and subtropics to the midlatitudes. Examples of this can be seen in Figures 5A, 5C, and 5E. On 30 June 2010, for example, TC Alex produced six TCTORs between 1500 and 2059 UTC while exhibiting closed circulation at the 500 hPa level but showed no signs of interaction with the midlatitude westerlies (Figure 5A). On the other end of this spectrum, TC Frances produced seven TCTORs between 2100 and 0259 UTC on 8−9 September 2004 while fully embedded within the midlatitude westerlies as a closed shortwave trough (Figure 5E). Figure 5B shows an intermediate stage in which a TC may produce TCTOR clusters. Here, TC Floyd has begun interacting with the midlatitude westerlies, as indicated by its position just equatorward of the southern-most circumpolar isoheight (5,800 m), but has not yet embedded within the westerly flow as a shortwave trough. Figures 5B, 5D, and 5F show that, in general, TCs that are interacting with, or embedded within, the midlatitude westerlies are proximate to an upper-level jet streak, especially when a midlatitude trough is located to the northwest or north of the TC. Note that TCs Floyd (Figure 5D) and Frances (Figure 5F), which are beginning to interact with and fully embedded within the midlatitude westerlies, respectively, are substantially closer to the right entrance region of the dominant upper-level jet streak than is TC Alex (Figure 5B), which is completely isolated from the midlatitude westerly flow. Upper-level divergence associated with the right entrance region of an upper-level jet streak in the Northern hemisphere (left entrance region in the Southern Hemisphere) favors rising motion through the lower levels of the atmosphere and supports severe convection (Beebe and Bates, 1955; Rose et al., 2004; Clark et al., 2009). In a composite plot of the 200 hPa vector wind field, Cohen (2010) showed that substantially tornadic TCs often are located to the southeast of an upper-level jet streak,

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placing them near the right entrance region. Figures 5D and 5F are similar to Cohen's (2010) composite in that the TC is located near the right entrance of an upper-level jet, but Figure 5B shows that TCs are capable of producing TCTOR clusters without the upper-level support provided by jet streaks.

FIGURE 5 500 HPA AND 200 HPA GEOPOTENTIAL HEIGHTS CORRESPONDING TO THREE OF THE IDENTIFIED CLUSTERS (UNIT=M; INTERVAL=50M). PLOTS WERE OBTAINED

FROM NOAA (2012) AND MODIFIED BY THE AUTHORS In addition to the upper-level support provided by jet streaks, those TCs beginning to interact with, and those embedded within, the midlatitude westerlies also may undergo internal dynamic changes that promote TCTOR genesis. As it tracks towards the midlatitude westerlies, a TC generally encounters increasing amounts of wind shear, especially under a meridional flow regime with a trough elongated toward the equator (Jones et al., 2003; Molinari and Vollaro, 2010b). Studies have shown that as TCs begin to encounter moderate amounts of ambient wind shear, thermodynamic and wind shear parameters such as CAPE and SRH are amplified in their downshear half (Molinari and Vollaro, 2008 and 2010a; Molinari et

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al., 2012). Low-level convergence, widespread upward vertical motion, severe convection, and lightning also have been shown to be greater in the downshear half of the TC environment (Harr and Elsberry, 2000; Hart and Evans, 2001; Corbosiero and Molinari, 2002; Klein et al., 2000; Ritchie and Elsberry, 2003 and 2007; Molinari and Vollaro, 2010b). In a TC located in predominately westerly flow, the downshear half of the TC generally coincides with its right half, relative to north, which is where nearly all TCTORs are produced. Given this spatial overlap, it is plausible that the internal changes to the TC environment brought upon by the ambient shear ultimately amplify the likelihood of TCTOR production.

4. CONCLUSION

In this study, TCTOR clusters were identified and their corresponding synoptic-scale environments were manually analyzed using NCEP-NARR synoptic plots. The primary goal of the synoptic analysis was to explore the synoptic plots and search for recurring patterns that may provide insight into possible synoptic-scale forcings that increase the likelihood for TCTORs. The three general conclusions drawn from this preliminary analysis are:

TCTORs often occur in temporal clusters, most of which consist of relatively few

TCTORs, but TCs are capable of producing a large number of TCTORs (thirty or more) over a short time period (six hours).

Mid-level dry air entrainment, often into the eastern half of the TC environment, likely increases the potential for TCTORs. Dry air aloft may steepen lapse rates through the processes of evaporative cooling aloft and surface heating, which, in turn, could increase the potential for severe convection.

TCs interacting with or embedded within the midlatitude westerlies are more likely to produce more, and more severe, TCTOR clusters than those TCs that are isolated from the westerlies. TCs that are interacting with or embedded with the westerlies typically are closer to an upper-level jet streak, which provides a source of dynamic lift and favors deep convection. The ambient shear associated with the westerlies also may induce internal changes to TCs that ultimately favors TCTOR production, changes such as increased CAPE, SRH, and severe convection.

The synoptic plots corresponding to some of the clusters identified in this study

verified the general synoptic patterns and composites reported by previous studies (e.g., Curtis, 2004; Verbout et al., 2007; Cohen, 2010). They also, however, illustrated that TCs may produce a substantial number of TCTORs in a short period of time under a range of synoptic conditions, even when synoptic-scale forcing is not evident. The preliminary results of this analysis pose additional topics of inquiry. In particular, future research will further analyze the 500 hPa geopotential height patterns to determine if the frequency and severity of TCTOR clusters varies between those TCs that are isolated from the westerlies and those that are embedded within them.

5. REFERENCES Baker, A.K., M.D. Parker, and M.D. Eastin. 2009. Environmental ingredients for supercells and

tornadoes within Hurricane Ivan. Weather and Forecasting 24(1): 223–243. Beebe, R.G., and F.C. Bates. 1955. A mechanism for assisting in the release of convective

instability. Monthly Weather Review 83(1): 1−10. Clark, A.J., C.J. Schaffer, W.A. Gallus Jr., and K. Johnson-O'Mara. 2009. Climatology of

storm reports relative to upper-level jet streaks. Weather and Forecasting 24(4): 1032−1051.

Cohen, A.E. 2010. Synoptic-scale analysis of tornado-producing tropical cyclones along the Gulf Coast. National Weather Digest 34(2): 99–115.

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Corbosiero, K.L., and J. Molinari. 2002. The effects of vertical wind shear on the distribution of convection in tropical cyclones. Monthly Weather Review 130(8): 2110–2123.

Curtis, L. 2004. Midlevel dry intrusion as a factor in tornado outbreaks associated with landfalling tropical cyclones from the Atlantic and Gulf of Mexico. Weather and Forecasting 19(2): 411–427.

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514

AUTHOR INDEX

A

Acheson, G. …………...………. 237 Al Nasralla, M. ………....... 385, 441

B

Badurek, C. A. …….... 332, 451, 478 Bailey, T. ……………………….. 47 Barnes, K. ……………………... 377 Beaird, H. ………….……... 385, 441 Bennett, J. ……………………... 174 Bergstrom, R. D. ……………..... 127 Blackwood, C. ……………….... 192 Blanchard, R. D. ………………. 367 Blue, S. A. …………………….. 467 Boehm, R. G. ………………….. 264 Boykin, A. ……………………... 432 Brown, S. R. ……….…………... 256 Brysch, C. P. …………………... 264 Burger, P. …………………….... 495

C

Che, D. ……………………….... 415 Chendev, Y. G. ………………... 156 Chloupek, B. …………………... 495 Christoffel, T. J. ……………….. 246 Chow, T. E. ……………………. 367 Ciarleglio, M. ………………….. 146 Clennon, E. …………………..... 367 Cockerill, K. …………………... 332 Combs, H. J. …………………... 495 Comer, J. ……………………..... 210 Cromley, G. A. ……………..….. 441 Currit, N. ……………………..... 290

D

De Stoppelaire, G. H. ………….. 339 Dixon, R. W. ………………... 1, 358 Dock, J. P. ……………………... 146 Duarte, A. ……………………….. 74

E

Earl, R. A. ……………………... 299 Evans, A. ……………………..... 107

F

Forbes, D. J. ………………….... 165 Foster, A. …………………….... 137

French, J. C. ………………..….. 478 G

Gaskins, M. …………………..... 432 Gatrell, J. D. ………………….... 174 Gritzner, J. …………………….. 220

H

Hale, R. ………………………... 332 Hansen, K. J. …………………... 127 Hare, T. S. ……………………... 228 Harper, C. …………………….... 290 Harrington, J. Jr. …………... 11, 309 Hildebrandt, M. L. …………….. 348 Holmes, M. E. …………………. 467 Holst, H. ……………………….. 183 Hooey, C. A. ………………...….. 47 Hug, A. W. …………………….. 316 Hutchins, M. G. ……………….. 451 Hutchinson, S. …………………. 309

I

Irvin, S. ………………………..... 74 J

Jackson, S. …………………….. 432 Jennings, S. ……………………... 83 Jensen, J. L. R. …………….. 74, 290 Johnson, N. …………………..... 228 Arévalo, C. J. …………………...406

L

Laingen, C. …………………….... 37 Lash, J. ……………………….... 117 Lebedeva, M. G. ………………. 156 Lee, J. …………………….. 385, 441 Lein, J. ………………………….. 64 Li, Y. ……………………..... 98, 458 Liu, Z. …………………………... 98 Logue, E. ………………..... 385, 441 Lorch, P. ……………………….. 192 Lupo, A. R. ………………...….. 156

M

Mann, M. M. ……………... 406, 432 Markwith, S. H. ……………….... 27 Mathews, A. J. ………………….. 17

515

Marzen, L. J. ………….….. 316, 458 McBride, A. ………………….... 348 McDonnell, C. ……………….... 432 McGregor, K. M. …………….... 423 Millett, B. V. …………………... 220 Mitra, C. ………………….. 316, 458 Mohler, R. L. ………………….... 92 Moore, T. ……………………….... 1 Mukherjee, F. ………………….. 505

O

Ornelas, R. T. ………………….... 55 P

Parr, D. A. ……………………... 299 Parylak, R. K. ………………….. 358 Pattern, M. T. ………………….... 17 Petin, A. N. …………………..... 156 Pető, B. ……………………….... 406 Pockrandt, B. ………………….. 309 Pridemore, B. J. ……………….. 228

R

Rae, R. ……………………….... 427 Raghavan, R. ………………….… 11 Rahman, M. ………………….... 470 Rajendran, V. ………………….. 517 Rapp, C. J. ……………………... 200 Rice, M. D. ……………….. 283, 293

S

Sandifer, J. …………………….. 335 Seal, K. D. ……………………... 408 Shaker, R. R. …………………... 200 Smith, P. ……………………….. 228 Song, W. ………………………. 146 Suaya, A. ……………………..... 418

T

Taylor, E. …………………….... 192 Taylor, S. V. …………………... 127 Thebpanya, P. ………………..... 183 Tobin, G. A. ………………….... 137

W

Wang, O. ……………………..... 146 Wells, C. ……………………..... 228 Wikle, T. A. ………………..….. 222 Wilcut, E. …………………….... 311 Wilson-Chavez, O. …………….. 283 Wright, R. ……………………... 427

X Xie, Z. …………………………... 98

Y

Yarbrough, T. ………………….. 281

516

LIST OF REVIEWERS Special thanks to our reviewers. Timely reviews with helpful comments and recommendations are essential not only to publishing this volume but also to assuring that papers published adhere to quality standards of the profession. Many of the reviewers listed below reviewed multiple manuscripts that are published in this volume.

Gillian Acheson Christopher Badurek Ryan Bergstrom Denise Blanchard Richard Boehm Keith Bremer Rebecca Brown Stacey Brown David Butler Dawna Cerney Phil Chaney Deborah Che Yu-Lin Chi Jonathan Comer Edward Davis Michael DeMers James Dietric Richard Dixon Timothy Dolney Richard Earl Frank Engel Ellen Foster Carlos Guilbe Katherine J.Hansen Timothy Hare Tony Hernandez Donald Heubner Mark Hildebrandt Catherine Hooey Steve Jennings Jennifer Jensen David Kaplan

Stephanie Kozak Richard Kujawa Chris Laingen Jeff Lash Jay Lee James Lein Yingru Li Michael Mann Didi Martinez Luke Marzen Chandana Mitra M Audrey ohan Rhett Mohler Edris Montalvo Falguni Mukherjee Matt O’Mansky Michael Ratcliffe Murray Rice Eric Samson Thomas Schmidlin Richard Shaker Wei Song Melanie Stine Emariana Taylor Paporn Thebpanya V Brandon ogt Ophelia Wang Clayton Whiteside Thomas Wikle Brittany Wood Xinyue Ye Haifeng (Charlie)Zhang

Co-Sponsors: Kent State University Binghamton University Texas State University-San Marcos University of North Texas Southern Illinois University Edwardsville Florida Atlantic University George Mason University ESRI, Inc.