This award is one component of a mutli-investigator effort known as the Verification of the Origins of Rotation in Tornadoes Experiment 2 (VORTEX 2). VORTEX 2 is a follow on to VORTEX 1 whose field phase was conducted during the Spring of 1994 and 1995. The VORTEX 1 advanced knowledge of the kinematic structures of tornadic and non tornadic storms and provided some hints as to the sensitivity of the evolution of supercell storms and tornadogenesis to very fine spatial scale heterogeneity. The VORTEX 2 research objectives will focus on the genesis and maintenance of tornadoes and on the structure of the near wind field of the tornado. The VORTEX 2 is being conducted in conjunction with the National Oceanic and Atmospheric Administration and it will involve an unprecedented observational network of stationary and mobile facilities that include Doppler radars, surface and upper air observations. .
The Principal Investigators will perform detailed ground and aerial damage surveys and collect high-resolution photographic data of tornadic storms during the VORTEX II. This data will be combined with high-resolution, ground-based radar data to address the following three objectives. The first objective is to better understand the relationship between the tornado and its parent circulation. Specifically, the time evolution of tornado, mesocyclone, and damage intensities will be examined. Previous studies suggest both strong and weak correlations between tornado and mesocyclone strength. The causes of nonlinear surface damage patterns such as trochoidal and scalloping marks, left and right turns, and sinusoidal patterns documented in past damage survey data will also be explored. These patterns have been attributed to single or multiple vortices orbiting around the parent circulation. Surprisingly, no previous study has verified the visual characteristics of suction vortex and trochoidal marks in surface damage.
Recent high-resolution mobile Doppler radar data sets have revealed intriguing single-Doppler velocity features, multi-parameter signatures, and reflectivity features such as weak echo eyes and debris rings within the hook echo of tornadic supercells. The second objective will be to superimpose damage survey and cloud photography data onto these radar features. Such an analysis will further understanding of the relationship between the visual characteristics of the tornado and attendant debris cloud, damage, and the radar-detected features within the hook echo.
Finally, it has been shown that ground based Doppler radars at close range to large tornadoes are able to sample the flow within and around the tornado. The third objective is to examine the relationship between radar-detected wind speeds with wind speed estimates based on the Enhanced Fujita (EF) scale assessments. Such an analysis will verify the wind speeds associated with the various degrees of damage for a given damage indicator and potentially identify new damage indicators. The analysis will also examine the correlation of different wind intensity metrics such as highest wind gusts, duration of intense winds, time integrated wind speeds, and local accelerations with observed damage intensity.
Intellectual Merit Realizing the above objectives will further understanding of the relationship between the mesocyclone, tornado, and attendant surface damage intensity and damage patterns. Superposition of photography and damage survey data onto high-resolution radar data will allow proper interpretation of intriguing features observed within the hook echo region. It is also anticipated that a better understanding of how tornadic flow creates observed damage will result from this research along with refinements to the newly adopted EF scale.
Broader Impacts The research results will have important operational implications for the tornado detection and warning process. A better understanding of the relationship between the mesocyclone and tornado will be very useful in the tornado warning process. An improved understanding of the single-Doppler data within the hook echo may lead to tornadic precursors or identifiable features when the tornado is producing damage at the surface. Any modifications to the EF scale will improve the accuracy of the United States tornado climatology. The research will also expose undergraduate students to the data collection process during a major field experiment and the subsequent analysis. The work will enhance the research infrastructure at Lyndon State College (LSC) and the knowledge gained will be incorporated into many of the undergraduate classes taught at LSC.
One of the objectives of this project was to understand the visual structure and evolution of the tornado and attendant debris with what it looks like in high-resolution mobile Doppler-radar data. By transmitting and receiving microwave radiation, mobile Doppler radars are able to map out particle (rain drops and debris) location in and around tornadoes and estimate their motion. This research objective was realized by superimposing radar data directly onto photographs of the funnel. Data collected during the second Verification of the Origin in Tornadoes Experiment (VORTEX2) were utilized. Photo and radar teams collected high-resolution data on an EF2 tornado that formed over southeastern Wyoming on 5 June 2009. Four findings based on these analyses are as follows. First, high-resolution radar data in and around tornadoes often shows a ring of higher reflectivity values surrounding the center of the tornado. The reflectivity field is a measure of the number and sizes of particles. The "reflectivity ring" has been hypothesized to be due to lofted debris. By superimposing radar data of a "debris ring" on photographs of the tornado funnel and debris, we were able to verify, for the first time, that lofted debris is responsible for creating the ring of higher reflectivity surrounding the tornado (Figure 1). The debris ring is located on the outer edge of the funnel cloud. Second, mobile Doppler radars detected tornadic, damaging wind speeds before the funnel was observed to make contact with the ground. The radar-observed tornado winds were sampled 14 minutes before the funnel made contact with the ground. Thus, it is possible for a tornado to produce damaging surface winds even when the funnel is not making contact with the ground, or even visible. Third, tornadoes often form within a larger scale low-level circulation called the mesocyclone. It is often an order of magnitude larger (3-7 km) than the tornado (Figure 2). Due to sampling limitations, radars can observe and detect the larger mesocyclone, but often not the smaller tornado. An important question that could be addressed with the VORTEX2 data is whether or not the tornado intensity is well correlated to the mesocyclone parent circulation. As the mesocyclone becomes stronger(weaker), does the tornado also strengthen(weaken)? The analysis showed that the mesocyclone and tornado intensities were not well correlated. It was observed that even has the tornado funnel was widening (strengthening tornado), the mesocyclone parent circulation was weakening. Finally, two problems observing tornadoes with mobile Doppler radars are 1) sampling the tornadic winds near the ground and 2) particles (rain drops and debris) near the strong tornadic circulation do not move in the same direction as the air. The particles are "centrifuged" outward from the tornado whereas the air is not. Radars largely detect the particle motion. Yet, it is the air motion that researchers are trying to estimate. These two sampling problems lead to errors when trying to create the three-dimensional flow field in and around tornadoes. In particular, we were able to examine the wind-field errors due to particle centrifuging. When the effect of particle centrifuging was not accounted for, the retrieved wind field in and around the tornado was characterized by strong downward and outward flow at low levels (see Figure 3). Accounting for particle centrifuging (Figure 4), the low-level flow field was much different. Low-level winds blew into and upward relative to the funnel. Therefore, not accounting for "centrifuging" may lead to errors when interpreting the low-level winds within and around the tornado.
