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REU 2003

May 26 - August 2

 

 

 

Projects

Multiple Radar Comparison and Analysis of the 8 May 2003 Oklahoma City Tornadic Supercell by Michael E. Charles, and mentors David L. Andra Jr., Michael P. Foster, and Daniel J. Miller

"This paper will examine the structure and evolution of the 8 May 2003 Central Oklahoma tornadic supercell using two different radars: the KTLX WSR-88D and the Central Oklahoma TDWR. Measurements of the vertical vorticity and convergence of each of three scales of rotation (mesocyclone, tornado cyclone signature [TCS], and tornadic vortex signature [TVS]) were made by subjectively choosing maximum outbound and inbound velocities from each time/elevation angle of each radar dataset. Data was graphed in the form of time-height plots of mesocyclone and TCS vorticity, and TVS delta-velocity, for both radars. Temporal variation of low-level convergence associated with the supercell was also analyzed. It was found that the TDWR, with much higher spatial and temporal resolution, was superior to the WSR-88D in resolving the evolution of small-scale storm features. The TCS was always more easily discernable in the TDWR velocity data. The TDWR velocity couplet associated with the TVS tracked very close to the tornado damage path, while the KTLX data was much less accurate at times. The TDWR was also able to resolve one or more surges on the rear-flank downdraft (RFD) that descended into the mesocyclone region and eventually was tied to the development of intense low-level convergence and the TCS. The KTLX WSR-88D did resolve an RFD surge, but it was difficult to track and observe in great detail because of the radar's lower temporal and spatial resolution. The TDWR data was also found to at times be difficult to interpret because of its ability to resolve detailed structures and its tendency to suffer velocity dealiasing failure. Nevertheless, the TDWR was shown to have advantages over the WSR-88D in observing important small-scale storm features."

Reviewing the SPC/NSSL Spring Program 2003:An Evaluation of the Use of Short-Range Ensemble Forecasting Systems and New High Resolution Deterministic Models in the Prediction of Severe Thunderstorms by Marc R. Dahmer, and mentors Steven J. Weiss and David Bright

"The SPC/NSSL Spring Program is typically held during the heart of the severe convective weather season in Norman, Oklahoma. This is an opportunity for researchers and operational meteorologists to interact and collaborate on a variety of experimental forecast and other operationally relevant research programs. This year's program focus was two-fold. The primary objectives were to explore the use of Short-Range Ensemble Forecasting (SREF) systems to provide meaningful guidance in severe weather forecasting, and to examine the ability of new high-resolution deterministic models to predict convective initiation and evolution. These objectives were subjectively analyzed by participants and evaluated for its operational forecasting uses. The participants of the program were also surveyed to glean insight into the program's utility. Through the evaluation of the objectives, it was found that the SREF output does have positive use operationally. It was also found that just because a model's QPF is initially misplaced or missing, does not mean the model should be discounted as a tool in the prediction of severe weather as it pertains to watch lead time."

Analyzing Statistical Models of Hourly Precipitation Events by Jennifer Esker, and mentor Harold Brooks

"Understanding the national precipitation distribution can be useful in many fields of study, but finding those patterns is not easy. Overwhelming amounts of data create roadblocks for detailed analysis, but constructing statistical models can reduce the mount of data needed. This study applied gamma distributions to a year's worth of processed hourly precipitation data to examine the national precipitation. The set represents all precipitation events of the contiguous United States as elliptical objects and produced a precipitation regime classification based on the gamma parameters assigned to the precipitation within the object. Starting with a general model of the national precipitation the analysis continues to categorize the data by location, season and precipitation regime to produce detailed relationships. Examining plots of the gamma parameters also provides insights into the variability of these categories and additionally confirms that these models present an accurate representation of annual precipitation."

Summertime Precipitation Variability and Atmospheric Circulation over the South American Altiplano: Effects of Lake Titicaca and Salar de Uyuni by Maura Hahnenberger, and mentors Michael Douglas and Jose Galvez

"The South American Altiplano is a high altitude plateau located between 15°S and 22°S and lying between two mountain chains of the Central Andes. Within the plateau are two large features of surface discontinuity that influence local circulations. Lake Titicaca, at the north end of the Altiplano is has an area of 8,300 square km making it the 2nd largest lake in South America. The Salar de Uyuni is the largest dry salt lake in the world with a surface area of 9000 square km. These features and their influences on local circulation can possibly change weather and climate of their surrounding areas. The aim of this study is to use pilot balloon soundings and rain gauge measurements to describe the influence of these features on their surroundings, and the impact on precipitation. Large-scale results showed a relationship between upper-level easterly flow and wet days on the Altiplano, in addition to the opposite; westerly flow and dry days on the altiplano. On the local scale we observed a tendency for increased precipitation with proximity to the lake. The difference in flow on wet and dry days also modified the diurnal breeze circulation of the lake. Analysis of morning and afternoon near-surface winds at the lake and salar indicate morning confluence and afternoon difluence, which may be linked to increased morning convection over the lake indicated by satellite imagery. Comparison of the Salar and Lake indicated a stronger breeze signal at the Salar, possibly a result of the resistance of the salt surface to heating, and reduction of daytime surface heating surrounding Lake Titicaca due to increased vegetation."

A Validation of the National Centers for Environmental Prediction's Short Range Ensemble Forecast by Andrew Hamm, and mentor Kimberly Elmore

"This paper investigates the performance of soundings generated from the National Centers for Environmental Prediction's Short Range Ensemble Forecast (NCEP SREF). The NCEP SREF is an operational ensemble forecast model with 15 members. Rank histograms are used as the primary tool to investigate consistent bias problems as well as ensemble dispersal. For the period spanning 1 May 2003 and 19 July 2003, nine different locations scattered about the continental U.S. are validated with rawinsonde data. Ensembles modified by a lagged bias correction and ensembles modified by both a lagged bias correction and the addition of observational errors are considered. Rank histograms constructed from the unmodified ensemble imply either severe bias problems in the ensemble or a significantly underdispersed ensemble, depending on the variable examined, forecast time, pressure level, and location. Because forecasts between the different locations are poorly correlated, the assumption of independence is acceptable and rank histograms for each location are merged into combined rank histograms for all cities for a given variable, forecast time, and pressure level to produce adequate sample sizes. Combined rank histograms constructed from the bias corrected ensemble are U-shaped, which may be caused either by an under-dispersed ensemble, a non-homogeneous bias structure, or observational errors. However, including observational errors with the bias correction often results in uniform, or occasionally over-dispersed, rank histograms. Analysis of other factors, including the non-homogeneous biases of the ensemble, is shown to help understand the combined rank histograms. Without the bias correction, this ensemble if of limited utility, but the lagged bias correction greatly enhances the ensemble performance."

Intercomparison of Cloud Base Height at the ARM Southern Great Plains Site by Christina P. Kalb, and mentors Andy Dean, Randy Peppler, and Karen Sonntag

"Instruments that measure cloud base height at the Atmospheric Radiation Measurement (ARM) Program site in Lamont and Blackwell Oklahoma are examined. These instruments include, the Micropulse Lidar, Belfort Laser Ceilometer, Vaisala Ceilometer, and Millimeter-Wavelength Cloud Radar. Instruments at the ARM sites record information regarding cloud radiative forcing and feedback effects, variables that represent a great amount of uncertainty in climate prediction. However, flawed observations and dissimilarities in instrument performance when reporting cloud types hinder our ability to fully understand these processes. Also, users of ARM data assume these instruments are interchangeable, but this may not be the case. The purpose of this paper is to address the observed differences between these instruments under different atmospheric conditions and cloud types both qualitatively and statistically, and to test a method that may be useful to identify outliers. Qualitative analysis revealed that the Micropulse Lidar is superior in reporting high cloud bases and jagged cloud bases, but inferior to both ceilometers when reporting low clouds. However, statistical results were inconclusive, due to large standard deviations encountered in all cloud episodes. Histograms used to identify outliers gave reasonable results when cloud bases were visibly similar, but resulted in skewed or bimodal distributions for other cases. These results are discussed for observations taken during the Spring 2000 Cloud Intensive Observing Period."

Conditions Associated with Derechos Occurring in Dry Boundary Layer Environments by Allen L. Logan, and mentors David A. Imy and Stephen F. Corfidi

"The purpose of this study is to determine environmental conditions that are most favorable for the development of widespread convectively induced windstorms that occur within relatively dry boundary layer conditions. Events such as this are difficult to forecast, as are most organized convective windstorms occur within a moist boundary layer. In this study, a dataset composed of 8 dry boundary layer organized wind events that occurred during the months of March, April, May, July and November for a 12-year period of 1989-2001."

Quality Control of Radar Data to Improve Mesocyclone Detection by Rebecca J. Mazur, and mentors Greg J. Stumpf and V. Lakshmanan

"Real-time severe weather algorithms that are used to identify various storm attributes can be adversely affected by the presence of meteorological and non-meteorological contaminants such as anomalous propagation (AP), ground clutter (GC), clear-air return or biological scatters in the radar reflectivity data. We examine the Quality Control Neural Network, a new algorithm which classifies precipitation and non-precipitation returns from radar data and provides reflectivity tilts where the majority of contaminants are removed. We demonstrate that using the reflectivity tilts from the QCNN rather than the unedited reflectivity data improves the skill of the NSSL Mesocyclone Detection Algorithm (MDA). In order to determine a positive effect at classifying radar echoes, the MDA is run both without and with the QCNN filtering the original data. Results using 15 nationwide storm events show that the application of the QCNN effectively removes false MDA detection in clear air return while essentially not impacting the ability to detect mesocyclones in precipitation and storm regions."

Extratropical Cyclones with Multiple Baroclinic Zones and their Relationship to Severe Weather by Nicholas Metz, and mentors David M. Schultz and Robert H. Johns

"Cyclones from the central United States and south-central Canada were examined from 1982 and 1989 to determine how often they contained more than one baroclinic zone. A baroclinic zone was defined if a gradient of 8°F (4.4°C) per 220 km was found and a length of 440 km was achieved. Forty-three percent of cyclones were found to have multiple baroclinic zones. The greatest frequency of cyclones with multiple baroclinic zones occurred during the transition months of April, May, August, and September. In addition, the baroclinic zones appeared to follow a seasonal progression. Ninety-four percent of all baroclinic zones were coincident with a moisture gradient that was apparent through isodrosotherm analysis every 4°F (2.2°C), and 73% contained a veering wind shift across them of at least 20°. Of cyclones with multiple baroclinic zones, severe weather was found to occur along 57% of southern baroclinic zones, significant severe weather along 41%, tornadoes along 35%, and significant tornadoes along 24%. During the spring and summer, severe weather occurred along 83% of southern baroclinic zones, significant severe weather along 65%, tornadoes along 57%, and significant tornadoes along 39%. The occurrence of severe weather, significant severe weather, tornadoes, and significant tornadoes was relatively consistent along the southern baroclinic zones between 1982 and 1989. Finally, the formation of multiple baroclinic zones was examined and two main forms were found. A second baroclinic zone can be the result of an interaction with a historical cold/stationary front, or can result through the attachment of a baroclinic zone from the north."

Click here for Nick's figures.

Analysis of Mesocyclone Detection Algorithm Attributes to Increase Tornado Detection by Christina M. Nestlerode, and mentor Michael B. Richman

"The Mesocyclone Detection Algorithm (MDA) is used in the Weather Surveillance Radar -1988 Doppler (WSR-88D) to detect rotation associated with tornadoes and other severe weather. The MDA analyzes Doppler radar radial velocity volume scans to compose a number of attributes thought to be related to mesocyclone formation. The 23 attributes of the MDA are compared to truthed tornado data in exploratory and diagnostic analyses to examine the underlying structure of the MDA. Results of these analyses indicate that the MDA is a highly correlated system with a wide variety of complexity in those correlations. This multicollinearity can hinder statistical prediction. Measured associations between the attributes vary from near zero correlation to complex correlations with values greater than 0.8, binding up to nine MDA attributes. In diagnostic analyses, linear and logistic regressions are performed on various sets of MDA attributes in an attempt to distinguish tornado events from non-tornado events. Logistic regression is found to be the most successful model due to its parsimony and ability to classify correctly tornado versus non-tornado cases. This research has shown that the number of attributes in the MDA can be decreased by projecting the 23 correlated attributes on a number of uncorrelated dimensions. Using principal component analysis (PCA), multivariate exploration of the data determines that 9 dimensions are needed to describe 85% of the variability of the MDA attributes. While the MDA is currently an improvement over older algorithms, this research shows that it is advantageous to reduce the redundancy of the MDA to make it a more useful tool."

A Study of Proximity Sounding Derived Parameters Associated with Significant Severe Weather by Corey K. Potvin, and mentors Steven J. Weiss and Sarah J. Taylor

"This study focuses on the sensitivity of significant severe weather climatology to proximity criteria. Six independent definitions of proximity are used. These criteria are then used to develop a climatology of several sounding derived parameters for significant wind, hail, and tornado cases. Geographical and significant severe type comparisons are made. One of the major findings is that little variance occurs in distributions of the parameters studied over the range of proximity criteria considered, namely, from 40 km and 30 min to 185 km and 3 h. Therefore, criteria on the upper end of this range can be confidently applied to significant severe storm climatologies in order to maximize sample size. Substantial differences between the climatological significant severe thunderstorm environment in the High Plains and that of other regions of the country are noted. However, significant tornado cases in all the regions studied are found to be associated with higher values of wind shear between the surface and 1 km, and lower mean layer LCL heights. The climatology compiled in this study describes mean significant severe weather environments for eight regions of the United States."

The Impact of High Wind Events on the Central Business District of Oklahoma City by Dustin Rapp, and mentor Jeff Basara

"It is critical to understand airflow through cities due to the possibilities of biological and chemical terrorist attacks, pollution, and accidental chemical spills. Currently very few studies have used field measurements of wind conditions within a city to study urban air flow. This paper investigates the airflow at specific locations within Oklahoma City during two synoptic high wind events using data collected at fifteen different sites within the central business district. Wind speed and direction were averaged for each site before and after the frontal passages. The wind shifts and changes in the magnitude of the wind vectors were analyzed at specific locations and time periods to understand air flow based on street orientation and building structures within the city."

A Comparison of Sounding Parameters for the Southeastern United States During El Niño, La Niña, and Neutral Winters by Victoria Sankovich, and mentors Joe Schaefer and Jason Levit

"Previous research based upon examinations of previous weather events speculates that the El Nino/Southern Oscillation affects severe weather in the United States. However, in this study, thermodynamic and kinematic parameters associated with severe weather are calculated from rawinsonde data to explore differences in the atmospheric stratification during the El Nino, La Nina, and Neutral ENSO phases. The soundings used in this investigation are taken over the southeastern United States during the winter season. Two separate datasets are examined: one of soundings from severe weather events and another of all 00UTC soundings. Surface-3km Storm Relative Helicity, Surface CAPE, and Surface-6km Bulk Shear are analyzed for the severe weather dataset, and results show that severe weather occurs under the same atmospheric conditions regardless of ENSO phase. For the dataset of all weather soundings, three thermodynamic parameters (Mean Layer CAPE, Surface Convective Inhibition, and Mean Layer 300mb Lifted Index) and three kinematic parameters (Surface-6km Bulk Shear, Surface-1km Storm-related Helicity, and Surface-3km Storm-Related Helicity) are examined. The results from this analysis reveal that the thermodynamic parameters favor storm development during the La Nina ENSO phase and that the dynamic parameters favor the El Nino and Neutral phases for severe thunderstorms."