The high frequency of cyclogenesis in the northwestern Gulf of Mexico is often attributed to warm sea surface temperature. In this thesis, the importance of surface fluxes were documented to understand the air-sea interaction effect on the cyclogenesis and storm intensification by using a coupled ocean-atmosphere model of the extratropical 1993 SuperStorm (12-14 March 1993). This storm, also known as the "Storm of the Century," had a wide-reaching effect on the Northern Gulf of Mexico region and the East Coast of the United States. In this study, the ocean response and its effects on the storm and upper level troughs and precipitation were examined using the Gulf of Mexico Regional Coupled Modeling System (GoM-CRMS). GoM-CRMS incorporates two-way coupling between the atmospheric model (Weather Research & Forecasting Model, WRF) and the ocean model (Regional Ocean Modeling System, ROMS). The WRF horizontal resolutions studies are 15 km, 5 km, or ~1.7 km resolutions respectively and the ROMS horizontal resolution is 8 km. Comparisons between Climate Forecast System Reanalysis (CFSR) data, observations and simulations showed that the simulations, especially finer atmospheric resolution simulations, were in better agreement with the observations, root mean square differences (RMSD) between observation and simulations for mean sea level pressure (MSLP), 2-meter air temperature, and wind speed values were ranging between 1 to 4.5 mb, 1.4 to 5.7 ms-1 and 1.2 to 7.2 oC, respectively. Storm tracks for each simulation compared well to the reference storm track extracted from the North American Surface Analysis. Simulations also showed that the latent heat flux is affected by model domain resolution and sea surface temperature temporal resolution. The 500 mb relative vorticity and geopotential height analysis of GoM-CRMS simulation illustrate the shortwave troughs which is leading the storm to intensify and 6 hours accumulated precipitations amount maps that showed the precipitation area located over the downstream of the trough were similar compared to CFSR representation, and were largely insensitive to the SST forcing and model resolution. Therefore, the changes in surface characteristics are largely driven by the differences in resolution and SST coupling, rather than changes aloft. / A Thesis submitted to the Department of Earth, Ocean, and Atmospheric Sciences in partial fulfillment of the requirements for the degree of Master of Science. / Spring Semester, 2015. / December 23, 2014. / Includes bibliographical references. / Eric Chassignet, Professor Directing Thesis; Mark Bourassa, Committee Member; Robert E. Hart, Committee Member; Panagiotis Velissariou, Committee Member.

Floods are among the most destructive forces of nature, costing human lives and property. In order to study the causes and effects of flooding, characteristics of meteorology and hydrology must be combined. The purpose of this study is to examine tropical cyclone-induced flooding and simulate river characteristics to aid in flood forecasting. The Florida State University Global Spectral Model (FSUGSM) is used to generate precipitation forecasts for Hurricane Floyd of 1999, which caused major flooding along the eastern coast of the United States. A track forecast for Floyd is generated by the FSU hurricane superensemble, which provides real-time forecasts for the tracks and intensities of storms over the Atlantic Ocean. These forecasts, when compared to other Numerical Weather Prediction (NWP) models, have been shown to have reduced position errors out to three days. The FSU NWP superensemble (FSUSE) is used to produce precipitation forecasts for Tropical Storm Allison of 2001, a slow-moving storm that caused flooding along the southern Gulf Coast states. These forecasts are compared to the observed rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM). Compared to its member models, the superensemble has been shown to improve precipitation forecasts out to three days. Because of the greater accuracy in storm track forecasts from the FSU hurricane superensemble, a method is proposed to adjust the forecast tracks of precipitation to the storm track positions for each event. Precipitation occurs on small scales ( 10 km) rainfall generated in NWP forecasts. A method for downscaling is proposed, which is then applied using a Land Analysis System (LAS) developed by the National Aeronautics and Space Administration (NASA). This is incorporated into the input variables for a land-surface hydrologic model. The hydrology model is used to predict streamflow for two river basins (from each tropical cyclone case) that suffered major flooding as a result of heavy precipitation. Using a digital elevation model at 1 km resolution, a watershed domain and stream network are delineated for each case. Selected vegetation, land, and soil parameters are also derived and used to drive the small-scale aspects of the hydrologic model. Simulated streamflow from the model is then compared to the observed streamflow for each case. The results are used to gain insight into the methodologies of flood forecasting. To improve simulated versus observed streamflow, accurate parameterizations within the hydrology model are required. Only daily observed data was available, so the averaging of hourly hydrology model output negatively affected the results. However, adjusting the FSUGSM precipitation forecasts for Hurricane Floyd towards the FSU hurricane superensemble track improved the location of heavy precipitation. These, in turn, slightly improved the simulated streamflow output from the hydrology model by producing a secondary peak near the time of Floyd's landfall. For the river basin affected by Tropical Storm Allison, the simulated streamflow related very closely to the observed streamflow, in regards to the timing and magnitude of peak streamflow. These results give confidence in the coupling of meteorology and hydrology data to forecast heavy precipitation, river conditions, and possible floods. / A Thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science. / Degree Awarded: Spring Semester, 2004. / Date of Defense: March 18, 2004. / San Jacinto River, Tammy, Tar River / Includes bibliographical references. / T.N. Krishnamurti, Professor Directing Thesis; Paul Ruscher, Committee Member; Robert Hart, Committee Member.

Statistical guidance equations are developed to determine the probability of noon to midnight lightning activity (the occurrence or non occurrence of at least one flash) in eastern Miami-Dade and Broward Counties during the warm season (May-September). The guidance assumes that the sea breeze provides the dominant forcing for afternoon convective and lightning activity. The guidance product is developed to assist Florida Power and Light Corporation personnel in deciding whether extra line crews will be needed after normal business hours. Fourteen years (1989-2002) of warm season lightning data from the National Lightning Detection Network and 1200 UTC Miami radiosonde data are used to develop and test the guidance equations. The lightning data document whether lightning occurred within the areas of interest during the noon to midnight time period. The radiosonde data are used to calculate fifty-four potential predictors, including wind, moisture, stability and temperature parameters. Two persistence variables (the previous day's afternoon activity and the current day's morning activity) also are included as potential predictors. Binary logistic regression is used to relate the noon to midnight lightning activity to the pool of potential predictors. A stepwise screening procedure is used to build separate models for each month during the warm season for both counties. Deriving separate monthly models is found to improve forecast skill compared to a single warm season model. Each monthly model generally contains persistence and the wind, moisture, and stability parameters which are known to influence the strength and movement of the sea breeze and convective development. A cross-validation procedure is used to test the models on independent data and to determine the stability of the models. The cross-validation process reveals that the models are statistically stable and perform well when tested on independent data. The probability of detection, calculated from the independent testing, ranges from ~67% during May to ~90% in August, while false alarm rates range from ~30% during May to only 15% in August. Results from independent testing of the models also show that they improve on forecasts based solely on persistence. For example, the threat score for the guidance equations is ~69% versus ~61% for persistence alone. Furthermore, the hit rate improves from ~71% to ~77%. Although persistence is a powerful predictor of lightning activity in South Florida during the warm season, the guidance equations provide superior results. Days when the models produced an incorrect forecast are examined. When no lightning was forecast but occurred anyway, quartiles of lightning activity are considered. The percent of incorrect forecasts decreases from low activity days (i.e., 1st quartile days, 1-7 afternoon flashes) to high activity days (4th quartile days, >125 afternoon flashes). Thus, incorrect forecasts are least likely on the most important days. Fewer days with lightning occurrence are incorrectly forecast during July and August than during May. A similar trend is observed on days when no noon to midnight lightning was observed but had been forecast.125 afternoon flashes). Thus, incorrect forecasts are least likely on the most important days. Fewer days with lightning occurrence are incorrectly forecast during July and August than during May. A similar trend is observed on days when no noon to midnight lightning was observed but had been forecast. / A Thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science. / Degree Awarded: Summer Semester, 2004. / Date of Defense: June 15, 2004. / Binary Logistic Regression, Thunderstorms, Florida, South Florida, Lightning, Statistical Guidance, Statistics, Forecasting / Includes bibliographical references. / Henry E. Fuelberg, Professor Directing Thesis; Kwang Yul Kim, Committee Member; Philip Cunningham, Committee Member.

A diagnostic study of rainfall variability in Africa in the area from 5oS to 10oN and from 10oE to 30oE was carried out using a gauge rainfall data. Emphasis was placed on determining the time-scales of interannual variability, the characteristics of interseasonal fluctuations, and on regionalization of the data. The latter was used in order to reduce the number of regions utilized for studying this variability in the context of sea-surface temperature fluctuations, El Nino/La Nina, and atmospheric circulation variables. Five homogeneous regions were found in this manner. Generally, the most relevant aspects of SST variability for interannual variability of rainfall appear to be: ENSO, Atlantic and Indian Oceans SSTs, Atlantic upwelling and Atlantic dipole. The importance of these varies seasonally and, to a lesser extent, regionally. There is no "symmetry" between the factors associated with wet conditions and those producing dry conditions. Rainfall response to SSTs is clearly seasonally specific. This is manifestation of the complexity of the factors influencing rainfall over Central Africa and of the pronounced seasonality of rainfall over this region. Overall, regions 1, 2 and 3 show strong teleconnection to factors that control variability. For regions 4 and 5 such teleconnections were not found which suggests the possibility that these two regions are not as homogeneous as it appeared initially. One of the reasons for this could be that these two regions represent a transition zone between influences of the Atlantic Ocean to the west and Indian Ocean to the east. / A Thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science. / Degree Awarded: Fall Semester, 2003. / Date of Defense: September 9, 2003. / La Nina, Climatic Variability, El Nino / Includes bibliographical references. / Sharon Nicholson, Professor Directing Thesis; T. N. Krishnamurti, Committee Member; James J. O`Brien, Committee Member.

This study will examine scale interactions and energy transformations that occur during hurricane genesis. A high-resolution mesoscale model that uses initial and boundary conditions obtained from the National Centers for Environmental Prediction (NCEP) Global Final Tropospheric Analyses and that produces a reasonable simulation on hurricane genesis will be employed. We will first explore the organization of convection during hurricane genesis to establish which scales are evolving and to determine which wavenumbers constitute the hurricane scale. Next, complete energy budgets during hurricane genesis will be examined. This is aimed at sorting out energy flow during hurricane genesis. The framework of the study is based on the seminal papers by Saltzman (1957, 1970) on atmospheric energetics in the wavenumber domain. A complete energy budget includes examination of the generation of available potential energy, conversion from available potential energy to eddy kinetic energy, the rate of change of kinetic energy due to nonlinear triad interactions, the rate of change of potential energy due to nonlinear triad interactions, zonal to waves flow of kinetic energy, and zonal to waves flow of potential energy. The main findings of this study are that individual cloud elements and cloud clusters are evolving into larger scale (symmetric) clusters around the eye of the hurricane and that a hurricane's scale can be described by wavenumbers 0, 1, and 2. The largest contributor to the energy exchange was found to be both of the in-scale quadratic nonlinearities, particularly the baroclinic conversion from available potential energy to kinetic energy. The transfer of energy between the different scales are small compared to the in-scale energy exchanges. The generation of available potential energy for the hurricane scale increases during hurricane genesis indicating the organization of clouds along the hurricane scale. The conversion of available potential energy to eddy kinetic energy mirrors the generation of available potential energy and indicates that the warm core of the storm is building up. In particular, it was found that conversion to KE due to vertical overturnings was important on the cloud scale during the formative stage of the hurricane. By the hurricane stage, the cloud scales became less important while the largest conversion occurred among the mean. The general pattern is for the mean and the large-scale asymmetries to lose available potential energy to the cloud scales indicating a down-gradient sensible heat flux. The kinetic energy exchanges between the different scales tend to be slightly smaller than the exchanges of available potential energy and are more variable. During the formative stage the general pattern is for the mean to lose kinetic energy to the large-scale asymmetries. By the hurricane stage, the exchanges between the mean and the large-scale asymmetries are similar in magnitude, but the patterns are inconsistent. However, it was found that the cloud scales receive the bulk of the KE during the hurricane stage. / A Dissertation Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy. / Summer Semester, 2006. / June 16, 2006. / Scale Interactions, Hurricane Genesis, Convection / Includes bibliographical references. / T. N. Krishnamurti, Professor Directing Dissertation; Ruby Krishnamurti, Outside Committee Member; Philip Cunningham, Committee Member; Guosheng Liu, Committee Member; Robert Hart, Committee Member.

A method for determining the diurnal sea surface temperature (SST) cycle through satellite data has previously been developed by Clayson and Curry (1996). In their work they applied a parameterized equation from Webster et al. (1996) that uses the magnitude of peak solar insolation, the cumulative amount of daily precipitation, and average daily wind speed to compute the diurnal warming of SSTs. This parameterization has been applied to data obtained by the International Satellite Cloud Climatology Project (ISCCP) and Special Sensor Microwave/Imager (SSM/I) data to produce a daily diurnal warming database for the global tropics during the years 1996-2000. Precipitation values were not yet available and were found to play a smaller role in diurnal warming, so they were not used in this study. Daily files of diurnal warming (dSST) were created at a spatial resolution of 0.25 deg. longitude x 0.25 deg. latitude. This study examines the spatial and temporal variability of dSST over the global tropics by examining averages of these values seasonally and year to year and by conducting an EOF analysis of the data for the tropical Atlantic, Indian, and Pacific Oceans. Results show that different atmospheric processes influence dSST for each tropical ocean basin. Also, dSST is shown to be driven by surface fluxes and not the underlying ocean characteristics. However, diurnal warming can affect the depth of mixing and entrainment cooling in the upper ocean by influencing the oceanic stability at the surface. / A Thesis Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Master of Science. / Spring Semester, 2005. / March 30, 2005. / Diurnal Warming, Sea Surface Temperature, Satellite Observation / Includes bibliographical references. / Carol Anne Clayson, Professor Directing Thesis; Mark Bourassa, Committee Member; T. N. Krishnamurti, Committee Member.

Scatterometer observations of vector winds are used to examine the amplitudes of synoptic and diurnal cycles. Scatterometers have the advantage of providing global coverage over water; however, irregular temporal sampling complicates the analyses. A least squares technique is used in determination of the amplitudes and phases of the diurnal and synoptic cycles on spatial scales of 5°, 15°, and 30°. In open ocean areas and regions with sufficient open water, the magnitudes of the diurnal and synoptic cycles are 1.0 ms-1 and 3.5ms-1, respectively. Diurnal amplitudes are highest in the polar regions and close to land surfaces due to sea breeze effects. The fraction of variance explained by the diurnal cycle is greatest near the equator. Synoptic amplitudes are consistently larger downwind of land from storm tracks and in the southern polar region as the time analyzed is during the southern winter season. / A Thesis Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Master of Science. / Fall Semester, 2004. / July 20, 2004. / Rotary Spectra, Least Squares Regression, QSCAT, Midori2, Oceanic Winds / Includes bibliographical references. / Mark Bourassa, Professor Directing Thesis; James O’Brien, Committee Member; Jon Ahlquist, Committee Member; Carol Anne Clayson, Committee Member.

The "water wars" of the Apalachicola-Chattahoochee-Flint (ACF) River Basin are fueled largely by historic and current droughts in the southeastern United States. In attempts to describe climatological circumstances that could lead to low flows in the ACF, this study examines relationships between some available surface climatological variables connected to evapotranspiration and four climatic oscillations using canonical correlation analysis (CCA). The surface meteorological variables for the dependent data set include monthly values of maximum and minimum temperature, as well as precipitation, extracted from the National Climatic Data Center (NCDC) and the Parameter-elevation Regressions on Independent Slopes Model (PRISM) data sets for four climate divisions in the ACF. The precipitation data are used to compute standardized precipitation index (SPI) values for three, six, twelve, and twenty-four month periods (SPI3, SPI6, SPI12, SPI24) for 1901-2000. The oscillations chosen based upon their previously researched associations to climate patterns in the southeastern United States include the global scale Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), and Southern Oscillation Index (SOI). We apply analysis thresholds to the canonical loadings and cross loadings for the canonical roots extracted at the 95% significance level to display the relational results for two separate tests conducted using CCA. The dependent data set for one test consists of the temperature data and SPI6, while the independent data set consists of all the indices for four seasons, allowing for time-lagged and concurrent relationship discoveries. In this test, the standardized temperature data account for much of the variance explained for the CCA-derived concocted variate, with the strongest canonical relationships occurring during the winter season (DJF). Precipitation appears in the wetter spring (MAM) and summer (JJA) season with an indirect relationship to SOI (spring) and PDO (summer). The climate indices with intra-annual frequencies tend to show inverse relationships with temperature throughout the year. The second test utilizes only the four intervals of SPI values for the dependent variable set to focus on precipitation variability at different time scales for the northernmost and southernmost sub-basin areas. The variations of precipitation in the Apalachicola sub-basin (southernmost) results are most sensitive to the SOI in the winter and spring seasons, where a significant relationship is found with the standardized precipitation indices with the higher variance (SPI3 and SPI6). Quite differently, the Upper Chattahoochee sub-basin results largely consist of indirect relationships between the climate oscillations with longer frequencies (AMO and PDO) with the longest time averaged SPI variable (SPI24). These findings reveal that weather and climate patterns in the ACF are not heterogeneous, and that multiple scales and multiple indices appear to be required to develop a comprehensive understanding of the nature of drought in this region. / A Thesis Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Master of Science. / Spring Semester, 2008. / November 13, 2007. / Climatology, Meteorology, ACF / Includes bibliographical references. / Paul Ruscher, Professor Directing Thesis; Jon E. Ahlquist, Committee Member; Henry Fuelberg, Committee Member.

Surface albedo is defined as the ratio of the reflected to the incident solar radiation on the earth's surface. Some general circulation model simulations indicate that an increase in albedo due to desertification and deforestation may lead to reduction in precipitation and evapotranspiration. The monthly mean of an earlier surface albedo dataset and MODIS are used to examine the surface albedo spatial and temporal variations of Africa. In order to study surface albedo temporal variations the African continent is divided into three regions: northern, equatorial and southern. Even though every month is analyzed, only the four months of February, April, July and November are discussed. In the northern region both the earlier dataset and MODIS the surface albedo showed the largest annual range in surface albedo in the semi-arid and arid areas. It is in these areas where the Meteosat surface albedo values were highest. While MODIS also showed a similar annual range in these areas, however this range was over a much smaller area. The spatial variations in surface albedo in the northern region depict the geographical features of the region. Also in the semi-arid and arid areas of the northern region is where the two datasets most differed. The largest differences between the datasets occur in February, which is during the dry season. It is in these areas where the largest surface albedo values were found and these areas are near or are west of major dust sources. In the southern region as was the case in the northern region the semi-arid and arid areas had the largest annual ranges. In the southern region the actual surface albedo for the semi-arid and arid region are lower than the surface albedo in the northern region for the same areas. The two datasets differ the most in the semi-arid and arid areas. To further understand the temporal and spatial variations of surface albedo, two land cover classification schemes were examined. MODIS uses the International Geosphere-Biosphere Programme 17-land cover scheme. A second land cover dataset was created from White/UNESCO vegetation map to be used with the earlier surface albedo dataset. In some areas the maximum albedo occur in the wet season while in other areas maximum albedo occur in the dry season. In the areas where maximum albedo occurs in the wet season, vegetation tended to be the major factor in determining surface albedo. In Charney's classic 1975 paper he theorized that a reduction in vegetation would lead to an increase in surface albedo, which in turn would lead to a reduction in precipitation. In this for a majority of the vegetation groups minima in surface albedo and NDVI occur at the same time of year. These findings do not support Charney's theory that a reduction in vegetation will lead to an increase in surface albedo. Surface albedo may be influenced by an increase in reflective surfaces. One of the objectives of understanding the spatial and temporal variations in surface albedo is to compare model calculated surface albedo to satellite derived surface albedo. A Comparison of Biosphere-Atmosphere Transfer Scheme, Land Surface Model to Advanced Very High Resolution Radiometer lead to the parameterized albedo in the Community Land Model version 2 to be adjusted. As satellite instrumentation improves so must the land surface process of general circulation models. This study shows that the parameterized surface albedo in Community Land Model version 2 still may not correctly represent the semi-arid and arid regions of Africa. The parameterized vegetation and soil albedo values are still too low. / A Thesis Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Master of Science. / Fall Semester, 2005. / July 28, 2005. / MODIS, Surface Albedo, Africa, Meteosat / Includes bibliographical references. / Sharon E. Nicholson, Professor Directing Thesis; Jon E. Ahlquist, Committee Member; Guosheng Liu, Committee Member.

The Kennedy Space Center in east Central Florida is one of the few locations in the country that issues lightning advisories. These forecasts are vital to the daily operations of the Space Center and take on even greater significance during launch operations. The U.S. Air Force's 45th Weather Squadron (45WS), who provides forecasts for the Space Center, has a good record of forecasting the initiation of lightning near their locations of special concern. However, the remaining problem is knowing when to cancel a lightning advisory. Without specific scientific guidelines detailing cessation activity, the Weather Squadron must keep advisories in place longer than necessary to ensure the safety of personnel and equipment. This unnecessary advisory time costs the Space Center millions of dollars in lost manpower each year. This research presents storm and environmental characteristics associated with lightning cessation that then are utilized to create lightning cessation guidelines for isolated thunderstorms for use by the 45WS during the warm season months of May through September. The research uses data from the Lightning Detection and Ranging (LDAR) network at the Kennedy Space Center, which can observe intra-cloud and portions of cloud-to-ground lightning strikes. Supporting data from the Cloud-to-Ground Lightning Surveillance System (CGLSS), radar observations from the Melbourne WSR- 88D, and Cape Canaveral morning radiosonde launches also are included. Characteristics of 116 thunderstorms comprising our dataset are presented. Most of these characteristics are based on LDAR-derived spark and flash data and have not been described previously. In particular, the first lightning activity is quantified as either cloud-to-ground (CG) or intra-cloud (IC). Only 10% of the storms in this research are found to initiate with a CG strike. Conversely, only 16% of the storms end with a CG strike. Another characteristic is the average horizontal extent of all the flashes comprising a storm. Our average is 12-14 km, while the greatest flash extends 26 km. Comparisons between the starting altitude of the median and last flashes of a storm are analyzed, with only 37% of the storms having a higher last flash initiating altitude. Additional observations are made of the total lightning flash rate, percentage of CG to IC lightning, trends of individual flash initiation altitudes versus the average initiation altitude, the average inter-flash time distribution, and time series of inter-flash times. Five schemes to forecast lightning cessation are developed and evaluated. 100 of the 116 storms were randomly selected as the dependent sample, while the remaining 16 storms were used for verification. The schemes included a correlation and regression tree analysis, multiple linear regression, trends of storm duration, trend of the altitude of the greatest reflectivity to the time of the final flash, and a percentile scheme. Surprisingly, the percentile method was found to be the most effective technique and the simplest. The inclusion of real time storm parameters is found to have little effect on the results, suggesting that different forecast predictors, such as microphysical data from polarimetric radar, will be necessary to produce improved skill. When the percentile method used a confidence level of 99.5%, it successfully maintained lightning advisories for all 16 independent storms on which the schemes were tested. Since the computed wait time was 25 min, compared to the 45WS' most conservative and accurate wait time of 30 min, the percentile method saves 5 min for each advisory. This 5 min of savings safely shortens the Weather Squadron's advisories and saves money. Additionally, these results are the first to evaluate the 30/30 rule that is used commonly. The success of the percentile method is surprising since it out performs more complex procedures involving correlation and regression tree analysis and regression schemes. These more sophisticated statistical analyses were expected to perform better since they include more predictors in the forecasts. However, with the predictors available to us, this was not the case. While not the expected result, the percentile method succeeds in creating a safe and expedited forecast. / A Dissertation Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy. / Fall Semester, 2007. / September 10, 2007. / Lightning cessation, Total lightning, LDAR / Includes bibliographical references. / Henry E. Fuelberg, Professor Directing Dissertation; James B. Elsner, Outside Committee Member; Paul H. Ruscher, Committee Member; Jon E. Ahlquist, Committee Member; Robert Hart, Committee Member.