Last Updated: April 2, 2020
UPDATED 4/2/20... to show which projects are still "on" for a remote REU situation.
This is my holding place for project descriptions while I get them all identified. *These are draft descriptions.* Keep in mind that research projects can change quite a bit. That is part of the nature of research. You don't know how things will work out when no one has done your project before.
I put a link to a recent REU project for that mentor, when possible. That doesn't mean the proposed project is like that one, but will give you a flavor of that mentor's research. Likewise, some projects have "most directly applicable majors" listed. This does not necessarily limit who can choose the project, but instead is meant to reveal something of the nature of the project. If you have any hesitation or doubt or questions about a project please ask some questions before ranking it.
1. Understanding and Mitigating Sources of Error in Dual Polarization Precipitation Estimates
Mentor: Dr. Heather Grams (NOAA/NSSL)
Later this year, a new dual polarization radar-based precipitation product will be operational for National Weather Service users from the Multi-Radar Multi-Sensor (MRMS) system. It is called Q3 Dual Pol (Q3DP), and it will represent a major improvement in accuracy over the current precipitation estimates that do not consider dual-polarization information. However, even the newest techniques in precipitation estimation can have biases and errors. If the errors can be quantified, they can be useful for both better understanding the performance of the products in operational situations and for potentially applying corrections to the data to create an even more accurate estimate. The focus of this study will be to quantify the error characteristics of the MRMS Q3DP for a variety of precipitation regimes using rain gauge data to represent the "true" rainfall accumulations at the ground.
Desired skills: Basic understanding of Linux, programming (Python is a plus!), and statistics
Recent projects with this mentor: Impact of Rain Gauge Location Errors on Verification of Radar-Based Precipitation Estimates and Assessing the Skill of Updated Precipitation Type Diagnostics for Rapid Refresh With mPING
2. (WITHDRAWN) Rapid-Update Dual-Polarization Radar Data and its Potential Use in Severe Weather Warning Decisions
Mentors: Charles Kuster (CIMMS/NSSL)
Severe weather events, such as tornadoes and downbursts, evolve very quickly. Therefore, it is important to collect radar data as quickly as possible to sufficiently observe these events and provide the public with life-saving information. To test the potential operational benefits of rapid-update radar data, researchers have been operating a research dual-polarization radar using specialized sector scanning to collect data with < 2 min updates of many different storm types and intensities. The purpose of this study will be to identify and analyze useful dual-polarization signatures and explore potential benefits of rapid-update radar data to National Weather Service (NWS) forecasters. Potential cases for analysis include downburst-producing thunderstorms, supercells, and quasi-linear convective systems. The student will have the opportunity to analyze unique radar datasets and interact with NWS forecasters to learn about the warning decision process. Mentors will be available to teach and help with any data analysis and research skills needed to complete the project.
Desired skills: Background in atmospheric science and willingness to learn radar data analysis techniques and basic programming.
Recent projects with this mentor: Evolution of Dual-Pol Radar Signatures of QLCS Tornado Development
3. REU Project Topics With the Oklahoma Mesonet
Mentor: Dr. Brad Illston (Oklahoma Mesonet)
Choose One:
Eclipse Temperature Inversion
On August 21, 2017, a solar eclipse passed across the United States. The Oklahoma Mesonet collected 1-minute resolution data during the event. This project will analyze the air temperature data at 1.5m and 9m to determine how the surface layer and inversions changed during the passing of the eclipse.
Requirements: Basic Unix/Linux, Programming experience
Radar Rainfall Estimates vs. Station Rainfall Data
Radar estimates of rainfall are used in many applications including hydrological modeling and flood forecasting. This study will compare Oklahoma Mesonet rainfall measurements to the Stage 4 NWS Arkansas-Red Basin River Forecast Center rainfall estimates from WSR-88D QPE. They use the P3 precipitation estimator designed specifically for the ABRFC, which incorporates the Oklahoma Mesonet data to adjust the radar estimates.
Requirements: Basic Unix/Linux, Programming experience
Objective Analysis Schemes for Mesoscale Variables
Understanding the various methods for performing objective analysis on meteorological data sets is important in how this information is interpreted by end users. Different variables respond differently to objective analysis techniques mainly due to their horizontal and/or vertical spatial variability. This project will determine the accuracy of various objective analysis techniques through a systematic statistical approach of correlating interpolated values from actual Mesonet data values. The project will also analyze the accuracy by time of day and time of year, as well as, understanding how the exclusion of multiple input data points might impact accuracy results.
Requirements: Basic Unix/Linux, Programming experience (some tools are already written in Perl, but could be rewritten by student if needed)
Recent projects with this mentor: Analysis of wet-bulb globe temperature calculations using in-situ observations, Statistical Analysis of Heatburst Events Across Oklahoma From 1997-2016, and Analysis of Anti-Ice Coatings on Field Operational Anemometers
4. REU Topics with the Center for Autonomous Sensing and Sampling (CASS)
Mentors: Brian Greene (SoM & ARRC/CASS & OU/ARRC), a second graduate student (SoM & ARRC/CASS & OU/ARRC) and Dr. Elizabeth Pillar-Little (SoM & CASS)
There are several topics available. Choose one topic below if choosing this mentor team.
1) Spatio-temporal Variability in Kinematics and Thermodynamics Prior to Convective Initiation
During July 14-21, 2018, the Lower Atmospheric Process Studies at Elevation - a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) field campaign took place in the San Luis Valley in south-central Colorado. During this campaign, the University of Oklahoma (OU) deployed state-of-the-art weather observing rwUAS platforms to study convective initiation, morning PBL transitions, and drainage flows from the surrounding mountain ranges. As part of LAPSE-RATE, OU deployed mobile UAS teams to different locations in the valley. There were also multiple other universities deployed throughout the valley. This project would focus on days when convective initiation occurred. The goal is to characterize the boundary layer throughout the valley leading up to convective initiation using the numerous UAS that were in the valley.
Desired, but not necessary skills: computer programming skills in python and/or MATLAB
Directly applicable majors: atmospheric science/meteorology, physics, math
2) UAS Observations of Arctic Stable Atmospheric Boundary Layers
In February 2018, the Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer (ISOBAR) field campaign took place on the Finnish island of Hailuoto. ISOBAR aimed to better understand ultra-stable conditions present in the Arctic above sea ice in the wintertime to improve numerical weather prediction boundary layer parameterizations. To achieve these goals, this campaign leveraged recent advancements in atmospheric sampling with UAS in conjunction with observations from flux towers, sodars, and a lidar. OU contributed to UAS operations by flying continuous profiles throughout nighttime transitions of the PBL over a period of four weeks. This project would focus on synthesizing and analyzing data collected from the campaign to advance understanding of physical processes present in these extreme environments.
Desired, but not necessary skills: computer programming skills in python and/or MATLAB
Directly applicable majors: atmospheric science/meteorology, physics, math
Recent project with this mentor: Observations of Planetary Boundary Layer Ozone Concentrations Using Unmanned Aircraft Systems
5. (WITHDRAWN) Winter Weather and Traffic Collisions
Mentors: Dr. Andrew Rosenow (CIMMS/NSSL) and Dr. Heather Reeves (CIMMS/NSSL)
More people die in winter-related traffic collisions than are directly killed by other meteorological hazards (e.g. tornadoes, floods, lightning, etc.). Yet, there has been relatively little research done on the types of winter weather that contribute to these deaths. This project will build on the results of past REU research to better understand the characteristics of weather occurring at the time of fatal crashes. Crash data from the national Fatality Analysis Reporting System will be combined with meteorological data, including Multi-Radar Multi-Sensor (MRMS) radar and quantitative precipitation data, to expand our understanding of the characteristics of precipitation falling at the time of accidents involving at least one fatality.
Desired skills: Programming (Student will be expanding existing Python codebase)
Most applicable majors: Meteorology/Atmospheric Sciences
6. Building Simple Climate System Models for Instruction and Research
Mentor: Dr. John T. Snow (CA&GS Dean’s Office and SOM)
Toy models are deliberately simplistic models in which only essential physical processes are represented. Their functioning is easy to understand, so they can help in understanding the role of a process in a more complete model. Toy models can also very useful as instructional tools. Using the STELLA modeling and interactive simulation software ( https://www.iseesystems.com/store/products/stella-architect.aspx), I have been developing a sequence of toy models of a climate system analogous to Earth's. The intent is to use this sequence of models to explore the interactions of various physical processes, such as the poleward transport of energy, which can then be tested against observations and the results of more realistic (and much more complex) climate models. In this project, I would work with the student to develop the next model in the sequence. The student have discretion in formulating very simple representations of the meridional transport of energy by the atmosphere and oceans from the Equatorial Tropics to the Polar Regions.
Requirements: Undergraduate physics and ordinary differential equations for scientists and engineers; ability to learn and apply a new software package (STELLA) quickly.
7. (WITHDRAWN) Land-Atmosphere Interactions and Greenhouse Gas Measurements
Mentor: Dr. Sean Crowell (GeoCarb)
Several projects possible involving satellite measurement of atmospheric trace gases. This mentor will finalize a project idea if this project is chosen, in conjunction with the student if they would like to be involved in project formation.
Desired skills: Experience with math and statistics
Most applicable majors:
8. Investigating extended periods with multiple days of severe thunderstorms and tornadoes
Mentor: Dr. Harold Brooks (NSSL) and Dr. Kimberly Hoogewind (CIMMS/NSSL)
Extended periods (1–2 weeks) with multiple days of severe thunderstorm and tornado events are possible “forecasts of opportunity” for making skillful predictions of severe weather activity at lead times of two weeks or longer. A recent example was the second half of May 2019, and a much more significant example was 14-27 April 2011. A problem with understanding these events is that they are relatively rare, so that a long dataset is necessary to get a sufficient number of samples. Recently, version 3 of the 20th Century Reanalysis (20CRv3) has been released. 20CRv3 provides an estimate of the 3D structure of the atmosphere on subdaily time scales back into the middle of the 19th century. We want to look at cases such as April 2011, but also at cases far back in the record. For example, during a 14-day period in May 1896, the 3rd deadliest tornado in US history occurred, as well as tornadoes that fall within the top 5 deadliest tornadoes in Texas, Kansas, and Michigan, each occurring on separate dates. We plan to employ a variety of strategies, including large-scale analysis and dynamical downscaling using a convection-allowing model driven by the large-scale conditions of 20CRv3.
Desired skills: Python programming, familiarity with gridded datasets, basic statistical knowledge
Recent projects with one of these mentors: NWS Tornado Warnings: A Regional Analysis, Updraft Helicity as a Forecast Parameter, and The Effects of Antecedent Soil Moisture Anomalies on Tornado Activity in the United States
9. Investigation of Multi-Radar Multi-Sensor Rotation Track Data on Tornadoes in the Southeastern United States
Mentors: Dr. David Bodine (ARRC) and Tony Reinhart (CIMMS/NSSL)
The Multi-Radar Multi-Sensor (MRMS) system is an operational system actively developed at NSSL for use in operations and warning support for NWS, and private partners. MRMS seamlessly blends NEXRAD radar data together with rain gauge and satellite data to produce a real time high quality gridded radar product every 2 minutes on a 1 km grid across the contiguous United States.
This project will investigate MRMS rotation track data over specific VORTEX-SE events to determine changes in rotation track values in response to terrain or other storm characteristics. It has yet to be determined if the changes of terrain impact the larger mesocyclone scale in addition to the tornado scale. The project will include new thresholds to rotation track data so cleaner data can be utilized for this study.
Desired skills: interest in investigating severe storms and radar products, desire to help improve operational products used by the NWS
Most applicable majors: Atmospheric science/meteorology
Recent projects with one of these mentors: NWS Analysis of Tornadogenesis Failure Using Rapid-Scan Data from the Atmospheric Imaging Radar, Dual-Wavelength Polarimetric Radar Analysis of the May 20th 2013 Moore, OK, Tornado, and Observations of a Supercell and Weak Tornado Made With a Rapid-scan, Polarimetric, Mobile Radar
10. (WITHDRAWN) Why Wait Until It’s Too Late: Using Wideband FMCW Radar for Pre-Avalanche Detection
Mentors: Dr. Jay McDaniel (ECE/ARRC) and Dr. Justin Metcalf (ECE/ARRC)
Avalanches are a major concern for many outdoor enthusiasts including climbers and backcountry skiers. Moreover, with global warming effects and large daily temperature gradients, several Artic towns are experiencing deadly avalanches with little to no measurement or warning capabilities. Although many efforts have been put forth to mitigate risks, the unpredictability of avalanches still results in several deaths annually. In general, the need for newer technologies to aid in pre- avalanche detection is more prevalent now than ever before.
In some avalanche prone areas, radar technology is currently being used to monitor the movement of an avalanche through means of a Doppler shift in the radar’s frequency content. This method is ideal for triggering warnings for railroads and underpasses but can only detect an avalanche that has already begun. Therefore, this project will produce a paper study on the potential of a frequency-modulated continuous wave (FMCW) radar to detect dangerous conditions where an avalanche is likely to initiate. Specifically, this project will investigate and characterize the conditions that lead to avalanches, such as mountain slope angles and snow stack-up characteristics that yield a high probability of avalanche initiation. Armed with an understanding of these conditions, a paper design will be conducted to determine requirements for an FMCW radar capable of creating echograms of sufficient quality to detect and localize areas of high avalanche probability.
Desired, but not necessary skills: interest in radar, remote sensing, and applied electromagnetics
Most applicable majors: physics, geoscience, and electrical engineering
11. How does the extratropical transition of tropical cyclones impact tornado production?
Mentor: Dr. Ben Schenkel (OU/CIMMS)
Approximately 50% of landfalling tropical cyclones eventually transform into extratropical cyclones as part of a process known as extratropical transition. This transformation includes the following structural changes to tropical cyclones that may also impact thunderstorm-scale kinematic and thermodynamic environments: 1) development of warm and cold fronts, 2) weakening and expansion of the near-surface wind field, and 3) development of precipitation asymmetries. However, there has been no prior studies investigating how tornado production in tropical cyclones may respond to these changes during extratropical transition. Hence, the proposed study seeks to quantify how the number and location of tornadoes is impacted by the extratropical transition of tropical cyclones using observations.
Desired, but not necessary skills: 1) computer programming experience (preferably python) and 2) introductory atmospheric science classes
Recent project with this mentor: Assessing the Role of Tropical Cyclone Size in Tornado Production
12. Understanding the correlation between NWS impact-based Flash Flood Warning categories and various NWS flash flood tools
Mentors: Ms. Jill Hardy (OU/CIMMS & NWS/WDTD), Dr. JJ Gourley (NOAA/NSSL), Mr. Todd Lindley (NWSFO Norman), Steve Martinaitis (OU/CIMMS & NOAA/NSSL), Justin Gibbs (NWS/WDTD), Humberto Vergara (OU/CIMMS & NOAA/NSSL), Michael Magsig (NWS/WDTD)
In Fall 2019, the National Weather Service (NWS) implemented a tiered system for issuing Flash Flood Warnings (FFWs) based on projected and occurring impacts. These impact-based warnings (IBWs) give NWS forecasters a method for communicating increased confidence in the warning text using flash flood damage threat tags (i.e. base, considerable, catastrophic).
With this new tiered structure, NWS forecasters need to understand how current operational flash food warning tools correlate with the IBW tags. If forecasters can use their operational tools to better identify when impacts are increasing, then they can more effectively issue FFWs that include elevated language.
This project will classify a database of recent flash flood events based on their perceived IBW tags. The classifications will be based on storm reports, event summaries, warning text details, and ancillary information such as tweets, videos/images posted online, and media reports. Additionally, the project could expand to consider other operational tools including output from the NSSL FLASH suite (e.g. unit streamflow, precip return periods) and the Flash Flood Severity Index. Once classifications are made, statistics will be calculated to determine the distribution of base, considerable, and catastrophic flash flood events. This will provide value to NWS forecasters about: 1) how often each event occurs, and 2) potential thresholds in operational tools that identify each event.
Desired skills: Basic understanding of statistics; willingness to learn about hydrometeorological data and NWS flash flood operations
Most applicable majors: Meteorology/Atmospheric Science, Hydrology
13. Project coming, biology+climate
Mentors: Dr. Kirsten de Beurs (OU DGES), Dr. Tassie Hirschfeld (OU Anthropology), and Dr. Daniel Hicks (OU Economics)
Description coming.
Desired, but not necessary skills:
Most applicable majors:
14. Understanding the Nature of Lightning Associated with Towers
Mentors: Drs. Kristin Calhoun (NOAA/NSSL) and Darrel Kingfield (CIRES & ESRL/GSD)
The construction of communication and other tall towers affects the likelihood of cloud-to-ground in the area immediately around the tower (see Kingfield et al. 2017). We would like to build on the study of Kingfield et al (2017) and explore the structure of lightning that interacts with towers. From previous research studies using primarily video evidence, we know some of the CG flashes associated with towers are likely the result of natural terminations. However, these studies have shown that the majority of lightning associated with towers appears to be either lightning-triggered (ongoing in-cloud (IC) lightning above the tower induces lightning from the tower) or self-initiated upward lightning (lightning initiates from the tall tower and connects with charge in the cloud). The student in the project will analyze high-resolution 3D VHF data from Lightning Mapping Arrays to quantify the structure, behavior, and type of lightning that does and does not interact with the tower.