Dr. Nowotarski's Severe Convective Storms Research Group
My group's research interests are focused on severe thunderstorms. We seek to understand how these storms interact with their environments to produce severe weather including tornadoes, hail, and strong winds. We are also working on techniques to improve the prediction of these events in order to limit their adverse effects on society. The various current and previous projects pursued by our group are described below. For a complete list of presentations and publications from our group, please refer to my CV. If you have questions about our work, or are interested in potential collaborations, feel free to get in touch.
Current Project: Convective Storm Dynamics
Supercell thunderstorms, though relatively rare compared to other types of thunderstorms, are responsible for a disproportionately large number of severe weather reports. Nearly all strong and violent tornadoes are associated with supercell thunderstorms. Thus, understanding how vorticity is created, reoriented, and redistributed in supercells is of great interest. Moreover, better understanding how aspects of the near-storm environment and their changes during the evening transition affect supercell updraft forcing is also critical to severe wather prediction.
Through several previous and ongoing investigations, our group explores how supercell dynamics are influenced by the near-storm environment. The underlying motivation for this work is that a better understanding of the influence of predictable aspects of supercell environments on their characteristics will enable improved forecasting of the threats associated with supercells. This research largely relies on cloud-model simulations of supercells in idealized environments.
In past work, using idealized simulations and observations from existing operational and research datasets, we have explored how combinations of environmental low-level shear and relative humidity affect the morphology of supercell outflow, especially its updraft-relative position and motion (Guarriello et al. 2018; Brown and Nowotarski 2019). Ultimately, we were interested in how the characteristics of outflow (as modulated by the environment) affect the development, intensity, and evolution of low-level mesocyclones and tornadoes.
Suite of simulations varying low-level vertical wind shear orientation and depth showing the effects on simulated reflectivity, gust front position, and relative position of low- and midlevel mesocyclones in supercell thunderstorms.
Currently, we are working on collaborative NSF-funded research relating to understanding how aspects of the near-storm environment affect supercell downdrafts in a collaborative research project with Dr. John Peters at Penn State University, Dr. Jake Mulholland at the University of North Dakota, and Dr. Hugh Morrison at the National Center for Atmospheric Research.
Current Project: Untangling Meteorological from Potential Aerosol Effects on Deep Convection
The role of pollutants and other atmospheric aerosols form a key location for cloud droplets to condense and cloud ice particles to nucleate, forming the seeds for precipitation. In addition to affecting precipitation, the latent heat released by condensation and freezing may affect convective storm dynamics. The degree to which aerosols affect convection versus small modifications in the background meteorological conditions (static stability and vertical wind shear) is an unanswered question, due to limited observations and relatively few studies that appropriately isolate the effects of each. Our group is part of team of researchers including Dr. Anita Rapp and Dr. Sarah Brooks that are funded by the Department of Energy as part of the TRACER field program. In the summer of 2022 we collected mobile atmospheric chemistry, aerosol, and meteorological observations in the Houston region as part of TRACER. Our goal was to create vertial profiles of observed aerosols as well as measure the meteorological conditions via radiosonde on both sides of the ubiquitous sea-breeze front in the early-mid summer in this region. We are now busy analyzing this data in a series of studies using radar observations from TRACER and idealized modeling studies where we can control for the effects of our observed aerosol and meteorological conditions on deep convection.
Current Project: Tropical Cyclone Tornadoes
Among other hazards such as storm surge, high winds, and inland flooding, landfalling tropical cyclones often create conducive environments for tornadoes in their outer rainbands. Our group is finishing a collaborative project with researchers at the Storm Prediction Center (SPC) and local National Weather Service forecast offices to understand which tropical cyclones and which portions of tropical cyclones are most likely to produce tornadoes. This work involves comparison of the near-cell environments and radar attributes of convective cells that produce tornadoes and those that do not. Initial work focused on tornadoes in Hurricane Harvey (Nowotarski et al. 2021), but we have expanded our analysis to all landfalling tropical cyclones in the United States since 2013. Part of this work also involves validating numerical model analyses and forecasts of vertical profiles of temperature, moisture, and winds as well as sounding derived parameters relevant to tropical cyclone tornado forecasting (MacDonald and Nowotarski 2023).
Graduate students currently involved in this research: Justin Spotts
Current Project: Overshooting Top Dynamics during DCOTSS
Our group has recently started a collaboration with TAMU Professors Dr. Kenneth Bowman and Dr. Anita Rapp as well as Dr. Cameron Homeyer at Oklahoma University and Dr. Gretchen Mullendore at the National Center for Atmospheric Reserach to investigate the dynamics controlling overshooting tops of deep convection and how this influences exchange of water vapor and other chemicals with the stratosphere. Our involvement relies on high-resolution idealized simulations of real overshooting events observed during the NASA Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) field project. We are comparing the overshots in these high-resolution simulations to coarser real-data WRF simulations.
Past Project: Supercell Updrafts during the Evening Transition
This project relied on idealized simulations with temporally varying base states to investigate how changes in stability and vertical wind shear associated with the low-level jet onset affect dynamic and buoyant updraft forcing. Nowotarski et al. (2020) examined the layers from which supercell thunderstorm updrafts ingest air in varying low-level stability regimes, while Peters et al. (2019, 2020) determined a key impact of vertical wind shear on supercell thunderstorms is its ability to widen updrafts and reduce the deterimental effects of entrainment on updraft cores. Bremenkamp et al. (2022) investigated how the evening transition and the onset of the low-level jet affects the vertical accelerations in supercell updrafts.
Comparison of air drawn into supercell updrafts from above (top), within (middle), and below (bottom) the "effective inflow layer"
Past Project: Southeastern United States Tornado Environments
As part of the Verification of the Origins of Rotation in Tornadoes Experiment Southeast (VORTEX-SE) project, we launched weather balloons in the Meso18-19 field project. From 1 November 2018 - 30 April 2019, we collected information from the Texas A&M University Campus via radiosonde - an instrument package attached to a weather balloon that measures the vertical profile of pressure, temperature, moisture, and winds in the atmosphere. During active severe weather events we joined a network of other university and National Weather Service sites in launching radiosondes every six hours. This data provides much-needed data to improve real-time high-resolution numerical weather prediction of these events in addition to establishing a dataset rich with information regarding the spatial and temporal variability of severe weather environments in the Southeastern United States, before and during tornado outbreaks.
More recently, as part of NSF-funded work, we explored how Southeast US environments evolve over time. Brown and Nowotarski (2020) explored how various teleconnections indices may be used to predict severe weather outbreaks in the Southeast. We have also compared how the early evening transition varies in high-shear low-CAPE environments in the Southeast compared to the more typical evolution of high-shear, high-CAPE environments, developing improved sounding-derived parameters to predict whether storms in such environments may become tornadic (Brown et al. 2021).
Past Project: Probabilistic Forecasting
Another aspect of our research has involved using statistical methods to develop probabilistic forecasts of severe weather threats. Using self-organizing maps (SOMs), we are able to determine patterns in the magnitude and shapes of vertical profiles of environmental variables from a database of proximity soundings from the Rapid Update Cycle (Nowotarski and Jensen 2013). The distribution of threats (i.e., nontornadic, weak tornadoes, significant tornadoes) in each resulting cluster provides information about the relationship between environmental variables and storm type. This is useful for identifying specific environmental traits that are conducive to particular severe threats. By matching a storm environment to the most similar cluster, we can then generate a conditional probability of a given severe threat.
Example of a self-organizing map of profiles of ground-relative wind speed from 0-6 km AGL.
While the applications have been limited to forecasting supercell tornadoes, we plan to expand the capabilities of this technique to include profiles of multiple variables in each SOM (Nowotarski and Jones 2018), investigate different storm types, and predict multiple severe threats.
Past Project: Convection-Allowing Forecast Models and Data Assimilation
With the availability of ever-increasing computational power, convection-resolving (with horizontal grid spacing less than about 4 km) regional forecast models are feasible. Our group has investigated the sensitivity of local, convection-allowing WRF-ARW simulations to assimilation of non-standard observations collected in and around the Texas A&M University campus [e.g., special radiosonde launches, radar data collected from our onsite S-band Doppler radar (ADRAD)]. This work is geared towards understanding if, and in what situations, additional observations might improve the skill of high-resolution models (Benoit et al. 2018).
Collaborative Research Topics
Our group also collaborates with other groups in the College of Geosciences at Texas A&M. We have collaborated with Dr. Oliver Frauenfeld in the Department of Geography investigating how changes in Arctic permafrost may influence land surface characteristics, and how these land surface changes might influence surface fluxes, boundary layer properties, and ultimately clouds, precipitation, and synoptic-scale weather patterns over the Siberian Plateau using real-data WRF simulations (Vecellio et al. 2019). Other work as part of this collaboration has explored how sea-ice thickness modulates fluxes between the ocean and the atmospheric boundary layer, determining an "effective sea ice thickness" and investigating how this may change in future climates (Ford et al. 2021) We have also been collaborating with faculty in the College of Engineering and the College of Architecture to incorporate weather model and radar data into virtual reality (VR) visualization techniques for both research and education.
Current Postdoctoral Scholars and Graduate Students Advised by Dr. Nowotarski
Dr. Milind Sharma (Postdoc)
Milind is a postdoctoral research associate studying interactions between aerosols and deep convective storms. His current research involves analyzing ground-based radar observations from the TRacking Aerosol Convection interactions Experiment (TRACER) to better understand the impact of spatio-temporal heterogeneities in the continental and maritime air masses across the sea and bay-breeze fronts on deep convective updrafts. Milind uses statistical techniques on observational data to address this research problem. These data include polarimetric radar fingerprints and cell characteristics coupled with thermodynamical and kinematical environmental profiles retrieved from radiosonde data and cloud condensation nuclei concentration from LiDAR/spectrometer data. He plans to follow up the observational analyses with a WRF-based numerical modeling study to systematically isolate the influence of background meteorology and aerosol concentration on updraft characteristics. Prior to arriving at TAMU, Milind received his Ph.D. from Purdue University, where he worked with Prof. Robin Tanamachi to investigate the relationship between cloud electrification and microphysical processes in tornadic storms in the southeast U.S. In his spare time, Milind can be found playing trivia with friends and family, storm chasing, cooking, or hiking.
Devin Bissell (PhD)
Devin hails from Bemidji, Minnesota and joined our group after receiving a B.S. and M.S. in Atmospheric Sciences from the University of North Dakota. Devin is continuing research using idealized numerical modeling and data from the DCOTSS field campaign to investigate the dynamics overshooting tops in deep convection and how they and their transport of water vapor into the stratosphere are depicted in numerical models. He loves all things extreme weather, from blizzards to supercells to hurricanes. When he isn't doing research you'll find Devin cheering on the Minnesota Wild, Vikings, Twins, and UND hockey or hiking, travelling, playing racquetball, or reading. One of his goals is to visit every national park.
Grace Van Patter (MS)
Grace joined the research group after receiving a B.S. in Meteorology from Penn State University. Grace's research focuses on understanding how near-storm environmental properties like vertical wind shear and relative humidity influence the strength, origin height, and forcing mechansims for downdrafts in supercell thunderstorms. Her work mainly relies on high-resolution idealized modelling studies. She is originally from Pennsylvania.
David Topping (MS)
David is a Virginia Tech Hokie, earning a B.S. degree in Meteorology there before coming to Texas A&M. He uses idealized computer models to understand how supercell cold pool properties depend on the ambient environment, and how cold pools related to the potential of supercells to produce tornadoes. Specifically, David compares common Great Plains supercell environments to those more typical of the Southeastern United States.
Justin Spotts (MS)
Justin joined our research group as an undergraduate researcher working on our tropical cyclone tornadoes project. He's continued in this work as a MS student, taking an active role in mentoring other undergraduate students in the group as he develops an automated algorithm to track radar attributes of tornadic cells in the outer rainbands of landfalling tropical storms. J-Dog is also our department's radar guru, helping to maintain and operate the Aggie Doppler Radar (ADRAD). In his spare time you'll probably find Justin riding some thermals in a glider!
Research Group Alumni
Originally from North Carolina, Leland is also another Aggie, joining our group in 2019 after earning a BS in our department. Leland worked on our tropical cyclone tornadoes project. She defended her MS thesis validating RAP and HRRR model analses and forecasts within tropical cyclones by comparing grid-point profiles to radiosonde observations. As an undergrad, Leland was an active participant in our VORTEX-SE field project launching radiosondes at all hours of the night. Leland is a salsa dancer (where she met her husband Luis!). Ask her about pear salad sometime.
MS (2022): "Verification of the Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR) Models within Landfalling Tropical Cyclones toward the Improvement of Rainband Tornado Forecasting"
Matt Brown came to our group from Penn State University. During his time at TAMU, he worked on projects related to supercell dynamics and the unique evolution of Southeast US storm environments and subsequent effects on storm dynamics. He also participated in VORTEX-SE radiosonde launches. He's an avid Nittany Lions fan, and was the resident dessert chef for all our research group parties. Matt is currently employed as a postdoctoral scholar at the National Severe Storms Laboratory in Norman, OK.
PhD (2021): "Multiscale Evolution of Southeast US Storms and their Environments"
MS (2018): "The Influence of Lifting Condensation Level on Low-LEvel Outflow and Rotation in Simulated Supercell Thunderstorms"
Coming from Colby, KS and an undergraduate degree from the University of Oklahoma, Marc joined our group in 2018. Marc specialized in numerical modeling of supercells during the evening transition where the nocturnal low-level jet increases but the static stability increases. He also helped develop virtual reality platforms for visualizing radar and model data, and partcipated in VORTEX-SE radiosonde launches. He was a fixture on intramural sports teams, and he and his wife Caitlyn and their dogs look foward to starting a family in Kansas City. While in grad school, Marc started work as a student inten at Energy Forecasting Solutions, where he is currently employed full time.
MS (2021): "Multiscale Evolution of Southeast US Storms and their Environments"
One of the first students in our group, Michelle hails from Reading, PA and Millersville University. At TAMU, Michelle analyzed NEXRAD radar data to examine the alignment of midlevel and low-level mesocyclones as related to ther near-storm environments. Always passionate about education and outreach, Michelle spent time working at a science museum after graduation. Michelle currently works for Yarker Consulting, an atmospheric science and education consulting service.
MS (2018): "Radar-Detected Mesocyclone Tilt in Tornadic and Nontornadic Supercells"
Another research group original and an Aggie, Mark continued at TAMU in our group after earning his BS in our department. Mark is a radiosonde specialist, participating in countless balloon launches during his time here. He spun this familiarity with radisondes into a MS project exploring how radiosondes launched in College Station could improve numerical weather forecasts over the region if included as part of the assimilated data. Naturally, Mark worked for InterMet Systems, a radiosonde manufacturer, after graduate school. He's now a math and science teacher in Austin, TX.
MS (2016): "Sensitivity of High-Resolution WRF Forecasts to a Single Radiosonde in a Data-Sparse Region"
Originally from Pennsylvania and Millersville University, somehow we were able to convince Felicia to come to Texas A&M even without a visit in 2014! Felicia worked on our first NSF project, doing idealized numerical simulations of supercell thunderstorms to explore how low-level wind profiles affected the alignment of midlevel and low-level mesocyclones. Felicia introduced me to Python and we still use some of her code today! After graduation, Felicia worked at KBR, a contractor for NOAA, working on the LAMP model as a code developer. Felicia is now the NOAA Weather Program Office Testbeds Coordinator.
MS (2016): "The Effects of Low-Level Wind Shear Orientation, Depth, and Magnitude on Low-Level Rotation in Simulated Supercell Thunderstorms"