Robert Trapp
· Director of the School of Earth, Society & EnvironmentVerifiedUniversity of Illinois Urbana-Champaign · Atmospheric Sciences
Active 1920–2026
About
Dr. Robert Trapp is the Director of the School of Earth, Society and Environment and a Professor of Atmospheric Sciences at the University of Illinois Urbana-Champaign. His research focuses on severe convective storms, including their dynamics and associated hazards, as well as their connection with climate change and variability. He conducts research on climate variability and change, thunderstorm dynamics, and weather and climate risk. Prior to joining Illinois in 2014, Dr. Trapp was a Professor in the Department of Earth and Atmospheric Sciences at Purdue University from 2003 to 2014, and a research scientist with the National Severe Storms Laboratory (NSSL) through the Cooperative Institute for Mesoscale Meteorological Studies in Norman, Oklahoma from 1996 to 2003. He also spent four years as a visiting scientist at the National Center for Atmospheric Research in Boulder, Colorado. Dr. Trapp is the author of the textbook “Mesoscale-Convective Processes in the Atmosphere,” published by Cambridge University Press. His educational background includes a B.S. in Agriculture/Atmospheric Science from the University of Missouri-Columbia, an M.S. in Meteorology from Texas A&M University, and a Ph.D. in Meteorology from the University of Oklahoma, where he was also a National Research Council Postdoctoral Fellow.
Research topics
- Climatology
- Geography
- Geology
- Meteorology
- Political Science
- Geodesy
- Physics
- Engineering
- Environmental science
- Atmospheric sciences
- Geophysics
Selected publications
Seasonal prediction of springtime tornado activity in the United States using a hybrid model
2026-02-04
articleOpen accessSenior authorAbstract. Tornado activity in the contiguous United States (CONUS) causes fatalities and financial losses every spring, motivating attempts to skillfully predict springtime tornadoes. Such predictions would facilitate decision-making and resource management for both public and private stakeholders. Using ERA5 reanalysis, we identify five April–May weather regimes (WRs) from 1981–2023, some of which strongly modulate tornado activity. ECMWF seasonal forecasts initialized on April-1st are applied to predict WR frequency, including persistent and non-persistent WRs (lasting ≥5 and <5 consecutive days, respectively). The WR information are incorporated into a hybrid model to predict April–May CONUS tornado activity, including tornado outbreaks (days with > 10 EF-1+ tornadoes). Prediction skill is evaluated using leave-one-year-out cross-validation. Predicted and observed tornado outbreak frequencies are significantly correlated (cc=0.4). Outbreak predictions are more skillful during the positive phase of the Arctic Oscillation (AO) and Pacific North American pattern (PNA), with a proportion correct of 0.75 and 0.71, respectively. This implies that low-frequency climate modes can be used to identify forecasts of opportunity. SSTs over the North Pacific and North Atlantic may help explain the predictability of tornado activity but further work needs to be done to confirm those results. Our study demonstrates the potential for skillful prediction of spring tornado outbreaks using WR forecasts and should be prioritized in future work.
2026-02-11
peer-reviewOpen accessSenior author<strong class="journal-contentHeaderColor">Abstract.</strong> Tornado activity in the contiguous United States (CONUS) causes fatalities and financial losses every spring, motivating attempts to skillfully predict springtime tornadoes. Such predictions would facilitate decision-making and resource management for both public and private stakeholders. Using ERA5 reanalysis, we identify five April–May weather regimes (WRs) from 1981–2023, some of which strongly modulate tornado activity. ECMWF seasonal forecasts initialized on April-1<sup>st</sup> are applied to predict WR frequency, including persistent and non-persistent WRs (lasting ≥5 and <5 consecutive days, respectively). The WR information are incorporated into a hybrid model to predict April–May CONUS tornado activity, including tornado outbreaks (days with > 10 EF-1+ tornadoes). Prediction skill is evaluated using leave-one-year-out cross-validation. Predicted and observed tornado outbreak frequencies are significantly correlated (cc=0.4). Outbreak predictions are more skillful during the positive phase of the Arctic Oscillation (AO) and Pacific North American pattern (PNA), with a proportion correct of 0.75 and 0.71, respectively. This implies that low-frequency climate modes can be used to identify forecasts of opportunity. SSTs over the North Pacific and North Atlantic may help explain the predictability of tornado activity but further work needs to be done to confirm those results. Our study demonstrates the potential for skillful prediction of spring tornado outbreaks using WR forecasts and should be prioritized in future work.
2026-03-10
articleConvection-permitting dynamical downscaling (CPDD) allows for an explicit representation of the convective storms that generate tornadoes, hail, severe thunderstorm winds, and locally heavy precipitation. Possible changes in such hazardous convective weather (HCW) due to human-induced climate change are therefore projected with higher confidence using CPDD than with analyses of relatively coarse global climate models (GCM). However, due to the the computational expense, CPDD-based future projections of HCW have tended to be based on a single experiment rather than an ensemble of experiments which allow for assessments of uncertainty. Herein we present “environment-informed” CPDD as a means to efficiently generate a CPDD ensemble driven by different GCMs. This variant of CPDD is applied only to a subset of days and geographical domains over which the meteorological conditions potentially favor supercell thunderstorms, which are the most frequent generators of significant HCW in the United States. The temporal and geospatial occurrence of supercells over the United States is demonstrated from the perspective of environment-informed CPDD as applied to eight different GCMs and the ERA5 reanalysis. Such occurrences vary considerably from downscaled GCM to GCM, thus demonstrating the value of an ensemble. Based on the ensemble mean, future supercell occurrence is projected to be most frequent over an area centered on the Missouri Bootheel. An earlier-start to the annual cycle of HCW risk is also projected.
2026-02-02
articleConvection-permitting dynamical downscaling (CPDD) allows for an explicit representation of the convective storms that generate tornadoes, hail, severe thunderstorm winds, and locally heavy precipitation. Possible changes in such hazardous convective weather (HCW) due to human-induced climate change are therefore projected with higher confidence using CPDD than with analyses of relatively coarse global climate models (GCM). However, due to the the computational expense, CPDD-based future projections of HCW have tended to be based on a single experiment rather than an ensemble of experiments which allow for assessments of uncertainty. Herein we present “environment-informed” CPDD as a means to efficiently generate a CPDD ensemble driven by different GCMs. This variant of CPDD is applied only to a subset of days and geographical domains over which the meteorological conditions potentially favor supercell thunderstorms, which are the most frequent generators of significant HCW in the United States. The temporal and geospatial occurrence of supercells over the United States is demonstrated from the perspective of environment-informed CPDD as applied to eight different GCMs and the ERA5 reanalysis. Such occurrences vary considerably from downscaled GCM to GCM, thus demonstrating the value of an ensemble. Based on the ensemble mean, future supercell occurrence is projected to be most frequent over an area centered on the Missouri Bootheel. An earlier-start to the annual cycle of HCW risk is also projected.
Journal of Structural Engineering · 2026-05-23
articleSenior authorClimate change impacts various extreme windstorms associated with specific meteorological phenomena in different ways. Because various windstorms contribute to the design wind speeds, this study systematically reviewed the state-of-the-art understanding of climate change effects on wind events that collectively contribute to structural wind design in North America, particularly the US, including extratropical cyclones (as well as nor’easters), tropical cyclones, thunderstorms, and tornadoes. For each windstorm type, the general evidence of climate change impacts on storm activities (e.g., occurrence frequency and intensity) are summarized, followed by the introduction of existing simulation frameworks for yearly (or subyearly) maximum storm winds under changing climate. Relevant simulation results demonstrating climate change impacts on design wind speeds are presented. In addition, major challenges associated with climate, weather, or wind simulations (e.g., resolution and duration) and data analyses (e.g., sample extrema and nonstationary extreme value analysis) to quantify the climate change effects on design wind speeds are discussed.
A storyline climate-change attribution study of the extreme hail event in Switzerland on 28 June 202
Open Access CRIS of the University of Bern · 2026-02-03
articleOpen access1st authorCorrespondingWe employed a “storyline” approach to explore possible anthropogenic climate change influences on the extreme hail event in Switzerland on 28 June 2021, with a particular focus on hailfall near Zurich, Switzerland. The event was successfully simulated using the weather research and forecasting model configured over a European regional domain, with initial and boundary conditions from ERA5. An ensemble of factual simulations with randomly perturbed initial and boundary conditions was compared to an ensemble of counter-factual simulations in which a mean climate change signal was removed from the initial and boundary conditions. This signal was computed using differences between global climate model (GCM) data averaged over current-day and pre-industrial time intervals; data from six different GCMs yielded a range of climate change signals, thus contributing to the counter-factual ensemble. Relative to factual simulations, counter-factual simulations exhibited overall less hail, particularly for diameters ≥ 3 cm. This tendency is consistent with relatively lower convective available potential energy but comparable melting depths in the counter-factual environments. We quantified the fraction of attributable risk and concluded that the geographical area covered by hail of diameter larger than 3 cm and 5 cm appears to have been increased by the meteorological changes attributable to climate change.
Journal of Geophysical Research Atmospheres · 2026-03-27
articleOpen accessAbstract Convection‐permitting dynamical downscaling (CPDD) allows for an explicit representation of the convective storms that generate tornadoes, hail, severe thunderstorm winds, and locally heavy precipitation. Possible changes in such hazardous convective weather (HCW) due to human‐induced climate change are therefore projected with higher confidence using CPDD than with analyses of relatively coarse global climate models (GCM). However, due to the computational expense, CPDD‐based future projections of HCW have tended to be based on a single experiment rather than an ensemble of experiments which allow for assessments of uncertainty. Herein, we present “environment‐informed” CPDD as a means to efficiently generate a CPDD ensemble driven by different GCMs. This variant of CPDD is applied only to a subset of days and geographical domains over which the meteorological conditions potentially favor supercell thunderstorms, which are the most frequent generators of significant HCW in the United States. The temporal and geospatial occurrence of supercells over the United States is demonstrated from the perspective of environment‐informed CPDD as applied to eight different GCMs and the ERA5 reanalysis. Such occurrences vary considerably from downscaled GCM to GCM, thus demonstrating the value of an ensemble. Based on the ensemble mean, future supercell occurrence is projected to be most frequent over an area centered on the Missouri Bootheel. An earlier‐start to the annual cycle of HCW risk is also projected.
2026-02-04
articleOpen accessSenior authorFigure S1: Cross-validation tests for tornado days and outbreaks using two-year (a-b), three-year (c-d), four-year (e-f), and six-year (g-h) testing periods.Pearson correlation and p-values are labeled on each plot.
Weather and Forecasting · 2025-07-29
articleAbstract The challenges associated with nowcasting quasi-linear convective system (QLCS) tornadoes are well documented. One key challenge is that QLCS tornadoes typically develop within mesovortices (MVs), but not all MVs are tornadic. This study used radar and in situ Pod data collected during the Propagation, Evolution, and Rotation in Linear Storms (PERiLS) field campaign to examine the characteristics that differentiate tornadic (TOR), wind-damaging (WD), and nondamaging (ND) MVs at various stages in their lifetimes and to investigate the low-level structure of QLCS MVs. Thirty-one QLCS MVs were manually identified and cataloged using the lowest elevation scans of the nearest WSR-88D and C-band on Wheels (COW) radars during the two years of PERiLS. TOR MVs, over their entire lifetimes, had stronger rotational velocities (Vrots), smaller diameters, and slightly longer lifetimes compared to WD and ND MVs. When MVs were analyzed during their pretornadic, predamaging, and prewarning phases (prephases), TOR and WD MVs had similar Vrots; however, TOR MVs typically had smaller diameters and contracted leading up to tornadogenesis, which could benefit nowcasters. In five cases, MVs were observed at the lowest WSR-88D elevation scans but were not visible in the COW data; the MV structure at different elevation angles for one case is presented. Eight Pods showed evidence of MV intercepts, demonstrated most notably by decreases in pressure. COW data, along with relatively weak wind speeds measured by Pods that collected data on MVs, suggest that vertical variations in low-level MV structure and strength can exist, which may not be adequately captured by the WSR-88D network.
Geophysical Research Letters · 2025-10-31
articleOpen accessAbstract Overshooting tops (OTs) are domed protrusions of deep convective updrafts that extend past the anvil of a cumulonimbus. Recent work has shown that OT depth and area may be sensitive to the thermodynamic environment in the upper troposphere/lower stratosphere (UTLS). What remains unknown is the extent to which the UTLS influence on OT characteristics competes with the influence of the tropospheric updraft. This study uses numerical simulations of supercell thunderstorms to test the relative influences of kinematic and thermodynamic environmental changes on updraft characteristics and ultimately, OT area and depth. Results show static stability in the UTLS is important for modulating depth, but not area. Tropospheric vertical wind shear, which is important for controlling the size of a supercell updraft, is shown to be important for the area of the OT but not its depth.
Recent grants
NSF · $616k · 2008–2012
NSF · $637k · 2017–2025
NSF · $440k · 2012–2015
NSF · $368k · 2003–2008
NSF · $275k · 2014–2016
Frequent coauthors
- 26 shared
Stephen W. Nesbitt
University of Illinois Urbana-Champaign
- 16 shared
Elyne Mitchell
Cooperative Institute for Mesoscale Meteorological Studies
- 12 shared
David M. Schultz
University of Manchester
- 12 shared
Sonia Lasher‐Trapp
University of Illinois Urbana-Champaign
- 12 shared
Noah S. Diffenbaugh
Stanford University
- 12 shared
Karen Kosiba
University of Alabama in Huntsville
- 11 shared
Michael E. Baldwin
University of Oklahoma
- 10 shared
Paola Salio
Education
- 1994
Ph.D., Meteorology
The University of Oklahoma
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