About

Michael French is an Associate Professor in the Office of the Dean at the School of Marine and Atmospheric Sciences (SOMAS) at Stony Brook University. His research interests revolve around using Doppler radar data to better understand the dynamics of mesoscale weather phenomena. He utilizes high spatial and temporal resolution datasets from phased array radars and dual-polarization radars, along with data from other observing tools, to gain insights into severe storm and tornado processes. French aims to extend these studies to cool season mesoscale weather systems such as lake effect snow and mesoscale snow banding. He is also interested in investigating radar signatures and their causes to assist operational forecasters in short-term forecasting and nowcasting of hazardous weather events. His work includes analyzing radar data to identify signatures associated with tornado dissipation, supercell thunderstorms, and storm evolution, contributing significantly to the understanding of severe weather phenomena.

Research topics

• Computer Science
• Meteorology
• Remote sensing
• Geology
• Physics
• Environmental science
• Geometry
• Mathematics
• Geography
• Telecommunications

Selected publications

• Radar Updraft Proxies for Supercell Tornadogenesis Prediction

  2025-08-08

  articleOpen access1st authorCorresponding

  The most fundamental feature of a convective storm is its updraft. The updraft plays a crucial role in the life cycle of a storm and the production of its hazards, including tornadoes. Recent studies, mostly using numerical models, have proposed direct links between updraft properties and tornado formation. However, it is difficult, outside of specialized field campaigns, to directly sample the vertical velocities that define a storm’s updraft. A lack of observations complicates efforts to verify proposed connections from theory and modeling studies between characteristics of storm updrafts and tornadogenesis.An alternative to direct observations of updrafts is to leverage features in radar data that result from vigorous updrafts. In this way, characteristics of a remote sensing updraft proxy may be used as an estimate of the characteristics of the storm updraft. For our work, we use a polarimetric radar signature, the ZDR column, as a proxy for supercell updrafts. We aim to study the theorized connection between tornadogenesis and both updraft size and updraft vertical alignment. The former link results from a 2021 paper that found evidence that storms with larger ZDR column areas were more likely to be tornadic than non-tornadic. The latter inquiry is based on studies that have found that supercell updrafts that are more vertically aligned (upright) are more likely to produce tornadoes. In this study, we analyze a large sample of ZDR column areas and vertical alignments in tornadic and non-tornadic supercells. For the updraft area part of the study, we examine a large number of WSR-88D volumes with a focus on whether ZDR column areas ≥ 40 km2, which we call “immense” updrafts, are only present in tornadic supercells. If so, the implication is that an immense updraft serves as a sufficient condition for imminent tornado formation. For the updraft alignment part of the study, we use the centroid of the ZDR column at storm midlevels and the storm hook echo at low levels to estimate updraft tilt in supercells; we also use radial velocity data to estimate mesocyclone tilt. The main objective is to identify if there is a difference in updraft (or mesocyclone) tilt between tornadic and non-tornadic supercells. In addition, we determine if there are tilt “cutoff” values large enough to significantly lower the probability of tornado formation. We also discuss study limitations in using radar proxy data and the implications of study results on operational nowcasting of imminent tornadogenesis.

  PublisherDOI

• Comments on “Identifying ZDR Columns in Radar Data with the Hotspot Technique”

  Weather and Forecasting · 2025-04-01 · 1 citations

  article1st authorCorresponding

  Abstract In convective storms, there are often enhanced regions of differential radar reflectivity Z DR above the 0°C level known as Z DR columns. The Z DR column serves as an updraft proxy and therefore is commonly used in both severe storm research and operations, which motivates the development of algorithms to automate their detection. A recent article details the development of a new algorithm to identify Z DR columns. In addition, the article includes intercomparisons between the new algorithm and other similar algorithms that have been developed for community use. However, the comparisons do not use real output from the previously developed algorithms as they were designed. In this article, we present a detailed description of several algorithms used to identify Z DR columns and provide additional context to Z DR column algorithm comparative cases by including output from the real algorithms. We also discuss the difficulty in objectively evaluating Z DR column algorithms given the lack of direct observations of vertical velocities in convective storms.

  PublisherDOI

• The Propagation, Evolution, and Rotation in Linear Storms (PERiLS) Project

  Bulletin of the American Meteorological Society · 2024-06-12 · 9 citations

  articleOpen access

  Abstract Quasi-linear convective systems (QLCSs) are responsible for approximately a quarter of all tornado events in the United States, but no field campaigns have focused specifically on collecting data to understand QLCS tornadogenesis. The Propagation, Evolution, and Rotation in Linear Storms (PERiLS) project was the first observational study of tornadoes associated with QLCSs ever undertaken. Participants were drawn from more than 10 universities, laboratories, and institutes, with over 100 students participating in field activities. The PERiLS field phases spanned 2 years, late winters and early springs of 2022 and 2023, to increase the probability of intercepting significant tornadic QLCS events in a range of large-scale and local environments. The field phases of PERiLS collected data in nine tornadic and nontornadic QLCSs with unprecedented detail and diversity of measurements. The design and execution of the PERiLS field phase and preliminary data and ongoing analyses are shown.

  PublisherOA PDFDOI

• The Influence of WSR-88D Intra-Volume Scanning Strategies on Thunderstorm Observations and Warnings in the Dual-Polarization Radar Era: 2011–20

  Weather and Forecasting · 2021-11-22 · 27 citations

  articleOpen accessSenior author

  Abstract The Weather Surveillance Radar-1988 Doppler (WSR-88D) network has undergone several improvements in the last decade with the upgrade to dual-polarization capabilities and the ability for forecasters to rescan the lowest levels of the atmosphere more frequently through the use of Supplemental Adaptive Intra-volume Scanning (SAILS). SAILS reduces the revisit period for scanning the lowest 1 km of the atmosphere but comes at the cost of a longer delay between scans at higher altitudes. This study quantifies how often radar volume coverage patterns (VCPs) and all available SAILS options are used during the issuance of 148 882 severe thunderstorm and 18 263 tornado warnings, and near 10 474 tornado, 58 934 hail, and 127 575 wind reports in the dual-polarization radar era. A large majority of warnings and storm reports were measured with a VCP providing denser low-level sampling coverage. More frequent low-level updates were employed near tornado warnings and reports compared to severe thunderstorm warnings and hail or wind hazards. Warnings issued near a radar providing three extra low-level scans (SAILSx3) were more likely to be verified by a hazard with a positive lead time than warnings with fewer low-level scans. However, extra low-level scans were more frequently used in environments supporting organized convection as shown using watches issued by the Storm Prediction Center. In recent years, the number of midlevel radar elevation scans is declining per hour, which can adversely affect the tracking of convective polarimetric signatures, like Z DR columns, which were found above the lowest elevation angle in over 99% of cases examined.

  PublisherOA PDFDOI

• Observed Bulk Hook Echo Drop Size Distribution Evolution in Supercell Tornadogenesis and Tornadogenesis Failure

  Monthly Weather Review · 2021-06-02 · 6 citations

  article

  Abstract The time preceding supercell tornadogenesis and tornadogenesis “failure” has been studied extensively to identify differing attributes related to tornado production or lack thereof. Studies from the Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX) found that air in the rear-flank downdraft (RFD) regions of non- and weakly tornadic supercells had different near-surface thermodynamic characteristics than that in strongly tornadic supercells. Subsequently, it was proposed that microphysical processes are likely to have an impact on the resulting thermodynamics of the near-surface RFD region. One way to view proxies to microphysical features, namely drop size distributions (DSDs), is through use of polarimetric radar data. Studies from the second VORTEX used data from dual-polarization radars to provide evidence of different DSDs in the hook echoes of tornadic and non-tornadic supercells. However, radar-based studies during these projects were limited to a small number of cases preventing result generalizations. This study compiles 68 tornadic and 62 non-tornadic supercells using Weather Surveillance Radar–1988 Doppler (WSR-88D) data to analyze changes in polarimetric radar variables leading up to, and at, tornadogenesis and tornadogenesis failure. Case types generally did not show notable hook echo differences in variables between sets, but did show spatial hook echo quadrant DSD differences. Consistent with past studies, differential radar reflectivity factor (Z DR ) generally decreased leading up to tornadogenesis and tornadogenesis failure; in both sets, estimated total number concentration increased during the same times. Relationships between DSDs and the near-storm environment, and implications of results for nowcasting tornadogenesis, also are discussed.

  PublisherDOI

• Tornado Formation and Intensity Prediction Using Polarimetric Radar Estimates of Updraft Area

  Weather and Forecasting · 2021-10-20 · 28 citations

  article1st authorCorresponding

  Abstract A sample of 198 supercells are investigated to determine if a radar proxy for the area of the storm midlevel updraft may be a skillful predictor of imminent tornado formation and/or peak tornado intensity. A novel algorithm, a modified version of the Thunderstorm Risk Estimation from Nowcasting Development via Size Sorting (TRENDSS) algorithm is used to estimate the area of the enhanced differential radar reflectivity factor (Z DR ) column in Weather Surveillance Radar – 1988 Doppler data; the Z DR column area is used as a proxy for the area of the midlevel updraft. The areas of Z DR columns are compared for 154 tornadic supercells and 44 non-tornadic supercells, including 30+ supercells with tornadoes rated EF1, EF2, and EF3; nine supercells with EF4+ tornadoes also are analyzed. It is found that (i) at the time of their peak 0-1 km azimuthal shear, non-tornadic supercells have consistently small (< 20 km 2 ) Z DR column areas while tornadic cases exhibit much greater variability in areas, and (ii) at the time of tornadogenesis, EF3+ tornadic cases have larger Z DR column areas than tornadic cases rated EF1/2. In addition, all nine violent tornadoes sampled have Z DR column areas > 30 km 2 at the time of tornadogenesis. However, only weak positive correlation is found between Z DR column area and both radar-estimated peak tornado intensity and maximum tornado path width. Planned future work focused on mechanisms linking updraft size and tornado formation and intensity is summarized and the use of the modified TRENDSS algorithm, which is immune to Z DR bias and thus ideal for real-time operational use, is emphasized.

  PublisherDOI

• Storm-Scale Polarimetric Radar Signatures Associated with Tornado Dissipation in Supercells

  Weather and Forecasting · 2021-11-09 · 14 citations

  article

  Abstract Polarimetric radar data from the WSR-88D network are used to examine the evolution of various polarimetric precursor signatures to tornado dissipation within a sample of 36 supercell storms. These signatures include an increase in bulk hook echo median raindrop size, a decrease in midlevel differential radar reflectivity factor ( Z DR ) column area, a decrease in the magnitude of the Z DR arc, an increase in the area of low-level large hail, and a decrease in the orientation angle of the vector separating low-level Z DR and specific differential phase ( K DP ) maxima. Only supercells that produced “long-duration” tornadoes (with at least four consecutive volumes of WSR-88D data) are investigated, so that signatures can be sufficiently tracked in time, and novel algorithms are used to isolate each storm-scale process. During the time leading up to tornado dissipation, we find that hook echo median drop size ( D 0 ) and median Z DR remain relatively constant, but hook echo median K DP and estimated number concentration ( N T ) increase. The Z DR arc maximum magnitude and Z DR – K DP separation orientation angles are observed to decrease in most dissipation cases. Neither the area of large hail nor the Z DR column area exhibit strong signals leading up to tornado dissipation. Finally, combinations of storm-scale behaviors and TVS behaviors occur most frequently just prior to tornado dissipation, but also are common 15–20 min prior to dissipation. The results from this study provide evidence that nowcasting tornado dissipation using dual-polarization radar may be possible when combined with TVS monitoring, subject to important caveats.

  PublisherDOI

• Rapid-Scan and Polarimetric Radar Observations of the Dissipation of a Violent Tornado on 9 May 2016 near Sulphur, Oklahoma

  Monthly Weather Review · 2020-08-18 · 12 citations

  article

  Abstract Rapid-scan polarimetric data analysis of the dissipation of a likely violent supercell tornado that struck near Sulphur, Oklahoma, on 9 May 2016 is presented. The Rapid X-band Polarimetric Radar was used to obtain data of the tornado at the end of its mature phase and during its entire dissipation phase. The analysis is presented in two parts: dissipation characteristics of the tornadic vortex signature (TVS) associated with the tornado and storm-scale polarimetric features that may be related to processes contributing to tornado dissipation. The TVS exhibited near-surface radial velocities exceeding 100 m s−1 multiple times at the end of its mature phase, and then underwent a two-phased dissipation. Initially, decreases in near-surface intensity occurred rapidly over a ~5-min period followed by a slower decline in intensity that lasted an additional ~12 min. The dissipation of the TVS in time and height in the lowest 2 km above radar level and oscillatory storm-relative motion of the TVS also are discussed. Using polarimetric data, a well-defined low reflectivity ribbon is investigated for its vertical development, evolution, and relationship to the large tornadic debris signature (TDS) collocated with the TVS. The progression of the TDS during dissipation also is discussed with a focus on the presence of several bands of reduced copolar correlation coefficient that extend away from the main TDS and the eventual erosion of the TDS as the tornado dissipated. Finally, TVS and polarimetric data are combined to argue for the importance of a possible internal rear-flank downdraft momentum surge in contributing to the initial rapid dissipation of the tornado.

  PublisherDOI

• Delayed Tornadogenesis Within New York State Severe Storms

  Journal of Operational Meteorology · 2020-07-09 · 3 citations

  articleOpen accessSenior authorCorresponding

  Past observational research into tornadoes in the northeast United States (NEUS) has focused on integrated case studies of storm evolution or common supportive environmental conditions. A repeated theme in the former studies is the influence that the Hudson and Mohawk Valleys in New York State (NYS) may have on conditions supportive of tornado formation. Recent work regarding the latter has provided evidence that environments in these locations may indeed be more supportive of tornadoes than elsewhere in the NEUS. In this study, Weather Surveillance Radar–1988 Doppler data from 2008 to 2017 are used to investigate severe storm life cycles in NYS. Observed tornadic and non-tornadic severe cases were analyzed and compared to determine spatial and temporal differences in convective initiation (CI) points and severe event occurrence objectively within the storm paths. We find additional observational evidence supporting the hypothesis the Mohawk and Hudson Valley regions in NYS favor the occurrence of tornadogenesis: the substantially longer time it takes for storms that initiate in western NYS and Pennsylvania to become tornadic compared to storms that initiate in either central or eastern NYS. An analysis of approximate near-storm environments using the 13-km Rapid Refresh (RAP) is used to confirm that the long-lived storms encounter more tornado-favorable conditions leading up to tornadogenesis in the NYS valley regions.

  PublisherDOI

• Statistical and Empirical Relationships between Tornado Intensity and Both Topography and Land Cover Using Rapid-Scan Radar Observations and a GIS

  Monthly Weather Review · 2020 · 17 citations

  Senior authorCorresponding
  • Computer Science
  • Geology
  • Remote sensing

  Abstract This study presents an investigation into relationships among topographic elevation, surface land cover, and tornado intensity using rapid scan, mobile Doppler radar observations of four tornadoes from the U.S. Central Plains. High spatiotemporal resolution observations of tornadic vortex signatures from the radar’s lowest elevation angle data (in most cases ranging from ~100 to 350 m above ground level) are coupled with digital elevation model (DEM) and 2011 National Land Cover Database (NLCD) data using a geographic information system (GIS). The relationships between 1) tornado intensity and topographic elevation or surface roughness and 2) changes in tornado intensity and changes in topographic elevation or surface roughness are investigated qualitatively, and statistical relationships are quantified and analyzed using a bootstrap permutation method for individual case studies and all cases collectively. Results suggest that there are statistically significant relationships for individual cases, but the relationships defy generalization and are different on a case-by-case basis, which may imply that they are coincidental, indicating a null correlation.

  PublisherOA PDFDOI

Recent grants

• Collaborative Research: A Polarimetric Radar Climatology of Supercell Thunderstorms in the United States

  NSF · $359k · 2018–2023

Frequent coauthors

• Howard B. Bluestein

  53 shared

• Jeffrey C. Snyder

  NOAA National Severe Storms Laboratory

  31 shared

• Darrel M. Kingfield

  NOAA Global Systems Laboratory

  31 shared

• Jana B. Houser

  The Ohio State University

  28 shared

• Nathaniel McGinnis

  Stony Brook University

  25 shared

• Kelly M. Butler

  NOAA National Severe Storms Laboratory

  25 shared

• Ivan PopStefanija

  ProSensing (United States)

  14 shared

• Robert Bluth

  Naval Postgraduate School

  14 shared

Education

• Ph.D., School of Meteorology

  University of Oklahoma

  2012

• M.S., School of Meteorology

  University of Oklahoma

  2006

• B.S., Earth and Atmospheric Sciences

  Cornell University

  2003

Awards & honors

• A Doppler Radar Climatology of Updraft Proxy Characteristics…
• Research Supercell (French, M. (PI), 2023-2027)
• The Development and Maintenance of Low-Level Rotation in Lin…
• IMPACTS: Investigation of Microphysics and Precipitation for…
• A Polarimetric Radar Climatology of Supercell Thunderstorms…