Knowledge of severe storm patterns may improve tornado warnings

Date:
July 1, 2020
Source:
Penn State
Summary:
A radar signature may help distinguish which severe storms are
likely to produce dangerous tornadoes, potentially leading to more
accurate warnings, according to scientists.



FULL STORY ==========================================================================
A radar signature may help distinguish which severe storms are likely
to produce dangerous tornadoes, potentially leading to more accurate
warnings, according to scientists.


========================================================================== "Identifying which storms are going to produce tornadoes and which are
not has been a problem meteorologists have been trying to tackle for
decades," said Scott Loeffler, a graduate student in the Department of Meteorology and Atmospheric Science at Penn State. "This new research
may give forecasters another tool in their toolbox to do just that."
Scientists analyzed radar data from more than a hundred supercell thunderstorms, the most prolific producers of violent tornadoes, and
found a statistically significant difference in the structure of storms
that produced a tornado and those that did not.

Weather radar constantly monitors storms across the country, and data
similar to that used in the study are readily available to operational forecasters who issue warnings, the scientists note.

"These findings have potentially large implications for the accuracy and confidence of tornado warnings and public safety during severe storms,"
said Matthew Kumjian, associate professor of meteorology at Penn State
and Loeffler's adviser. "We look forward to getting this information in
the hands of operational meteorologists to assess the impact it has."
Tornado warning times have improved over the last several decades, thanks
in part to numerical modeling research and intensive field campaigns,
but decision-makers often must rely on readily available information like
radar data when issuing storm warnings, the scientists said. Previous
efforts using conventional radar have struggled to distinguish between
tornadic and nontornadic supercells.



========================================================================== According to the researchers, in 2013, the U.S. upgraded its radar network
to include polarimetric capabilities, which provide additional information about storms, including revealing the shape and size of raindrops.

Using this information, the scientists compared areas with large,
sparse raindrops and regions dense with smaller drops within supercell
storms. The orientation of these two areas was significantly different
in tornadic and nontornadic supercells, the researchers reported in the
journal Geophysical Research Letters.

"We found for nontornadic supercells, the orientation of the separation
between these two areas tended to be more parallel to the direction
of the storm's motion," Loeffler said. "And for tornadic supercells,
the separation tended to be more perpendicular. So we saw this shift in
the angles, and we saw this as a consistent trend." Loeffler said the algorithm from the study can easily be adapted so operational forecasters
could use the program in real time with the latest radar data available.

"Many factors go into issuing a tornado warning, but perhaps knowing
the orientation in real time could help them make a decision to pull
the trigger or to hold off," he said.

The scientists said while the signatures are promising, further numerical modeling studies are needed to understand better the relationship between
the orientations and tornado formation.

Michael Jurewicz, a meteorologist with the National Weather Service
and Michael French, assistant professor at Stony Brook University,
contributed to the study.

The National Oceanic and Atmospheric Administration and the National
Science Foundation supported this research.


========================================================================== Story Source: Materials provided by Penn_State. Note: Content may be
edited for style and length.


========================================================================== Journal Reference:
1. Scott D. Loeffler, Matthew R. Kumjian, Michael Jurewicz, Michael M.

French. Differentiating Between Tornadic and Nontornadic
Supercells Using Polarimetric Radar Signatures of Hydrometeor
Size Sorting. Geophysical Research Letters, 2020; 47 (12) DOI:
10.1029/2020GL088242 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/07/200701125413.htm

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