for explosive sales growth!” As you can imagine, that explosive
sales growth is not being funded out-of-pocket by property
owners; rather, it’s being funded by a parallel growth in insurance hail claims.
All modern, automated hail track products are built upon the
same fundamental data: output from National Weather Service
(NWS) dual-polarization weather radar processed through
a hail detection algorithm. Since these products all rely upon
dual-polarization radar’s ability to distinguish different precipitation types, they are all subject to the same data-based uncertainty and limitations.
This is not to say that such hail track products aren’t valuable.
They are: they provide a convenient and generally accurate account of where hail is being produced within a storm. Meteorologists, both operational and forensic, often use hydrometeor
classification algorithms (techno-speak for algorithms that offer
a best-guess as to the type of precipitation occupying a given section of sky) as a first step in identifying likely regions of hail production, although we take the algorithm output with a healthy
grain (or two) of salt when conditions warrant.
Dual-Polarization Radar: The basics
By collecting information from two dimensions instead of one
(hence the “dual” in dual-polarization), dual-pol radars can provide sophisticated information about the shape, density and variety of precipitation particles within a storm.
Such detailed information wasn’t always available. Before the
National Weather Service upgraded its network of NEXRAD
radars to dual-polarization operation during 2011-2013, those
radars were single-polarization and collected only one-dimen-sional information that did not explicitly reveal hydrometeor
properties. Radar algorithms had to infer precipitation type
based on characteristics like storm structure and the atmospheric freezing level.
Dual-pol changed that. The upgraded radars and their likewise
upgraded hydrometeor classification algorithms don’t have to
rely on such inferences. Instead, they can directly discern and discriminate between areas of heavy rain, hail, sleet and snow based
on collected data about hydrometeor shape, density and variety.
So dual-pol radar is a powerful tool, but like any tool, it can be
abused when its limitations and inherent uncertainty are not well
understood (or simply ignored). Which brings us to the dark side
The dark side
What conditions warrant skepticism when it comes to automated (algorithm-based) hail detection?
Discrepancies between hail detection algorithm output and
what’s actually observed on the ground generally boil down to
the following: hail melts as it falls out of a storm, no two storms
are exactly alike, and hail track maps can indicate an artificial
degree of certainty and detail.
As a radar beam propagates away from the dish, it spreads out
and moves upward in the atmosphere, like a flashlight beam
tilted slightly upward and shining across a vast room. For every 10 miles from the radar dish, the radar beam becomes about
1000 feet wider. Distance therefore limits both how low in the
atmosphere the radar can “see” as well as the spatial resolution
of the radar data. Farther away = higher radar beam and lower
Yet most hail track products provide street-level detail regardless of distance from the radar site. The hail swath map will show a
tidy, smooth dividing line between hail size zones — one house in
the 1.5" hail swath and another a block away in the 0.5" hail swath.
But nature and the data aren’t nearly so tidy. While those
smooth lines and precise hail size zones look lovely on the screen,
The relationship between distance from the radar site, height of the radar
beam, and width of the radar beam (which determines spatial resolution).
Source: National Weather Service (modified)
Radar Beam And Spatial Resolution
Near the radar, the
beam is lower to the
ground and “sees”
low in the storms.
As distance increases, the
beam’s altitude also increases
and can overshoot the core
of heavier precipitation.
Dual-polarization radar (bottom) collects data about both the horizontal
and vertical characteristics of precipitation. Since different precipitation
types have characteristic shapes and movement, this two-dimensional information can be used to distinguish between different precipitation types.
Horizontal electric field wave Vertical electric field wave
Current Radars (non-polarization)
New Dual-Pol Radars (polarization)