In recent years, hailstorms causing billions of dollars’ worth of damage
have occurred over Europe, North America and Australia. It is therefore important
to continue to improve the lead time of warnings and to include information in
warnings that will encourage people to take preventative action. Reporting hail
characteristics in real time is a critical step towards achieving this because this
information a) is invaluable in helping forecasters issue the best possible
forecast, and b) assists researchers by providing them with reliable data to
develop even better forecast tools.
Reporting the size and amount of hail is important because the damage
potential (or kinetic energy) is primarily a function of both the size and the amount of hail. In copious
amounts, even pea-sized or grape-sized hail can be devastating for crops and
clog drains in urban areas. Reporting
and measuring hail is, however, a tricky business: hailstones melt quickly, and
are slippery and cold. This is where a small blue bird could help us report
hail in a way that makes the information useful to forecasters and researchers.
More on that later.
Despite advances in the skill of weather forecasts in recent years
(today’s four-day forecast is a good as the one-day forecast 30 years ago),
forecasting the occurrence and size of hail remains a challenge. Major limiting
factors are that not all thunderstorms produce hail and that when they do, the hail
swaths (narrow bands of hail deposited by hailstorms) often cover a small area.
This makes it difficult to identify where hail actually fell and what the
maximum hail size was. Because conventional weather radar does not directly
identify the presence or size of hail, meteorologists are reliant on hail
reports from the public.
Public hail reports have issues
though. Consider a day when nasty storms are visible on radar but no reports of
hail are received. Was this because there was no hail, or did the storm affect
a sparsely populated area, or did no one report the hail for some reason? Even
if a hailstorm affects a densely populated area when it is producing the
largest hail, there is no guarantee that people reporting the hail will be able
to a) identify the largest hail, or b) make accurate measurements of the hail. Someone
may, for example, estimate the size of hail on their lawn by looking out their
kitchen window, or measure the hail after it has been on the ground for a while,
or, after showing it to others.
A recent study in the U.S. found that the mean hail diameter of reports
in the U.S. Storm Database was over 1 cm smaller (about 30%) than that measured
by teams of students who measured hail along several traverses across hail
swaths. This negative bias represents a significant barrier for developing
reliable forecast tools, especially empirically derived ones. The lack of
skillful guidance undermines the forecasters’ confidence, makes them wary of
issuing warnings and may prevent them from including important information in
warnings about hail.
The best tool for objectively measuring hail remains the hail pad. A
hail pad is typically a 30-cm square pad of painted styrofoam that records the
indentations made by hailstones. These data are then used to estimate the size
and number of hailstones and the kinetic energy. Unfortunately, hail pads are
of no use to forecasters because they do not provide real-time information. Additionally,
maintaining a sufficiently dense network of hail pads (i.e., spaced about 3 km
apart) is time-consuming and labour-intensive. Some might argue, in jest, that
cars are plentiful and make convenient hail pads, but using a car as a hail pad
would be exactly what we are hoping to avoid.
This all seems rather hopeless doesn’t it? Fortunately, this is where a small
blue bird enters the equation. I am referring to Twitter! In recent years, Twitter
has exploded onto the severe weather scene, with eager citizens tweeting about
all sorts of severe weather phenomena, real or perceived.
Notifying forecasters of hail has never been easier or quicker, and
“quicker” is critical for increasing the lead time of warnings. Also, information
from the hail swath (e.g., the maximum hail diameter, typical hail size, depth
of hail and damage) allows forecasters to include important information in the
warnings. People are more likely to be proactive in heeding a warning and
taking preventative action if they hear that a storm producing baseball-sized
hail is on its way.
There is a downside to legions of people tweeting reports of hail. First
and foremost, they will likely not be trained storm-spotters. There is a danger
of there being a deluge of well-intentioned but unhelpful tweets that
researchers and, more importantly, forecasters have to sift through. Tweeting “Huge hailstorm west of Moose Jaw!” is
not particularly helpful. Why? There could be more than one storm in the
vicinity. It is also unclear if “huge” refers to hail size or storm size. Also,
no details on the hail size or time of the event (the time of the tweet does
not always correspond to the time the hail was falling) are provided. That is
why I carefully worded the title of this post “How a small blue bird could help protect us from hail”. Make
no mistake, the potential for Twitter to improve warnings and to modernize hail
research is real, but like any tool, we have to use it properly in order to
maximize its usefulness.
Part of my job at Environment and Climate Change Canada is to develop (and
test) hail forecast products, including products from Canada’s radar network. A
critical component of this research is to verify the hail products against
observations. During the summer of 2014, I collected hundreds of tweets with
embedded photos reporting hail over the Canadian prairie provinces. After
carefully examination, however, I could use only about a quarter of them for
research.
The most common problem was that the photos did not include an object
that could be used to estimate the size of the hail. A photo of someone holding
a large stone in their hand looks neat and can serve as confirmation that hail
fell, but that is pretty much where its use for research ends. Estimating the
size of hail by sight alone is unreliable because people tend to be biased
towards reporting certain size classes of hail.
A colleague and I dealt with this bias when using the U.S. Storm
Database for a journal paper—specifically, we found that there were a significantly
disproportionate number of reports of golf ball-sized hail compared to the
adjoining size categories. Apparently people are predisposed to “seeing” golf ball-sized
hail; perhaps this phenomenon has something to do with the popularity of golf.
What we need is a standardized tool that allows people to objectively
and accurately report hail, while not introducing disincentives or delays. If
people had access to a universal application (app), this would go a long way in
avoiding some of the pitfalls currently associated with tweeting hail reports.
All the required features for such an app have been developed—they just need to
be combined into a single app by someone with the required skills.
Rather than estimating the diameter, the most accurate way to determine
the size and kinetic energy of a hailstone is to measure its mass. Given that
hail (at least hard hail that we are interested in) has a fairly consistent
density, if we know the mass then we can get a really good estimate of its
equivalent diameter, without having to worry about which of the hailstone’s
axes to measure and all that fiddly stuff. So, ideally, the app would convert
the smart phone into a scale that can be used to measure the mass of hailstones.
Yes, there really is an app for that, more than one in fact!
Additionally, the app could automatically include a scale on the photo
or have a feature that changes your screen into a ruler to permit the user to accurately
measure the hailstone’s dimensions. The app would geo tag the phone’s current
location. There would be no need to manually enter the latitude and longitude,
and there is no danger of typos. The app could also include a time stamp of
when the app was activated (this could be overridden to reflect the time the
hail started). Lastly, the user could have the option of entering more details
about the event. Hit send and voilĂ , the report with an
image and all the critical information is tweeted to Environment and Climate
Change Canada. Such an easy to use, nifty tool would improve the usefulness of
hail reports and increase the number of citizen reports.
A final observation—I am often surprised during the summer when someone
casually notes that it is hailing and doesn’t think about reporting it. First
off, “Hello, it is hailing! Where is my
scale?” Seriously though, I asked someone why this was. They said that
there had been watches for severe thunderstorms, so of course the
meteorologists were aware of the hail. I’m flattered by their confidence in us,
but no! Another reason why people don’t think of reporting hail is that it’s “only
small”. That may be, but knowing where there is small hail is still very useful
for developing and verifying forecast tools, not to mention that sufficient
amounts of small hail can also be very damaging.
So, only if it is safe, please do send along your hail information! Your
participation would be greatly appreciated.
Acknowledgements: I’m very grateful to
Gabrielle Gascon (ECCC), Neil Taylor (ECCC) and Nyree Sharp for their valuable
feedback on earlier versions of this post.
Julian Brimelow,
PhD., Physical Sciences Specialist, Applied Environmental Predictions Science
Meteorological Service of Canada (MSC), Prairie and Northern Region,
Environment & Climate Change Canada (ECCC).
Email: julian.brimelow@canada.ca
This blog post has been written by Julian Brimelow, Environment Canada, who will be presenting on February 1, 2016 at CatIQ's Canadian Catastrophe Conference during the "Dealing with Hail Risk" session at 3:00 pm.