Severe Weather Warnings - An Overview With a Look To the Future
Posted: 20 February
2013 Updated: whenever -
This is in response to some recent questions I've been asked, so I'm
providing a summary here. As usual, this is purely my own opinion
and represents nothing that
been formally reviewed/vetted by anyone. Comments are welcome
if you're willing to have them posted here, along with my
responses. Send me an email to cdoswell
& earthlink.net (click on the email link or cut and paste,
replacing _&_ with @) with your comment(s).
The first order of business with respect to severe weather warnings is
to recognize that with all its problems and challenges, the existing
system for severe weather warnings (of all
sorts, including hurricanes, tornadoes, winter weather, flash floods,
etc.) is responsible for having saved tens
of thousands of lives (by my estimate) since the modern process began
in the spring of
1952, with the inception of the Severe Local Storms Unit (SELS) - the
forerunner of today's Storm Prediction Center (SPC) in Norman,
OK. I'm going to focus on severe convective storm hazards herein
- primarily tornadoes. I've said a lot of the topics mentioned
here in other essays, blogs, etc. - this simply puts all of the things
I've said previously in the context of an overview. Once the
Weather Bureau (forerunner of the National Weather Service - NWS)
understood that the mention of the word "tornado"
in a forecast would not initiate a dangerous panic among the populace,
the way was clear to begin to apply the science of meteorology and new
observing technology (mainly, weather radar) to the task of providing
life-saving information to people in threatened areas, as well as
deploying storm spotters to supplement the radar.
Thus, before we start tinkering with the warning system, we must keep
in mind a simple principle often applied in the health care
profession: First, do no harm!
If we begin to mess around with the warning system in the absence of
clear evidence that our changes will cause no harm, we run the risk of
damaging the credibiity of our warnings beyond repair.
The warning system didn't evolve in any
orderly, systematic fashion. Rather, a series of top-down
issued, starting in 1952, to commence tornado forecasting, so forecasters had to put together the elements of the system
in response to those mandates in the absence of any guidance and supporting information on which
to base their ad hoc decisions. No one has ever done any systematic
analysis of how best to do this critically important task. It
begs the question: If you could wipe it all away and re-design it
from the ground up, what would the warning system look like? It's
highly unlikely anyone will ever do the work to re-create a warning
system starting from nothing - it will always have to fit within
certain constraints created by where we are now. But suppose we
had that privilege - how might we go about a systematic program to
develop the most effective warning system possible.
Step 1 - What is a warning system trying to accomplish?
Keep in mind that a warning is a forecast - generally, a short-range
forecast (on the order of an hour or less) for convective storm
activity. Because it's a forecast, it's inherently
storm processes can change substantially in
five min or less. A tornado can form from nothing in that short
interval, so forecasting convective storms is a challenging task.
I believe the
goal of a severe weather warning is to provide effective severe weather information to
forecast users of all sorts, in order to help them make appropriate
decisions when confronted with a potential threat of severe weather.
Broadly speaking, it's my impression that most people have quite limited
understanding of the quantitative risks they confront. People
make choices based on their perception
of risks, not on the actual risk level. We kill 40,000 American
people per year in traffic, but no one is particularly fearful of
driving, per se. More than 10,000 people die in the US from food
poisoning, but most people have no fear of eating. In the worst
years, fewer than 1,000 people are killed by tornadoes annually in the
USA - in recent decades, typically fewer than 100. Although the tornado fatality
risk is small, someone dies in a tornado every year. It's
possible to prepare for the tornado threat without giving up
much. People always have to make choices - no decision is always
still a decision, of sorts!
when most homes (even in Oklahoma) are built without a tornado-resistant shelter, this
suggests that the perception of tornado risk is low enough to choose
not to spend that money on a
shelter, preferring instead that that investment should go toward a
or fancy kitchen cabinets, or a swimming pool. Given that the
of risk even in Oklahoma is that low, it seems unlikely that a few
minor wording changes in
our warnings are going to make them dramatically more effective!
Imagine the perception of risk in New England, or the intermountain
west and what that might imply about public preparations for severe
weather. The choice of whether or not to do something to prepare
tornadoes depends on that very perception of the risk. Obviously,
we meteorologists believe we have the public's best interests at heart
with our warning efforts,
but if "the public" (far from a monolithic block of people with
identical risk perceptions and level of commitment to being prepared to
deal with severe storms) has a dramtically different set of priorities
from those of meteorologists, some careful thinking and well-conceived research are needed to do
something about that perception gap.
I believe strongly that we need the help many social science-related
disciplines: communication specialists, sociologists,
psychologists, economists, etc. We need hard information about
public attitudes and perspectives. If we make changes to the
warning system without compelling evidence based on solid data that we're changing it in a
way that really will allow our warnings to be more effective, we risk
doing harm to the existing system.
Step 2 - What is good and bad about the existing system?
Any attempt to change the warning system necessarily should begin with an assessment of public
perceptions regarding our existing
warning system. What are the most
effective aspects of the present warning system? What are the
problems with that system? There may be regional variations in
public perception, of course. And those perceptions change all
the time, so this isn't a task we can do once and it's done
forever. A commitment to use the social sciences to guide how our
warning system should be constructed involves a substantial, long-term
commitment of resources. I don't believe many in the NWS
magnitude of the commitment to the involvement of the social sciences
they appear to be willing to make.
From where I sit, an evaluation of the existing warning system is a massive task that remains more or less undone in any scientifically substantive way.
No one knows very much about public perceptions because the work has only begun! What we typically have in abundance
are comments from bureaucrats and meteorologists saying words along the
lines of, "What the public wants is ...!" These words actually
mean, "What I think
the public wants is ...!" There's precious little evidence
to back up most such statements. We have the unvalidated opinion
someone who knows essentially nothing about what "the public" actually
wants - it's more based on that person's anecdotal experience than
studies. In other words, such comments have little substantive
value! I've tried (and failed) to get a proposal funded to
investigate these issues, with the collaboration of a social
scientist. Multidisciplinary research is still not supported very
strongly - it's difficult to find potential collaborators outside of
your own discipline and put together a plan for a project of mutual
Let's assume, nevertheless, the research has been done and we can say with some confidence that
we know just what is working and not working with the existing
system. Now we're ready to consider ...
Step 3 - How do we go about making the warning system be more effective at doing what we want it to?
Producing accurate severe weather warning information is not that easy,
as I've suggested, but let's assume for the moment that the information we hope to provide
already exists at some moment in a weather office. In order for that
information to be effective, the following conditions must be met:
However we might define perfection, even a perfect forecast/warning
will be of no value if any one of these conditions isn't met. There
are many pitfalls along this path, even if the severe weather forecasts
do their job perfectly. When users don't hear the warning, all the
rest is irrelevant - the warning is useless to them. If they hear it
but don't understand what it's saying - the warning is useless to
them. If they hear it, understand it, but don't know how to use that
information - the warning is useless to them. If they hear it,
understand it, know what to do with it, but don't believe the
information (for instance, because they perceive such warnings are
predominantly false alarms) - the warning is useless to them. If they hear
it, understand it, know what to do with it, believe it, but there's
nothing they can do about that information (for instance, because they
have no effective place to take shelter) - the warning is useless to
them. If all the conditions are met except they choose not to respond
(for whatever reason) - the warning is useless to them.
- The users must receive the information
- The users must understand the information
- The users must know what to do with the information
- The users must believe the information
- The users must be able to take effective action
- The users must respond by taking that action when the potential threat materializes
Make no bones about it, the meteorological challenge to producing a
severe weather warning is not a trivial thing. But an even bigger
problem is associated with what happens when the forecast is disseminated. The effectiveness of that warning, once
it has been issued, is mostly out of our hands. We meteorologists
aren't trained in communication, sociology, psychology, etc. Since the
goal of our warning system it to provide information, that information requires
Based on the preceding, it seems to me we have a strong obligation to be much
more effective in our public outreach efforts - to educate the public
about all these aspects of the risks they confront from severe weather beforethey're
forced to deal with a severe weather event. We can't make up for
that ignorance in the 30 minutes (or less!) that might separate the
issuance of a warning from its impact on a community. To a large
extent, our ability to produce effective warnings depends heavily on
what we've done beforehand
- prior to the time when dangerous convective storms threaten our users. We have to
make certain everyone is on board with what we can provide them and how
to prepare/respond. No amount of tinkering with the wording of
warnings can fill that gap!
- Mechanisms of dissemination to allow users to receive the warning
- Public education to help users understand what we are trying to say in our warnings
- Public education to help users recognize the appropriate things to do
- Public education to understand the limitations of our ability to forecast severe weather
- Public education to help users prepare for severe weather by giving themselves via options
- Public education to help users use the information to take action
We need broad-based surveys, done by people who actually know something
about how to construct and carry out a proper survey, working with
meteorologists who can explain what we do and, particularly, the limitations
on what we can provide. Surveys need to be done to assess the
potential impact of proposed changes before we even consider
implemented them in public forecasts. We need to be confident
that any proposed changes meet the preceding conditions on the effectiveness of the warnings.
Once we have some idea of what changes seem to make sense to implement,
then we should do experiments based on the notions that have survived this rigorous
pre-testing. Depending on the outcome of those experiments, we
should do more surveys to see if they've indeed been successful
If, in the process, we discover a problem with a a proposed change,
then we need to revise it or eliminate it. Only those changes
that prove to be effective should be implemented operationally.
And the need for continuing
surveys and re-evaluation of NWS warning products should be evident. The landscape in which warning products are
issued is constantly changing. It's affected by new technology,
new science, new economic realities, social change, and so on. As noted, there
will be a sustantial investment required if there's to be an enduring
meaningful collaboration between meteorology and social science.
Step 4 - How do we best incorporate uncertainty into severe weather warnings?To
repeat, warnings are forecasts. All forecasts
are uncertain. Therefore, all warnings are uncertain. This
can't be avoided and should not be swept under the rug or
ignored. Adding uncertaintly information to warnings is a
dramatic change from the existing system. Forecast uncertainty
drive forecasters directly to the classic dilemma of an asymmetric
penalty: no one dies from an event that didn't happen! This
asymmetry strongly encourages overforecasting using a dichotomous
(yes/no - binary) forecast product. Thus, the severe weather
warnings all show a heavy overforecasting bias: a preponderance
of false alarms. With probablistic
forecasting, it should be possible to achieve unbiased warnings.
Furthermore, to fail to express uncertainty is to withhold information
users. We meteorologists are acutely aware of our
uncetainty and, when properly calibrated, are quite good at estimating
it quantitatively in terms of probability. Keeping this to
ourselves is doing our users a huge
The challenge we all confront is to be able to express
that uncetainty in a way that is understandable, believable, and
effective in helping people make decisions about how they should
respond. Although it's well-known that probability is the
proper language of uncertainty, there may be ways to express it that
don't use the dreaded "p-word". Or we might produce a forecast
product that caters to all potential users of that information, not
just the lowest common denominator. I've discussed this topic at
some length elsewhere,
but I admit freely I have no clue how best to accomplish this goal in
the most effective way for severe weather warnings.
The simple reality is that severe convective storm warnings should be able to express variable threat levels.
Not all situations constitute an equal threat. In order for a
specific situation to generate a warning, there should be some
systematic way to decide some minimum threat probability that would
trigger a warning. Once that threshold is achieved, then the
warning should be able to convey the warning forecaster's confidence
that a meteorological threat exists in a specific region for a specific
time interval. I make no claim to anything more than some vague
ideas about how best to achieve this goal from the standpoint of all
the conditions enumerated above (in Step 3). My education and
training is in meteorology, not risk communication. But as a
meteorologist, the need to be able to express uncertainty is not negotiable.
It's necessary and inevitable if we wish to convey accurately and
comprehensively what we think about the weather! See the links
above for some discussion.
There have been a handful of notable successes using the phrasing
"tornado emergency" to indicate a potential high-impact event.
Less publicized are the many times "tornado emergency" has been used
without a high-impact event actually occurring. A few notable
successes constitute only anecdotal evidence that forecasters can
discriminate potential high-impact events from lesser impact
situations. Any experiment
done without a thorough evaluation of our aggregate ability to
forecast them is premature, at best, and certainly ill-advised.
Ideas about how graded threat levels might be done should be tested in
surveys to gauge public reaction to them. Depending on the survey
results, different ways to express uncertainty might need to be
tried. Those potential changes would need to be tested ... and, of course,
the testing, evaluation, and revision should go on indefinitely! It's a virtual certainty
there's no single answer that will fit all possible future situations now or in the future.
I've not really spent much time on how best to do the
meteorology associated with severe storm warnings. With all of
its imperfections, the existing warning system works pretty well,
especially for long-track, violent tornadoes associated with
supercells. Since these account for a disproportionate share of
the annual tornado fatlalites, this aspect of the system seems to be working
pretty well, for the most part. We certainly have work to do to improve our warnings
for lesser events but this is not very pressing, given the realtively
low fatality counts associated with this relatively poorly forecast
class of tornadoes.
As I see it, the most important meteorological issue associated with
severe storm warnings is to quantify the uncertainty. Education
and training can help with some of this. Proper calibration of
severe weather threat probabilities is a challenge precisely because
severe convective storms are rare events. Calibration takes
experience and it takes years of experience to do it really well.
I won't dwell on training and education issues, but they constitute a
problem within the NWS, which is an organization not committed to meaningful training
and which assumes zero responsibility for education. Under these
circumstances, forecaster skill at severe weather warning will continue to span a wide range,
with a few superstars, a few superduds that need to be flushed, and a
vast middle ground of variable forecasting ability. Product
consistency is a known issue within the NWS, for convective storm
events and others, as well.
The meteorological issues aren't trivial, but I don't see them as the
major barrier to creating more effective warnings. Unfortunately,
when you convene meteorologists to address the issue of forecast value,
they tend always to drift toward what they know:
meteorology. We shouldn't shut out the social sciences, but
rather get them involved immediately.