26 April 2016 (coincidentally, the 25th
anniversary of a major tornado outbreak in the Plains) is a classic
illustration of the challenges associated with tornado forecasting. The connection between the
synoptic-scale weather systems and the occurrence of a major tornado outbreak
("outbreak" means different things to different people – there's no formal
definition) is complicated and depends heavily on details at smaller
scales. One can get the
synoptic-scale forecast mostly right but the development of tornadic supercells can be quite sensitive to the detailed structure and evolution at scales ranging
from the size of a single storm to features on scales thousands of km across. In meteorology, getting all of those details exactly right
in the forecast is something that more or less never happens. We can forecast tornado outbreaks in
advance with varying levels of confidence, but they're never a sure thing. Sometimes the details conspire to ruin the forecast. What looks portentious, even a few
hours in advance, can unravel quickly, such that the event doesn't unfold
as forecast.
This case reflects certain
facts about how severe storm forecasts work at the Storm Prediction
Center. The "culture" of the
office contributed to the way the forecasts evolved. If the situation looks like a possible outbreak, there‘s
pressure from a variety of sources to give advance notice of upcoming tornado
outbreak potential. Once a forecast
is issued, subsequent forecasts tend to maintain a relatively high level, even
when new information (or a new forecaster) might suggest a downgrade of the forecast. There's a reason for that: users are uncomfortable with
vacillation of the threat level, and if the threat is downgraded, and then even
newer information means a return to enhanced threat, the indecision can come
across as incompetence. In other
words, it can be unwise to back off the threat level. Moreover, there's an asymmetric penalty for missed
forecasts: a false alarm for an
event that never occurs can't result in human casualties and destruction,
whereas an unforecasted event that kills people can be cause for investigations and
possible disciplinary action. This
makes overforecasting almost inevitable.
In this case, there were some indications from the forecast
models that the probability of a major tornado outbreak was decreasing as the
fateful day approached, but the outlooks continued to raise concerns that a
tornado outbreak could occur. I
don't necessarily see that as an error; it's realistic given the current state of our science. An interesting facet to the case is that in the morning outlook on the day of the event, the forecast tornado probability was still
only 10%. The outlook was not
upgraded to "High Risk". I believe
this is a plausibly accurate reflection of forecaster uncertainty. However, the media were continuing the
drumbeat of concern for a major event - the issue of the media is not going to be dealt with here.
Technically, a severe weather outlook is not focused only on tornadoes,
and the nontornadic aspects of the forecast worked out pretty well. Therefore, my comments here are restricted only
to the forecast of a significant tornado outbreak with multiple, long-track,
strong to violent tornadoes (EF2-EF5)
In my view, and this is purely a personal opinion, the
biggest "mistake" from the SPC was issuing a PDS ("Particularly dangerous situation")
watch in the early afternoon. This
was not warranted by the information of which I was aware (I was out storm
chasing). Whatever explanation might
be offered in justification of this decision is in direct contradiction to the observed events. I'm sure if offered a "do-over", the
choice would be not to make it a PDS watch.
Make no bones about it. Tornado forecasting isn't an easy job and perfection is out
of the question. I mean no disrespect to any forecaster involved in this event but we have to accept that the outcome is generating some backlash that's quite understandable. Uncertainty is
inevitable and probability is the language of uncertainty; by whatever verbiage we use to express it, we meteorologists need to communicate our uncertainty to our users such they accept the
real capabilities of meteorological science as applied to the task of
forecasting tornadoes. By all
means, we need to find out how to communicate with our users so that they
understand our message, and know how to respond in the appropriate way to our
weather forecasts. We simply
can't provide a 100% level of confidence in the forecast information we
provide. Our users must learn that
they bear some responsibility for their own self-interests. Weather hazards can present people with life-and-death
situations, so in their own best interests, they need to pay attention and learn how to make the best use of
what the science allows us to provide.
