In the October 17, 2014 issue of
Science, Brooks et al publish the claim that tornadoes, while
not increasing in frequency, are increasingly “concentrated” among fewer, more intense days. [Ref: H.E. Brooks, G.W. Carbin, P.T.Marsh. Science, 346, 349-352 (2014).] This claim is
based on analysis of EF1 or greater tornadoes in the NOAA Severe
Weather Database files [Ref: http://www.spc.noaa.gov/wcm/#data
] for the 60 years 1954 - 2013.
It is well known that increased
population and improved doppler weather radar systems has allowed
weaker and more remote tornadoes that previously would have gone
undetected to be counted. It is also well known that strong EF3+
tornadoes have been declining over this period. So, I suspected that
this report of increasingly “concentrated” tornado days, much
like the reports of increased rainfall intensity, in the absence of
increasing precipitation overall, was an exercise in data torture and
failure to recognize biased data. As you will see, I was not
disappointed.
Let's begin with the last 60 years of
tornado data, collected by year and by intensity on the enhancedFujita scale of EF0-EF5:
Figure 1: Annual count of US tornadoes
by enhanced Fujita scale classification reveals a sharp rise in the
detection of weak tornadoes after 1990.
It is immediately evident that the
annual number of recorded US tornadoes is rising, and that this
increase appears to be driven by EF0 tornadoes, after 1990. This is
not surprising, because 1990-1997 were the years that the national
NEXRAD doppler radar network was deployed. [Ref:
http://en.wikipedia.org/wiki/NEXRAD#Deployment]
To the eye, the EF1 and EF2 numbers do not appear to be biased by a
similar sharp increase. But, let's look a little closer. First, we
know that weaker tornadoes occur more frequently than stronger
tornadoes, but we assume that the ratio of weak to strong tornado
frequencies should not change very much over time. This is consistent with the theoretical
and observed power law, or 1/f law, governing the relative
frequencies of storms of different energies. [Ref: J B Elsner et al
2014 Environ. Res. Lett. 9 024018
http://iopscience.iop.org/1748-9326/9/2/024018/article
] Therefore we can
examine how much more frequently EF0, EF1, and EF2 tornadoes are observed relative to EF3+ tornadoes. While it is very difficult to quantify
exactly how much detection bias contaminates the tornado frequency
data, we can approximate it by assuming that EF3, 4 and 5 tornadoes
are unlikely to have been missed in any of the last six decades.
Figure 2: Frequency of EF0-2 tornadoes
in the US relative to EF3+ tornadoes, 1954 – 2013.
Viewed in this way, the contamination
of both EF0 and EF1 frequency data by detection bias is clear. In the
1960s and 1970s, EF1 tornadoes were recorded 4-5 times as frequently
as EF3+ tornadoes, but since 2000, they have been detected about 8
times as frequently. There is no physical basis for this to be the
case, which violates the approximate power law behavior of tornadoes [Ref: J B Elsner et al 2014 Environ. Res. Lett. 9 024018]. It is also clear that the EF2 data is not similarly
biased, maintaining a flat frequency that is about 3 times that of
the EF3+ tornadoes for the last 60 years, which is consistent with value of 2.8 taken from the observations of Elsner et al.
Brooks et al produced this figure,
showing the number of days with EF1+ tornadoes, along with the number
of days with over 30 EF1+ tornadoes:
Figure 3: (Brooks et al 2014 Fig. 4) used to claim that EF1+ tornadoes are increasingly clustered.
Using the NOAA source data and the
OpenOffice spreadsheet program, I was able to reproduce essentially
the same figure:
Figure 4: The number of days with
observed EF1+ tornadoes is trending down, but the number of days per
year with more than 30 observed EF1+ tornadoes (right side scale) has
increased.
If the method of Brooks et al is
applied in the same way to EF2+ tornadoes, while accounting for the
fact that EF2+ tornadoes are about one-third as frequent, and
adjusting the clustering threshold to >10 EF2+ tornadoes per day, figure 5
is obtained:
Figure 5: The number of days per year
with observed EF2+ tornadoes is decreasing, but the number of those
days with more than 10 observed EF2+ tornadoes (right side scale)
remains flat at about 2.7 days per year.
Finally, if we restrict ourselves to
the most destructive tornadoes, those of EF3 or greater, it is
obvious that the frequency of EF3+ tornadoes in the United States is
decreasing, and that there is no increased “clustering” of days
with more than three:
Figure 6: Declining frequency of EF3+
tornadoes 1954 – 2013, and number of days with more than three
(right side scale).
I was disappointed to see this
misleading abuse of statistics reported so uncritically in Science.
It is unfortunate that the Science reviewers were not able to
see what someone with an undergraduate understanding of statistics
should readily see. As demonstrated in the above figures, there is no reason to believe the perceived increase in days with large numbers of tornadoes claimed by Brooks et al is
anything other than another artifact of detection bias, because it
only applies to weak tornadoes that could have escaped detection in
the past, and disappears when restricted to EF2+ or EF3+ tornadoes.
This seems to be part of a trend towards credulity by reviewers, and
lack of rigor by authors of papers that support public concern about climate
change. One never sees this in the medical literature on new cancer
treatments, although 30 or 40 years ago, one did.
I understand the frustration of global
warming activists who want to be able to claim that destructive
weather phenomena, like tornadoes, are becoming worse in some way,
when the data says the opposite. Rather than following the data
wherever it leads, Brooks et al have chosen to torture the data until
it confesses. As the Scottish poet, Andrew Lang said in 1910, "He
uses statistics in the same way that a drunk uses a lamp post, for
support rather than illumination."