1148 V
OLUME
13WEATHER AND FORECASTING
q 1998 American Meteorological Society
A Baseline Climatology of Sounding-Derived Supercell and
Tornado Forecast Parameters
E
RIK
N. R
ASMUSSEN AND
D
AVID
O. B
LANCHARD
Cooperative Institute for Mesoscale Meteorological Studies, National Severe Storms Laboratory and
University of Oklahoma, Norman, Oklahoma
(Manuscript received 21 November 1997, in final form 30 July 1998)
ABSTRACT
All of the 0000 UTC soundings from the United States made during the year 1992 that have nonzero convective
available potential energy (CAPE) are examined. Soundings are classified as being associated with nonsupercell
thunderstorms, supercells without significant tornadoes, and supercells with significant tornadoes. This classi-
fication is made by attempting to pair, based on the low-level sounding winds, an upstream sounding with each
occurrence of a significant tornado, large hail, and/or 10 or more cloud-to-ground lightning flashes. Severe
weather wind parameters (mean shear, 0–6-km shear, storm-relative helicity, and storm-relative anvil-level flow)
and CAPE parameters (total CAPE and CAPE in the lowest 3000 m with buoyancy) are shown to discriminate
weakly between the environments of the three classified types of storms. Combined parameters (energy–helicity
index and vorticity generation parameter) discriminate strongly between the environments. The height of the
lifting condensation level also appears to be generally lower for supercells with significant tornadoes than those
without. The causes for the very large false alarm rates in the tornadic/nontornadic supercell forecast, even with
the best discriminators, are discussed.
1. Introduction
This paper establishes a baseline climatology of pa-
rameters commonly used in supercell thunderstorm fore-
casting and research. The climatology is derived from
over 6000 soundings from 0000 UTC during 1992, all
of which had nonzero convective available potential en-
ergy (CAPE) (Moncrieff and Miller 1976).
It is believed that a baseline climatology is needed
to support certain aspects of operational thunderstorm
forecasting. For example, values of CAPE are often cit-
ed in forecasts as being ‘‘marginal,’’ ‘‘large,’’ ‘‘ex-
treme,’’ etc. However, no known baseline climatology
exists that is adequate to support these quantifications
for most of the commonly used parameters [except the
climatology of Doswell and Rasmussen (1994) for
CAPE]; rather, they generally are based on the subjec-
tive experience and ‘‘mental calibration’’ of the fore-
casters. Similar problems exist with the operational use
of storm-relative helicity (SRH; Davies-Jones et al.
1990): what are climatologically large or extreme values
of SRH? At what values should forecasters become con-
cerned about mesocyclone potential?
There are a number of motivations for this study in
the area of convection research. Because this is a 1-yr
Corresponding author address: Dr. Erik N. Rasmussen, NSSL,
3450 Mitchell Lane, Building 3, Room 2034, Boulder, CO 80301.
E-mail: rasmussen@nssl.noaa.gov
climatology, it contains no information on the interan-
nual variability of convection-related sounding-derived
parameters. Thus, this study is suitable as a baseline for
efforts to assess the interannual variability.
Another motivation is similar to the forecasting con-
cerns mentioned above. Certain parameters have been
established through theoretical or modeling work as be-
ing important in supercell structure, organization, etc.
[e.g., the bulk Richardson number (Weisman and Klemp
1982), CAPE, SRH]. These parameters are then used in
case studies and forecasting without thorough clima-
tological verification. It is desirable to begin to assess
the climatological occurrence of physically important
parameters before they are proposed for use in opera-
tional meteorology. Conversely, it would seem to be
desirable for those performing numerical modeling and
theoretical studies to have data that indicate whether or
not they are exploring physically relevant parts of a
given parameter space.
It appears that there are no other sounding climatol-
ogies of this magnitude related to the environments of
convective storms. Other investigations have focused
more narrowly on various types of convection. For ex-
ample, Maddox (1976) analyzed 159 proximity sound-
ings to assess the effects of environmental winds on
tornado production. In a similar study, Darkow and
Fowler (1971) compared 53 tornado proximity sound-
ings with ‘‘check’’ soundings farther away in the en-
vironment and found that winds were most noticeably
D
ECEMBER
1998 1149RASMUSSEN AND BLANCHARD
different in the 3–10-km layer. Much more exhaustive
analyses of both wind and thermodynamic conditions
near tornadic storms, and 6–12 h prior to their occur-
rence, can be found in Taylor and Darkow (1982) and
Kerr and Darkow (1996).
Based on some of the foregoing studies, more recent
work has tended to focus on SRH and other measures
of lower-tropospheric shear, in combination with mea-
sures of potential buoyancy. In a limited sample, Ras-
mussen and Wilhelmson (1983) examined the combi-
nation of mean shear (related to hodograph length) and
CAPE in the environments of tornadic, nontornadic se-
vere, and nonsevere storms. As SRH increased in pop-
ularity as a forecast tool, climatological studies of
sounding-derived parameters began to focus on com-
binations of CAPE and SRH (e.g., Davies 1993). Ex-
cellent summaries of the most recent climatological
analyses of buoyancy and shear in the environments of
tornadic storms can be found in Johns et al. (1993) and
Davies and Johns (1993). An examination of helicity as
a forecast tool is given by Davies-Jones et al. (1990),
and Davies-Jones (1993) analyzed the mesoscale vari-
ation of helicity during tornado outbreaks using sound-
ings from special sounding networks.
Sounding climatologies have also been used to assess
the environments related to particular types of thun-
derstorms. Bluestein and Parks (1983) utilized sound-
ings to compare the environments of low-precipitation
storms and classic supercells, and Rasmussen and Straka
(1998) investigated these and high-precipitation super-
cells using a sounding climatology. Bluestein and Parker
(1993) have used soundings to investigate the modes of
early storm organization near the dryline. A climato-
logical sounding analysis of the environments associ-
ated with severe Oklahoma squall lines is reported in
Bluestein and Jain (1985) and nonsevere squall lines in
Bluestein et al. (1987).
In section 2, the methodology used in this climato-
logical analysis is described, along with its limitations.
Various parameter spaces are then investigated: shear
(section 3), CAPE (section 4), combinations of CAPE
and shear (section 5), and low-level thermodynamics
(section 6). In section 7, the parameter space of Brooks
et al. (1994a) is investigated. The forecast utility of the
various parameters is compared in an objective manner
in section 8. The results of this investigation are sum-
marized in terms of tornadogenesis and supercell-fa-
voring environments, and tornadogenesis failure modes,
in section 9.
2. Methods
a. Sounding database
The soundings evaluated here are contained in Ra-
winsonde Data for North America, 1946–1992 (Forecast
Systems Laboratory and National Climatic Data Center
1993) and were all made at 0000 UTC nominal sounding
time from the U.S. sites only. The year 1992 was chosen
for this climatology in a completely arbitrary manner.
The sounding data were subjected to two quality control
checks only (beyond those performed in producing the
CD-ROM dataset): hydrostatic checks and checks for
missing wind data. Many soundings from 1992 have
been examined using an interactive skew T–logp pro-
gram, and no serious data problems have been encoun-
tered. Every sounding was evaluated for CAPE using
the algorithm described below. If CAPE . 0, the sound-
ing was further evaluated for a number of other param-
eters; 6793 soundings had nonzero CAPE and were uti-
lized in this study.
b. Proximity–inflow method
An objective method has been devised to associate
each meteorological event with a sounding. A meteo-
rological event is defined as a cloud-to-ground lightning
flash or a severe weather report. The method has been
designed to find a reasonably nearby sounding that is
in the ‘‘inflow sector’’ of the event and to reduce the
likelihood that the sounding has been contaminated by
convection. For example, the lower troposphere may
have been stabilized by outflow, the upper troposphere
warmed and moistened by anvils, and the wind structure
altered radically. For a more thorough examination of
the issues related to selecting ‘‘proximity soundings’’
see Brooks et al. (1994a). To accomplish the goal of
establishing a sounding as an inflow sector sounding,
the boundary layer mean wind vector was computed
using the average of the u and
y
wind components in
the lowest 500 m. The sounding was assumed to be in
the inflow sector of any meteorological event if it was
within 400 km and the event fell within 6758 of the
boundary layer mean wind vector. This is illustrated in
Fig. 1, which shows soundings B and C meeting the
inflow and range criteria.
If more than one sounding satisfied the inflow and
range criteria, for simplicity the sounding with the larg-
est CAPE was chosen as being ‘‘representative’’ of the
event. This was done to alleviate two major problems:
with some events, soundings taken in the warm sector,
behind the dryline, and north of the warm front in a
developing cyclone could all be considered as ‘‘inflow’’
soundings. Further, soundings meeting the inflow and
range criteria but contaminated by convection likely
have reduced CAPE and thus were more likely to be
eliminated. The CAPE criterion sets this study apart
from other similar studies and has important implica-
tions for the interpretation of the results herein. In any
given case, it is quite possible that a sounding with
nonzero CAPE that is in close proximity to the event
is excluded in favor of a more distant sounding with
greater CAPE. From a forecasting perspective, it means
that the results herein should be applied in terms of the
largest CAPE in a fairly large ‘‘inflow region’’ rather
than the CAPE in the immediate storm inflow. Further,
1150 V
OLUME
13WEATHER AND FORECASTING
F
IG
. 1. Schematic illustrating the rules for choosing a representative
sounding for an event. Sounding sites are at A, B, C, and the weather
event is at the square marked ‘‘Event.’’ The boundary layer winds
at the sounding sites are denoted using conventional plotting symbols.
The ‘‘inclusion areas’’ are the 1508 sections with 400-km radius cen-
tered on the boundary layer wind vector. The event meets the inclu-
sion criteria for sites B and C, but not A. When more than one
sounding meets the criteria, the one with the largest CAPE becomes
the representative sounding.
T
ABLE
1. Criteria for sounding classification and numbers of
soundings.
Cate-
gory
name
No. of
sound-
ings Criteria for association
TOR 51 One or more tornadoes having damage rated as
F2 or greater
SUP 119 One or more reports of hail . 5.07 cm (2 in.)
diameter, but no tornadoes having damage .
F1 (F0, F1 allowed)
ORD 2767 10 or more CGs, but no reports of hail . 5.07
cm diameter, tornadoes of any F rating, nor
wind damage allowed
it means that the results herein may not be directly com-
pared to results from similar studies; this point will be
reiterated in later sections where appropriate.
Admittedly, the process described above may not be
the ideal means of selecting a sounding representative
of a meteorological event. A more appropriate method
might be to choose only those routine or special sound-
ings that truly were proximate to a given event [e.g.,
the method of Brooks et al. (1994a)]. Alternatively, one
could perform objective analysis or utilize gridded nu-
merical model data to determine the conditions proxi-
mate to an event. However, the chosen approach re-
moves all questions about the subjective decisions made
in including or excluding various soundings. The
‘‘rules’’ used to associate a sounding with each event
are summarized below.
Step 1: Assemble list of all soundings that are within
400 km of the event.
Step 2: Assemble the subset of soundings that contain
the event in a 1508 sector centered on the
boundary layer mean wind vector.
Step 3: Choose the sounding with the maximum
CAPE.
After every possible event had a sounding associated
with it, the events were tabulated on a sounding-by-
sounding basis, giving counts of events associated with
each sounding.
c. Lightning database
Since the primary emphasis of this climatology is on
convection, a method was needed to determine which
soundings actually were associated with convection and
which were not. This is a difficult problem with such a
large dataset. The technique chosen was to determine
if cloud-to-ground (hereafter CG) lightning flashes were
associated with a given sounding. A minimum of 10
flashes was required before the sounding was assumed
to be associated with convection.
The CG flash data are from the National Lightning
Data Network operated by Geomet Data Services, Inc.
All CGs that occurred between 2100 and 0600 UTC
(i.e., 23to16 h from nominal sounding time) were
treated as individual meteorological events, and an at-
tempt was made to find a representative sounding for
each one using the rules listed in section 2b. Out of a
total of 5 711 187 flashes during the 9-h daily window
in all of 1992, 3 748 833 individual CGs (;⅔) were
associated with soundings. Based on the rules listed in
section 2b, it is apparent that many CGs occurred too
far from nonzero CAPE soundings (e.g., far offshore),
there were no soundings in the inflow sector of the CG,
and, in some cases, there were no nonzero CAPE sound-
ings. No attempt was made to quantify the reasons for
CGs not being matched with soundings. Out of 6793
soundings with nonzero CAPE, 2767 were associated
with 10 or more CG flashes (see Table 1).
d. Severe weather reports and classification
The goal of this work is to utilize available data,
suitable for a large climatology, to ascertain the asso-
ciation of sounding-derived parameters with severe
weather related to supercells. Severe weather reports
were taken from Severe Local Storms Unit log for 1992
and were filtered as follows. Tornado reports were fil-
tered into significant (F2 or greater) versus other tor-
nadoes because of the well-known reporting vagaries
(e.g., Doswell and Burgess 1988). Only hail larger than
or equal to 5.1 cm (2.0 in.) was considered under the
assumption that it is associated with supercells when it
occurs. Wind reports were not considered in this study
because of the difficulty in determining if the severe
wind was due to a supercell or not. Only events oc-
curring within 23to16 h of 0000 UTC were consid-
D
ECEMBER
1998 1151RASMUSSEN AND BLANCHARD
F
IG
. 2. Illustration of storm motion computation. Hodograph is
curve with heights labeled in kilometers. Dots are at the 0–500 m
AGL mean and 4 km AGL. Gray vector S is the BL–4-km shear
vector; black vector is 0.6 S. Predicted storm motion vector M is 8.6
ms
21
orthogonal to the right of 0.6 S.
ered. These events were matched with soundings using
the proximity rules described above.
Three categories of soundings were defined as sum-
marized in Table 1. The categories were designed with
the intent to identify soundings associated with tornadic
supercells, nontornadic supercells, and nonsupercell
storms. Because there is no climatological record of the
supercell character of storms, this must be inferred
through the available reported phenomena. This requires
certain caveats regarding the interpretations and limi-
tations of these categories as described in the following.
TOR: This category was designed to identify sound-
ings associated with tornadic supercells. While some of
the reports of tornadoes of F2 and greater damage in-
tensity in 1992 possibly were associated with nonsu-
percell tornadoes, nothing in the database of severe
weather reports allows nonsupercell to be distinguished
from supercell tornadoes. The justification for the ex-
clusion of F0 and F1 tornadoes in TOR was to generally
exclude nonsupercell tornadoes, as well as to filter some
of the myriad of erroneous tornado reports (Doswell
and Burgess 1988) that generally are given the F0 or
F1 rating. The label TOR is used here mainly for con-
venience; the strict interpretation of the category is
soundings associated with tornadoes rated F2 or great-
er.
SUP: For comparison to the TOR category, infor-
mation from the climatological database was sought to
identify supercells without significant tornadoes. The
only information readily available is reports of large
hail in the absence of significant tornadoes. Further re-
search is required to quantify the actual association of
large hail with supercells versus nonsupercells, although
Cotton and Anthes (1989) state that supercell storms
‘‘generally produce the largest hailstones.’’ It may be
determined that the occurrence of large hail is a poor
indicator of supercell structure invalidating the present
supercell classification. Further, it is likely that many,
if not a majority, of supercells do not produce hail of
the required size and were excluded. The label SUP is
used for convenience; the strict interpretation of the cat-
egory is soundings associated with storms that produce
large hail but not significant tornadoes, in itself an im-
portant category of storms in operational meteorology
regardless of the supercell characteristics.
ORD: This category was designed to exclude super-
cells. This was done by including soundings associated
with a modest amount of cloud-to-ground lightning, but
excluding soundings associated with damaging wind,
large hail, or any tornado. This exclusion is based on
the idea that most supercells produce some severe
weather at the surface (Burgess 1976; Moller et al.
1994).
e. Computation of storm motion
In all computations, the assumed storm motion is that
computed based on the limited climatology of Rasmus-
sen and Straka (1998). The hodographs for represen-
tative soundings for 45 supercell cases were translated
so that the 0–500 m above ground level (AGL) (assumed
boundary layer, hereafter BL) mean wind was at the
origin and rotated so that the BL–4 km AGL shear
vector was aligned with the 1u axis. The storm motions
were plotted. It was found that for LP (low precipitation
updraft region, based on subjective visual classification)
and classic supercells, the motion was always within 4
ms
21
of a point found as follows: 8.6 m s
21
orthogonal
to the right of the tip of the 0.6S vector, where S is the
BL–4 km shear vector (Fig. 2). It is this storm motion
vector that is used in the present study and has been
tested for several years in the National Center for At-
mospheric Research (NCAR) operational version of the
Mesoscale Model, version 5, forecast model (J. Bresch
1998, personal communication). Recently, Bunkers et
al. (1998) have derived a very similar formula for pre-
dicting supercell motion using a sample of 125 super-
cells based on a technique proposed by M. Weisman
(1998, personal communication). Note that unlike the
common methods based on angular deviation from deep
mean wind vectors, the present method is Galilean in-
variant. A hodograph produces the same hodograph-
relative motion regardless of where it falls relative to
the origin. In the limited climatology, high precipitation
(HP) supercells generally deviated much more than 4
ms
21
from the ‘‘predicted’’ motion and did not seem
to be strongly related to the shear in the lower half of
the troposphere. Supercell motion forecasting derived
from the above technique, based largely on the work of
Rotunno and Klemp (1982), is the subject of an ongoing
investigation.
3. Shear-related parameters
In this section, the climatology of sounding-derived
shear parameters is presented. The computation of spe-
cific parameters is described in the appropriate sections.
All integrals were computed using the trapezoidal meth-
od and the actual reported data. The upper and lower
limits of many integrals occur between reported data
levels; data at these levels were linearly interpolated (in
1152 V
OLUME
13WEATHER AND FORECASTING
T
ABLE
2. Confidence levels for the multiresponse permutation pro-
cedure. Dashes indicate ,95% confidence level; only 95% and 99%
are shown. Two-dimensional parameters at the bottom (2D) indicate
that the test was run in two-dimensions using the two quantities that
define the parameter space for that parameter (e.g., SRH and CAPE
for EHI).
Parameter
SUP/
ORD
TOR/
ORD
TOR/
SUP
BRN
BL–6-km shear
b Brooks parameter
CAPE
EHI
LCL
Mean shear
SRH
Upper storm-relative wind speed
BRN (2D)
Brooks (2D)
EHI (2D)
VGP (2D)
99
99
99
99
99
99
99
99
99
99
95
99
99
99
99
99
99
99
—
99
99
99
99
99
99
99
—
—
—
—
95
99
99
95
—
—
99
95
95
F
IG
. 3. Box and whiskers graph of BL–6-km shear for soundings
associated with supercells with significant tornadoes (TOR; right),
supercells without significant tornadoes (SUP; middle), and nonsu-
percell thunderstorms (ORD; left). Gray boxes denote 25th to 75th
percentiles, with heavy horizontal bar at the median value. Thin ver-
tical lines (whiskers) extend to the 10th and 90th percentiles.
height) between reported data. Wherever mean values
are required, the mean is computed as the average of
the values reported weighted by the thickness of the
layer represented by that observation (or derived from
reported levels) in the sounding. In interpreting the re-
sults, it should be noted that the means of the samples
in the three categories were examined for statistically
significant differences using the t test, as well as the
more appropriate technique of multiresponse permuta-
tion procedures (Mielke et al. 1976; Mielke et al. 1981).
In general, the means were statistically significantly dif-
ferent between the three permutations of category pairs,
as documented in Table 2.
This section describes the climatology of storm-rel-
ative helicity (Davies-Jones et al. 1990), ‘‘mean shear’’
(Rasmussen and Wilhelmson 1983), and storm-relative
upper-tropospheric wind speed (Rasmussen and Straka
1998). Several quantities were investigated that did not
seem to have significant utility, especially for distin-
guishing between the TOR and SUP classes of super-
cells (viz., storm-relative boundary layer wind speed
and storm-relative wind speeds every 1000 m in ele-
vation between 3 and 7 km AGL).
a. Boundary layer to 6-km shear
In this section, the magnitude of the shear vector be-
tween the 0–500 m AGL mean wind and 6 km AGL
wind (hereafter BL–6-km shear) is examined. Figure 3
shows the frequency of occurrence of various magni-
tudes of BL–6-km shear as a function of category. The
gray boxes contain the middle 50% of the events, with
the median shown with a horizontal black line. The
vertical black bar contains the middle 80% of the events.
Graphs of this type can be used to gain an understanding
of the overall distribution of a parameter, but more im-
portantly they can be used to gauge the relative value
of a parameter in distinguishing among categories. It
can be seen that BL–6-km shear has value for distin-
guishing between the populations of soundings asso-
ciated with the TOR and SUP categories, and that as-
sociated with the ORD category. In the case of ORD
soundings, BL–6-km shear is between five and 15 m
s
21
in half of the cases, while for TOR–SUP the equiv-
alent range is 11–21 m s
21
. From Fig. 3 it can also be
seen that BL–6-km shear has no utility for distinguish-
ing between the SUP and TOR categories.
b. Storm-relative helicity
SRH (Davies-Jones et al. 1990) is defined as
h
]V
SRH 52 k ·(V 2 c) 3 dz, (1)
E
]z
0
where V is horizontal velocity, c is the storm motion
vector, and h is the depth over which the integration is
performed (3 km herein). SRH shows considerably
greater utility for distinguishing among the categories
than BL–6-km shear (Fig. 4). Most ORD have small
SRH (75% with SRH ,100 m
2
s
22
). Half of the SUP
soundings have SRH between 64 and 208 m
2
s
22
.
Soundings in the TOR category are quite distinct from
the ORD soundings, with no overlap in SRH among the
central 50% of cases. The mean value of SRH in TOR
soundings is almost 200 m
2
s
22
. However, it is not true
that large SRH implies that a particular sounding will
be associated with a significant tornado. The 23% of
ORD soundings with SRH between 100 and 168 m
2
s
22
