ArticlePDF Available

Cold Pools and MCS Propagation: Forecasting the Motion of Downwind-Developing MCSs



The primary factors that affect the direction of propagation and overall movement of surface-based mesoscale convective systems (MCSs) are discussed. It is shown that although propagation is indeed related to the strength and direction of the low-level jet as previous studies have shown, it is more specifically dependent upon the degree of cold-pool-relative flow and to the distribution of conditional instability present along a system's gust front. An updated technique that may be used to forecast the short-term (3-6 h) motion of MCS centroids based on these concepts is introduced. The procedure builds on the long-established observation that MCS motion is a function of 1) the advection of existing cells by the mean wind and 2) the propagation of new convection relative to existing storms. Observed wind and thermodynamic data, in conjunction with anticipated cold-pool motion and orientation, are used to assess the speed and direction of cell propagation, that is, whether propagation will be upwind, downwind, or some combination of the two. The technique ultimately yields an estimate of overall system movement and has application regardless of scale, season, or synoptic regime.
18 D
Cold Pools and MCS Propagation: Forecasting the Motion of
Downwind-Developing MCSs
F. C
NOAA/NWS/NCEP/Storm Prediction Center, Norman, Oklahoma
(Manuscript received 13 March 2003, in final form 20 May 2003)
The primary factors that affect the direction of propagation and overall movement of surface-based mesoscale
convective systems (MCSs) are discussed. It is shown that although propagation is indeed related to the strength
and direction of the low-level jet as previous studies have shown, it is more specifically dependent upon the
degree of cold-pool-relative flow and to the distribution of conditional instability present along a system’s gust
front. An updated technique that may be used to forecast the short-term (3–6 h) motion of MCS centroids based
on these concepts is introduced. The procedure builds on the long-established observation that MCS motion is
a function of 1) the advection of existing cells by the mean wind and 2) the propagation of new convection
relative to existing storms. Observed wind and thermodynamic data, in conjunction with anticipated cold-pool
motion and orientation, are used to assess the speed and direction of cell propagation, that is, whetherpropagation
will be upwind, downwind, or some combination of the two. The technique ultimately yields an estimate of
overall system movement and has application regardless of scale, season, or synoptic regime.
1. Introduction
Thunderstorms are frequently organized in lines or
clusters known as mesoscale convective systems
(MCSs). The term MCS is generally reserved for en-
sembles of storms that satisfy certain spatial or temporal
criteria (see, e.g., Houze 1993, p. 334; Parker and John-
son 2000). In a less restrictive sense, however, any me-
soalpha- or mesobeta-scale (Orlanski 1975) area of
moist convection might be considered an MCS (Ray
Because MCSs produce a disproportionate share of
significant convective weather (high winds, flash flood-
ing, etc.) and because their evolution is often not pre-
dicted well by operational numerical guidance, fore-
casting MCS motion is of considerable importance to
operational meteorologists. Forecasts of MCS motion
are dependent upon anticipation of the predominant
propagational mode or modes likely during an event. In
particular, it is important to distinguish between MCS
environments conducive to upwind propagation and
those that exhibit downwind storm development and
sometimes evolve into derecho-producing squall lines.
Attempts to forecast MCS movement have met with
mixed results. Merritt and Fritsch (1984) examined the
motion of more than 100 MCSs, most of which were
mesoscale convective complexes (MCCs; Maddox
Corresponding author address: Stephen F. Corfidi, Storm Predic-
tion Center, 1313 Halley Circle, Norman, OK 73069.
1980). They were among the first to recognize that
though no true ‘‘steering level’’ exists for MCC motion,
such systems typically move approximately parallel to
the contours of the 1000–500-hPa thickness. They also
noted that although most convective systems move
downshear along the contours, others inexplicably move
upshear. The speed of MCC motion was found to be
modulated by the location of maximum low-level mois-
ture convergence relative to existing convection.
Newton and Katz (1958) and Chappell (1986), among
others, showed that the motion of a convective system
can be thought of as being the vector sum of 1) an
advective component approximated by the direction and
magnitude of the mean cloud-layer wind and 2) a prop-
agation component governed by the rate and location
of new cell formation relative to existing convection.
Building on this idea, and extending the work of Merritt
and Fritsch, Corfidi et al. (1996) showed that the prop-
agation component is, in many cases, directly propor-
tional but opposite in direction to the low-level jet. This
finding is somewhat surprising given that MCS prop-
agation can be influenced by a myriad of factors such
as the distribution of convective available potential en-
ergy (CAPE), convective inhibition, gravity waves, out-
flow boundaries, and orographic effects.
This paper discusses MCS motion, with emphasis on
those factors related to a system’s cold pool that most
influence cell propagation and, ultimately, overall sys-
tem movement. Based on this presentation, a vector-
based forecast technique is developed for predicting the
998 V
. 1. Schematic of the original vector technique, with MCS core
motion (thick dotted arrow) expressed as the vector sum of 1) ad-
vection of cells by the mean cloud-layer wind (arrow pointing to
upper right) and 2) cell propagation directed into the low-level jet
(arrow pointing to bottom of page). MCS centroid is depicted by the
cross symbol (after Corfidi et al. 1996).
motion of MCSs characterized by downwind propaga-
2. Background
a. The original vector technique
Corfidi et al. (1996) developed a simple technique to
predict the short-term (3–6 h) motion of the mesobeta-
scale cores or ‘‘centroids’’ of MCSs using the low-level
jet to estimate the direction and rate of storm propa-
gation. Forecast centroid motion is taken to be the sum
of 1) a vector that represents cell advection by themean
cloud-layer wind (with ‘‘cloud layer’’ taken to be the
850–300-hPa layer)
and 2) a vector that represents
storm propagation, that is, new cell development, equal
in magnitude but directed opposite to the low-level jet
(Fig. 1). In practice, the 850-hPa wind is used to ap-
proximate the low-level jet, although it is recognized
that this approach may not identify the true jet in all
cases. In the absence of a distinct low-level speed max-
imum in the vertical direction, the strongest wind in the
lowest 5000 ft (1.5 km) is generally used, in accordance
with Bonner (1968).
The vector technique is applicable in any kind of
environmental wind regime and requires knowledge of
only the 850-hPa and mean cloud-layer winds. The pro-
cedure is especially useful in identifying those kinematic
situations conducive to the development of quasi-sta-
tionary and ‘‘back building’’ MCSs (Bluestein and Jain
1985). Quasi-stationary systems arise when the wind
profile is unidirectional and cell advection is exactly
offset by cell propagation. Back building occurs under
similar conditions but when propagation exceeds ad-
vection, resulting in overall upwind motion. Identifi-
cation of such events is important because they fre-
quently are associated with excessive rainfall (Chappell
The original vector concept, while useful, is never-
theless subject to several limitations. First, the scheme
does not account for spatial and temporal changes in
the environmental wind that, in altering both cell ad-
The speed and direction of the mean cloud-layer wind are cal-
culated using the following relationship: Vmean 5(V850 1V700
1V500 1V300)/4, where V850 is the 850-hPa vector wind, etc.
vection and propagation, can affect MCS movement.
Therefore, motion estimates must be updated frequently
when the wind field exhibits significant spatial or tem-
poral variability. Second, there is no accounting for the
influence of terrain on convective development and low-
level flow. As a result, the concept is more difficult to
apply in cases of orographically forced convection(e.g.,
Pontrelli et al. 1999).
A more serious shortcoming of the original vector
approach follows from its assumption that new cell de-
velopment and, therefore, system propagation always
occur in the direction opposite that of the low-level jet,
or, more generally, the low-level flow. To be sure, many
warm-season MCSs over the central United States in-
deed do exhibit propagation in that direction (see, e.g.,
Moore et al. 1993; and Junker et al. 1999) at a rate
approximated by the speed of the jet.
It is clear, how-
ever, that this is not always the case. For example, de-
recho-producing squall lines often move at a substantial
angle to the low-level flow, especially during their ini-
tiation (Johns et al. 1990). Radar data reveal that, al-
though propagation is largely responsible for the ob-
served motion of these systems, new cell development
is not necessarily directed into the low-level flow but
rather occurs on the leading (downwind) edge of the
system cold pool. For this reason, to be more universally
applicable, the vector concept must be modified to ac-
count for the presence of cold pools and the potential
for propagation away from the low-level flow.
b. Cold-pool and gust-front motion
One of the more distinctive features of a well-orga-
nized MCS is the cold pool that develops at lower levels
beneath or just behind the strongest convection. Cold
pools represent the collective outflow of individual con-
vective cells and the negative buoyancy of parcels with-
in or beneath the convection. Sublimation and/or melt-
ing and evaporation of precipitation falling through un-
saturated air, precipitation drag, and vertical perturba-
tion pressure gradients are all factors that may enhance
downdraft development and cold-pool strength.
The periphery of a cold pool, that is, the gust front
or outflow boundary, is marked by low-level conver-
gence and ascent (Purdom 1973; Charba 1974; Goff
1976). As a result, gust fronts are often the site of new
cell development. Such activity typically is not distrib-
uted evenly along such boundaries. Instead, storm ini-
tiation tends to occur in discrete zones, within which
kinematic and/or thermodynamic factors are most fa-
vorable for development. Observation suggests that new
cell development occurs most readily where the ambient,
The original dataset used by Corfidi et al. (1996) was composed
primarily of nocturnal MCCs that were associated with well-defined
low-level jets east of the Rockies. In retrospect, therefore, it is not
surprising that propagation was found to be correlated well with the
low-level jet.
2003 999CORFIDI
. 2. Plan-view schematic depicting temporal elongation of a
cold pool and gust front associated with the hypothetical quasi-uni-
directional wind profile shown at right. Motion of boundary relative
to ground is depicted by conventional frontal symbols. Dashed lines
indicate gust-front positions at earlier times. Indicated spatial scale
is for illustrative purposes only.
low-level inflow relative to the boundary is greatest.
This result follows because areas of strong relative in-
flow will also be regions of maximum lower tropo-
spheric convergence. As previously noted, these regions
are often governed by the position of the low-level jet.
If a significant degree of relative motion exists between
a gust front and the low-level environmental wind, how-
ever, convergence maxima may develop along the
boundary in locations away from the low-level jet.
It is obvious that motion of a gust front must be
known if the pattern and intensity of relative inflow
along it are to be assessed. Many studies (see, e.g.,
Charba 1974; Goff 1976; Wakimoto1982; Droegemeier
and Wilhelmson 1987; Rotunno et al. 1988) have ex-
amined the motion of gust fronts. These investigations
determined that storm outflow behaves more or less as
a gravity current. Indeed, observational studies (e.g.,
Wakimoto 1982) have confirmed that downstream gust-
front speed is governed largely by the density difference
between the downdraft air and that of the surrounding
environment and by the depth of the outflow. Because
evaporative cooling and precipitation drag often vary
markedly over time and space, however, downdraft pro-
duction is both temporally and spatially unsteady. In
addition, cold-pool depth and horizontal density differ-
ences ordinarily cannot be measured in real time. For
these reasons, gravity-current theory has proven to be
of limited operational value in forecasting gust-front
Given the limited utility of gravity-current theory, it
is worthwhile to consider the role of momentum transfer
in determining gust-front motion, because lower-tro-
pospheric wind data are generally readily available in
an operational setting. It is clear that, because of mo-
mentum transfer, a gust front will move preferentially
in the direction of the motion associated with the parcels
that contributed to the parent cold pool. Momentum
transfer largely explains, for example, why derecho-pro-
ducing MCSs embedded in northwesterly midtropo-
spheric flow typically move southeastward (Johns and
Hirt 1987). The systems move southeast because their
gust fronts advance primarily in that direction. With
boundary layer convergence maximized along the gust
front on the southeast (downwind) side of the cold pools,
new cell development and, therefore, overall system mo-
tion are toward the southeast (assuming the existence
of a favorable thermodynamic environment).
Perhaps more surprising is that observation suggests
that momentum transfer may also be used to estimate
gust-front speed. Many processes, of course, can influ-
ence gust-front motion on the local (i.e., mesogamma)
scale. Because these processes are often nonlinear,gust-
front speed is typically unsteady over periods on the
order of tens of minutes. Over longer intervals, however,
downwind gust-front behavior is observed to be more
uniform (e.g., Fovell and Ogura 1989). In fact, subjec-
tive examination of nearly 50 forward-propagating
MCSs over the central and eastern United States during
the last two decades has determined that, at least to a
first approximation, average downwind gust-front speed
may be estimated by the mean cloud-layer wind or, more
specific, the speed of the parcels that contribute to the
parent cold pool. As will be shown in later sections,
this finding may be used to help to estimate the motion
of a forward-propagating MCS.
c. The role of gust-front orientation
Implicit in the observation that cold-pool motion is
determined to a large extent by momentum transfer is
the fact that, over time, cold pools tend to elongate in
the direction of the mean wind. This tendency is most
pronounced when the flow is unidirectional. As a cold
pool elongates, some parts of its associated gust front
necessarily become oriented perpendicular to the mean
wind while other portions come to lie parallel to it.
Continued production of storm outflow forces boundary
segments oriented perpendicular to the mean wind to
progress downwind with time while flow-parallel por-
tions move very slowly or not at all (Fig. 2).
The orientation of a gust front relative to the mean
wind is important in determining the direction of cell
propagation and, therefore, the kind of MCS that will
be most favored along it. For example, if sufficient sur-
face-based instability is present along those segments
aligned parallel to the mean flow, new storm develop-
ment is likely to occur repeatedly where low-level con-
vergence along the boundary is greatest. This, of course,
is often in the direction of the low-level jet. In a typical
situation, a component of the propagation will be up-
wind relative to the mean flow. As a result, cells sub-
sequently track downwind in succession (‘‘train’’)along
the front (Fig. 3, top). Because the boundary does not
move, extended periods of such upwind development
can yield excessive precipitation as long as the wind
profile remains unchanged. Indeed, this scenario de-
1000 V
. 3. (right) Plan view of an elongating cold pool, with cross sections perpendicular to the gust front along (top)
a quasi-stationary segment and (bottom) a progressive segment, showing direction of cell propagation. Hypothetical
wind profiles at left are for illustrative purposes only.
scribes the ‘‘mesohigh’’ flash-flood MCS pattern of
Maddox et al. (1979).
If instability is present along those portions of the
gust front oriented perpendicular to the mean wind, ther-
modynamics are favorable for the formation of strong
convective-scale downdrafts, and sufficient conver-
gence is present to initiate storms, downwind or ‘‘for-
ward’’ propagation is likely to occur. Assuming that
these conditions are maintained for some period of time,
a bow echo or derecho-producing MCS may develop
(Fig. 3, bottom). Because cell advection and propagation
are additive, some degree of front-to-rear flow will nec-
essarily be present relative to the gust front. Such sys-
tems occasionally move much faster than the mean wind
when the propagation rate is great.
d. Concurrent upwind and downwind propagation
The role of gust-front orientation in determining prop-
agation direction and MCS type is perhaps best dem-
onstrated by the occasional observation of concurrent
back-building and forward-propagating convective sys-
tems in environments of largely unidirectional mean
flow and minimal cloud-layer shear. As Chappell(1986)
noted, environments that are kinematically supportive
of quasi-stationary or back-building MCSs may also
yield fast-moving, forward-propagating squall lines. In-
deed, the implied wind profile in Maddox et al.’s(1979)
schematic depicting a back-building ‘‘synoptic’’ flash-
flood-producing MCS (their Fig. 6) is similar to that
found by Johns et al. (1990) to be associated with de-
recho-producing squall lines (their Figs. 4–8). What dis-
tinguishes between the two propagational modes is the
orientation of the gust front relative to the mean wind.
The radar evolution of two concurrent bow echo/
back-building MCS events is depicted in Fig. 4. The
first occurred in moderate westerly flow on the northern
edge of a subtropical ridge on 24 August 1998 (Fig.
4a). A small bow-shaped MCS moved across northern
Illinois and Indiana, producing wind gusts to 80 kt (40.0
) near Chicago, Illinois. The bow MCS was fol-
lowed by a back-building convective cluster that sub-
sequently caused heavy rain over neighboring parts of
northern Illinois. The latter system developed along and
just behind the trailing outflow boundary (gust front)
associated with the bow MCS as the boundary became
quasi-stationary and parallel to the westerly unidirec-
tional mean wind.
A similar event affected the Kansas City, Missouri,
area several weeks later (Fig. 4b). Thunderstorms de-
2003 1001CORFIDI
. 4. Composite Doppler radar depiction of reflectivity over (a) northern Illinois, 1700–2000 UTC 24 Aug 1998
and (b) northern Missouri, 0030–0200 UTC 5 Oct 1998.
1002 V
. 5. Skew T–logpplot of radiosonde observations for (a) Lincoln, IL (near Springfield), at 1800 UTC 24 Aug 1998, and (b) Topeka,
KS, at 1800 UTC 4 Oct 1998. Winds are in knots [barb 510 kt (5 m s
); flag 550 kt (25 m s
)]. Lifted parcel ascent curve (large
dashed line) is for most unstable parcel, including correction for virtual temperature (rightmost small dashed line). Wet-bulb zero line is
shown as a dashed line between environmental temperature and dewpoint profiles. Numbers on the hodograph in the upper-right-hand side
depict the altitude above ground level in kilometers.
veloped during the afternoon along a stationary front
oriented parallel to a zone of strong unidirectional south-
west flow aloft. By evening, the activity evolved into a
linear MCS containing an embedded bow echo. The
bowed segment of the system produced damaging winds
in northern Missouri. Of more significance was the flash
flooding in Kansas City that accompanied the trailing
southwestern part of the same complex. The flooding
occurred as storm cells repeatedly developed and moved
northeast along the stalled outflow boundary left by the
exiting bow.
The MCS genesis region in both the Illinois and Mis-
souri events was characterized by unidirectional low-
to-midtropospheric flow, with limited shear in thecloud-
bearing layer [Figs. 5a,b; note that the Topeka, Kansas,
sounding (Fig. 5b) was taken just west of the surface
front mentioned in the previous paragraph; the portion
of sounding above 850 hPa is believed to be represen-
tative of warm-sector conditions east of the front]. Sim-
ilar conditions prevailed farther downstream, along the
paths taken by the forward-propagating members of
each event. As the cold pools elongated, the gust-front
segments oriented perpendicular to the mean wind be-
came the site of downwind convective development
while upwind propagation persisted on those portions
of the boundary that became quasi stationary.
Although not recognized as such at the time, one of the first
documented concurrent bow-echo/back-building MCS events was the
Independence Day storm of 4–5 July 1969. Widespread damage from
high winds followed by flash flooding left 41 dead across Michigan,
Ohio, and Lake Erie (Hamilton 1970).
e. The role of dry air
Previous work has suggested that, in addition to gust-
front orientation and motion, thermodynamic factors
might also play a role in determining the primary mode
of MCS propagation. For example, Corfidi (1998) con-
ducted a preliminary examination of proximity sound-
ings from MCSs that occurred in environments of large-
ly unidirectional flow over the central and eastern Unit-
ed States between 1980 and 1998. The results suggest
that a characteristic common to those systems that
evolved into bow echoes and/or derechos was the pres-
ence of relatively dry air, either at midlevels or in the
subcloud layer, ahead of the developing convectivesys-
tem. This air appeared to be associated with the for-
mation of a strong cold pool. In converse, quasi-sta-
tionary and back-building MCSs were found to occur
in moister or nearly saturated lower-tropospheric en-
vironments, with comparatively weak cold pools. In
short, the potential to produce cold convective-scale
downdrafts (and, therefore, a strong cold pool) appeared
to distinguish forward-propagating environments from
those more conducive to upwind development.
Dry air is, of course, clearly associated with the oc-
currence of derechos and bows. Johns et al. (1990) noted
the presence of large dewpoint depressions at 700 and
500 hPa in the vicinity of long-lived derechos, and the
ingestion of dry air from the prestorm environment can
assist in the formation and maintenance of surface me-
sohighs by enhancing storm-scale buoyant pressure
fields and their associated gust-front circulations.
More recent analysis, however, using a dataset of 48
forward-propagating MCSs associated with damaging
surface winds, along with examination of quasi-station-
2003 1003CORFIDI
ary systems that produced major flash floods in recent
decades, suggests that the relationship between cold-
pool strength and forward-propagating MCS develop-
ment is not so clear. Cold pools are not necessarily weak
in all cases of quasi-stationary or back-building con-
vection; indeed, some quasi-stationary MCSs exhibit
prominent cold pools. For example, the system that pro-
duced the Johnstown, Pennsylvania, flood in July of
1977 (Hoxit et al. 1978; Bosart and Sanders 1981) had
a strong cold pool, and a similarly strong cold pool was
present in the Kansas City flood case just discussed.
Cold-pool strength and, therefore, expansion rate are
certainly positively correlated with downwind MCS de-
velopment, but it is clear that the potential to produce
a strong cold pool cannot alone be used to distinguish
between environments conducive to upwind versus
downwind development; gust-front orientation and mo-
tion are also important.
3. A vector technique for downwind-propagating
a. Development of a vector scheme for downwind-
developing MCSs
In this section, a scheme similar to that presented in
Corfidi et al. (1996) to estimate the short-term motion
of forward-propagating MCSs is described. Using the
original (1996) technique as a starting point, the ap-
proach applies the concepts discussed in the previous
section to account for cell propagation away from the
low-level jet, along the downwind side of a cold pool.
It has been noted that momentum transfer forces gust-
front segments oriented perpendicular to the mean flow
to move downwind over time. It has been noted also
that the rate of downwind gust-front motion is strongly
correlated with the speed of the mean cloud-layer wind.
Because the gust front is the mobile locus of new con-
vective development in a forward-propagating MCS, a
motion estimate for the boundary (i.e., the cloud-layer
wind) can serve as a proxy for the advective component
of forward-propagating MCS motion.
If one accepts that the advective component of a for-
ward-propagating convective system is given by the
mean cloud-layer wind, examination of the schematic
depicting the original vector technique (Fig. 1) reveals
that the MCS motion vector provided by that scheme
is, in fact, the propagation vector of a forward-propa-
gating system. This result follows because the motion
vector of the original scheme represents the vector dif-
ference between a gust front moving at the speed of the
mean cloud-layer wind and the low-level flow. In other
words, the motion vector provided by the original tech-
nique is, in fact, the negative of the gust-front-relative
low-level flow for a boundary moving with the speed
and direction of the mean cloud-layer wind.
The length of the motion vector provided by the orig-
inal technique is directly proportional to the degree of
convergence and rate of new cell development along
the gust front. Addition of this vector representing cell
propagation along the gust front to that representing the
downwind motion of the boundary (i.e., the mean cloud-
layer wind) can therefore provide an estimate of the
overall motion of a forward-propagating MCS. In short,
the vector approach for a forward-propagating system
requires just one extra vector addition beyond the two
used in the original method (where upwind cell devel-
opment is assumed) and can yield a drastically different
forecast motion, as shown in Fig. 6.
b. Results
Table 1 presents the results of applying the forward-
propagating vector technique to 48 convective systems
associated with damaging surface winds. The events
occurred throughout the central and eastern United
States, predominantly during the spring and summer.
They were selected on the availability of a sounding
representative of the inflow environment [uncontami-
nated, and within 100 n mi (185 km) and 2 h of the
event] and composite radar data. Forecasts were made
for the 3-h motion of the strongest MCS radar reflec-
tivity core (the MCS centroid).
As the table shows, successful forecasts [defined as
direction and speed of motion within 208and 10 kt (5.0
), respectively, of observed] were produced for 38
of the 48 events. On average, the speed errors are ran-
dom, although there appears to be a tendency to un-
derestimate the forward motion of systems containing
embedded supercells and/or strong rear-inflow jets (la-
beled ‘‘SPRCL/RIJ’’ in right-most column of Table 1)
Enhanced and/or otherwise altered downstream propa-
gation rates associated with the presence of these fea-
tures are believed to be responsible for the errors.
The directions of motion forecast by the downwind
technique display a small left bias (negative directional
errors in Table 1). This observation most likely reflects
the large-scale warm-advection environment within
which the MCSs occurred. Because the lower-tropo-
spheric shear typically turns right (clockwise) down-
stream from warm-advection maxima, there is a ten-
dency for forward-propagating MCSs to turn right with
time (e.g., Johns et al. 1990). Of course, these systems
do not physically change direction per se; the ‘‘turning’
reflects a gradual rightward shift in the area most fa-
vored for new cell development as the systems move
downwind. Because application of the vector technique
uses instantaneous wind data obtained at a given point
in time, it is impossible to account for such longer-term
rightward deviation in any one forecast. The effect is,
however, seen easily if simultaneous forecast motions
are plotted spatially on a regional grid. Note also that,
for longer-lasting systems, Coriolis accelerations acting
on the rear-to-front and front-to-rear flows may also bias
motion to the right (Skamarock et al. 1994).
A surface boundary external to the convective system
that forced propagation to occur away from the purely
downwind direction resulted in significant directional
1004 V
. 6. Comparison schematics of (top) original (upwind) and (bottom) downwind versions
of the vector technique to forecast short-term motion of upwind-developing systems (MCSmotion
given by thick red arrows) and downwind-developing systems (MCS motion given by thick green
arrow at bottom of figure), respectively. Vector lengths are proportional to wind speed; MCS
centroids are denoted by the cross symbol.
errors in three warm-season cases (11, 32, and 36). It
is clear that surface data in the vicinity of a developing
MCS must be examined carefully to identify any syn-
optic or mesoscale boundaries that might have such an
effect. Such situations will require modification of the
vector technique (namely, rotation of the propagation
vector) to account for the altered direction of propa-
Three of the 10 unsuccessful forecasts in Table 1 ap-
pear to have been related to the large-scale environment
in which the events occurred. Each was associated with
a serial bow MCS along a cold front (Johns and Hirt
1987), and forecast speed was overestimated in each case.
In one instance (case 16), overall system motion was
slowed because surface-based instability, present both
upwind and downwind from the initial convective area,
enabled the MCS to exhibit simultaneous upwind and
downwind propagation. In the remaining two cases (20
and 29), system motion appeared to be overestimated
because propagation was very limited relative to advec-
tion. The squall lines moved downstream roughly at the
speed of the mean wind and associated cold front, ap-
parently as a result of nearly saturated conditions in the
surface-to-700-hPa layer (not shown). Further discussion
of this topic is provided in section 5.
The factors associated with two of the remaining un-
successful forecasts (cases 1 and 12) were not readily
apparent and await further investigation.
4. Case applications of the downwind vector
a. Comparison application of the original and
downwind techniques: 16 August 1997
Figure 7a shows a proximity thermodynamic sounding
and wind profile associated with the incipient stage of a
forward-propagating MCS that subsequently moved
across northern Ohio and Pennsylvania on 16 August
1997 (case 48 in Table 1). The system developed in an
environment of moderate, unidirectional westerly flow in
the warm sector of a surface wave crossing southern
Quebec, Canada (Fig. 7b). Large-scale forcing was weak,
similar to situations described by Coniglio and Stensrud
(2001) and Evans and Doswell (2001). Considerable sur-
face-based instability was present, however, throughout
the warm sector, within which afternoon temperatures
warmed to above 908F (308C; not shown).
Using a mean wind vector of 2608/35 kt (18 m s
and a low-level ‘‘jet’’ of 2508/32 kt (16 m s
), appli-
cation of the original vector technique yields a system
movement toward the east-southeast at approximately
2003 1005CORFIDI
1. Forward-propagating MCS events used to test the downwind vector technique. Data include date/time (year 11900, month,
day, UTC hour), three-letter identification of sounding (raob) site used to calculate pertinent wind vectors, forecast (FCST) and observed
(OBSVD) MCS motion [direction (DIR)/speed (SPD); speed is in knots; 1 kt is about 0.5 m s
], and direction/speed errors. Direction and
speed errors exceeding 208and 10 kt (5.0 m s
), respectively, are in boldface. The apparent source of failure for those events exceeding
the above criteria is indicated in right-most column (Boundary means external boundary was present; SPRCL/RIJ means system contained
supercells and/or a rear-inflow jet; Translational means system was strongly affected by the translational motion of a mesoalpha-scale
environment conducive to storm initiation; Unknown means the source of error was not readily apparent). See text for details.
Case no. Date/time
(YYMMDDHH) Raob site
(DIR/SPD) Observed motion
(DIR/SPD) Direction error
(FCST2OBSVD) Speed error
(FCST2OBSVD) Apparent failure
22 89050500
89050600 SEP
CHS 290/53
240/45 310/65
). As Fig. 7c (top) shows, the original
vector approach depicts a scenario in which cell ad-
vection is offset almost totally by cell propagation.
However, as might be expected given the availability
of dry air at midlevels (Fig. 7a), the MCS began to
produce strong convective downdrafts early in its life
cycle; by 1400 UTC, a well-defined cold pool was pres-
ent beneath it (not shown).
Because the associated
downdrafts brought strong westerly winds to the sur-
Note that the sounding in Fig. 7a was taken around local sunrise;
insolation after this time resulted in substantial boundary layer warm-
ing downwind from the incipient convective system, enhancing both
updraft strength and downdraft production.
1006 V
. 7. (a) Same as Fig. 5a, but for White Lake, MI (near Detroit), 1200 UTC 16 Aug 1997. (b) Regional surface
mesoanalysis, valid for the same time as in (a): thermodynamic data (8F), wind (kt), and pressure (hPa, with first
two digits omitted); synoptic-scale boundaries are depicted with large pips, mesoalpha-scale gust front is shown with
small pips, and center of the MCS mesohigh is indicated by the ‘‘B’’ (‘‘bubble high’’) over southeast Michigan. (c)
(top) Application of original and (bottom) downwind versions of the vector technique to the 16 Aug 1997 MCS,
based on sounding data in (a). Forecast motions are depicted by heavy solid arrows, with the MCS centroid depicted
by the cross symbol. Directions are in degrees azimuth, and speeds are in knots. (d) Three-hourly radar-observed
positions of leading convective line (solid lines) and severe-weather reports (damaging winds are crosses, hail is
dots, and tornadoes are small squares) associated with the forward-propagating MCS of 16 Aug 1997.
face, the cold pool elongated toward the east. At the
same time, capping prohibited the development of new
convection toward the west (i.e., in the upwind direc-
tion), despite the fact that the near-surface flow wasfrom
the west. As a consequence, with strong system-relative
convergence and instability both present in the down-
wind (east) direction, ascent along the progressive part
of the gust front readily led to new cell development in
the downwind direction, and the system propagated to
the east. Because cell advection was also toward the
2003 1007CORFIDI
east, however, advection and propagation were nearly
directly additive (Fig. 7c, bottom). Thus, the MCS did
not remain nearly stationary as the original vector tech-
nique would suggest but rather accelerated eastward as
a forward-propagating squall line that moved at a speed
faster than that of the mean wind (Fig. 7d). The down-
wind vector technique’s motion estimate of 2658at 40
kt (20 m s
; Fig. 7c, bottom) compares favorably to the
9-h observed mean motion of 2758at 45 kt (22 m s
The original vector technique seriously underesti-
mated the motion of the squall line because it failed to
account for the fact that propagation would occur down-
wind rather than upwind. This case demonstrates the
need to identify the region of greatest system-relative
convergence and the distribution of surface-based con-
ditional instability along the gust front when determin-
ing the preferred direction of propagation. Use of the
850-hPa wind or some other estimate of the low-level
flow to represent propagation will yield erroneous re-
sults when convergence is maximized in a direction
away from the low-level jet in the presence of condi-
tional instability.
1008 V
. 8. (a) Same as Fig. 7d, but for the forward-propagating MCS of 19–20 Jul 1983. (b) Same
as Fig. 5a, but for Bismarck, ND, 1200 UTC 19 Jul 1983. (c) Same as Fig. 7b, except valid for
the same time as in (b). The center of the MCS mesohigh is indicated by the ‘‘B’’ (bubble high)
over northwest North Dakota. (d) Application of the downwind vector technique for the the 19
Jul 1983 MCS, based on sounding data in (b). Directions are in degrees azimuth, and speeds are
in knots. The MCS centroid is depicted by the cross symbol.
b. Application of downwind technique to a derecho:
19–20 July 1983
In the middle (low) latitudes, where the mean tro-
pospheric flow is typically westerly (easterly), gust-
front-relative flow will be enhanced when the boundary
layer winds have an easterly (westerly) component. In
some instances, the magnitude of gust-front-relative
flow sometimes exceeds that of the mean cloud-layer
wind. Depending upon thermodynamic conditions, con-
vective systems developing in this kind of environment
occasionally attain speeds that are more than 2 times
that of the mean wind. The classic derecho of 19 July
1983, which produced a swath of widespread wind dam-
age across the upper Mississippi Valley (Fig. 8a; see
Johns and Hirt 1985), serves as an example of this type
of an event.
Figure 8b, the thermodynamic sounding and wind
profile taken at Bismarck, North Dakota, at 1200 UTC
19 July, is representative of conditions during the ini-
tiation of the MCS. CAPE, calculated by lifting a parcel
from near 850 hPa, is substantial (around 4000 J kg
and nearly dry adiabatic lapse rates are present at mid-
levels to foster strong convective downdraft develop-
ment. As Fig. 8c shows, the system formed in a region
2003 1009CORFIDI
of high boundary layer moisture content [average sur-
face dewpoints around 658F (188C)] on the north side
of a weak west–east front that had become stationary,
parallel to the mid- and upper-tropospheric flow. The
MCS raced east-southeast during the following 15 h,
averaging more than 50 kt (25 m s
), despite the fact
that the mean cloud-layer wind over the region during
the period was westerly at only 25 kt (12 m s
Conditions were favorable for downwind develop-
ment as the boundary layer moisture axis extended east
into Wisconsin, and an easterly component was present
in the lower levels to enhance inflow to the gust front.
At the same time, capping associated with amplification
of the large-scale ridge upstream from the system (not
shown) prohibited convective initiation on the upwind
side of the cold pool produced by the first storms over
northwest North Dakota. Application of the downwind
vector technique (Fig. 8d) readily illustrates how ex-
1010 V
treme system motions can be attained when cell advec-
tion and propagation are not only additive, but propa-
gation speed is enhanced by an ‘‘opposing’’(in this case,
easterly) component to the boundary layer wind.
Another factor that can contribute to the rapid down-
wind movement and may have been a factor in thiscase
is of thermodynamic origin. It is frequently noted (e.g.,
Johns 1993) that boundary layer moisture tends to
‘‘pool’’ on the poleward side of weak warm-season
fronts, such as the one over South Dakota and lowa
(Fig. 8c). Indeed, evapotranspiration can significantly
augment the local boundary layer moisture content, es-
pecially when the mixed-layer depth remains constant
as a result of cloudiness and/or the presence of a frontal
inversion. The added moisture lowers the level of free
convection and assists convective initiation along the
gust front, thereby hastening downwind propagation.
c. Application of downwind technique to a cool-
season derecho: 20–21 November 1989
Although storm-scale downdrafts are believed to orig-
inate primarily above the lifting condensation level
(Wakimoto 2001), some of the cases examined in this
study suggest that forward propagation may also be fos-
tered by mesohigh development associated with the
presence of dry air in the subcloud layer. This ‘‘orga-
nized microburst’’ MCS mode occurs most frequently
in arid regions, although systems of this kind occasion-
ally develop elsewhere when moisture is sparse but steep
lower-tropospheric lapse rates are present to enhance
convective downdraft development. For example, sev-
eral mesosystems of this type have produced significant
wind damage in the mid-Atlantic region and over the
Midwest and plains in recent years. Moisture in such
situations is often so limited that thunderstorms can only
develop where sustained convergence is provided by a
gust front, orography, or some other mechanical initi-
ating mechanism. Once storms do form, the resulting
MCS is sustained by a downwind succession of micro-
Operational experience has shown that systems that
form in environments of this kind typically display weak
radar reflectivities but can produce devastating winds.
For example, in the 20 November 1989 case discussed
here, thunderstorm echo tops associated with the even-
ing squall line were at or below 20 000 ft (7 km), and
maximum reflectivities were less than 30 dBZ. Never-
theless, the storms produced a continuous swath of dam-
aging winds from central Pennsylvania into southeast
New York and southern New England, with measured
gusts in excess of 70 kt (35 m s
; Fig. 9a).
The environment across the mid-Atlantic region on
the afternoon of 20 November was characterized by fast,
largely unidirectional west-northwesterly flow in ad-
vance of a short-wave disturbance and cold front over
the upper Great Lakes (not shown). Modified, dry polar
air was present ahead of the front. Because boundary
layer moisture was limited [surface dewpoints below
458F(78C)], CAPE was minimal (Figs. 9b,c; note that,
because the sounding site was south of the MCS track
and south of the associated midlevel jet streak, an in-
version is depicted at 700 hPa that was substantially
weaker or nonexistent farther north). Nevertheless, lapse
rates were steep, especially for the time of the year and
the region. Sunshine and westerly (downslope) flow east
of the Appalachians warmed afternoon surface temper-
atures to the mid-60s Fahrenheit (18–208C) over the
lower elevations of eastern Pennsylvania and New Jer-
sey, producing large dewpoint depressions.
The warm
air enhanced the buoyancy, fostering late-day thunder-
storm development along the cold front in central Penn-
sylvania. Sustained uplift along the front and ideal con-
ditions for cold downdraft production allowed the
storms to grow quickly into a linear MCS. Because
storm advection and propagation were additive, thesys-
tem accelerated southeastward at nearly 60 kt (30 m
), more than 20 kt (10 m s
) faster than the mean
cloud-layer wind (Fig. 9d).
5. Practical aspects of application
a. Elevated systems
A significant forecast problem involving MCS de-
velopment on the cool side of surface boundaries is
determining whether the system will remain elevated or
will at some point become ‘‘rooted’’ in the boundary
layer. Dependent as they are on the existence of surface-
based convection along a gust front, it is clear that nei-
ther the original nor downwind versions of the vector
scheme can be applied to a purely elevated MCS. De-
termining the potential for surface-based development
with an elevated MCS is difficult, although systems with
strong cold pools and relatively warm/moist ‘‘cool’’ sec-
tors are good candidates. In the 19–20 July 1983 event,
for example, daytime heating eroded the shallow skin
layer present in the morning over North Dakota (Fig.
8b), resulting in a deep afternoon mixed layer over Min-
nesota and Wisconsin (not shown). This allowed bound-
ary layer parcels north of the stationary front to be lifted
along the gust front, contributing to the rapid down-
stream propagation observed. It should not be assumed,
however, that an MCS will remain completely elevated
just because the low-level air is cold (e.g., Schmidt and
Cotton 1989). Upon selection of a representative ‘‘in-
flow’’ wind, the vector technique may, of course, always
be used to estimate future system motion if it appears
that an elevated MCS might become surface based.
Such environments, in theory, are characterized by a substantial
degree of downdraft CAPE (DCAPE). Because of the limitations of
parcel theory used in its development DCAPE is often not a reliable
estimator of cold-pool strength, especially in the presence of sub-
stantial shear (Gilmore and Wicker 1998).
2003 1011CORFIDI
b. MCSs containing supercells and mesoscale
The presence of embedded supercells can signifi-
cantly affect MCS evolution and motion. Many MCSs,
especially those that produce derechos, initiate as su-
percells (e.g., Johns and Leftwich 1988; Klimowski et
al. 2000). In other cases, the onset of forward propa-
gation and bow-echo development appears to be related
to the appearance of rotating updrafts in existing con-
vection [e.g., the Texas derecho of 4 May 1989 (Smith
1990) and the 17 August 1994 Lahoma, Oklahoma,
event (Janish et al. 1996)]. At the same time, embedded
supercells sometimes occur in back-building or quasi-
stationary convection [e.g., Texas to Mississippi, 15–16
November 1987 (Corfidi et al. 1990) and Arkansas/Ten-
nessee, 1 March 1997 (Rogash et al. 2000)].
As Schmidt and Cotton (1989) and others have
shown, the presence of a supercell can drastically alter
storm-scale flow within an MCS, thereby influencing its
overall motion, strength, and longevity. For example,
in a case included in the developmental sample for the
downwind vector technique (case 46 in Table 1; Spoden
et al. 1998), forecast speed was significantly underes-
timated [forecast: 40 kt (20 m s
); observed: 70 kt (35
)], although the system’s eastward motion was
correctly depicted. The presence of a strong, cyclonic
circulation in the northern part of the MCS may have
hastened the system’s forward movement by increasing
westerly flow in the cold pool. In a case presented by
Schmidt and Cotton (1989), redistribution of the pre-
cipitation cascade by a persistent rotating storm in an
elevated squall line altered the shape of the system’s
cold pool. This not only affected storm propagation, but
also the location of strongest surface winds. It is also
worth noting that the presence of ‘‘book-end vortices’
can hasten MCS motion by fostering the development
of rear-inflow jets (e.g., Weisman 1993).
Long-lasting MCSs sometimes contain larger-scale
convectively induced circulations known as mesoscale
vorticity centers (MCVs). These features, which develop
in response to Coriolis acceleration of the rear-to-front
or front-to-rear flow and/or in response to tilting and
stretching of environmental and system-generated vor-
ticity, also affect MCS motion and longevity (e.g., Bran-
des 1990; Bartels and Maddox 1991; Davis and Weis-
man 1994; Skamarock et al. 1994; Trier et al. 1997;
Weisman and Davis 1998). The original dataset of Cor-
fidi et al. (1996) and the cases examined for the down-
wind vector technique include events with both MCVs
and supercells. In fact, the prominent mesoscale vortex
associated with one of the cases in the original study
(6–7 July 1982) was the subject of detailed investigation
(Menard and Fritsch 1989). Absence of high-resolution
radar data precludes an accurate assessment of the rel-
ative frequency of MCVs and supercells in the datasets
used to develop the vector technique. It is clear that the
influence of supercells and other vortices is too complex
to be addressed explicitly by the scheme. Nevertheless,
because the collective impact of these features was an
unwitting factor in its development, the presence of a
supercell or MCV in a given MCS does not necessarily
mean that the technique will yield erroneous results.
c. Influence of the background synoptic-scale
The advective component of MCS motion becomes
increasingly dominant relative to propagation as the
translational motion of the background synoptic-scale
‘‘support’’ for an MCS increases. This effect is most
apparent in conjunction with cool-season serial bow
MCSs (Johns and Hirt 1987). Because the support (usu-
ally a short-wave trough) in such cases often moves
rapidly, and because nearly saturated conditions and/or
inversions are typically present in the lower troposphere
to limit downwind propagation, the vector technique
often overestimates the motion of serial bows, as was
noted in section 3. With the convection confined to a
narrow zone of forced ascent along a front, systems of
this kind essentially move with the speed of the asso-
ciated synoptic-scale disturbance.
Although it is often not obvious to the casual ob-
server, the translational speed of an MCS’s synoptic
support can significantly influence the sensible weather
produced by the system. For example, cold fronts in
environments of strong, largely unidirectional flow are
often accompanied by quasi-linear MCSs (Hobbs and
Persson 1982). These systems sometimes exhibit con-
siderable forward motion because of movement of the
front (and the short-wave trough) and therefore often
do not yield excessive rainfall. Inspection of time-lapse
radar data and application of the original vector tech-
nique reveals, however, that many such MCSs are ac-
tually quasi stationary or back building relative to the
front. The absence of excessive precipitation reflects the
‘‘external’’ component of motion that maintains system
An example of this kind of event occurred in con-
junction with an intense cyclone over the Mississippi
Valley on 9–10 November 1998. The linear MCS in
question extended for more than 400 n mi (740 km),
embedded in deep unidirectional southwest flow ahead
of a progressive short-wave trough (Fig. 10a). The nar-
row line of forced convection moved northeast at 30 kt
(15 m s
), roughly with the speed of the cold front/
upper trough responsible for its development. The ther-
modynamic environment (not shown) was such that sur-
face-based storm initiation was prohibited except along
the front, and cold convective downdraft potential was
minimal. As a result, the weak cold pool that did develop
elongated parallel to the mean flow, and individual
storms trained from south to north along the boundary
as the convective system swept northeastward. Rain was
briefly heavy as the line passed, but excessive rainfall
1012 V
. 9. (a) Same as Fig. 7d, but for the forward-propagating MCS of 20–21 Nov 1989. (b)
Same as Fig. 5a, but for Sterling, VA (near Washington, DC), 0000 UTC 21 Nov 1989. (c) Same
as Fig. 7b, except valid 1800 UTC 20 Nov 1989. (d) Same as Fig. 8d, but for the 20–21 Nov
1989 MCS and based on sounding data in (c).
did not occur because of the external motion provided
by the synoptic-scale trough.
In contrast, extensive flooding accompanied a similar
convective system that moved very slowly across south-
ern California on 6 February 1998. The California MCS,
like the one over the central United States, was also
embedded in large-scale southwest flow ahead of a deep
trough. The translational motion of the region conducive
to thunderstorm development was limited in the Cali-
fornia event, however, because the large-scale pattern
was much less progressive (Fig. 10b). The short-wave
impulse approaching southern California at 1200 UTC
6 February lifted north-northeast to off of the Oregon
coast on 7 February, maintaining deep, unidirectional
southwesterly flow over the affected region for an ex-
tended period. As a result, excessive rainfall did occur,
and the training/back-building nature of the embedded
convection was more readily apparent than in the No-
vember event.
d. Environments of weak mean flow
In contrast to the systems embedded in strong mean
flow, the motion of convective systems in weak flow is
dominated by propagation. The advective component
2003 1013CORFIDI
nevertheless remains important in determining the most
favored direction for propagation.
The combination of strong propagation and weak
advection accounts for the somewhat unusual behavior
of the convective clusters that occasionally produce
damaging winds in the Phoenix, Arizona, area each
summer. Such systems are typically associated with
modest east to northeasterly midtropospheric flow
(e.g., Maddox et al. 1995; McCollum et al. 1995).
Northeasterly midlevel winds and downslope flow fa-
vor the southwestward motion of gust fronts produced
by diurnal thunderstorms forming over the high terrain
north and east of the city. Convergence along the con-
vective outflow, coupled with the presence of steep
lower-tropospheric lapse rates and large dewpoint de-
pressions, fosters additional downdraft development.
This outflow drives convective initiation sequentially
southwest across central and southern Arizona through
the day. Depending upon the boundary layer moisture
availability over the lower deserts, such activity some-
times propagates as far southwest as southern Cali-
fornia. The extent to which propagation is involved in
system motion is one of the more unique characteristics
of organized severe convection in Arizona, and sys-
tems of this kind are generally well forecast by the
downwind vector technique.
1014 V
. 10. (a) National Oceanic and Atmospheric Administration daily weather map of North American 500-hPa height analyses at (top)
1200 UTC 10 Nov and (bottom) 1200 UTC 11 Nov 1998. Heights (dam) are depicted by solid lines, and temperatures (8C) are shown by
dashed lines. Heavy solid line denotes the position of the linear MCS at map time. (b) Same as (a), but for (top) 1200 UTC 6 Feb and
(bottom) 1200 UTC 7 Feb 1998.
e. Computation of mean wind/cold-pool motion and
low-level inflow
Little has been said thus far about the depth of the
layer used to compute cloud-layer mean wind (in the
original technique) and cold-pool motion (in the down-
wind version). The layer used in the developmental da-
tasets, 850–300 hPa, was chosen because inclusion of
200-hPa data was found, on average, to overestimate ob-
served cell speed and, hence, the cloud-layer mean winds
computed for the original (Corfidi et al. 1996) study.
Examination of several recent forward-propagating
systems that moved faster than forecast by the down-
wind technique suggests, however, that the underesti-
mation may in fact have been due in part to exclusion
of data above 300 hPa. Because each case was char-
acterized by very large (i.e., greater than 5000 J kg
surface-based CAPE, it is speculated that a substantial
amount of cloud material was likely present above 300
hPa and/or that the cold pools were stronger and, there-
fore, faster moving than average. Use of wind data up
to 200 hPa is encouraged when calculating the mean
wind in regions of very high CAPE.
Careful consideration should also be given to the
depth of the layer used to estimate the low-level jet (or,
more proper, the propagation component) in the vector
scheme, because propagation is so sensitive to the lower-
tropospheric flow. Definitions suggested by Bonner
(1968) were used to identify low-level jets in theoriginal
2003 1015CORFIDI
(Corfidi et al. 1996) study. Given our limited under-
standing of the microphysical and cloud-scale aspects
of thunderstorm initiation and given the constraints of
parcel theory (e.g., Ziegler and Rasmussen 1998), it is
clear that selection of the most appropriate inflow layer
is best made on a case-by-case basis. For ease of cal-
culation, the maximum wind in the lowest 5000 ft (1.5
km) was found to provide a useful estimate in most of
the events used in the current study, but a somewhat
deeper layer might prove more appropriate when the
lifting condensation level is very high.
6. An MCS continuum
For the purposes of discussion, the MCSs in this pre-
sentation have been referred to as being of either the
forward- or backward-propagating type. In reality, of
course, the interplay of variables that affect MCS prop-
agation is complex and may vary over space and time.
As a result, observed systems typically exhibit a con-
tinuum of MCS propagational modes. Section 2 shows
that a given MCS may simultaneously exhibit both up-
wind and downwind development. The tendency for
downwind or upwind development may also change
over time. Forward-propagating systems, for example,
sometimes assume back-building characteristics later in
their life cycles, or at least periods of diminished down-
wind development. This change may occur as a result
of moistening of the low to midtroposphere by nearby
convection (which decreases negative buoyancy) and/
or as a result of diurnal cooling (which reduces potential
for new cell development). An event that exhibited such
evolution was the 4 October 1998 MCS in Kansas City.
Because propagation in real-life systems is rarelypurely
of one form or another, in general, it is advantageous
to recompute or slightly modify previously calculated
motion vectors to account for varying degrees of for-
ward propagation along the gust front over space and
time. This recomputation may require multiple ‘‘local
refinements’’ to previously computed vector calcula-
tions during the life of an event.
Researchers in recent decades have identified many
of the synoptic and mesoalpha-scale meteorological pat-
terns associated with MCSs that produce hazardous
weather such as excessive rainfall. These valuable in-
vestigations have enhanced recognition of impending
weather threats and have helped to increase warning lead
times. In some instances, however, it appears that at-
tention has been focused on enumerating minor differ-
ences that might exist between events occurring in dif-
ferent geographical areas or seasons at the expense of
emphasizing those characteristics universal to MCS-in-
duced weather hazards in general. For example, the
Johnstown flood in July of 1977 was one of the most
notorious mesohigh flash floods to have occurred in re-
cent years. Analysis reveals, however, that the mesoal-
pha-scale meteorological setup of the Johnstown tragedy
was very similar to that of the October 1998 flood in
Kansas City, even though the synoptic environments of
the two events were much different.
Both featured a
mesoscale outflow boundary that had become parallel
to the mean cloud-layer flow in a moist, largely uni-
directional wind regime, and, in both cases, the bound-
ary remained stationary for an extended period of time.
In lieu of pattern recognition, it seems advantageous
to focus on the salient processes common to such events
almost universally, regardless of the prevailing synoptic,
geographical, or seasonal environment. This idea is in
accord with the ingredients-based approach to forecasting
advocated by Doswell et al. (1996), and the vector con-
cept can be used to facilitate it. For example, from a
vector perspective, it is apparent that back-building
MCSs, lake-effect convective plumes (Peace and Sykes
1966; Niziol 1987), cool-season convective trains (Rey-
nolds 1998), and many cold-frontal rainbands are, in fact,
regional and/or seasonal variations of a common kine-
matic and thermodynamic theme: the presence of weak,
unidirectional cloud-layer flow in a nearly saturated en-
vironment, with a slow-moving or stationary initiating
mechanism. Lake-effect plumes produce heavy snow for
much the same reason that back-building MCSs produce
flash floods: system propagation is offset by advection,
and the initiating mechanism (a lake-enhanced boundary
in the case of snowbands; a gust front in the case of a
back-building MCS) remains nearly stationary.
7. Summary
A more complete technique for estimating short-term
MCS motion that builds on the work of Corfidi et al.
(1996) has been presented. It is based on the fact that
the preferred direction of system propagation (i.e., the
location of new cell development relative to existing
activity) is not always determined by the low-level jet.
Propagation direction is, instead, more generally dic-
tated by the location of maximum gust-front conver-
gence in the presence of conditional instability. For
some convective systems (in particular, many MCCs),
the location of maximum gust-front convergence is, in-
deed, in the direction of the low-level jet. Because their
advective motion is partially offset by propagation,
MCSs of this kind tend to move more slowly than the
mean cloud-layer flow. For these systems, the original
vector technique may be used to provide a forecast of
MCS motion.
In contrast, the greatest gust-front convergence occurs
on the downwind or forward side of bow-echo and de-
recho-producing convective systems. Such systems de-
velop when conditions are supportive of downstream
convective development along a gust front. Because the
advective and propagation components of overall sys-
tem motion are additive, these MCSs sometimes move
The Johnstown flood occurred near the axis of a broad upper-
level anticyclone, whereas the Kansas City event occurred on the
eastern side of a progressive, large-amplitude short-wave trough.
1016 V
faster than the mean wind. The downwind vector
scheme may be used to estimate their motion.
In part because system cold pools tend to elongate in
the direction of the mean wind over time, environments
of strong flow with minimal cloud-layer shear may be
associated with both forward-propagating MCSs and qua-
si-stationary and/or back-building systems. This situation
is especially true when wind profiles are unidirectional.
Portions of the gust front that align parallel to the mean
flow become favorable sites for upstream development,
whereas parts that orient perpendicularly become sup-
portive of downstream development. This observation,
coupled with knowledge of the spatial and temporal dis-
tribution of surface-based instability, may be used to de-
termine whether cell propagation will be directed primarily
upwind or downwind and, therefore, whether a system
will exhibit forward or back-building development (or per-
haps both) during its evolution (appendix).
Based as it is on simple assumptions about cold-pool
behavior and motion, the vector technique can, at best,
provide only a rough estimate of MCS movement. The
scheme could be refined by incorporating more detailed
real-time thermodynamic data that describe the potential
for convective downdraft development than are now
available. The technique, however, may be used with
both observed data and model output, and it can assist
in anticipating the predominant convective mode that
will be assumed by an incipient MCS. The scheme also
may be used to visualize better the constant interplay
between cell advection and propagation that accounts
for observed MCS motion.
Acknowledgments. The author thanks P. Banacos, D.
Blahyj, C. Doswell, J. Evans, S. Goss, D. Imy, R. Johns,
J. Kain, C. Mead, J. Moore, J. Racy, D. Schultz, D.
Stensrud, R. Thompson, and S. Weissfor valuable com-
ments and P. Banacos, G. Carbin, and P. Janish for as-
sistance with figures. Special thanks are given to J.
Evans for providing data on forward-propagating sys-
tems. Thanks also are given to R. Grumm, R. Maddox,
B. Schwartz, and an anonymous reviewer for providing
substantial constructive criticism of the manuscript.
Summary of Cold-Pool Factors that Affect
MCS Propagation
1) A cold pool will elongate in the direction of the mean
cloud-layer wind as a result of momentum transfer.
2) The degree of elongation increases as the wind pro-
file becomes more unidirectional, and this effect oc-
curs on all time- and space scales.
3) Propagation, or new cell development relative to ex-
isting storms, occurs most readily on the periphery
of the cold pool (i.e., along those portions of the gust
front), where the relative inflow is strongest and where
surface-based convective instability is present:
(a) upwind-developing MCSs are most favored
along quasi-stationary (mean flow parallel) por-
tions of the gust front, and
(b) downwind-developing MCSs are favored on the
more progressive (mean flow perpendicular)
parts of the boundary.
4) Thermodynamic factors modulate the role played by
gust-front orientation and motion:
(a) upwind-developing environments are character-
ized by comparatively moist conditions through
the low to midtroposphere and, therefore, rela-
tively weak convective-scale downdrafts, and
(b) downwind-developing environments are char-
acterized by comparatively dry conditions at
midlevels and/or in the subcloud layer and,
therefore, a tendency to produce strong convec-
tive-scale downdrafts.
Bartels, D. L., and R. A. Maddox, 1991: Midlevel cyclonic vortices
generated by mesoscale convective systems. Mon. Wea. Rev.,
119, 104–118.
Bluestein, H. B., and M. H. Jain, 1985: Formation of mesoscale lines
of precipitation: Severe squall lines in Oklahoma during spring.
J. Atmos. Sci., 42, 1711–1732.
Bonner, W. J., 1968: Climatology of the low-level jet. Mon. Wea.
Rev., 96, 833–850.
Bosart, L. F., and F. Sanders, 1981: The Johnstown Flood of July
1977: A long-lived convective system. J. Atmos. Sci., 38, 1616–
Brandes, E. A., 1990: Evolution and structure of the 6–7 May 1985
mesoscale convective system and associated vortex. Mon. Wea.
Rev., 118, 109–127.
Chappell, C. F., 1986: Quasi-stationary convective events. Mesoscale
Meteorology and Forecasting, P. S. Ray, Ed., Amer. Meteor.
Soc., 289–310.
Charba, J. P., 1974: Application of gravity current model to analysis
of squall-line gust front. Mon. Wea. Rev., 102, 140–156.
Coniglio, M. C., and D. J. Stensrud, 2001: Simulation of a progressive
derecho using composite initial conditions. Mon. Wea. Rev., 129,
Corfidi, S. F., 1998: Forecasting MCS mode and motion. Preprints,
19th Conf. on Severe Local Storms, Minneapolis, MN, Amer.
Meteor. Soc., 626–629.
——, N. W. Junker, and F. H. Glass, 1990: The Louisiana/Mississippi
flash flood and severe outbreak of 15–16 November 1987. Pre-
prints, 16th Conf. on Severe Local Storms, Kananaskis Park, AB,
Canada, Amer. Meteor. Soc., 627–633.
——, J. H. Merritt, and J. M. Fritsch, 1996: Predicting the movement
of mesoscale convective complexes. Wea. Forecasting, 11, 41–
Davis, C. A., and M. L. Weisman, 1994: Balanced dynamics of me-
soscale vortices produced in simulated convective systems. J.
Atmos. Sci., 51, 2005–2030.
Doswell, C. A., III, H. E. Brooks, and R. A. Maddox, 1996: Flash
flood forecasting: An ingredients-based methodology. Wea.
Forecasting, 11, 560–581.
Droegemeier, K. K., and R. B. Wilhelmson, 1987: Numerical simu-
lation of thunderstorm outflow dynamics. Part 1: Outflow sen-
sitivity experiments and turbulence dynamics. J. Atmos. Sci., 44,
Evans, J. S., and C. A. Doswell III, 2001: Examination of derecho
environments using proximity soundings. Wea. Forecasting, 16,
Fovell, R. G., and Y. Ogura, 1989: Effect of vertical wind shear on
2003 1017CORFIDI
numerically simulated multicell storm structure. J. Atmos. Sci.,
46, 3144–3176.
Gilmore, M. S., and L. J. Wicker, 1998: The influence of midtro-
pospheric dryness on supercell morphology and evolution. Mon.
Wea. Rev., 126, 943–958.
Goff, R. C., 1976: Vertical structure of thunderstorm outflows. Mon.
Wea. Rev., 104, 1429–1440.
Hamilton, R. E., 1970: Use of detailed intensity radar data in me-
soscale surface analysis of the July 4, 1969 storm in Ohio. Pre-
prints, 14th Radar Meteorology Conference, Tucson, AZ, Amer.
Meteor. Soc., 339–342.
Hobbs, P. V., and O. G. Persson,1982: The mesoscale and microscale
structure and organization of clouds and precipitation in mid-
latitude cyclones. Part V: The substructure of narrow cold-frontal
rainbands. J. Atmos. Sci., 39, 280–295.
Houze, R. A., Jr., 1993: Cloud Dynamics. Academic Press, 570 pp.
Hoxit, L. R., R. A. Maddox, C. F. Chappell, F. L. Zuckerberg, H. M.
Mogil, and I. Jones, 1978: Meteorological analysis of the Johns-
town, PA flash flood, 19–20 July 1977. NOAA Tech. Rep. ERL
401-APCL 43, 71 pp.
Janish, P. R., R. H. Johns, and K. C. Crawford, 1996: An evaluation
of the 17 August 1994 Lahoma, Oklahoma, supercell/MCS event
using conventional and non-conventional analysis and forecast-
ing techniques. Preprints, 18th Conf. on Severe Local Storms,
San Francisco, CA, Amer. Meteor. Soc., 76–80.
Johns, R. H., 1993: Meteorological conditions associated with bow
echo development in convective storms. Wea. Forecasting, 8,
——, and W. D. Hirt, 1985: The derecho of July 19–20, 1983 . . . A
case study. Natl. Wea. Digest, 10, 17–32.
——, and ——, 1987: Derechos: Widespread convectively induced
windstorms. Wea. Forecasting, 2, 32–49.
——, and P. W. Leftwich, 1988: The severe thunderstorm outbreak
of 28–29 July 1986: A case exhibiting both isolated supercells
and a derecho-producing convective system. Preprints, 15th
Conf. on Severe Local Storms, Baltimore, MD, Amer. Meteor.
Soc., 448–451.
——, K. W. Howard, and R. A. Maddox, 1990: Conditions associated
with long-lived derechos: An examination of the large-scale en-
vironment. Preprints, 16th Conf. on Severe Local Storms, Kan-
anaskis Park, AB, Canada, Amer. Meteor. Soc., 408–412.
Junker, N. W., R. S. Schneider, and S. L. Fauver, 1999: A study of
heavy rainfall events during the Great Midwest Flood of 1993.
Wea. Forecasting, 14, 701–712.
Klimowski, B. A., R. Przybylinski, G. Schmocker, andM. R. Hjelm-
felt, 2000: Observations of the formation and early evolution of
bow echoes. Preprints, 20th Conf. on Severe Local Storms, Or-
lando, FL, Amer. Meteor. Soc., 44–47.
Maddox, R. A., 1980: Mesoscale convective complexes. Bull. Amer.
Meteor. Soc., 61, 1374–1387.
——, C. F. Chappell, and L. R. Hoxit, 1979: Synoptic and meso-
scale aspects of flash flood events. Bull. Amer. Meteor. Soc., 60,
——, D. M. McCollum, and K. W. Howard, 1995: Large-scale pat-
terns associated with severe summertime thunderstorms over
central Arizona. Wea. Forecasting, 10, 763–778.
McCollum, D. M., R. A. Maddox, and K. W. Howard, 1995: Case
study of a severe mesoscale convective system in central Ari-
zona. Wea. Forecasting, 10, 643–665.
Menard, R. D., and J. M. Fritsch, 1989: A mesoscale convective
complex–generated inertially stable warm core vortex. Mon.
Wea. Rev., 117, 1237–1261.
Merritt, J. H., and J. M. Fritsch, 1984: On the movement of the heavy
precipitation areas of mid-latitude mesoscale convective com-
plexes. Preprints, 10th Conf. on Weather Analysis and Fore-
casting, Clearwater Beach, FL, Amer. Meteor. Soc., 529–536.
Moore, J. T., C. H. Pappas, and F. H. Glass, 1993: Propagation char-
acteristics of mesoscale convective systems. Preprints, 17th
Conf. on Severe Local Storms, St. Louis, MO, Amer. Meteor.
Soc., 538–541.
Newton, C. W., and S. Katz, 1958: Movement of large convective
rainstorms in relation to winds aloft. Bull. Amer. Meteor. Soc.,
39, 129–136.
Niziol, T. A., 1987: Operational forecasting of lake effect snowfall
in western and central New York. Wea. Forecasting, 2, 310–
Orlanski, I., 1975: A rational subdivision of scales for atmospheric
processes. Bull. Amer. Meteor. Soc., 56, 527–530.
Parker, M. D., and R. H. Johnson, 2000: Organizational modes of
midlatitude mesoscale convective systems. Mon. Wea. Rev., 128,
Peace, R. L., and R. B. Sykes Jr., 1966: Mesoscale study of a lake
effect snowstorm. Mon. Wea. Rev., 94, 495–507.
Pontrelli, M. D., G. Bryan, and M. Fritsch, 1999: The Madison Coun-
ty, Virginia, flash flood of 27 June 1995. Wea. Forecasting, 14,
Przybylinski, R. W., 1995: The bow echo: Observations, numerical
simulations, and severe weather detection methods. Wea. Fore-
casting, 10, 203–218.
Purdom, F. W., 1973: Meso-highs and satellite imagery. Mon. Wea.
Rev., 101, 180–181.
Ray, P., 1990: Convective dynamics. Radar in Meteorology, D. Atlas,
Ed., Amer. Meteor. Soc., 348–400.
Reynolds, D. W., 1998: Cool season convective trains. Preprints, 16th
Conf. on Weather Analysis and Forecasting, Phoenix, AZ, Amer.
Meteor. Soc., 199–201.
Rogash, J. A., and R. D. Smith, 2000: Multiscale overview of a violent
tornado outbreak with attendant flash flooding. Wea. Forecast-
ing, 15, 416–431.
Rotunno, R., J. B. Klemp, and M. L. Weisman, 1988: A theory for
strong, long-lived squall lines. J. Atmos. Sci., 45, 463–485.
Schmidt, J. M., and W. R. Cotton, 1989: A High Plains squall line
associated with severe surface winds. J. Atmos. Sci., 46, 281–
Skamarock, W. C., M. L. Weisman, and J. B. Klemp, 1994: Three-
dimensional evolution of simulated long-lived squall lines. J.
Atmos. Sci., 51, 2563–2584.
Smith, B. E., 1990: Mesoscale structure of a derecho-producing con-
vective system: The southern Great Plains storms of 4 May 1989.
Preprints, 16th Conf. on Severe Local Storms, Kananaskis Park,
AB, Canada, Amer. Meteor. Soc., 455–460.
Spoden, P. J., C. N. Jones, J. Keysor, and M. Lamb, 1998: Obser-
vations of flow structure and mesoscale circulations associated
with the 5 May 1996 asymmetric derecho in the lower Ohio
Valley. Preprints, 19th Conf. on Severe Local Storms, Minne-
apolis, MN, Amer. Meteor. Soc., 514–517.
Trier, S. B., W. C. Skamarock, and M. A. LeMone, 1997: Structure
and evolution of the 22 February 1993 TOGA COARE squall
line: Organization mechanisms inferred from numerical simu-
lation. J. Atmos. Sci., 54, 386–407.
Wakimoto, R. M., 1982: The life cycle of thunderstorm gust fronts
as viewed with Doppler radar and rawinsonde data. Mon. Wea.
Rev., 110, 1060–1082.
——, 2001: Convectively driven high wind events. Severe Convective
Storms, Meteor. Monogr., No. 50, Amer. Meteor. Soc., 255–298.
Weisman, M. L., 1993: The genesis of severe, long-livedbow echoes.
J. Atmos. Sci., 50, 645–670.
——, and C. A. Davis, 1998: Mechanisms for the generation of
mesoscale vortices within quasi-linear convective systems. J.
Atmos. Sci., 55, 2603–2622.
Ziegler, C. L., and E. N. Rasmussen, 1998: The initiation of moist
convection at the dryline: Forecasting issues from a case study
perspective. Wea. Forecasting, 13, 1106–1130.
... The motion of a convective system can be considered as the vector sum of (1) an advection component approximated by the direction and magnitude of the mean cloudlayer wind, which is represented by the average wind of 300, 500, 700 and 850 hPa, and (2) a propagation component governed by the location of new cell (Newton and Katz 1958;Corfidi 2003). MCS propagation can be influenced by many factors, such as the distribution of convective available potential energy (CAPE), convective inhibition (CIN), outflow boundaries, gravity waves and orographic effects. ...
... direction to the LLJ (Corfidi et al. 1996;Corfidi 2003). As mentioned above, most MCSs in North China move eastward, they have the longest moving distance, and their average moving direction is consistent with the advection component ( Fig. 6a-1). ...
Full-text available
In this study, a total of 339 mesoscale convective systems (MCSs) are obtained in North China using the temperature of brightness blackbody (TBB) data from the FY-2E in the warm season from 2010 to 2018. The number of meso-α-scale convective systems (MαCSs) is much more than that of meso-β-scale convective systems (MβCSs). The number of mesoscale elongated convective systems (MECSs) is more than that of mesoscale circular convective systems (MCCSs). Most MCSs occur in July and August, which have the widest influence range, the longest duration, and the strongest convection. The MαCS develops slowly and weakens rapidly. The diurnal variation of MαCSs presents a bimodal distribution, most of MαCSs form in the afternoon, while some of MαCSs form in the evening. The MCSs activities in the warm season of North China are concentrated in two belts, namely, the east–west-oriented belt along Henan Province, Shandong Province and the Yellow Sea, and the south–north-oriented belt along central-western Shandong, Tianjin City, the west of Bohai Sea and the northeast of Hebei Province. MCSs mainly move eastward, and only some MECSs move southwestward and northwestward. The easterly and northerly moving MCSs are mainly affected by the steering flow, while the southerly moving MCSs are mainly affected by storm propagation. The MCSs of North China mainly form in the high temperature, high humidity and high energy area, with favorable dynamic conditions, such as middle-level trough or vortex, low-level shear line, surface inverted trough or surface convergence line, and the terrain. Meanwhile, the MCS pregnant environment is often accompanied by low-level jet and relatively strong vertical wind shear.
... -8 September 2022 (Fig. 1b): it is characterized by the evolution of a supercell into a quasi-linear convective system (QLCS) and then, for a short period, into a stationary V-shaped storm, with accumulated rainfall up to 163 mm in 3 h. Corfidi (2003) vectors were helpful for forecasters to predict the correct evolution of the system. Compared to the operational prediction of the case of 2012, more precise indications on the affected areas (the east side of the region) were added by local forecasters. ...
... Therefore, warnings are issued only after the merging of different forecasters' opinions, to take into account different perspectives in the prediction. The application of some propagation vectors, well known in the scientific literature, such as Corfidi (2003) and Bunkers et al. (2006) vectors, can be helpful to identify the right conceptual model, although they are mainly diagnostic tools for the a posteriori analysis. Limited area models are analyzed to provide support to the correct interpretation of the scenario, but often they do not provide exact information on the occurrence of the event in time and space. ...
Full-text available
A workshop on high-impact meteorological events in Italy was jointly organized by the newly formed Italia Meteo Agency (AIM) and the Italian Association of Atmospheric Sciences and Meteorology (AISAM) on September 27, 2022. The aim of the workshop was to promote the sharing of the experiences that all operational and research meteorological centers in Italy have gained on specific types of high-impact events, favoring the establishment of a common know-how of Italian operational meteorology.
... Efforts to better understand the initiation and maintenance of back-building MCSs can be traced back to Miller (1978), who found such MCSs occurred along outflows produced from previous convection. Corfidi et al. (1996) and Corfidi (2003) also investigated back-building MCSs and found that their propagation direction is generally dictated by the location of the maximum low-level convergence along the cold pool within a conditionally unstable environment. In contrast, based on their analysis of six back-building cases, Schumacher and Johnson (2009) found no apparent surface boundaries nearby, but noted the presence of a midlevel cyclonic vorticity maximum generated by the MCS that is often referred to as a mesoscale convective vortex (MCV). ...
Full-text available
The bow-and-arrow Mesoscale Convective System (MCS) has a unique structure with two convective lines resembling the shape of an archer's bow and arrow. These MCSs and their arrow convection (located behind the MCS leading line) can produce hazardous winds and flooding extending over hundreds of kilometers, which are often poorly predicted in operational forecasts. This study examines the dynamics of a bow-and-arrow MCS observed over the Yangtze-Huai Plains of China, with a focus on the arrow convection provided. The analysis utilized backward trajectories and Lagrangian vertical momentum budgets to simulations employing the WRF-ARW and CM1 models. Cells within the arrow in the WRF-ARW simulations of the MCS were elevated, initially forming as convectively unstable air within the low-level jet (LLJ), which gently ascended over the cold pool and converged with the MCS's mesoscale convective vortex (MCV) at higher altitudes. The subsequent ascent in these cells was enhanced by dynamic pressure forcing due to the up-draft being within a layer where the vertical shear changed with height due to the superposition of the LLJ and the MCV. These dynamic forcings initially played a larger role in the ascent than the parcel's buoyancy. These findings were bolstered by idealized simulations employing the CM1 model. These results illustrate a challenge for accurately forecasting bow-and-arrow MCSs as the updraft magnitude depends on dynamical forcing associated with the interaction between vertical shear associated with the environment and due to convectively generated circulations.
... The composite hodographs show, in both regions, a very similar shape of the RAOB and ERA5 data, proving the ability of the latter to correctly reproduce the observed wind profiles. For CT, the linear shape indicates more favorable conditions for multicell systems [37], with some directional shear distinguishable only at the lower levels. The latter is mainly due to the contribution of the tornadoes originated inland ( Figure A1a), while for those originated as waterspouts ( Figure A1b) the low-level shear is mainly related to a strong change in wind speed and very weak directional shear in the lower 1 km (this behavior suggests the presence of a low-level jet and favorable conditions for isolated supercells in this subcategory). ...
Full-text available
An updated climatology of EF1+ (Enhanced Fujita category 1 or stronger) tornadoes in Italy (445 events in the period of 1990–2021) confirms that the central Tyrrhenian (CT) and the southeastern (SE) regions of the Italian peninsula represent two of the areas most affected by tornadoes in the Mediterranean. We performed a comparative analysis between these two hotspots, examining the large-scale atmospheric features associated to the tornado occurrences, throughout the analysis of radiosounding observations and reanalysis (ERA5) fields. The conditions in which the tornadoes develop are investigated using metrics regarding atmospheric instability and/or horizontal/vertical wind shear. Common synoptic characteristics are found for both regions, i.e., a prevalent occurrence of tornadoes on the eastern flank of approaching troughs, with moderate shear/CAPE mean values. A large number of events develop in a high-shear/low-CAPE (HSLC) environment, in the presence of positive sea surface and 850 hPa temperature anomalies. Conversely, the upper-level winds suggest different characteristics of the tornado-spawning cells in the two areas, i.e., multi-cells/linear systems for CT and isolated supercells for SE. The maximum values for some typical atmospheric fields/instability parameters in the areas around the tornado hotspots permit the obtention of thresholds that identify the most favorable environments for tornado formation in these Italian areas.
... The composite hodographs (figure 3c-d) show a very similar shape in the two cases (RAOB and ERA5), with moderate values of bulk shear. Mean southerlies are visible in the low levels and westsouthwesterlies above; the storm relative motion is toward the right of the vertically averaged steering flow, following Corfidi et al. (1996) and Corfidi (2003). In this relatively straight hodograph, directional shear is noticeable only in the low levels. ...
Full-text available
On 28 July 2019 an EF2 tornado affected a small rural area in central Italy causing several damages and one casualty. The tornado was spawned by a thunderstorm embedded in a linear convective system that crossed the central Tyrrhenian regions of Italy. The environment was characterized by high values of convective available potential energy (CAPE) and deep layer wind shear (DLS). The severity of this type of events highlights the importance of carrying out multi-scale integrated analysis on tornado phenomena in the area, one of the most affected by these events and on which dedicated studies have not yet been carried out so far. Tornadoes in the area are identified in the years 1990–2021, allowing to perform a synoptic/mesoscale analysis of the main patterns associated to these events. The 32-year analysis is carried out using both radiosonde observations and ERA5 reanalysis. The average synoptic configuration is dominated by an upper level trough over the central Mediterranean Sea and by a low surface pressure area over northwestern Italy, with southwesterly upper-level winds over the Tyrrhenian Sea and higher-than-average northwesterly winds entering the western Mediterranean through the gulf of Lion. Moderate mean values of CAPE (about 700 J Kg⁻¹) and DLS (about 15 m s⁻¹) are found, and the linear shape of the hodograph indicates favorable conditions for multicell systems. High-resolution WRF (Weather Research and Forecasting) model simulations of the 28 July 2019 case study correctly reproduced the event and the structure of the storm. Extreme values of the typical instability parameters/indices denote an environment particularly favorable for tornado formation; some sensitivity tests permitted to evaluate the role of several forcing (Sea Surface Temperature, surface fluxes and orography) in the development and the trajectory of the storm.
... This method classifies the wind field in six main wind sector types, with an additional undefined type when no majority is found, being further discriminated by the degree of cyclonicity, resulting in 14 atmospheric circulation types. The levels of 700 hPa and 500 hPa were chosen since they are regularly used by forecasters to identify the horizontal movement of the convective systems (Corfidi, 2003). Actually, due to this feature, we considered this classification as the base for our final classification of the hailfall days ( Figure 4). ...
The current study aims to portray the specific weather patterns associated with hail falls in north-eastern Romania. This was done using multiple hail records data covering a long period of time (1981–2020). COST733 software enabled us to assess objectively the atmospheric circulation classification types for the middle troposphere (500 hPa) and also for the ground level (sea level pressure) over the study region. Based on these, we have identified 5 major weather patterns (MPs) which explain up to 85% of the recorded hail events over the region. In terms of wind vector direction and speed, driving the hailstorm cells, these MPs are represented by two main groups of synoptic patterns. The first one is characterized by weak advective patterns (cut-off lows, north-easterly anticyclonic flow), while the second one is characterized by strong advective patterns (westerly, south-westerly, and north-westerly atmospheric flows). Further, these major patterns are split into 16 combined circulation types (CCTs), as indicated by the atmospheric circulation at the ground level. Our analysis showed that in May and June hailstorms are determined especially by weak advective patterns over north-eastern Romania, while from June to August the strong advective patterns are more common for these extreme weather events. The atmospheric environment associated with these synoptic conditions, as indicated by instability parameters, is also described using a series of atmospheric parameters: sea pressure level, 500 hPa geopotential field, 700 hPa wind vector, and precipitation amount at the continental scale. This analysis indicates that hail occurs in a regional atmospheric environment characterized by a MUCAPE >500 J/kg and high wind shear in the lower troposphere. The results obtained are meant to become a useful tool in regional hail forecast.
... Investigating the propagation velocity of MCS is not only of fundamental scientific interest, but is also of utility for operational severe weather forecasting given that estimating approximate time-of-arrival is important for early warnings and severe-weather preparedness [167,168]. In addition, for a region of complex terrain such as the NAM, exploring which mechanisms are responsible for MCS propagation is an urgent task [23,159,161,169,170]. For the purpose of this study, we focus on MCS occurring between 2011-2017 so that lightning data can be employed to explore the intensity and convective lifecycle along these three common trajectories. ...
Full-text available
Mesoscale Convective Systems (MCS) may vary greatly with respect to their morphology, propagation mechanism, intensity, and under which synoptic-scale conditions as a function of topographic complexity. In this study, we develop a long-term climatology of MCS during the North American Monsoon focusing on MCS morphology, lifecycle, and intensity as well as possible propagation mechanisms. We employ an MCS tracking and classification technique based on 23 years (1995 to 2017) of GOES IR satellite data. MCS intensity is also gauged with 7 years (2011 to 2017) of Vaisala GLD360 lightning data and, finally, monthly and interannual variability in synoptic conditions are examined with ERA5 reanalysis data. Our results based on 1594 identified MCS reveal that 98% are morphologically classified as Persistent Elongated Convective Systems. During the 23 summers (June through September) observed, the number of MCS varied considerably, averaging 70 MCS with minimum of 41 and maximum of 94. MCS typically have an average duration of around 8 h ± with a 2 h standard deviation. Propagation speeds, estimated with Hovmöller diagrams in addition to MCS centroid initial and final position, vary slightly depending on the trajectory. A notable result suggests that MCS propagation speeds are more consistent density currents or cold pools and not gravity waves nor steering-level winds. The results of this study could also provide a dataset for examining larger-scale controls on MCS frequency in addition to assesing convective parameterization and convective-resolving models in regions of complex topography.
Full-text available
This study examines the deep convection populations and mesoscale convective systems (MCSs) simulated in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non‐hydrostatic domains) winter project. A storm tracking algorithm is applied to six DYAMOND simulations and a global high‐resolution satellite cloud and precipitation data set for comparison. The simulated frequencies of tropical deep convection and organized convective systems vary widely among models and regions, although robust MCSs are generally underestimated. The diurnal cycles of MCS initiation and mature stages are well simulated, but the amplitudes are exaggerated over land. Most models capture the observed MCS lifetime, cloud shield area, rainfall volume and movement speed. However, cloud‐top height and convective rainfall intensity are consistently overestimated, and stratiform rainfall area and amount are consistently underestimated. Possible causes for the model differences compared to observations and implications for future model developments are discussed.
The degree of improvement in convective representation in NWP with horizontal grid spacings finer than 3 km remains debatable. While some research suggests sub-km horizontal grid spacing is needed to resolve details of convective structures, other studies have shown that decreasing grid spacing from 3-4 km to 1-2 km offers little additional value for forecasts of deep convection. In addition, few studies exist to show how changes in vertical grid spacing impact thunderstorm forecasts, especially when horizontal grid spacing is simultaneously decreased. The present research investigates how warm-season central U.S. simulated MCS cold pools for eleven observed cases are impacted by decreasing horizontal grid spacing from 3 to 1 km while increasing the vertical levels from 50 to 100 in WRF runs. 3 km runs with 100 levels produced the deepest and most negatively buoyant cold pools compared to all other grid spacings since updrafts were more poorly resolved, resulting in a higher flux of rearward-advected frozen hydrometeors, whose melting processes were augmented by the finer vertical grid spacing, which better resolved the melting layer. However, the more predominant signal among all eleven cases was for more expansive cold pools in 1 km runs, where the stronger and more abundant updrafts focused along the MCS leading line supported a larger volume of concentrated rearward hydrometeor advection and resultant latent cooling at lower levels.
The quantitative precipitation forecast (QPF) performance by numerical weather prediction (NWP) methods depends fundamentally on the adopted physical parameterization schemes (PS). However, due to the complexity of the physical mechanisms of precipitation processes, the uncertainties of PSs result in a lower QPF performance than their prediction of the basic meteorological variables such as air temperature, wind, geopotential height, and humidity. This study proposes a deep learning model named QPFNet, which uses basic meteorological variables in the ERA5 dataset by fitting a non-linear mapping relationship between the basic variables and precipitation. Basic variables forecasted by the highest-resolution model (HRES) of the European Centre for Medium-Range Weather Forecasts (ECMWF) were fed into QPFNet to forecast precipitation. Evaluation results show that QPFNet achieved better QPF performance than ECMWF HRES itself. The threat score for 3-h accumulated precipitation with depths of 0.1, 3, 10, and 20 mm increased by 19.7%, 15.2%, 43.2%, and 87.1%, respectively, indicating the proposed performance QPFNet improved with increasing levels of precipitation. The sensitivities of these meteorological variables for QPF in different pressure layers were analyzed based on the output of the QPFNet, and its performance limitations are also discussed. Using DL to extract features from basic meteorological variables can provide an important reference for QPF, and avoid some uncertainties of PSs.
Full-text available
An approach to forecasting the potential for flash flood-producing storms is developed, using the notion of basic ingredients. Heavy precipitation is the result of sustained high rainfall rates. In turn, high rainfall rates involve the rapid ascent of air containing substantial water vapor and also depend on the precipitation efficiency. The duration of an event is associated with its speed of movement and the size of the system causing the event along the direction of system movement. This leads naturally to a consideration of the meteorological processes by which these basic ingredients are brought together. A description of those processes and of the types of heavy precipitation-producing storms suggests some of the variety of ways in which heavy precipitation occurs. Since the right mixture of these ingredients can be found in a wide variety of synoptic and mesoscale situations, it is necessary to know which of the ingredients is critical in any given case. By knowing which of the ingredients is most important in any given case, forecasters can concentrate on recognition of the developing heavy precipitation potential as meteorological processes operate. This also helps with the recognition of heavy rain events as they occur, a challenging problem if the potential for such events has not been anticipated. Three brief case examples are presented to illustrate the procedure as it might be applied in operations. The cases are geographically diverse and even illustrate how a nonconvective heavy precipitation event fits within this methodology. The concept of ingredients-based forecasting is discussed as it might apply to a broader spectrum of forecast events than just flash flood forecasting.
Full-text available
Models, used in juxtaposition, enable us to address the important theoretical issue of whether a squall line is a system of special, a long-lived cells, or whether it is a long-lived system of ordinary, short-lived cells. Our review of the observational literature indicates that the latter is the most consistent paradigm for the vast majority of cases, but, on occasion, a squall line may be composed of essentially steady, supercell thunderstorms. The numerical experiments presented herein show that either type of squall line may develop from an initial line-like disturbance depending on the magnitude and orientation of the environmental shear with respect to the line. -from Authors
Quasi-stationary, or very slowly moving, storm systems are of particular interest to the forecaster, because they frequently produce heavy rainfall and flash floods. These convective weather systems are composed at any moment of many individual storms, all in various stages of their life cycles. The individual storms frequently have trajectories that carry them repeatedly over the same region, producing pulsating heavy rains that quickly cause streams and rivers to overflow their banks.
By means of hourly rainfall data from the Hydroclimatic Network, the motions of large rainstorms, of the kind associated with squall lines, are examined in relation to the winds aloft. Very little correlation is found between the speed of movement of the rainstorms and the wind speed at any level, although the fastest moving storms were associated with strong winds aloft. Significant correlation is found between direction of motion of rainstorms, and wind direction at 700 mb or higher levels. On the average, the rainstorms move with an appreciable component toward right of the wind direction. The difference between these results, and those from other studies based on small precipitation areas, is ascribed to propagation. The mechanism involved is discussed briefly.
A particular class of weather system, the Mesoscale Convective Complex (MCC), is identified, defined, and contrasted with other types of convective weather systems. It is found that MCC systems frequently occur over the central United States, grow to tremendous areal extent, and often persist for periods exceeding 12 h. -from Author
In this first paper of a two-part series, a two-dimensional numerical model is developed and used to investigate the dynamics of thunderstorm outflows. By focusing only on the outflow and using essentially inviscid equations and high spatial resolution, we are able to explicitly represent important physical processes such as turbulent mixing. To simplify interpretation of the results, the model atmosphere used in all experiments is calm and dry adiabatic. This approach allows us to establish basic characteristics of modeled outflows in simple physical settings, and provides a foundation for future studies using more realistic environments.All simulated outflows are initialized by prescribing a (controlled) horizontal flux of cold air into the model domain through a lateral boundary. In a series of sensitivity tests, we examine three parameters of the cold air source region: 1) the vertical temperature deficit profile, 2) the magnitude of the temperature deficit, and 3) the cold-air depth. By holding two of these quantities fixed while varying the third, we establish relationships among outflow speed, depth, and internal temperature deficit by comparing model results with laboratory density current experiments, inviscid fluid theory, and observations of thunderstorm outflows.Our simulations indicate that the internal outflow head circulation is governed primarily by the outflow's vertical temperature distribution, and that this circulation plays a key role in determining the gust front propagation speed and outflow head depth. A pressure jump precedes the onset of cold air at the surface, and is shown to be dynamically induced by the collision of the outflow and environmental air masses at the gust front. In addition, the surface pressure distribution behind the outflow head is a consequence not only of hydrostatic effects, but also horizontal rotation aloft associated with a breaking head wave.Turbulent mixing within the modeled outflows is associated with breaking Kelvin-Helmholtz billows which form at the shear interface atop the cold-air pool. These billows are qualitatively and quantitatively similar to turbulent eddies found in laboratory density currents, and are found to be sensitive to the magnitude of the computational smoothing as well as the grid resolution. Time-dependent air parcel trajectories are utilized to elucidate the kinematic structure of the simulated flow fields.
This paper discusses common modes of mesoscale convective organization. Using 2-km national composite reflectivity data, the authors investigated linear mesoscale convective systems (MCSs) that occurred in the central United States during May 1996 and May 1997. Based upon the radar-observed characteristics of 88 linear MCSs, the authors propose a new taxonomy comprising convective lines with trailing (TS), leading (LS), and parallel (PS) stratiform precipitation. While the TS archetype was found to be the dominant mode of linear MCS organization, the LS and PS archetypes composed nearly 40% of the studied population. In this paper, the authors document the characteristics of each linear MCS class and use operational surface and upper air data to describe their different environments. In particular, wind profiler data reveal that the stratiform precipitation arrangement associated with each class was roughly consistent with the advection of hydrometeors implied by the mean middle- and upper-tropospheric storm-relative winds, which were significantly different among the three MCS modes. Case study examples are presented for both the LS and PS classes, which have received relatively little attention to this point. As well, the authors give a general overview of the synoptic-scale meteorology accom- panying linear MCSs in this study, which was generally similar to that observed by previous investigators.
This study focuses on the progressive derecho, a widespread, convectively induced windstorm produced by a mesoscale convective system that often occurs within a relatively benign synoptic-scale environment. Sounding data from 12 progressive derechos, which occurred in weakly forced large-scale environments, are composited in order to examine important large-scale features in the preconvective environment. This analysis captures many features that are common in warm season derecho environments, such as an upper-level wind maximum, a relatively dry midtroposphere, and low-level warm advection. Initial and boundary conditions for the Pennsylvania State University-National Center for Atmospheric Research fifth-generation Mesoscale Model (MM5) are created using this analysis. A three-dimensional, horizontally nonhomogeneous, explicitly resolved simulation of a progressive derecho is produced and compared to previous, more idealized simulations of similar convective systems that have been used to explain the strength and structure of observed long-lived squall lines and bow echoes. A subset of previous squall line simulations produced within horizontally homogeneous environments without wind shear above 5 km suggests that a balance between the positive vorticity associated with the environmental low-level shear (Deltau) and the negative vorticity created baroclinically at the leading edge of the cold pool (C) is the essential ingredient that determines the strength and time-dependent structure of long-lived squall lines (local balance theory). In the simulation presented here, which occurs in an environment with deep-tropospheric shear but relatively weak low-level shear, the model develops a realistic, rapidly moving squall line with embedded bow echoes that maintains its strength for much longer than the squall lines within previous idealized simulations that develop and evolve within similar less than optimal balance conditions (C/Deltau > 2). Previous simulations of squall lines under similar less than optimal conditions contain updrafts that progressively weaken and become more upshear tilted with time as the cold pool surges ahead of the updrafts within 1-3 h after the system develops. However, the simulated squall line used here contains convective updrafts that remain almost directly above the gust front, maintains a nearly constant upshear tilt for several hours, and produces severe, near-surface winds for over 8 h. Examination of the maximum grid-resolved vertical velocity indicates that the cells are not weakening with time relative to their thermodynamic potential, which contrasts the behavior of the cells within the less than optimal squall lines of the previous, idealized simulations. These results support the idea that local balance theory, which attempts to explain both the strength and longevity of squall lines, may be incomplete within environments that often favor warm season progressive derechos. In particular, tests with a simple two-dimensional cloud-scale model indicate that both significant upper-tropospheric shear above 5 km (which is found in the composite analysis and in the MM5 solution) and low-level shear play significant roles in maintaining the strength of squall lines over long periods and need to be considered in order to fully understand and forecast these events.
Despite the large number of convective systems that occur over the US every year, there are typically only a few well-defined, midlevel vortices apparent in satellite imagery after the overlying anvil debris from some convective complexes has dissipated or advected away. A climatology of mesoscale convectively generated vortex (MCV) events for 1981-1988 is presented and the synoptic setting in which the circulation becomes apparent is discussed. Most MCVs emerge from MCC-type (i.e., circular) systems, but of the cases noted (24 events over the central US between 1981-1988) only half originated in systems that met Maddox's stringent MCC size and duration criteria. -from Authors