severe convective storms, theory
Pieter Groenemeijer
FMI
Helsinki, 2 May 2005
“one-slide introduction” of myself
I am Pieter Groenemeijer
• M.Sc. in Physics and Astronomy at
Utrecht University
• Oklahoma University (spring semester 2002)
• ESWD (European Severe Weather Database)
• “Sounding-derived parameters associated with large hail and
tornadoes in the Netherlands“
• Co-initiator of ESTOFEX (with Johannes Dahl and Christoph
Gatzen), Oct, 2002.
my contribution this morning
1.
Ingredients-based forecasting
- instability
- lift
2.
Storm structure
- wind shear: multicells and supercells
- other factors: linear convective systems
_________________________________________ (short break)
•
•
Convection parameters
Severe weather hazards
-
5.
a study in Holland
A case
Questions, discussion
what will we discuss?
severe convective storms:
storms that produce hazardous weather like:
•
•
•
•
•
lightning
heavy rain (leading to flash floods)
strong winds (straight-line winds)
large hail
tornadoes
ingredients-based forecasting (Doswell, 2004)
• What is“ingredients-based forecasting”?
an “ingredient” is something necessary for some event to occur
I will cover the theory by exploring those
ingredients
ingredients for convective storms
1. latent instability
2. lift (rising motion)
instability
• lapse rate definition:
or:
dT/dz > 1.0 C/km
in dry air
dT/dz > moist adiabatic lapse rate
in saturated air
these are the definitions of
absolute and conditional instability
instability
• layer definition:
when lifting a layer, saturation occurs and
dT/dz becomes > moist adiabatic lapse rate
Or equivalently: theta-e (and theta-w) decrease with height
potential instability
instability
a convective bubble is more like a parcel than a layer...
• parcel definition:
parcel becomes warmer than environment after lift
latent instability (Normand, 1937)
several “convective parameters” are based on the concept of latent
instability:
• CAPE (in all its forms)
• LI (Lifted Index)
• Showalter Index
instability
parcel theory
parcel theory
parcel theory
EL
Tv '
CAPE   g dz
Tv
LFC
EL
CIN 

source level
g
Tv '
dz
Tv
limitations of parcel theory
Realize that parcel theory is a simplification of
reality:
• what in reality is a parcel? is it undiluted?
• and its environment? is it not influenced by
convection?
objection:
We neglect pressure perturbation forces!
(come back to that later)
lift
latent instability ≠ storms
• a “cap”, CIN may be present, or
• entrainment may inhibit the development of
convective storms
lift
• can weaken the “cap”, or
• is associated with convergence at the surface:
- helps to sustain initiating convective bubbles
lift and convective inhibition
lift and convective inhibition
lift and convective inhibition
lift and convective inhibition
entrainment
we have identified...
two ingredients for convective storms...
• latent instability
• (sufficient) lift
okay... but when should we become worried
about extreme events?
are other ingredients required?
storm structures / convective modes
• some severe events are associated with
particular storm structures (or convective
modes)
EXAMPLES from my home country
multicell line
multicell clusters
isolated supercell
storm structures / convective modes
• some severe events are associated with
particular storm structures (or convective
modes), others are not, e.g.:
- strong tornadoes are known to occur mostly with
supercell storms
- extreme rainfall and lightning can occur with any storm
structure, but generally...
anticipating storm structure is very important
to predict the quantity and quality of the
severe weather that may occur
factors influencing storm structures
1. vertical wind shear
2. other factors
vertical wind shear
• vertical wind shear has a strong influence on
convective organisation
it affects
• storm propagation
• vertical speeds in up- and downdrafts
• storm longevity
storm in weak vertical shear
weak shear:
single-cell storms
1. updraft grows
2. precipitation
forms
3. cold pool forms
and spreads out
4. updraft ceases
5. storm ceases
reality
a gust front made visible by blowing dust and sand
storm in moderate vertical shear
moderate shear:
multicell storms
1.
2.
3.
4.
5.
time
updraft grows
precipitation forms
cold pool forms and
spreads out >>>>> 1.
2.
updraft ceases
3.
storm ceases
4.
5.
new updraft grows
precipitation forms
cold pool forms and
spreads out >>>>> 1.
2.
updraft ceases
3.
storm ceases
4.
5.
new updraft grows
precipitation forms
cold pool grows and
spreads out
updraft ceases
storm ceases
new cells form at the edge of the cold pool....
RKW-theory
from Rotunno, Klemp and Wilhelmson, 1988
when horizontal vorticity produced by the cold pool
and that of the environments are roughly equal
the strongest lift will occur
new cells form at the edge of the cold pool....
RKW-theory
no vertical wind shear
from Xue et al., 1997
RKW-theory
low-level vertical wind shear
from Xue et al., 1997
RKW-theory
RKW-theory is not undisputed...
it seems to work better in the laboratory than in
reality
storm in moderate vertical shear
multicell cluster
the cells may not be
distinguished by a radar
scanning at a low
elevation....
storm in moderate vertical shear
multicell line:
squall line
watch the cells forming at
the front of the system that
move backward w.r.t. the
system
storm in strong vertical shear
strong shear:
supercell storms
supercell
definition:
a supercell is a storm with a persistent, deep
rotating updraft (that is, a mesocyclone)
a few characteristics:
• very strong updrafts
• often: very strong downdrafts
...resulting in a high potential for severe weather
• don’t move with the mean wind
hodographs
hodographs
hodographs
hodographs
storm-relative helicity
vertical shear
implies horizontal
vorticity
storm-relative helicity
SRH   v avg  c   ω dz
storm-relative helicity
(e.g. Davies, 1985;
Droegemeier et al., 1993)
hodographs
hodographs
hodographs
hodographs
hodographs
right-moving supercell
left-moving supercell
hodographs
hodographs
LP supercell near Waynoka, OK
April 17th 2002
Tornado Team Utrecht
Mesocyclone near Selby SD
June 8th 2002
Tornado Team Utrecht
supercells on (Doppler) radar
we have identified...
three ingredients for the most severe convective
storms...
• latent instability
• (sufficient) lift
• vertical wind shear
we have identified...
three ingredients for the most severe convective
storms...
• latent instability
• (sufficient) lift
• vertical wind shear
note that I didn’t say that CAPE should by higher than some
threshold. Storms have caused F4 tornadoes with only a few
100’s of J/kg available!
other factors than wind shear that influence
storm structure...
It is hard to predict if and how quickly storms will
cluster into a linear MCS.
-MCS’s often form when cold pools formed by
multiple storms merge
Factors favoring clustering into an MCS:
-strong lift
(e.g. caused by an intense shortwave trough, frontal wave)
-convective initiation along a boundary
-weak cap (low CIN)
bow echoes
Convective systems may develop into bow echoes.
bow echoes
Amsterdam
The Hague
Rotterdam
Image made at KNMI
bow echoes
1639 UTC
Amsterdam
The Hague
Rotterdam
Image made at KNMI
bow echoes
1639 UTC
Amsterdam
The Hague
Rotterdam
Image made at KNMI
Image made at KNMI
17 July 2004 - Image by Patrick Weegink
ingredients-based forecasting (Doswell, 2004)
an “ingredient” is something necessary for some
event to occur
• helps with information overload
• helps prevent overlooking important factors
• prevents “tunnel-vision”
we have identified...
three ingredients for the most severe convective
storms...
• latent instability
• (sufficient) lift
• vertical wind shear
 certain parameters may help to quantify
those
convective parameters
but, beware....
convective parameters
but, beware, some parameters....
Total totals index (TOTL) = T850 + Td850 - 2 * T500 [°C]
K index = T850 + Td850 - T500 - (T-Td)700 [°C]
Sweat index = 12*Td850+20*(TOTL-49)+2*U850+5*U500+125*(0.2+sin(f))
where f=(wind direction500-wind direction850), U=wind speed[kts], TOTL=0 if TOTL<49
convective parameters
but, beware, some parameters....
Total totals index (TOTL) = T850 + Td850 - 2 * T500 [°C]
K index = T850 + Td850 - T500 - (T-Td)700 [°C]
Sweat index = 12*Td850+20*(TOTL-49)+2*U850+5*U500+125*(0.2+sin(f))
where f=(wind direction500-wind direction850), U=wind speed[kts], TOTL=0 if TOTL<49
...combine different physical atmospheric properties (moisture,
temperature, wind shear) into one parameter in some “magical
way”
convective parameters
but, beware, some parameters....
Total totals index (TOTL) = T850 + Td850 - 2 * T500 [°C]
K index = T850 + Td850 - T500 - (T-Td)700 [°C]
Sweat index = 12*Td850+20*(TOTL-49)+2*U850+5*U500+125*(0.2+sin(f))
where f=(wind direction500-wind direction850), U=wind speed[kts], TOTL=0 if TOTL<49
...combine different physical atmospheric properties (moisture,
temperature, wind shear) into one parameter in some “magical
way”
...come with a list of thresholds, that may not be valid in your
forecast region (if at all...)
convective parameters
but, beware, some parameters....
Total totals index (TOTL) = T850 + Td850 - 2 * T500 [°C]
K index = T850 + Td850 - T500 - (T-Td)700 [°C]
Sweat index = 12*Td850+20*(TOTL-49)+2*U850+5*U500+125*(0.2+sin(f))
where f=(wind direction500-wind direction850), U=wind speed[kts], TOTL=0 if TOTL<49
...combine different physical atmospheric properties (moisture,
temperature, wind shear) into one parameter in some “magical
way”
...come with a list of thresholds, that may not be valid in your
forecast region (if at all...)
...require no physical understanding of the weather situation
convective parameters
but, beware, some parameters....
Total totals index (TOTL) = T850 + Td850 - 2 * T500 [°C]
K index = T850 + Td850 - T500 - (T-Td)700 [°C]
Sweat index = 12*Td850+20*(TOTL-49)+2*U850+5*U500+125*(0.2+sin(f))
where f=(wind direction500-wind direction850), U=wind speed[kts], TOTL=0 if TOTL<49
...combine different physical atmospheric properties (moisture,
temperature, wind shear) into one parameter in some “magical
way”
...come with a list of thresholds, that may not be valid in your
forecast region (if at all...)
...require no physical understanding of the weather situation
...don’t increase one’s understanding either.
you can not find out what went wrong and do better next time!
my convective parameters
INSTABILITY parameters
parameter
for prediction of
remarks
CAPE
(if not available:
LIFTED INDEX)
instability
beware of different
parcels that are lifted
CAPE RELEASED
BELOW 3 KM*
low-level instability
buoyant parcels close to
the surface can cause
rapid vortex stretching
tornadoes
* = will discuss this later on
my convective parameters
LIFT parameters
parameter
for prediction of
remarks
forcing term of
differential vorticity
advection
upward motion,
convective initiation
forcing term of
temperature
advection
upward motion,
convective initiation
upward motion in
numerical models may
be contaminated by the
convection itself....
or, alternatively Q-vector divergence or PV-analysis
* = will discuss this later on
my convective parameters
WIND SHEAR parameters
parameter
for prediction of
remarks
0-6 km BULK
SHEAR
convective organisation
remark: convective
organisation is strongly
influenced by the
amount of lift as well
0-1 km BULK
SHEAR*
tornadoes
0-3 KM STORMRELATIVE
HELICITY
potential for supercell
convection
0-1 KM STORMRELATIVE
HELICITY*
potential for tornadoes
* = will discuss this later on
my convective parameters
other parameters
parameter
for prediction of
MOISTURE AT MIDLEVELS*
strong downdrafts if low
remarks
MOISTURE AT LOW strong downdrafts if low deep, dry boundary layers
LEVELS*
cause evaporative cooling
and a high potential for
strong wind gusts
LCL HEIGHT*
tornadoes
tornadoes unlikely with
LCL > around 1500 m
WIND SPEED AT
850 hPa*
wind gusts
vertical transport of
horizontal wind speeds
(very) relevant for wind
speed in downdrafts
* = will discuss this later on
My M.Sc thesis research...
Sounding-derived parameters associated with
large hail and tornadoes in the Netherlands
study done at Institute for Marine and
Atmospheric Research Utrecht
Basic idea
1. Find soundings taken in the proximity of
severe weather events (here: tornadoes)
2. Find if they have special characteristics
(w.r.t. other soundings)
method: look at parameters
that represent something physical
and that have been studied before
Proximity soundings
What is a proximity sounding…?
Used definition:
• within 4 hours of the sounding
(before or after)
• within 100 km from a point that
is advected by the 0-3 km mean
wind from the sounding location
at the sounding time
Data sets
•
radiosonde observations
Dec 1975 – Aug 2003
(thanks to KNMI, DWD,
KMI)
•
severe weather reports
from Dutch voluntary
observers (VWK)
Sinds 1974
Vereniging voor Weerkunde en Klimatologie (VWK)
http:/www.vwkweb.nl
Data
soundings associated with:
hail (2.0 - 2.9 cm)
hail (>= 3.0 cm)
tornadoes F0
tornadoes F1
tornadoes F2
waterspouts
thunder (1990-2000 only)
all soundings
number
46
47
24
37
6
26
2045
67816
Most-unstable CAPE (MUCAPE)
Number of
events 
US studies: MUCAPE highly
variable with tornadoes.
Strong tornadoes may occur
with low CAPE when shear
is high
maximum
 75th perc.
median
 25th perc.
MUCAPE high with hail; less with tornadoes…
Most-unstable CAPE released below 3 km A.G.L.
US studies: Davies (2004)
has found a relation between
tornado occurrence and high
CAPE below 3km (in his
study mixed-layer CAPE)...
MUCAPE<3km high with F0, not with F1+
(most-unstable) LFC height (m)
US studies: Davies (2004)
has found a relation between
low LFC and tornado
occurrence
LFC relatively low with tornadoes (esp. F0)…
LCL height (50 hPa mixed layer parcel)
US studies: Low LCL favors
significant tornadoes, e.g.
Craven et al. (2002)
LCL not sign. diff. between tornadic and thunder
Average soundings
LARGE HAIL
F0
F1+
note the distribution of parcel buoyancy with height
0-6 km A.G.L. bulk shear (m/s) (1)
US studies: strong tornadoes and (very)
large hail often occur with supercells.
These are associated with >20 m/s 0-6 km
shear (e.g. Doswell&Evans, 2003)
0-6 km A.G.L. bulk shear (m/s) (2)
likelihood of hail increases with 0-6 km shear, but the majority of hail events
occur with moderate shear
0-1 km A.G.L. bulk shear (m/s)
US studies: strong 0-1 km shear
favours sign. tornadoes (e.g.
Craven et al., 2002).
0-1 km shear high with F1, esp. F2 tornadoes...
and with wind gusts
0-1 km A.G.L. storm-relative helicity (m2/s2)
US studies: high values
favor supercell tornadoes
(e.g. Rasmussen, 2003).
0-1 km shear high with F1, esp. F2 tornadoes..
Conclusions of the study
• MUCAPE and 0-6 km bulk shear are useful
predictors for large hail, especially when combined
• most large (> 2cm) hail in the Netherlands is
associated with multicells rather than supercells
Conclusions of the study
• F1 and esp. F2 tornadoes occur with higher-thanaverage 0-1 km shear and SRH.
• F0 tornadoes (and waterspouts) occur with lowerthan-average 0-1 km shear values
• (MU)CAPE is not extreme with tornadoes and
thereby has limited value for tornado forecasting.
Submitted to Atmospheric Research
Some conclusions
• MUCAPE released below 3 km / low LFC heights
seem to be important for the formation of weaker
(and likely non-supercellular) tornadoes….
(but of course we rather want to forecast the stronger
tornadoes)
• LCL heights are probably not as much a limiting
factor for tornado development in the NL than in
much of the U.S.A.
i.e. LCL heights are practically always low enough
here for tornadoes
using convective parameters
23th June, 2004
analysis prepared in cooperation with Christoph Gatzen (ESTOFEX)
source: ESTOFEX
photo: Christian Schöps
23 June, 2004: 500 hPa height, wind speed
23 June, 2004: 850 hPa height, theta-e
23 June, 2004: MUCAPE, deep layer wind shear
23 June, 2004: MUCAPE, low level wind shear
23 June, 2004: LCL height
23 June, 2004: LFC height
Sounding from the action
area. It indicates...
• rather weak CAPE
• most of it below 3km
• winds veer strongly with
height (indicating helicity)
• strong low level wind
shear
In this case, the forecast didn’t work out. The favourable veering of wind wind height in
the lowest km, was not at all predicted by most numerical models that forecasted
SWly winds instead of SEly winds.
Conclusion and highlights
• the ingredients-based methodology can help to structurize the
forecasting process
• for severe convection the essential ingredients are:
• latent instability (CAPE)
• lift
• vertical wind shear (20 m/s…40 kts is supercell threshold)
• Convective parameters with a single obvious physical meaning
are probably the most useful.
Most important for forecasting….
HAIL
CAPE and convective mode
TORNADOES
0-1 km shear, SREH and convective mode
WIND GUSTS
850 hPa wind, dry low or mid-levels and
convective mode
References
Craven, J. P., H. E. Brooks, and J. A. Hart, 2002: Baseline
climatology of sounding derived parameters associated with deep,
moist convection. Preprints, 21st Conference on Severe Local
Storms, San Antonio, Texas, American Meteorological Society, 643–
646.
Davies, J. M., 2002: On low-level thermodynamic parameters
associated with tornadic and nontornadic supercells. Preprints, 21st
Conf. on severe local storms, Kananaskis Park, Alberta, Canada,
Amer. Meteor. Soc., 558–592.
Davies, J. M., 2004: Estimations of CIN and LFC Associated with
Tornadic and Nontornadic Supercells. Wea. Forecasting, 19, 714–
726.
Fujita, T. T., 1971: Proposed Characterization of Tornadoes and
Hurricanes by Area and Intensity, SMRP Research Paper No. 91,
University of Chicago.
Doswell, C. A. III, and J. S. Evans, 2003: Proximity sounding
analysis for derechos and supercells: An assessment of similarities
and differences. Atmos. Res., 67-68, 117–133.
Rasmussen, E. N., 2003: Refined supercell and tornado forecast
parameters. Wea. Forecasting, 18, 530–535.