severe convective storms, theory
DESCRIPTION
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) - PowerPoint PPT PresentationTRANSCRIPT
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severe convective storms, theory
Pieter Groenemeijer
FMI
Helsinki, 2 May 2005
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“one-slide introduction” of myself
I am Pieter Groenemeijer
• M.Sc. in Physics and Astronomy atUtrecht 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.
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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
- a study in Holland
5. A case
Questions, discussion
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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
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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
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ingredients for convective storms
1. latent instability
2. lift (rising motion)
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instability
• lapse rate definition: dT/dz > 1.0 C/km in dry air
or: dT/dz > moist adiabatic lapse rate in saturated air
these are the definitions of
absolute and conditional instability
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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
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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
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instability
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parcel theory
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parcel theory
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parcel theory
EL
level source
d'
g zT
TCIN
v
v
EL
LFC
d'
g zT
TCAPE
v
v
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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)
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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
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lift and convective inhibition
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lift and convective inhibition
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lift and convective inhibition
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lift and convective inhibition
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entrainment
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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?
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storm structures / convective modes
• some severe events are associated with particular storm structures (or convective modes)
multicell line multicell clusters isolated supercell
EXAMPLES from my home country
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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
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factors influencing storm structures
1. vertical wind shear
2. other factors
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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
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storm in weak vertical shear
weak shear:single-cell storms
1. updraft grows2. precipitation forms3. cold pool forms
and spreads out4. updraft ceases5. storm ceases
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reality
a gust front made visible by blowing dust and sand
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new cells form at the edge of the cold pool....
storm in moderate vertical shear
moderate shear: multicell storms
1. updraft grows
2. precipitation forms
3. cold pool forms and spreads out >>>>>
4. updraft ceases
5. storm ceases
time
1. new updraft grows
2. precipitation forms
3. cold pool forms and spreads out >>>>>
4. updraft ceases
5. storm ceases
1. new updraft grows
2. precipitation forms
3. cold pool grows and spreads out
4. updraft ceases
5. storm ceases
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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
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RKW-theory
from Xue et al., 1997
no vertical wind shear
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RKW-theory
from Xue et al., 1997
low-level vertical wind shear
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RKW-theory
RKW-theory is not undisputed...
it seems to work better in the laboratory than in reality
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storm in moderate vertical shear
multicell cluster
the cells may not be distinguished by a radar scanning at a low elevation....
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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
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storm in strong vertical shear
strong shear:supercell storms
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supercell
definition:a supercell is a storm with a persistent, deeprotating 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
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hodographs
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hodographs
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hodographs
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hodographs
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storm-relative helicity
vertical shear
implies horizontal
vorticity
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storm-relative helicity
zSRH avg d ωcv storm-relative helicity
(e.g. Davies, 1985;Droegemeier et al., 1993)
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hodographs
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hodographs
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hodographs
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hodographs
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hodographs
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right-moving supercell
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left-moving supercell
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hodographs
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hodographs
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LP supercell near Waynoka, OKApril 17th 2002 Tornado Team Utrecht
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Mesocyclone near Selby SD June 8th 2002 Tornado Team Utrecht
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supercells on (Doppler) radar
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we have identified...
three ingredients for the most severe convective storms...
• latent instability• (sufficient) lift• vertical wind shear
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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!
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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)
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bow echoes
Convective systems may develop into bow echoes.
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Amsterdam
Rotterdam
The Hague
Image made at KNMI
bow echoes
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Image made at KNMI
Amsterdam
Rotterdam
The Hague
1639 UTC
bow echoes
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Image made at KNMI
Amsterdam
Rotterdam
The Hague
1639 UTC
bow echoes
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Image made at KNMI
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17 July 2004 - Image by Patrick Weegink
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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”
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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
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convective parameters
but, beware....
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convective 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
but, beware, some parameters....
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convective parameters
...combine different physical atmospheric properties (moisture, temperature, wind shear) into one parameter in some “magical way”
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
but, beware, some parameters....
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convective parameters
...combine different physical atmospheric properties (moisture, temperature, wind shear) into one parameter in some “magical way”
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
but, beware, some parameters....
...come with a list of thresholds, that may not be valid in your forecast region (if at all...)
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convective parameters
...combine different physical atmospheric properties (moisture, temperature, wind shear) into one parameter in some “magical way”
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
but, beware, some parameters....
...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
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convective parameters
...combine different physical atmospheric properties (moisture, temperature, wind shear) into one parameter in some “magical way”
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
but, beware, some parameters....
...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!
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* = will discuss this later on
my convective 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
INSTABILITY parameters
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my convective parameters
parameter for prediction of remarks
forcing term of differential vorticity advection
upward motion,
convective initiation
upward motion in numerical models may be contaminated by the convection itself....forcing term of
temperature advection
upward motion,
convective initiation
or, alternatively Q-vector divergence or PV-analysis
LIFT parameters
* = will discuss this later on
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my convective 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 STORM-RELATIVE HELICITY
potential for supercell convection
0-1 KM STORM-RELATIVE HELICITY*
potential for tornadoes
WIND SHEAR parameters
* = will discuss this later on
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my convective parameters
parameter for prediction of remarks
MOISTURE AT MID-LEVELS*
strong downdrafts if low
MOISTURE AT LOW LEVELS*
strong downdrafts if low deep, dry boundary layers 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
other parameters
* = will discuss this later on
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study done at Institute for Marine and Atmospheric Research Utrecht
Sounding-derived parameters associated with large hail and tornadoes in the Netherlands
My M.Sc thesis research...
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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
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Proximity soundings
What is a proximity sounding…?
Used definition:• within 4 hours of the sounding
(before or after)
• within 100 km from a point thatis advected by the 0-3 km meanwind from the sounding locationat the sounding time
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• radiosonde observations
Dec 1975 – Aug 2003
(thanks to KNMI, DWD, KMI)
• severe weather reports from Dutch voluntary observers (VWK)
Data sets
Sinds 1974
Vereniging voor Weerkunde en Klimatologie (VWK)
http:/www.vwkweb.nl
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Data
soundings associated with: number
hail (2.0 - 2.9 cm)
hail (>= 3.0 cm)
tornadoes F0
tornadoes F1
tornadoes F2
waterspouts
thunder (1990-2000 only)
46
47
24
37
6
26
2045
all soundings 67816
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Most-unstable CAPE (MUCAPE)Number of events
maximum
median
75th perc.
25th perc.
MUCAPE high with hail; less with tornadoes…
US studies: MUCAPE highly variable with tornadoes. Strong tornadoes may occur with low CAPE when shear is high
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Most-unstable CAPE released below 3 km A.G.L.
MUCAPE<3km high with F0, not with F1+
US studies: Davies (2004) has found a relation between tornado occurrence and high CAPE below 3km (in his study mixed-layer CAPE)...
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(most-unstable) LFC height (m)
LFC relatively low with tornadoes (esp. F0)…
US studies: Davies (2004) has found a relation between low LFC and tornado occurrence
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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
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LARGE HAIL F0 F1+
Average soundings
note the distribution of parcel buoyancy with height
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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)
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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
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0-1 km A.G.L. bulk shear (m/s)
0-1 km shear high with F1, esp. F2 tornadoes...and with wind gusts
US studies: strong 0-1 km shear favours sign. tornadoes (e.g. Craven et al., 2002).
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0-1 km A.G.L. storm-relative helicity (m2/s2)
0-1 km shear high with F1, esp. F2 tornadoes..
US studies: high values favor supercell tornadoes (e.g. Rasmussen, 2003).
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• 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
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• F1 and esp. F2 tornadoes occur with higher-than-average 0-1 km shear and SRH.
• F0 tornadoes (and waterspouts) occur with lower-than-average 0-1 km shear values
• (MU)CAPE is not extreme with tornadoes and thereby has limited value for tornado forecasting..
Conclusions of the study
Submitted to Atmospheric Research
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• 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
Some conclusions
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using convective parameters23th June, 2004analysis prepared in cooperation with Christoph Gatzen (ESTOFEX)
photo: Christian Schöps
source: ESTOFEX
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23 June, 2004: 500 hPa height, wind speed
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23 June, 2004: 850 hPa height, theta-e
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23 June, 2004: MUCAPE, deep layer wind shear
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23 June, 2004: MUCAPE, low level wind shear
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23 June, 2004: LCL height
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23 June, 2004: LFC height
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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.
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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 modeTORNADOES 0-1 km shear, SREH and convective modeWIND GUSTS 850 hPa wind, dry low or mid-levels and
convective mode
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ReferencesCraven, 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.