Deep Convection: Forecast Parameters
Mesoscale
M. D. Eastin
Deep Convection: Forecast Parameters
CAPE and CIN
Lifted Index
Bulk Vertical Wind Shear
Bulk Richardson Number (BRN)
Storm Relative Environmental Helicity (SREH)
Energy Helicity Index (EHI)
Other parameters…
Effective use of the Parameters
CAPE / Shear “Phase Space”
Mesoscale
M. D. Eastin
Mesoscale Forecasting
Two Step Process:
1. Convective Outlook
• Use available synoptic and mesoscale observations to forecast synoptic-scale
regions where severe weather development is possible
• NOAA Storm Prediction Center (SPC) [ http://www.spc.noaa.gov ]
• Issue Mesoscale Discussions and 3-day Convective Outlooks
• Issue Fire Weather Outlooks
• Issue Watches for Severe Thunderstorms and Tornados
2. Nowcasts
• Monitor the available mesoscale observations in order to update or alter
forecasts for potential severe weather as needed
• Once convection has developed, continuous monitoring of storm type,
structure, evolution, and motion with Doppler radar is required
• Local NWS Forecast Offices [ http://www.nws.noaa.gov/ ]
• Monitor the Local WSR-88D radar
• Issue Warnings for Severe Thunderstorms, Tornadoes, Flash Floods,
Winter Storms, Freezes, and High Surf
Mesoscale
M. D. Eastin
CAPE
• We estimate the total buoyancy force available to
accelerate an updraft air parcel by computing the
Convective Available Potential Energy (CAPE)
EL
CAPE 

LFC
g
Tpar  Tenv
Tenv
dz
• Recall water-loading and entrainment are always
neglected in its calculation (sometimes moisture)
• Directly related to maximum updraft velocity
wmax 
2CAPE
Values:
Range:
Typical:
“Small”
“Moderate”
“Large”
Mesoscale
0 – 5000 J/kg
800 – 3000 J/kg
< 1000 J/kg
1000 – 2500 J/kg
> 2500 J/kg
common severe weather threshold
M. D. Eastin
CAPE
Surface Based CAPE (SBCAPE):
• Computed using only the surface temperature and moisture observations
Strengths:
• Integrates through the entire
atmospheric depth
Weaknesses:
• Does not account for layers
that are not well mixed
• May grossly underestimate
instability when strong
nocturnal inversion
exists (morning soundings)
• Overestimates instability when
very shallow moist layers
are present
• Assumes no mixing between
the parcel and environment
• Neglects water loading
Mesoscale
M. D. Eastin
CAPE
Mean Layer CAPE (MLCAPE):
• Computed using the lowest 100 mb AGL mean layer temperature
and moisture observations
Strengths:
• Most realistic for convection
originating near the surface
• Incorporates daytime boundary
layer mixing
• Helps remove any nocturnal
boundary layer effects
Weaknesses:
• Underestimates instability if
convective initiation is elevated
(e.g. behind a cold/warm front)
• Assumes no mixing between
the parcel and environment
• Neglects water loading
Mesoscale
M. D. Eastin
CAPE
Most Unstable CAPE (MUCAPE):
• Computed using the temperature and moisture observation pair within
the lowest 300 mb AGL that results in the most unstable parcel
Strengths:
• Most realistic for elevated
convection
• Helps remove the nocturnal
boundary layer effect
Weaknesses:
• Underestimates instability if
convective initiation is near
the surface
• Assumes no mixing between
the parcel and environment
• Neglects water loading
Mesoscale
M. D. Eastin
CAPE
Climatology of Ordinary – Supercell CAPE:
• Rasmussen and Blanchard (1998)
• Computed MLCAPE for over 6000 soundings
taken at 0000 UTC during 1992
• Stratified the soundings as follows:
TOR: Sounding associated with
a tornadic supercell
SUP: Sounding associated with
a non-tornadic supercells
that produced large hail
ORD: Soundings associated with
thunderstorms not containing
severe winds, large hail, or a
tornado
• Performed a simple statistical analysis
on the MLCAPE distribution
Mesoscale
Boxes denote 25th and 75th percentile
Horizontal bar denotes median value
Lines extend to the 10th and 90th percentiles
Values at each percentile are shown
M. D. Eastin
CIN
• We estimate the total buoyancy force available to
decelerate an updraft air parcel by computing the
Convective Inhibition (CIN)
LFC
CIN 

g
T par  Tenv
SFC
Tenv
dz
• CIN is often the result of a capping inversion
• Represents the amount of energy that must be
given to a parcel (overcome) to reach the LFC
• In general, CIN is bad…
Values:
Range:
Typical:
“Small”
“Moderate”
“Large”
Mesoscale
0 – 500 J/kg
20 – 200 J/kg
< 10 J/kg
10 – 50 J/kg
> 50 J/kg
common severe weather threshold
M. D. Eastin
CIN
Strengths:
• Helps discriminate between deep convection
(low CIN) and no convection (high CIN)
• Can relate CIN to the required vertical velocity
needed to overcome the negative area:
wrequired lift 
2CIN 
Weaknesses:
• Can be difficult to assess the required lift
when no mesoscale boundaries are present
• Very sensitive to changes in BL temperature
and moisture values and thus CAPE choice
• Assumes parcel mixing with the environment
• Neglects water loading
Mesoscale
M. D. Eastin
CIN
Climatology of Ordinary – Supercell CIN:
• Rasmussen and Blanchard (1998)
• Computed CIN for over 6000 soundings
taken at 0000 UTC during 1992
• Stratified the soundings as follows:
TOR: Sounding associated with
a tornadic supercell
SUP: Sounding associated with
a non-tornadic supercells
that produced large hail
ORD: Soundings associated with
thunderstorms not containing
severe winds, large hail, or a
tornado
• Performed a simple statistical analysis
on the CIN distribution
Mesoscale
Boxes denote 25th and 75th percentile
Horizontal bar denotes median value
Lines extend to the 10th and 90th percentiles
Values at each percentile are shown
M. D. Eastin
Lifted Index (LI)
• Simple parameter used to characterize the
instability of an environment
• Raise a surface parcel to its LCL, and then
moist adiabatically to 500 mb
LI  Tenv  Tparcel
• Limited by only estimating buoyancy at
one level (can be misrepresentative)
• The more negative the LI, the greater
the chance for deep convection and
severe weather
Values:
Range:
Typical:
+20 to –14
+2 to –6
<0
< –3
< –5
< –8
Mesoscale
Convection possible
Convection probable
Strong convection and severe weather potential
Grab a video camera and start chasing…
M. D. Eastin
Bulk Wind Shear
• Simple parameter used to characterize the
wind shear in the layer most relevant to
storm structure and evolution
• Low values denote environments favoring
the formation of ordinary (single) cells
• High values denote environments favoring
the formation of supercells
Bulk Shear
Vector
• Often calculated in the 0-6 km AGL layer
 Helps distinguish between ordinary,
multicell, and supercell formation
Values:
Range: 0 – 60
Typical: 5 – 30
< 10 Ordinary cells
10 – 20 Multicells
> 20 Supercells
Mesoscale
M. D. Eastin
Bulk Wind Shear
Climatology of Ordinary – Supercell Bulk Shear:
• Rasmussen and Blanchard (1998)
• Computed Bulk Shear for over 6000 soundings
taken at 0000 UTC during 1992
• Stratified the soundings as follows:
TOR: Sounding associated with
a tornadic supercell
SUP: Sounding associated with
a non-tornadic supercells
that produced large hail
ORD: Soundings associated with
thunderstorms not containing
severe winds, large hail, or a
tornado
• Performed a simple statistical analysis
on the Bulk Shear distribution
Mesoscale
Boxes denote 25th and 75th percentile
Horizontal bar denotes median value
Lines extend to the 10th and 90th percentiles
Values at each percentile are shown
M. D. Eastin
Bulk Richardson Number (BRN)
• Simple parameter used to characterize the
relative importance of buoyancy and vertical
wind shear processes in controlling storm
structure and evolution
BRN 
CAPE
1 U2
2
• Low values are indicative of environments
in which shear related processes will
play a significant role
 Helps distinguish between supercell and
multicell formation
Values:
Range: 1 – 4000
Typical: 10 – 400
< 50
> 50
Mesoscale
Supercells possible
Multicells possible
BRN Shear (½U2): One half the square of the
vector difference between the
mean 0-6 km AGL wind and
the mean 0-0.5 km AGL wind
Provides a measure of the
“bulk” wind shear
M. D. Eastin
Bulk Richardson Number (BRN)
Strengths:
• Combines both instability and vertical
shear into a single parameter
• Provides estimate of rotation potential
without considering storm motion
Weaknesses:
• No measure of directional shear
• Does not account for hodograph
curvature
• Same weaknesses as for CAPE
• Does not account for the vertical
distribution of instability
• No indication or measure of CIN
Mesoscale
M. D. Eastin
Storm-Relative Helicity (SREH)
• Parameter used to characterize the strength
of the low-level, storm-relative speed and
directional shear
 The greater the “helicity”, the more
likely the updraft will rise in a helical
manner and produce a mesocyclone
 Helps forecast supercell formation
 Calculation method (see pp. 230-213 in text):
• Estimate storm motion
• Compute storm-relative winds
• SREH is two times (2×) the total area
swept out by the storm-relative winds
between 0-3 km AGL (green area)
Values:
Range: 0 – 1000
Typical: 50 – 400
> 100 Supercells Possible
> 200 Supercells Likely
Mesoscale
M. D. Eastin
Storm-Relative Helicity (SREH)
Strengths:
• Provides estimate of rotation potential
while also considering storm motion
• Does account for both total shear and
hodograph curvature
• Can discriminate between supercells
and tornadic supercells
Weaknesses:
• Very sensitive to the storm motion
• Very sensitive to change in low-level
wind vectors
Note: SREH can be computed for a variety of
depth or layers. Common layers are:
0-3 km
0-2 km
0-1 km
Mesoscale
Good for supercell forecasts
Good for tornado forecasts
M. D. Eastin
Storm-Relative Helicity (SREH)
Climatology of Supercell –Tornado SREH:
• Rasmussen and Blanchard (1998)
• Computed SREH for over 6000 soundings
taken at 0000 UTC during 1992
• Stratified the soundings as follows:
TOR: Sounding associated with
a tornadic supercell
SUP: Sounding associated with
a non-tornadic supercells
that produced large hail
ORD: Soundings associated with
thunderstorms not containing
severe winds, large hail, or a
tornado
• Performed a simple statistical analysis
on the SREH distribution (0-3 km layer)
Mesoscale
Boxes denote 25th and 75th percentile
Horizontal bar denotes median value
Lines extend to the 10th and 90th percentiles
Values at each percentile are shown
M. D. Eastin
Energy Helicity Index (EHI)
 Parameter used to characterize the likelihood
of supercell formation and tornadic activity
EHI 
CAPE  SREH
160,000
• The divisor of 160,000 is simply used to
obtain a manageable number
• CAPE is computed using the mean layer (ML)
• SREH is computed from either the 0-1 km,
0-2 km, or the 0-3 km layer.
Values:
Range:
Typical:
0.0 – 30.0
0.0 – 5.0
> 0.5
Supercells Likely
> 1.0
Tornadoes Likely
Note: These rough criteria are valid for
all SREH layers (0-1, 0-2, or 0-3 km)
Mesoscale
M. D. Eastin
Energy Helicity Index (EHI)
Strengths:
• Incorporates instability, vertical shear
magnitude, shear curvature, and
storm motion into a single parameter
• Most effective discriminator for
significant tornadoes associated
with supercells
Weaknesses:
• Same weaknesses as for CAPE
• Very sensitive to the storm motion
• Very sensitive to change in low-level
wind vectors
Mesoscale
M. D. Eastin
Energy Helicity Index (EHI)
Climatology of Ordinary – Supercell EHI:
• Rasmussen and Blanchard (1998)
• Computed EHI for over 6000 soundings
taken at 0000 UTC during 1992
• Stratified the soundings as follows:
TOR: Sounding associated with
a tornadic supercell
SUP: Sounding associated with
a non-tornadic supercells
that produced large hail
ORD: Soundings associated with
thunderstorms not containing
severe winds, large hail, or a
tornado
• Performed a simple statistical analysis
on the EHI distribution (0-3 km layer)
Mesoscale
Boxes denote 25th and 75th percentile
Horizontal bar denotes median value
Lines extend to the 10th and 90th percentiles
Values at each percentile are shown
M. D. Eastin
Other Parameters
 A number of additional forecast parameters have been developed (and are regularly used)
at the SPC to issue severe weather watches:
Supercell Composite Parameter (SCP)
 MUCAPE   0  3km SREH   BRN Shear

  

SCP  
1  
2 2
2 2 
 1000 J kg   100m s
  40 m s 
• Developed by Thompson et al. (2003)
• Values > 1.0 suggest supercell formation is likely
Significant Tornado Parameter (STP)
 MLCAPE   0  1km SREH   0  6km Shear  (2000 MLLCL) 

  
  

STP  
1  
2 2
2 2
1500m
 1000 J kg   100m s
  20 m s
 

• Developed by Thompson et al. (2003)
• Values > 1.0 suggest strong (EF2-EF5) tornado formation is likely
Additional Forecast Parameters:
Mesoscale
Useful Severe Weather Forecast Parameters
M. D. Eastin
Effective Use of Parameters
Use the forecast parameters as they were intended!!!
 Use CAPE (any variety), CIN, and LI to determine the likelihood of deep convection
• Large CAPE, low CIN, and low LI indicates an increased chance
 Use Bulk Shear, BRN, and SCP to identify the storm type (ordinary, multicell, supercell)
 Use SREH to determine which multicells or supercells will develop rotating updrafts
• Larger values indicate an increased chance for large hail and/or tornadoes
 Use EHI and STP to determine which multicells or supercells will develop tornadoes
• Larger values indicate an increased chance for stronger tornadoes
• Values are positively correlated with tornado strength
 Use DCAPE to determine if any cell type will develop strong downdrafts
• Larger values increase the chance of severe straight-line winds
Remember:
These parameters and their numerical criteria are only guidelines
based on statistical analysis (i.e., In the long run, they work)
Pay very close attention to the “weaknesses” for each parameter
Mesoscale
M. D. Eastin
SPC Sounding Analysis
Mesoscale
M. D. Eastin
CAPE / Shear Phase Space
 Joe Klemp and Morris Weisman (NCAR)
conducted a series of numerical simulations
(each yellow dot) whereby the model was
initialized with different environments that
characterize the wide spectrum of CAPE
and vertical wind shear values that are
often observed
 One result was a “phase space” diagram
that helps forecast the convective storm
type on any given day
 Many other aspects of how vertical shear
and buoyancy processes influence storm
structure and evolution were discovered
from these simulations
• Let’s look at these simulations in detail…
Complete the UCAR COMET Module: A Convective Storm Matrix
http://www.meted.ucar.edu/convectn/csmatrix/
Mesoscale
M. D. Eastin
References
Brooks, H. E., C. A. Doswell, and J. Cooper, 1994: On the environments of tornadic and nontornadic mesocyclones.
Wea. Forecasting, 9, 606-618.
Brooks, H. E., and R. B. Wilhelmson, 1993: Hodograph curvature and updraft intensity in numerically modeled supercells.
J. Atmos. Sci., 50, 1824-1833.
Doswell C. A., 1991: A review for forecasters on the applications of hodographs to forecasting severe thunderstorms.
National Weather Digest, 16, 2-16.
Droegemeier, K. K., aS. M. lazarus, and R. Davies-Jones, 1993: The influence of helicity on numerically simulated
convective storms. Mon. Wea. Rev., 121, 2005-2029.
Lilly, D. K., 1986: The structure, energetics and propagation of rotation convective storms. Part II: Helicity and storm
stabilization. J. Atmos. Sci., 43, 126-140.
Markowski, P. M., J. M. Straka, and E. N. Rasmussen, 2002: Direct surface thermodynamic observations within the rearflank downdrafts of nontornadic and tornadic supercells. Mon. Wea. Rev., 130, 1692-1721.
Rasmussen, E.N., and D. O. Blanchard, 1998: A baseline climatology of sounding-derived supercell and tornado forecast
parameters. Wea. Forecasting, 13, 1148-1164.
Thompson, R. L., R. Edwards, J. A. Kart, K. L. Elmore, and P. Markowski, 2003: Close proximity soundings within supercell
environments obtained from the Rapid Update Cycle. Wea. Forecasting, 18, 1243-1261
Thompson, R. L., and C. M. Mead, and R. Edwards, 2007: Effective storm-relative helicity and bulk shear in supercell
thunderstorm environments. Wea. Forecasting, 22, 102-115.
Weisman, M. L., and J. B. Klemp, 1982: The dependence of numerically simulated convective storms on vertical wind
shear and buoyancy. Mon. Wea. Rev., 110, 504-520.
Weisman, M. L., and J. B. Klemp, 1984: The structure and classification of numerically simulated convective storms in
directionally varying wind shears. Mon. Wea. Rev., 112, 2479-2498.
Mesoscale
M. D. Eastin