Transcript Some Applications of Indices to Forecasting 12 Great Divide Workshop, 10/7/2008

Some Applications of
Indices to Forecasting
12th Great Divide Workshop, 10/7/2008
Matthew J. Bunkers, SOO Rapid City, SD
Outline
• Make note of several “indices”
• Discuss utility & attributes of indices (+ / -)
• Show several examples of testing indices for
operations – implications for training
A cornucopia of “indices”
Lifted Index (LI)*
Total Totals (TT)
K Index (KI)
Showalter Index (SI)
Severe Weather Threat (SWEAT)
CAP Strength (700 mb LI)
Lapse Rate (LR)*
Relative Humidity (RH)*
* Can be calculated over many different layers/levels/parcels
A cornucopia of “indices”
Lifted Index (LI)*
Total Totals (TT)
K Index (KI)
Showalter Index (SI)
Severe Weather Threat (SWEAT)
CAP Strength (700 mb LI)
Lapse Rate (LR)*
Relative Humidity (RH)*
Lifted Condensation Level (LCL)*
Level of Free Convection (LFC)*
Equilibrium Level (EL)*
Wet Bulb Zero (WBZ)
Melting Level (MLT)
Warm Cloud Depth (WCD)*
Precipitable Water (PW)*
Equivalent Potential Temperature (e)*
Moisture Flux “Convergence” (MFC)*
* Can be calculated over many different layers/levels/parcels
A cornucopia of “indices”
Lifted Index (LI)*
Convective Available Potential Energy (CAPE)*
Total Totals (TT)
Convective Inhibition (CIN)*
K Index (KI)
Bulk Richardson Number (BRN)*
Showalter Index (SI)
Bulk Richardson Number Shear (BRNSHR)
Severe Weather Threat (SWEAT)
Bulk Vertical Wind Shear*
CAP Strength (700 mb LI)
Total Vertical Wind Shear*
Lapse Rate (LR)*
Storm-Relative Wind*
Relative Humidity (RH)*
Storm-Relative Helicity (SRH)*
Downdraft CAPE (DCAPE)
Lifted Condensation Level (LCL)*
Normalized CAPE (nCAPE)*
Level of Free Convection (LFC)*
Equilibrium Level (EL)*
Wet Bulb Zero (WBZ)
Melting Level (MLT)
Warm Cloud Depth (WCD)*
Precipitable Water (PW)*
Equivalent Potential Temperature (e)*
Moisture Flux “Convergence” (MFC)*
* Can be calculated over many different layers/levels/parcels
A cornucopia of “indices”
Lifted Index (LI)*
Convective Available Potential Energy (CAPE)*
Total Totals (TT)
Convective Inhibition (CIN)*
K Index (KI)
Bulk Richardson Number (BRN)*
Showalter Index (SI)
Bulk Richardson Number Shear (BRNSHR)
Severe Weather Threat (SWEAT)
Bulk Vertical Wind Shear*
CAP Strength (700 mb LI)
Total Vertical Wind Shear*
Lapse Rate (LR)*
Storm-Relative Wind*
Relative Humidity (RH)*
Storm-Relative Helicity (SRH)*
Downdraft CAPE (DCAPE)
Lifted Condensation Level (LCL)*
Normalized CAPE (nCAPE)*
Level of Free Convection (LFC)*
Equilibrium Level (EL)*
Wind Index (WINDEX)
Wet Bulb Zero (WBZ)
Dry Microburst Index (DMI)
Melting Level (MLT)
Theta-E Index (TEI)
Warm Cloud Depth (WCD)*
Microburst Day Potential Index (MDPI)
Precipitable Water (PW)*
Wet Microburst Severity Index (WMSI)
Equivalent Potential Temperature (e)*
Moisture Flux “Convergence” (MFC)*
* Can be calculated over many different layers/levels/parcels
A cornucopia of “indices”
Lifted Index (LI)*
Convective Available Potential Energy (CAPE)*
Total Totals (TT)
Convective Inhibition (CIN)*
K Index (KI)
Showalter Index (SI)
Severe Weather Threat (SWEAT)
HI = Haines Index*
HMI = Hybrid Microburst Index
Bulk Richardson Number (BRN)*
LSI = Lid Strength Index
DCI = Deep Convective Index
Bulk Richardson Number Shear (BRNSHR) TQ Index = for “low-topped
instability”
Bulk Vertical Wind Shear*
CAP Strength (700 mb LI)
Total Vertical Wind Shear*
Lapse Rate (LR)*
Storm-Relative Wind*
Relative Humidity (RH)*
Storm-Relative Helicity (SRH)*
Downdraft CAPE (DCAPE)
Lifted Condensation Level (LCL)*
Normalized CAPE (nCAPE)*
Level of Free Convection (LFC)*
Equilibrium Level (EL)*
Wind Index (WINDEX)
Wet Bulb Zero (WBZ)
Dry Microburst Index (DMI)
Melting Level (MLT)
Theta-E Index (TEI)
Warm Cloud Depth (WCD)*
Microburst Day Potential Index (MDPI)
Precipitable Water (PW)*
Wet Microburst Severity Index (WMSI)
Equivalent Potential Temperature (e)*
Moisture Flux “Convergence” (MFC)*
* Can be calculated over many different layers/levels/parcels
A cornucopia of “indices”
Lifted Index (LI)*
Convective Available Potential Energy (CAPE)*
Total Totals (TT)
Convective Inhibition (CIN)*
K Index (KI)
Showalter Index (SI)
Severe Weather Threat (SWEAT)
HI = Haines Index*
HMI = Hybrid Microburst Index
Bulk Richardson Number (BRN)*
LSI = Lid Strength Index
DCI = Deep Convective Index
Bulk Richardson Number Shear (BRNSHR) TQ Index = for “low-topped
instability”
Bulk Vertical Wind Shear*
CAP Strength (700 mb LI)
Total Vertical Wind Shear*
Indices of Indices (“Inbreeding”)
Lapse Rate (LR)*
Storm-Relative Wind*
Energy-Helicity Index (EHI)*
Relative Humidity (RH)*
Storm-Relative Helicity (SRH)* Vorticity Generation Parameter (VGP)*
Lifted Condensation Level (LCL)*
Downdraft CAPE (DCAPE)
Supercell Composite Parameter (SCP)*
Normalized CAPE (nCAPE)*
Significant Tornado Parameter (STP)*
Level of Free Convection (LFC)*
Significant Hail Parameter (SHIP)
Equilibrium Level (EL)*
Wind Index (WINDEX)
Significant Severe Parameter (SSP)
Wet Bulb Zero (WBZ)
Dry Microburst Index (DMI)
Strong Tornado Parameter (STP)
Melting Level (MLT)
Theta-E Index (TEI)
Warm Cloud Depth (WCD)*
Microburst Day Potential Index (MDPI)
Precipitable Water (PW)*
Wet Microburst Severity Index (WMSI)
Equivalent Potential Temperature (e)*
Moisture Flux “Convergence” (MFC)*
* Can be calculated over many different layers/levels/parcels
A cornucopia of “indices”
Lifted Index (LI)*
Convective Available Potential Energy (CAPE)*
Total Totals (TT)
Convective Inhibition (CIN)*
K Index (KI)
Showalter Index (SI)
Severe Weather Threat (SWEAT)
HI = Haines Index*
HMI = Hybrid Microburst Index
Bulk Richardson Number (BRN)*
LSI = Lid Strength Index
DCI = Deep Convective Index
Bulk Richardson Number Shear (BRNSHR) TQ Index = for “low-topped
instability”
Bulk Vertical Wind Shear*
CAP Strength (700 mb LI)
Total Vertical Wind Shear*
Indices of Indices (“Inbreeding”)
Lapse Rate (LR)*
Storm-Relative Wind*
Energy-Helicity Index (EHI)*
Relative Humidity (RH)*
Storm-Relative Helicity (SRH)* Vorticity Generation Parameter (VGP)*
Lifted Condensation Level (LCL)*
Downdraft CAPE (DCAPE)
Supercell Composite Parameter (SCP)*
(SCP)
Normalized CAPE (nCAPE)*
Significant Tornado Parameter (STP)*
Level of Free Convection (LFC)*
Significant Hail Parameter (SHIP)
Equilibrium Level (EL)*
Wind Index (WINDEX)
Significant Severe Parameter (SSP)
Wet Bulb Zero (WBZ)
Dry Microburst Index (DMI)
Strong Tornado Parameter (STP)
Melting Level (MLT)
Theta-E Index (TEI)
Warm Cloud Depth (WCD)*
Microburst Day Potential Index (MDPI)
Precipitable Water (PW)*
Wet Microburst Severity Index (WMSI)
Equivalent Potential Temperature (e)*
Moisture Flux “Convergence” (MFC)*
Mesoscale Convective System Forecast Index (MCS Index)
 a recent index published in WAF (2007)
* Can be calculated over many different layers/levels/parcels
 This list is not nearly exhaustive!
What’s a forecaster to do?
Outline
• Make note of several “indices”
• Discuss utility & attributes of indices (+ / -)
• Show several examples of testing indices for
operations – implications for training
Attributes of indices
• Doswell and Schultz (2006)
– “On the Use of Indices and Parameters in
Forecasting Severe Storms”
– Electronic Journal of Severe Storms Meteorology
– http://www.ejssm.org/
Benefits of indices
• Can summarize large amounts of data
• Can quickly draw attention to “critical” areas
for further diagnosis
– Both are attractive when under time pressure
Index limitations
• Not necessarily forecast parameters; may be
diagnostic (e.g., SPC meso page)
– Diagnostic variables give current state
(≠ /t), where  = STP, SCP, CAPE, etc.
• Most indices are not rigorously developed or
validated – arbitrarily combined variables
Index limitations
• Can lead to faulty perceptions of atmosphere
via over-simplification
– Little value in isolation; different combos can
produce similar values
– Flavor of the parameter? (e.g., EHI and its inputs)
– Constituents can evolve quasi-independently
• Action often occurs at “The Edge” – next three slides
The Edge: 20 Jun 2006 – Rushville, NE
Tornadic left-moving supercell
LSCP
(1-EF1)
The Edge: 16 Sep 2006 – Rogers, MN
(1-EF2)
The Edge: 28 Feb 2007 – Eastern KS
(1-EF4)
Important to train new forecasters not to focus on bulls-eyes.
Outline
• Make note of several “indices”
• Discuss utility & attributes of indices (+ / -)
• Show several examples of testing indices for
operations – implications for training
The STP index
• Thompson et al. (2003, WAF)
– Significant Tornado Parameter (STP)
•
•
•
•
Mean-layer CAPE (MLCAPE, lowest 100mb)
0-6km shear vector magnitude (SHR6)
0-1km storm-relative helicity (SRH1)
Mean layer LCL (MLLCL, lowest 100mb)
Let’s test this
• Estimate valid ranges and calculate each term
– For example: MLCAPE ~ 100 to 5000 J kg-1
• Term 1 thus ranges from 0.1 to 5
– (100/1000) = 0.1
– (5000/1000) = 5
Versions of the STP
Versions of the STP
Versions of the STP
If you use them, know your indices!
Outline
• Make note of several “indices”
• Discuss utility & attributes of indices (+ / -)
• Show several examples of testing indices for
operations – implications for training
Example of coord system sensitivity
• SWEAT Index (SW): 27-28 May 2001 OK case
• SW = 331
• What if 850 wspd
= 15 kts? (SW = 429)
• Now what if wdir 30
to left (SW = 331)
Supercell motion example: BUFKIT
• Bunkers et al. (2000)
– Non-weighted MW for
supercell motion, every
500 meters
• BUFKIT
– Uses ALL data for MW;
produces low-level bias
– Supercell motion often
too slow…so beware of
BUFKIT algorithm!
SCM: Excel vs. BUFKIT
275° 28 kts
12-kt difference between the two!
…but AWIPS is okay
Summary for indices
• Look at the raw data (e.g., surface maps,
soundings, 0-1km shear, MLLCL, etc.)
• View the indices’ constituent components
(e.g., 4-panel mode)…”STP = 2 means what?”
• Test new indices before implementing them in
operations (e.g., the MCS index)
– Folly to develop indices away from operations
One final thought
“The author’s most regrettable severe storm forecast
mistakes have arisen from ignoring data that were
relevant to the daily diagnosis…and/or failing to
complete the diagnosis on what initially appeared to
be a benign weather day.”
– Al Moller (2001, Severe Convective Storms Monograph)
• Analysis and diagnosis of observational data is critical – yet
this has become a lost art.