statistical severe convective risk assessment model (sscram) spc mesoanalysis data every hour from...
DESCRIPTION
SSCRAM Design – Gathering The Data SfcOA grid (40-km RUC-2/RAP)TRANSCRIPT
The Statistical Severe Convective Risk Assessment Model(SSCRAM)
John A. Hart and Ariel E. CohenNWS Storm Prediction Center, Norman, OK
Statistical Severe Convective Risk Assessment Model (SSCRAM)
SPC Mesoanalysis Data every hour from 2006-2014(Bothwell et al. 2002)
+CG NLDN LightningData 2006-2014
+Severe Reports2006-2014
SSCRAM – NWA 2015
System that relates current meteorological conditions near thunderstorms to short-term forecasts of severe weather (2006-
2014).
SSCRAM Design – Gathering The DataSfcOA grid (40-km RUC-2/RAP)
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Lightning strikes in the initial hour.
SSCRAM Design – Gathering The Data
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Grid the lightning strikes.
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SSCRAM Design – Gathering The Data
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- Example documentation: Top of hour at gridbox "4"
- Date/Time- Centerpoint (lat,lon)- # strikes- Bunkers storm motion- Environmental info from
SPC Mesoanalysis system
SSCRAM Design – Gathering The Data
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Bunkers et al. (2000) right-moving supercell motion.
x representstop-of-hourgrid center point
SSCRAM Design – Gathering The Data
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1 341 forecast point midway
through first hour;
gather all reports in areain first hour (40-km search radius)
forecast point midway through second hour;
gather all reports in areain the second hour (40-km search radius)
40 km
SSCRAM Design – Gathering The Data
40 km
SSCRAM Objectives• Produce probability distributions for numerous parameters.
• One of the most comprehensive datasets for severe forecasting.• Sample size of over 3.8 million lightning/environment grid-hours.
• Relate downstream severe reports with diagnostic parameters and lightning, and consider null events.
• Explore use of diagnostic parameters in a prognostic manner – motivated by Doswell and Schultz (2006).
• Base future impacts from present atmospheric state.
• Incorporation of ongoing environmental information can contribute to “warn-on-forecast” (Stensrud et al. 2009) and “Forecasting a Continuum of Environmental Threats” initiatives (Rothfusz et al. 2013).
SSCRAM – NWA 2015
How to Read The Charts
SSCRAM – NWA 2015
Conditional probability component –
Probability of severe report within parameter range...given lightning in grid box and other constraints.
Incorporate null set.0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20Prob (%)
How to Read The Charts
SSCRAM – NWA 2015
Relative frequency component (RF) –
Proportion of severe-producing environments associated with parameter range (with listed constraints/lightning occurrence).
Strictly requires reports.RF (%)
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20RF (%)
0
How to Read The Charts
SSCRAM – NWA 2015
Combined
Prob (%)RF (%)
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Most Unstable CAPE SSCRAM – NWA 2015
Prob (%)
Prob (%)
Prob (%)
Prob (%)
RF (%) RF (%)
RF (%)RF (%)
0 1 2 3 4 5
0 1 2 3 4 5
MUCAPE/1000
0 1 2 3 4 5
0 1 2 3 4 5
Increasing svr probabilities with increasing MUCAPE for wind/hail.
Most severe occurring for MUCAPE < 3000 J kg-1. Probabilities flat-line for tornadoes.
Effective Bulk Shear SSCRAM – NWA 2015
Increasing svr probabilities with increasing effective shear (especially above 10-15 kt).
Thompson et al. (2007)
Prob (%)
Prob (%)
Prob (%)
Prob (%)
RF (%) RF (%)
RF (%)RF (%)
0 25 50 75 100
0 25 50 75 100
0 25 50 75 100
0 25 50 75 100
SVR WIND – Effective Bulk Shear (Vary MUCAPE)SSCRAM – NWA 2015
Thompson et al. (2007)
With increasing MUCAPE, bulk of severe-wind reports occur at weaker effective shear,
and severe-wind probabilities increase.
Significant Tornado Parameter (STP) SSCRAM – NWA 2015
Increase in tor probabilities with increase in STP. STP < 1 accounts for around 60% of weak-tor-linked grid
boxes around 37% of sigtor-linked grid boxes.
Thompson et al. (2012)
Prob (%)
Prob (%)
RF (%)
RF (%)
0 5 10 15 20
0 5 10 15 20
Mixed-Layer Lifting Condensation Level Height (MLLCL)SSCRAM – NWA 2015
Surface-based, organized convection
Nearly flat-line probabilities. MLLCL of 0.5-1.1 km account for bulk of
tor-linked grid boxes.
Prob (%)
Prob (%)
RF (%)
RF (%)
0.0 0.5 1.0 1.5 2.0
0.0 0.5 1.0 1.5 2.0
MLLCL/1000
MLLCL/1000
Conclusions We have…
Created and explained a system for pairing environmental information with severe-storm occurrences in the future (2 hours). Incorporates severe-report and null occurrences.
Investigated ability for diagnostic parameters to provide probabilistic guidance for future severe-storm report occurrences. Useful for warn-on-forecast initiatives/FACETS.
MUCAPE – utility in anticipating severe hail/wind. Effective shear – utility in anticipating all severe hazards.
Bulk of severe wind occurs at decreasing effective shear for increasing MUCAPE. STP – utility in anticipating tornado occurrences. Tornadoes occur within an optimal range of MLLCL values, although
MLLCL offers similar probabilities of tornado occurrences across multiple parameter ranges.
We can apply this system to analyzing season variability of parameter utility for assessing tornado potential.
SSCRAM – NWA 2015
References Bothwell, P. D., J. A. Hart, and R. L. Thompson, 2002: An integrated three-dimensional
objective analysis scheme in use at the Storm Prediction Center. Preprints, 21st Conf. on Severe Local Storms/19th Conf. on weather Analysis and Forecasting/15th Conf. on Numerical Weather Prediction, San Antonio, TX, Amer. Meteor. Soc., JP3.1. [Available online at https://ams.confex.com/ams/pdfpapers/47482.pdf.]
Bunkers, M. J., B. A. Klimowski, J. W. Zeitler, R. L. Thompson, and M. L. Weisman, 2000: Predicting supercell motion using a new hodograph technique. Wea. Forecasting, 15, 61–79.
Doswell, C. A., III, and D. M. Schultz, 2006: On the use of indices and parameters in forecasting severe storms. Electronic J. Severe Storms Meteor., 1(3), 1–22.
Rothfusz, L. P., E. Jacks, J. T. Ferree, G. J. Stumpf, and T. M. Smith, 2013: Next-Generation Warning Concept: Forecasting a Continuum of Environmental Threats (FACETs). 2nd Conf. on Weather Warnings and Communication, Nashville, TN, Amer. Meteor. Soc., 3.4.
Stensrud, D. J., and Coauthors, 2009: Convective-scale warn-on-forecast system: A vision for 2020. Bull. Amer. Meteor. Soc., 90, 1487–1499.
Thompson, R. L., C. M. Mead, and R. Edwards, 2007: Effective storm-relative helicity and bulk shear in supercell thunderstorm environments. Wea. Forecasting, 22, 102–115.
Thompson, R. L., B. T. Smith, J. S. Grams, A. R. Dean, and C. Broyles, 2012: Convective modes for significant severe thunderstorms in the contiguous United States. Part II: Supercell and QLCS tornado environments. Wea. Forecasting, 27, 1136–1154.
SSCRAM – NWA 2015