Statistical Severe Convective Risk Assessment Model (SSCRAM) SPC Mesoanalysis Data every hour from 2006-2014 (Bothwell et al. 2002) + CG NLDN Lightning

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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- Example documentation: Top of hour at gridbox "4"

- Date/Time- Centerpoint (lat,lon)- # strikes- Bunkers storm motion- Environmental info from

SPC Mesoanalysis system


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Bunkers et al. (2000) right-moving supercell motion.

x representstop-of-hourgrid center point


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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


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 (%)


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


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


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.


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

Documents

Statistical Severe Convective Risk Assessment Model (SSCRAM) SPC Mesoanalysis Data every hour from 2006-2014 (Bothwell et al. 2002) + CG NLDN Lightning