Storm Prediction Center: Storm-Scale Ensemble of Opportunity Israel Jirak & Steve Weiss Science Support Branch Storm Prediction Center Norman, OK Acknowledgments:

Storm Prediction Center:Storm-Scale Ensemble of Opportunity

Israel Jirak & Steve WeissScience Support BranchStorm Prediction CenterNorman, OK

Acknowledgments:Andy Dean, Gregg Grosshans, and Chris Melick

Storm-Scale Ensemble of OpportunityIntroduction

DATA OVERLOAD!!!NSSL WRF-ARW HRW WRF-ARW

CONUS WRF-NMM HRW WRF-NMM

NAM CONUS NEST

SSEO:An efficient way to summarize this information

An operational ensemble of convection-allowing models (CAMs) may not be available for some time, so SPC is exploring the utility of blending existing CAMs into a “storm-scale ensemble of opportunity” (SSEO)

Advantages: Data already available onsite Efficient method of summarizing data from multiple deterministic

models Data available year round, which allows for a large sample for

calibration purposes Disadvantages:

Little to no control over configuration and/or model changes Likely insufficient diversity

Storm-Scale Ensemble of OpportunityIntroduction

We can use what we’ve learned from working with the CAPS SSEF during the Spring Experiment.

Traditional ensemble probabilities of HMFs (Hourly Max Fields) from high-resolution models are not especially useful, owing to poor agreement among members at the grid point of these fields.

Applying a binary neighborhood approach to a storm-scale ensemble improves the statistical results of HMFs in forecasting severe weather ROI=20-40 km Sigma=30 grid points

SSEONeighborhood Method

03 May 2008 (Harless 2010)

Using built-in ensemble functions in N-AWIPS/GEMPAK to minimize post-processing

Ensemble products include [MN]: Ensemble mean [MX]: Ensemble max [PC]: Percentile values [PR]: Traditional ensemble probability (@ grid point) [PRS]: Smoothed traditional ensemble probability [NPR]: Binary neighborhood ensemble probability – code

written (C. Melick) to calculate neighborhood max [NPRS]: Smoothed binary neighborhood ens. probability [SP]: Spaghetti plots

SSEOProcessing and Products

SSEONMAP – Spaghetti Plots

SSEONMAP – Ensemble Fields

Ensemble selection window will pop up.

Select the appropriate cycle and hit accept.

1) NSSL WRF-ARW2) HRW WRF-ARW3) HRW WRF-ARW -12 h4) EMC WRF-NMM5) HRW WRF-NMM6) HRW WRF-NMM -12 h7) NMMB Nest

SSEO00Z Membership

HM Updraft Helicity > 25 m2s-2

SSEO 24-hr fcst valid 00Z 28 April

SSEO Severe[SP]:HM Updraft Helicity ≥25 m2s-2

SSEO forecasts of supercell tracks during 23-00z

Ensemble Maximum HM Updraft Helicity (m2s-2)


SSEO Severe[MX]:HM Updraft Helicity

The HMF UH values indicate tracks of intense, fast moving supercells during a 1-hr period.

Ensemble Probability HM Updraft Helicity >25 m2s-2


SSEO Severe[PR]:HM Updraft Helicity ≥25 m2s-2

Poor agreement at the grid point results in low traditional ensemble probabilities.

40-km Neighborhood Probability HM Updraft Helicity >25 m2s-2


SSEO Severe[NPR]:HM Updraft Helicity ≥25 m2s-2

Unsmoothed neighborhood probability illustrates 40 km search radius around each grid point

40-km Neighborhood Smoothed Prob HM Updraft Helicity >25 m2s-2


SSEO Severe[NPRS]:Updraft Helicity ≥25 m2s-2

Smoothing the 40-km neighborhood probability over 10 grid points better represents storm-scale predictability

3-hr Ensemble Maximum HM Updraft Helicity (m2s-2)


SSEO Severe[MX]:3-hr HM Updraft Helicity (m2s-2)

Post-processing UH over 3-h periods provides information about persistent long-track supercell corridors

3-hr spaghetti plot of UH ≥25 m2s2

SSEO SevereVerification: 16 April 2011 (18-21Z)


3-hr ensemble max of UH (m2s2)


3-hr neighborhood prob of UH ≥25 m2s2







SSEO SevereVerification: 22 May 2011 (21-00Z)








* Two members missing







The Fractions Skill Score (FSS) was calculated for smoothed binary neighborhood probability (ROI=40 km; σ=40 km) of updraft helicity ≥ 25 m2s-2 for the SSEO/SSEF versus practically perfect hindcasts of severe weather reports (ROI=40 km; σ=120 km) during SE2011.

The FSS is used here as a neighborhood approach to objectively assess the agreement between forecasts and observations.

SSEO SevereUH Verification SE2011

SSEO SSEF – 24 memberFSS = 0.84 FSS = 0.68

3-hr [NPRS]:UH ≥25 m2s-2 valid 06Z on 02 June 2011

Although the distributions of FSS for individual 3-h forecasts were similar among the ensembles, the SSEO had the highest cumulative (i.e., weighted) FSS during SE2011.

The number of members included in the SSEF did not seem to have a strong impact on the statistical results for updraft helicity during SE2011 when verified against severe weather reports.

SSEO SevereUH Verification SE2011

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SSEO SSEF - 24 SSEF - 15 SSEF - 50.44

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SSEO SSEF - 24 SSEF - 15 SSEF - 5

Cumulative FSSFSS Distribution of 3-h Forecasts

A three-level classification based on storm attributes has been developed for the SSEF/SSEO: 1) updraft helicity - supercell 2) updraft speed – multicell, ordinary/pulse 3) 10-m wind speed – bow echo/MCS

These smoothed 40-km neighborhood probabilities (e.g., [NPRS] UH>25 m2s-2) of are paired with SSEO neighborhood probability of 1-km AGL simulated reflectivity >40 dBZ [all fields are HMFs]

The probabilities are then binned and associated with a historical frequency of severe weather within 25 miles of a point [NPRS] UH>25 = 30% and [NPRS] Refl >40 = 40% :

>> 5% probability of severe weather

SSEO SevereCalibrated Severe

If [NPRS] UH>25 m2s-2 >0%, then Level 1

Predictor 1: [NPRS] UH>25 m2s-2 Predictor 2: [NPRS] 1-km AGL Refl >40 dBZ

Else If [NPRS] Updraft>10 m/s >0%, then Level 2

Predictor 1: [NPRS] Updraft>10 m/s Predictor 2: [NPRS] 1-km AGL Refl >40 dBZ

Else If [NPRS] 10-m WS>30 kts>0% & [NPRS] 1-km AGL Refl >40 dBZ, then Level 3:

Predictor 1: [NPRS] 10-m WS>30 kts Predictor 2: [NPRS] 1-km AGL Refl >40 dBZ

Else Probability of Severe = 0%

SSEO SevereCalibrated Severe

SSEO SevereCalibrated Severe Verification SE2011

Fractions Skill ScoreCalibrated Severe vs. Practically Perfect Reports

18 days during SE2011 - area of interest - f18-f30

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SSEO SSEF SREF SREF NEW FORECASTER

FS

S Independent Cal

Dependent Cal




ROC Area Under CurveCalibrated Severe vs. Reports (w/in 25 mi on 40-km grid)

18 days during SE2011 - HRW domain - f18-f30

0.885

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SSEO SSEF SREF SREF NEW

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Independent Cal

Dependent Cal


SSEO Dependent Calibration18 days during SE2011 – HRW Domain – f18-f30

SSEO Independent Calibration18 days during SE2011 – HRW Domain – f18-f30

SSEO SevereCalibrated Severe Example: 22 October 2011

SSEO SREF

Allows for a quick overview to gauge whether an area deserves a closer look in NMAP.

Also can be used for evaluation of performance on previous days.

SSEO SevereWebsite

Experimental storm-scale ensembles have potential to provide unique and useful information about the likelihood of convective storm occurrence, mode, and intensity

Our initial subjective assessment during the spring months including intensive examination during the 2011 HWT Spring Experiment indicates that the SSEO is capable providing guidance that is comparable to the larger SSEF and better than SREF

Initial statistical verification of calibrated severe probability forecasts during the Spring Experiment period supports the subjective evaluations

Additional testing and evaluation will be performed over a wider range of convective regimes during the summer, fall, and winter seasons

SSEO SevereSummary

Can utilize Refl ≥40 dBZ ([SP],[NPRS]) as proxy for thunderstorms. Has limitations, but may be used to add temporal and spatial resolution

to enhanced thunder when examined in conjunction with other data.

SSEO ThunderOverview

Examined the SSEO for 6-hr QPF during the 2011 Spring Experiment.

Subjective impressions were positive as noted in the graph below.

SSEO QPFOverview

from Dave Novak, HPC

Objective verification (below) validates subjective impressions during the Spring Experiment

SPC has been providing HPC with SSEO data since May, and they have been using it operationally for Day 1 QPF.

SSEO QPFOverview

from Tara Jensen, DTC

Pairwise Difference

SSEO favored over CAPS ensemble

Started exploring the utility of SSEO in fire weather applications during Fire Weather Experiment this summer.

Ensemble Products: [PR] Hourly Max 10-m Wind Speed [PR] 2-m RH [CPR] 10-m Wind Speed AND 2-m RH [MN], [MX], [PR] Fosberg Fire Wx Index

SSEO Fire WeatherOverview

SSEO Fire Weather[PR]:10-m Wind Speed ≥20 mph

Western Boundary

Notice high-resolution features, such as higher wind speeds over gulfs and bays.

SSEO Fire Weather [PR]:2-m RH <20%

SSEO Fire Weather[CPR]:10-m Wind Speed >20 mph & 2-m RH <20%

SSEO Fire Weather[MN]:Fosberg Fire Weather Index

SSEO SREF

SSEO Fire Weather [MX]:Fosberg Fire Weather Index

SSEO SREF

Notice local maxima in Fosberg, resulting from thunderstorm gusts.

SSEO Fire Weather [PR]:Fosberg Fire Weather Index >50

SSEO SREF

With low probabilities in those areas.

SREF Mean Fosberg ≥50

SSEO Mean Fosberg ≥50

SSEO Fire WeatherVerification using SFCOA Fosberg

SSEO Fire Weather Enhanced Temporal Resolution Over SREF

SSEO Fire Weather Enhanced Spatial Resolution Over SREF

The SSEO provides enhanced temporal and spatial resolution over the SREF.

Subjective impressions from a few late summer and fall cases have been positive on providing useful additional or confirming information.

00Z SSEO data available shortly after 36-h forecast of NSSL WRF-ARW comes in, which is typically ~815Z, but can vary on the day.

Drawbacks: Domain does not cover entire CONUS with no coverage

over WA, ORE, CA, & NV. HRW runs are often pre-empted during the hurricane

season, limiting the SSEO membership.

SSEO Fire WeatherOverview

Planning to explore the utility of SSEO for winter weather applications over the next few months.

Ensemble Products: [PR] Precipitation Type [MN], [PC] 1-km Refl (shaded by dominant p-type) [MN], [PC] 1-hr Prec (shaded by dominant p-type) [CPR] Refl>25 dBZ AND p-type = snow [CPR] Refl>15 dBZ AND p-type = fzrn

SSEO WinterOverview

SSEO Winter[MN]:1-hr Precip by Dominant P-Type

More than ½ members predicting rainMore than ½ members predicting zr

More than ½ members predicting snowThe residual – labeled as MIXED/IP

SSEO Winter[PC]:1-km Median Refl by Dominant P-Type

SSEO Winter[PR]:Precipitation Type

SSEO Winter[PR]:Precipitation Type

SSEO WinterVerification

SSEO WinterVerification

The use of high-resolution ensembles for winter weather forecasting is essentially a new application. HPC is planning on evaluating the 4-km AFWA 10-

member WRF-ARW ensemble during their Winter Weather Experiment.

We would appreciate feedback on the utility of the SSEO winter products for the issuance of winter MDs when applicable.

SSEO WinterOverview

Experimental storm-scale ensembles have potential to provide unique and useful probabilistic information: convective storm occurrence, mode, and intensity

Possible uses: 13Z, 1630Z, & 20Z Day 1 Outlooks, Enhanced Thunder Outlooks, Convective MDs

fire weather conditions Possible uses: Day 1 Fire Weather Outlooks

winter weather precipitation rate and type Possible uses: Winter Weather MDs

Things to keep in mind: Experimental2! Experimental processing of experimental models. Domain does not cover full CONUS, excludes WA, OR, CA, & NV. HRW runs are often pre-empted during the hurricane season, limiting SSEO

membership. Check spaghetti plot on website to verify members available. 00Z SSEO currently available ~0815Z after 36-hr NSSL WRF forecast

is processed. 12Z SSEO – essentially updates the 00Z SSEO with four 12Z members

(HRW WRF-ARW, HRW WRF-NMM, CONUS WRF-NMM, & NAM CONUS NEST) – available ~1745Z after the 12Z HRW runs are processed.

There are numerous exciting possibilities with the SSEO! We are interested in your feedback: comments, suggestions, criticisms, etc.

SSEOSummary

Documents

Storm Prediction Center: Storm-Scale Ensemble of Opportunity Israel Jirak & Steve Weiss Science Support Branch Storm Prediction Center Norman, OK Acknowledgments: