National Weather Service The Short-Range Ensemble Forecast: Applying Uncertainty and Probabilistic Forecasts of Winter Storms Matt Steinbugl, NOAA/NWS.

National Weather Service

The Short-Range Ensemble Forecast: The Short-Range Ensemble Forecast: Applying Uncertainty and Probabilistic Applying Uncertainty and Probabilistic

Forecasts of Winter Storms Forecasts of Winter Storms

Matt Steinbugl, NOAA/NWS Des Matt Steinbugl, NOAA/NWS Des MoinesMoines

Rich Grumm, NOAA/NWS State Rich Grumm, NOAA/NWS State CollegeCollege


Short-Range Ensemble Forecast Short-Range Ensemble Forecast ObjectivesObjectives

• ConveyConvey and and applyapply uncertainty to the uncertainty to the forecast processforecast process• RecognizeRecognize and and assignassign probabilities to probabilities to crucial winter weather forecast crucial winter weather forecast parametersparameters

This will allow forecasters:This will allow forecasters:• To To increase overall confidenceincrease overall confidence within within each individual forecast through a each individual forecast through a probabilistic approachprobabilistic approach• To To make better decisionsmake better decisions while allowing while allowing users better decision making capabilitiesusers better decision making capabilities


Why Ensembles – Why Ensembles – Uncertainty/ChaosUncertainty/Chaos


Why Ensembles?Why Ensembles?

•Uncertainty in initial conditions Uncertainty in initial conditions and model calculations can alone and model calculations can alone lead significant outcome changes lead significant outcome changes (run-to-run)(run-to-run)

•Need to account for non-linear Need to account for non-linear processesprocesses

•Atmosphere is chaotic in natureAtmosphere is chaotic in nature


Why Ensembles?Why Ensembles?

•Needed to deal with inherent forecast Needed to deal with inherent forecast uncertaintyuncertainty

•Improve significant winter weather Improve significant winter weather forecastsforecasts

•Recognize high uncertainty/high Recognize high uncertainty/high probability outcomes and relate these probability outcomes and relate these to each phase of the forecast processto each phase of the forecast process



What is the SREF?What is the SREF?

Multi-model based ensemble Multi-model based ensemble prediction system (EPS) with each prediction system (EPS) with each member having different dynamical member having different dynamical cores and physics packages.cores and physics packages.

21 individual members:21 individual members:

5 ETA (BMJ) + 5 ETA (KF) + 5 RSM 5 ETA (BMJ) + 5 ETA (KF) + 5 RSM ++6 WRF NMM/ARW (BMJ/KF) = 6 WRF NMM/ARW (BMJ/KF) = 21 21 membersmembers

-3 hourly output out to 87hrs-3 hourly output out to 87hrs-Produced at NCEP 03Z, 09Z, 15Z -Produced at NCEP 03Z, 09Z, 15Z and 21Z and 21Z


Deterministic (GFS) vs. Deterministic (GFS) vs. Probabilistic (SREF)Probabilistic (SREF)

ModelModel Initial Initial ConditionCondition

s (ICs)s (ICs)

Model Model corescores

RemarksRemarks

GFSGFS 1 IC1 IC 1 model 1 model corecore

run-to-run-to-run run

(jumpine(jumpiness)ss)

SREFSREF Multiple Multiple ICsICs

Multiple Multiple corescores

More More consistenconsisten

cycyComparing deterministic models is a 50/50 Comparing deterministic models is a 50/50

proposition!!!proposition!!!


SREF PerformanceSREF Performance


Case Study DataCase Study Data

•Examine 3 significant winter Examine 3 significant winter weather events across the weather events across the Eastern United StatesEastern United States

•We need to extract the We need to extract the following from the data:following from the data:

-Amounts/timing of pcpn?-Amounts/timing of pcpn?-PYTPE?-PYTPE?-Temps for Snow vs. Ice?-Temps for Snow vs. Ice?-Pattern Recognition?-Pattern Recognition?-Atypical/typical event?-Atypical/typical event?


Case Study #1 22-23 Dec 2004Case Study #1 22-23 Dec 2004


SpaghettiSpaghetti//Probability charts - 0° Probability charts - 0° isothermisotherm

Mean Mean and and probabilprobabilityity

sprespreadad

22mm

850850mbmb


Mixed/Conditional Probability Mixed/Conditional Probability charts PYTPEcharts PYTPE

RaiRainn

Ice Ice PelletsPellets

SnoSnoww

FZRFZRAA


Probability/Mean charts – Probability/Mean charts – 0.50/1.00” QPF0.50/1.00” QPF

National Weather ServiceMRCMRCCC


Case Study #2 23-25 April 2005Case Study #2 23-25 April 2005


Mixed/Conditional Probability Mixed/Conditional Probability charts PYTPEcharts PYTPE

RaiRainn

Ice Ice PelletsPellets

SnoSnoww

FZRFZRAA


Probability/Mean 0.40” QPFProbability/Mean 0.40” QPF


Detroit, MI Plume DiagramDetroit, MI Plume Diagram

National Weather ServiceNOHRSNOHRSCC


SummarySummary EPSs are an important means of:EPSs are an important means of:•Explicitly conveying and applying uncertainty Explicitly conveying and applying uncertainty through a probabilistic approachthrough a probabilistic approach

•Visualizing and quantifying uncertainty Visualizing and quantifying uncertainty within the forecast processwithin the forecast process

Using ensembles will allow forecasters to Using ensembles will allow forecasters to relate probabilities to each phase of the relate probabilities to each phase of the warning decision processwarning decision process

In turn, this will allow forecasters to make In turn, this will allow forecasters to make better decisions and users to have better better decisions and users to have better decision making capabilitiesdecision making capabilities


SpecialSpecial ThanksThanks

Rich Grumm, SOO CTPRich Grumm, SOO CTP

Karl Jungbluth, SOO DMXKarl Jungbluth, SOO DMX

Peter Manousos, SOO NCEPPeter Manousos, SOO NCEP

Jun Du, NCEP/EMCJun Du, NCEP/EMC

Steve Wiess, SPCSteve Wiess, SPC

Jeremy Grams, SPCJeremy Grams, SPC

David Bright, SPCDavid Bright, SPC


Questions ???Questions ???


ReferencesReferences

http://http://www.hpc.ncep.noaa.gov/ensembletrainingwww.hpc.ncep.noaa.gov/ensembletraining//

http://wwwt.emc.ncep.noaa.gov/mmb/SREF/WMO06_full.pdfhttp://wwwt.emc.ncep.noaa.gov/mmb/SREF/WMO06_full.pdf

http://wwwt.emc.ncep.noaa.gov/mmb/SREF-Docs/http://wwwt.emc.ncep.noaa.gov/mmb/SREF-Docs/

AWOC Winter IC 6.3: Using Ensembles in Winter Weather AWOC Winter IC 6.3: Using Ensembles in Winter Weather Forecasting Forecasting

http://mcc.sws.uiuc.eduhttp://mcc.sws.uiuc.edu

http://nws.met.psu.edu/severe/index.jsphttp://nws.met.psu.edu/severe/index.jsp

http://nws.met.psu.edu/severe/2006/11May2006.pdfhttp://nws.met.psu.edu/severe/2006/11May2006.pdf

SREF Exploitation at NCEP’s Hydrometeorological Prediction Center SREF Exploitation at NCEP’s Hydrometeorological Prediction Center (HPC) (HPC) http://nws.met.psu.edu/severe/2005/23April2005.pdfhttp://nws.met.psu.edu/severe/2005/23April2005.pdf

Dealing with uncertainties in forecasts – M Steven Tracton Dealing with uncertainties in forecasts – M Steven Tracton NWS/NCEP/EMCNWS/NCEP/EMC

http://weather.unisys.com/archive/index.htmlhttp://weather.unisys.com/archive/index.html

http://eyewall.met.psu.edu/plumes/Plume.pdfhttp://eyewall.met.psu.edu/plumes/Plume.pdf

http://eyewall.met.psu.edu/plumes/PlumeDisplay.htmlhttp://eyewall.met.psu.edu/plumes/PlumeDisplay.html

http://eyewall.met.psu.edu/ensembles/java/ModelDisplay.htmlhttp://eyewall.met.psu.edu/ensembles/java/ModelDisplay.html

National Weather Service The Short-Range Ensemble Forecast: Applying Uncertainty and Probabilistic Forecasts of Winter Storms Matt Steinbugl, NOAA/NWS.

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