HRRRTime-LaggedEnsemble(HRRR-TLE)Update

TrevorAlcott,Isidora Jankov,CurtisAlexanderSteveWeygandt,StanBenjaminESRLGlobalSystemsDivision,Boulder,CO

http://rapidrefresh.noaa.gov/hrrrtle/

Initial&LateralBoundaryConditions

Initial & Lateral Boundary Conditions

Expanded RAP

13-km Rapid Refresh (RAP) –21h (NCEP in July 2016)

39h (testing now at ESRL)

3-km High-Resolution Rapid Refresh (HRRR) –18h (NCEP in July 2016)

36h (testing now at ESRL)

750-m HRRR nest Wind Forecast

Improvement Project Experiment (ongoing)

Prototype 3-km storm-scale HRRR ensemble (HRRRE)Testing Spring 2016

3-km HRRR-Alaska

Testing now at ESRL

3-km HRRR Time-Lagged Ensemble (HRRR-TLE)

RAP/HRRRSuite:Hourly-UpdatingForecastModels

01z +0 +1

+0 +1 +2

+0 +1 +2 +3

Time-LaggedHRRRx2013ColoradoFloodCompositeReflectivity(dBZ)

valid02UTC12Sep

00z

23z

02zMRMS

Exp 3-MemberTime-LaggedEnsemblewith2-hourLatency

00ZRun(notready)

23ZRun(notready)

22Z(mostrecentavailable)

21ZRun

20ZRun

PeriodEnds06 Z

PeriodBegins00Z

MoremembersMorespread

LowerskillShorterleadtime

MoremodelsMorespreadUsefulspread?

Memberweighting

Givesnewestdatathehighestimpact>3runshaslittleadditionalimpactevenat100%weight

Time-LaggedEnsembletrade-offs

Prob

ability

PrecipitationAmount

Model

Observations

AddressingBiasandUnderdispersion

LowBias

HighBias

Spring2015

“Quantile Mapping”BiasCorrection

1.00”≅ 99th%ileofanalysisclimatology

99th%ile ofmodelclimatology

≅ 1.23”

=2weeks=1month=2months

40km≅ 13-grid-point radius

553pointsX3runs=1659ensemble“members”

Increasingspreadwithaspatialfilter

3vs.6Time-LaggedMembers

Results:Probabilityof0.5”Precipitationin6hoursMay-Aug2015

Over-confident

Under-confident

Forecastsvalid22-23z

10 - 11 hr forecast

9- 10 hr forecast

8 - 9 hr forecast

Forecastsvalid23-00z

11 - 12 hr forecast

10- 11 hr forecast

9 - 10 hr forecast

HRRR 11z Init

HRRR 12z Init

HRRR 13z Init

Probability (%)

Combiningspatialandtemporalfilters

RecentChangestoHRRR-TLE

• 24-hforecastlength

• Newsevere,flashflood,aviationproducts,allexperimental(ofcourse)

• Conversionofallfieldsto40-kmneighborhoodprobabilities

• TestedinWPCwinterweatherandSPC/HWTspringexperiments,andWPCFFaIR

Neighborhood/SpatialFilterAlgorithmDemonstration

50forecast/analysispairs

biascorrection

RawmemberQPF

Bias-correctedQPF

Neighborhood/SpatialFilterAlgorithmDemonstrationBias-correctedQPF

0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 00 0 0 1 0 0 0 0 0 00 0 0 1 0 0 0 0 0 00 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 00 0 0 0 0 0 1 0 0 00 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0

Identifygridpointswherebias-correctedQPFexceedsthe

thresholdofinterestandmarktheseasa“hit”(1)

Neighborhood/SpatialFilterAlgorithmDemonstrationBias-correctedQPF

0 0 0 0 0 0 0 0 0 00 0 1 1 1 0 0 0 0 00 0 1 1 1 0 0 0 0 00 0 1 1 1 0 0 0 0 00 0 1 1 1 0 0 0 0 00 0 0 0 0 1 1 1 0 00 0 0 0 0 1 1 1 0 00 0 0 0 0 1 1 1 0 00 0 0 0 0 0 0 0 0 0

Alsosetneighboringgridpointsto1.Simplified

exampleusesa1-grid-pointradius,butrealproductsuse40-km(about13gridpoints)

Neighborhood/SpatialFilterAlgorithmDemonstrationBias-correctedQPF

0 0 0 0 0 0 0 0 0 00 0 1 1 1 0 0 0 0 00 0 1 1 1 0 0 0 0 00 0 1 1 1 0 0 0 0 00 0 1 1 1 0 0 0 0 00 0 0 0 0 1 1 1 0 00 0 0 0 0 1 1 1 0 00 0 0 0 0 1 1 1 0 00 0 0 0 0 0 0 0 0 0

Nowapplythespatialfilter(typicallyamuchlargerradius

thantheneighborhood)

Neighborhood/SpatialFilterAlgorithmDemonstrationBias-correctedQPF

0 0 0 0 0 0 0 0 0 00 0 1 1 1 0 0 0 0 00 0 1 1 1 0 0 0 0 00 0 1 1 1 0 0 0 0 00 0 1 1 1 0 0 0 0 00 0 0 0 0 1 1 1 0 00 0 0 0 0 1 1 1 0 00 0 0 0 0 1 1 1 0 00 0 0 0 0 0 0 0 0 0

Inthisexample,48%ofpointsinthespatialfilterradiusare“hits”.Repeatthisforeach

member,andthefinalprobabilityistheaverageof

48%,A%,B%...

Python“fft_convolve”function

http://rapidrefresh.noaa.gov/hrrrtle/

PrecipitationProducts(exp)• 1-h,3-h,6-hPQPF• 6-hprobabilityofprecip exceeding100-yearARI• 3-hprobabilisticrunoff• 1-h,6-hprobabilisticsnowfall

HRRR 23z 13hr pcp fcst HRRR 00z 12 hr pcp fcst HRRR 01z 11 hr pcp fcst

ConsecutiveHRRRrunsproduced>6”precip in~12hrs06hrQPE>6”

Houston,TXFlashFlooding12UTC18April2016

HRRR-TLEforecasts>60%probabilityof6-hrQPFexceeding100-yearaveragereturninterval(ARI)inHoustonarea

ConvectiveProducts(exp)• 4-hprobabilitieswithin40-kmofapoint:

– Wind>50kt /Hail>1in/Tornado

• Hourlythunderstormprobability

AviationProducts(exp)• Hourlyprobabilityof:

– Visibility<5,3,1mi– Ceiling<3000,1000,500ft– IFRconditions– Echotops>25000,30000,35000ft

FireWeatherProducts(exp)• Hourlyprobabilityof:

– Drythunderstorm– 2-mRH<5,10,and/or15%– 10- or80-mwindspeedorgust>20,25and/or30mph– Combinationofaboveconditions

?

Hazard ModelField TruthHeavy rain QPF Stage-IV/MRMS

Heavysnow Explicit snowfrommodelmicrophysics

National snowfallanalysis

Thunderstorm Lightning threat3(graupelfluxandcolumnice)

NLDN

Severewind 10-m hourlymaxwind mesonet

Large hail Verticallyintegratedgraupel

MESH

Tornado Updrafthelicity,0-1-kmshear,SBCAPE/MUCAPE

stormreportsandMRMSrotationtracks

Visibility/Ceiling/EchoTop Visibility,cloudbase,echotopheight(18dBZ)

ASOS,MRMS

Red Flag- Fire 2-mRH,10-mwind URMA and/ormesonet

HRRR-TLE: Project TimelineOrganization/Experiment Hazards Platform Timeline

WPCWWE PQPF,Snowfall,Snow Rate NAWIPSandwebsite January 2016

NSSL/SPCEFP/EWP Tornadoes,Hail, Wind NAWIPSandAWIPSII May 2016

WPCFFaIR RefinedPQPFandFFguidance NAWIPS June2016

AWCSummerExperiment Initialaviationhazards:ceiling,visibility,convection

NAWIPS August 2016

WPCWWE RefinedwinterhazardsandPQPF NAWIPS January2017

AWCWinterExperiment Ceilingandvisibility NAWIPS February2017

NSSL/SPCEFP/EWP Refinedsevereweather guidance NAWIPSandAWPSII May 2017

WPCFFaIR RefinedFF guidance NAWIPS July 2017

AWCSummer Experiment/OPG Refinedaviationhazards NAWIPSandAWPSII August2017

Initiate NCO‘on-boarding” All IDP Late 2017or2018

ProductDevelopmentTimeline

EngageNationalCenterTestbeds

HRRRE-TLE

28Jun2016 17thWRFWorkshop 27

HRRR-TLEisakeycomponentofthisUSWRP-fundedproject:RefinementandEvaluationofAutomatedHigh-ResolutionEnsemble-BasedHazardDetectionToolsforTransitiontoNWSOperations