ESRL/GSD/AMB Modeling System Overview

WARN ON FORECASTAND HIGH IMPACT WEATHER WORKSHOP

09 February 2012

Use of Rapid Updating Meso and Storm scale Data ‐ ‐Assimilation to Improve Forecasts of

Thunderstorms and Other High Impact Weather: The Rapid Refresh and HRRR Forecast Systems

NOAA/ESRL/GSDCurtis Alexander, David Dowell, Steve Weygandt, Stan Benjamin, Ming Hu, Tanya Smirnova, Patrick Hofmann, Haidao Lin, Eric James and John Brown

ESRL/GSD/AMBModeling System Overview

3

Hourly Updated NOAA NWP Models

13km Rapid Refresh (RAP) (mesoscale)

13km RUC (mesoscale)

3km HRRR (storm-scale)

RUC – current oper Model, new 18h fcst every hour

High-Resolution Rapid Refresh Experimental 3km nest inside RAP, new 15-h fcst every hour

Rapid Refresh (RAP) replaces RUC at NCEP in 2012 WRF, GSI with RUC features

NOAA/ESRL/GSD/AMB Models

Model Version Assimilation Radar DFI Radiation Microphysics Cum

Param PBL LSM

RUC N/A RUC-3DVAR Yes RRTM/Dudhia Thompson Grell-

DevenyiBurk-

Thompson RUC

RAPWRF-ARW v3.2+

GSI-3DVAR Yes RRTM/Goddard Thompson G3 +

Shallow MYJ RUC

HRRRWRF-ARWv3.2+

None: RR I.C. No RRTM/

Goddard Thompson None MYJ RUC

Model Run at: Domain Grid Points

Grid Spacing

Vertical Levels

Vertical Coordinate

Boundary Conditions Initialized

RUC GSD, NCO CONUS 451 x

337 13 km 50 Sigma/ Isentropic NAM Hourly

(cycled)

RAP GSD,NCO

North America

758 x 567 13 km 50 Sigma GFS Hourly

(cycled)

HRRR GSD CONUS 1799 x 1059 3 km 50 Sigma RR Hourly

(no-cycle)

Model Configurations

HRRRPrimary CoSPA

(FAA)

NCEPESRL/GSD/AMB

RAPDev

RAPPrimary

HRRRDev

RUCOper

RAPNCO

RAPDev2

RAPRetro

HRRRRetro

Retrospective Real-Time

AMB RAP/HRRR verification system

NWS

ESRL/GSD/AMB Model Verification

Ceiling Vis 24-hr Precip (03-80 km)

Reflectivity(03-80 km) Upper-Air Surface

0.5 – 3.0 kft 0.5 -5.0 mi 0.01 – 3.00 in 15-45 dBZ Temp RH Wind Height Temp Dewpt Wind

CSI, Bias, PODy/n, FAR, TSS, HSS, Fcst Ratio, Obs Ratio RMS and Bias

Convection(04 km, 80 km) Other Weather Events?

0 – 100 % 0 – 100 %

CSI vs Bias, Reliability, ROC

Deterministic

Probabilistic

Spring 2011 Hourly HRRR Initialization from RAP

HourlyRAP

LateralBoundaryConditions

Interp to 3 km grid

HourlyHRRR 15-h fcst

Initial Condition

Fields

11 z 12 z 13 z

Time (UTC)

AnalysisFields

3DVARObs

3DVARObs

Back-groundFields

18-h fcst 18-h fcst

1-hrfcst

DDFI DDFI

1-hrfcst

18-h fcst

1-hrfcst

Interp to 3 km grid

15-h fcstUse 1-h

old LBC to reduce

latency

Use most recent IC (post-DFI)

to get latest radar info Reduced

Latency:~2h for 2011

- Hourly cycling of land surface model fields - 6 hour spin-up cycle for hydrometeors, surface fields

Rapid Refresh Partial Cycling

RAP Hourly cycling throughout the day

RAP spin-upcycle

GFSmodel

GFSmodel

RAP spin-upcycle

00z 03z 06z 09z 12z 15z 18z 21z 00z

Observationassimilation

Observationassimilation

ESRL/GSD/AMBModel Analysis/Forecast Bias

Inherent in Model Physics?Non-Optimal Use of Obs?

Limitations of Data Assimilation Method?

Need Accurate Mesoscale Environment for High Impact Prediction

RAP vs. RUC surface – cold season

COLD

W

ARM

LOW

H

IGH

2m Temper-ature (K)

2m Dew Point (m/s)

RAPRUC

3-week comparison9 – 30 Jan 2012Eastern US only

RUCRAP

Diurnal bias variation6-h fcst

RUC daytime quite cool, RAP good

Both too moist, especially during

day

Steve Weygandt

RAP vs. RUC surface – warm season

COLD

W

ARM

LOW

H

IGH

2m Temperature (K)

2m Dew Point (m/s)

RAPRUC

2-month comparison20 April – 20 July 2011

Eastern US only

RUCRAP

Diurnal bias variation6-h fcst

RUC daytime slightly cool, RAP warm, esp.

overnight

Both too moist, especially at night

RUC worse than RAP

Steve Weygandt

13-km CONUSComparison2 X 12 hr fcstvs. CPC 24-h analysis1 May – 15 July 2011Matched

RAP vs. RUC PrecipitationVerification

RAP

RUC

| | | | | | | |0.01 0.10 0.25 0.50 1.00 1.50 2.00 3.00 in.

| | | | | | | |0.01 0.10 0.25 0.50 1.00 1.50 2.00 3.00 in.

CSI(x 100)

RUC

RAP

100(1.0)

bias(x 100)

SPRING/SUMMER

Steve Weygandt

RAP and RUC Humidity BiasCONUS

All 00/12 UTC Raobs08 July – 08 Sept 2011

RUC/RR drier/moister below 650 mb, opposite aboveRR a closer fit to the observations by 6 hrs in lower tropWater vapor is the dominant source of the RH bias

RAPRUCRAP - RUC

00 hr (analysis) 06 hr fcsts

RAPRUCRAP - RUC

RAP and RUC Humidity BiasCONUS

All 00/12 UTC Raobs11-22 August 2011

NO RADAR DA

Without radar DA, model bias even more pronounced

RAPRUCRAP - RUC

00 hr (analysis) 06 hr fcsts

RAPRUCRAP - RUC

ESRL/GSD/AMBModel Analysis/Forecast Improvements 2012

16

Spring 2012 versions RAP (ESRL RAP and HRRR)

Model Data Assimilation

RAP (13 km) WRFv3.3.1+ Mods to physics (convection, microphysics, land-surface, PBL) Numerics changes (w-damp upper bound conditions, 5th-order vertical advection)

Soil adjustment, Temp-dep radar- hydrometeor buildingPW assim modsCloud assim modsTower/sodar observationsRadial wind assimGSI merge with trunk

HRRR (3 km) WRFv3.3.1+, Mods to physics (microphysics, land-surface, PBL)Numerics changes (w-damp upper bound conditions, 5th-order vertical advection)

Possible 3 km/15 min radar assimilationPossible 3km cloud cyclingPossible 3km land- surface cycling

Changes evaluated in current RAP/HRRR 2012 change bundle

Rapid Refresh prim ( ) vs. dev ( )RAP-dev has PBL-based pseudo-

observations

prim

dev

Residual mixed layer better depicted in RAP-dev (w/ PBL pseudo-obs) Observed

00z 7 July 2011Albany, NY sounding

23z 6 July 2011RAP sounding

RAP PBL pseudo-obs assimilation

18

Dewpoint bias in 6h RAP forecasts, eastern US, Aug 2011Reduced moisture bias as measured by 2-m dewpoint

Dry BiasMoist Bias

Real-time RAP

Retro RAP with soil adjustment and temp-dependent hydrometeor building from radar

Before DAAfter DA

conserving θv

Before DAAfter DA

NOT conserving θv

Improved cloud analysis by assuming conservation of virtual potential temperature

Latest 2012 Candidate HRRR EvaluationReflectivity ≥ 35 dBZ, 03 km ScaleSelect Cases 11-22 August 2011

CSI

03

kmB

IAS

03 k

m

Eastern US

Optimal

HRRR 2010 HRRR 2011HRRR 2012 – Reduced high BIAS infirst 6 hours and improved CSI

Latest 2012 Candidate HRRR EvaluationReflectivity ≥ 25 dBZ, 40 km ScaleSelect Cases 11-22 August 2011

CSI

40

kmB

IAS

03 k

m

Northeast Southeast

Optimal

Optimal

HRRR 2010 HRRR 2011HRRR 2012

12z + 4 hr fcstsValid 16z 14 Aug 2011

NSSL mosaic

RAPHRRR

2012 proto-type

retro test

RAPHRRR

2011 real-time

HRRR improvementsfrom RAP upgrades

(for 2012 HRRR CoSPA – more accurate convection,

reduced false alarm)

NSSL mosaicObservations

Valid 02z 18 Aug 2011

HRRR 2011 HRRR 2012HRRR 2010

18z 17 Aug 2011 Initializations8 hr forecasts

ESRL/GSD/AMBRadar Data Assimilation

Forward integration, full physicsApply latent heating from radar reflectivity, lightning data

Diabatic Digital Filter Initialization (DDFI)

-40 min -20 min Init +20 min

RUC/RR model forecast

Backwards integration, no physics

Obtain initial fields with improved balance, vertical circulations associated withongoing convection

Radar reflectivity assimilation in RUC and Rapid Refresh

Rapid Refresh (GSI + ARW) reflectivity assimilation example

Low-levelConvergence

Upper-levelDivergence

K=4 U-comp. diff (radar - norad)

K=17 U-comp. diff (radar - norad)

NSSL radar reflectivity

(dBZ)

14z 22 Oct 2008Z = 3 km

RAP – No radar data RAP – Radar data

HRRRReflectivity

00z 12 August 201100 hr forecasts

Convergence Cross-Section

RAP – No radar data RAP – Radar data

Convergence Cross-Section

01z 12 August 201101 hr forecasts

HRRRReflectivity

HRRR Reflectivity VerificationDDFI in 13-km RAP (parent model) AND in 3-km HRRR

Eastern US, Reflectivity > 25 dBZ14-24 July 2010

Application of DDFI at both scales results in spurious convectionSignificant loss of skill

2x Latent heating rate in RAP1x Latent heating rate in RAP1/3x Latent heating rate in RAP1x Latent heating in RR and HRRR

CSI 40 km BIAS 03 km

Optimal

2x Latent heating rate in RAP1x Latent heating rate in RAP1/3x Latent heating rate in RAP1x Latent heating in RR and HRRR

HRRR Reflectivity VerificationEastern US, Reflectivity > 25 dBZ

11-20 August 2011

Reflectivity DA in RAP/RUC increases HRRR forecast skillHRRR bias depends strongly on parent model

CSI 40 km

RUC->HRRR RadarRAP->HRRR Radar

RAP->HRRR No RadarRUC->HRRR No Radar

RAP->HRRR RadarRAP->HRRR No RadarRUC->HRRR RadarRUC->HRRR No Radar

BIAS 03 km

Optimal

Reflectivity DA on 3-km (HRRR) Grid

interpolation from RAP,hydrometeor specification

t060 min t045 min t030 min t015 min t0

reflectivity-based temperature tendency

NSSL3D

mosaic

HRRR composite reflectivityDavid Dowell

t045 min

t030 min t015 min t0

HRRR (3-km) grid produces convective storms explicitlyReflectivity-based temp. tendencies are applied during sub-

hourly cycling (forward model integration only, no digital filtering)

ESRL/GSD/AMBHRRR Forecast Post-Processing

Time-Lagged (TL) Ensemble

Spatio-temporal scale of probabilities

10-11 hr fcst

09-10 hr fcst

08-09 hr fcst

11-12 hr fcst

10-11 hr fcst

09-10 hr fcst

Forecasts valid 21-22z 27 April 2011 Forecasts valid 22-23z 27 April 2011

All six forecastssummed to formprobabilities valid22z 27 April 2011

HRRR 11z Init

HRRR 12z Init

HRRR 13z Init

The HCPF and HTPFHRRR Convective/Tornado Probabilistic Forecast (HCPF/HTPF) Estimate likelihood of convection and tornado production

• Intensity – ≥ 25 m2 s-2 Maximum Updraft Helicity 2-5 km AGL• Time – Two hour search window centered on valid times• Location – 45 km (15 gridpoints) search radius of each point• Members – Three consecutive HRRR initializationsHTPF = # grid points matching criteria over all members

total # grid points searched over all members

Caveats:Refinement needed to discriminate surface/elevated rotationEvaluate additional environmental fields that support tornado formationEvaluate additional diagnostic fieldsTornado scale not resolved

Case Selection from 2011

Date Region#

Tornado Reports

Max SPCRisk

Category*

Max SPCTornado

Probability*

14-Apr-2011 OK-AR 38 MDT 15%

15-Apr-2011 MS-AL 146 MDT 15%

16-Apr-2011 NC-SC-VA 139 HIGH 30%

26-Apr-2011 TX-AR-LA-MS-AL-TN 126 HIGH 30%

27-Apr-2011 MS-AL-TN-GA 292 HIGH 45%

28-Apr-2011 NC-SC-VA-MD 15 SLGT 10%

22-May-2011 OK-MO 75 MDT 15%

23-May-2011 22 MDT 10%

24-May-2011 OK-TX-AR 57 HIGH 45%

25-May-2011 MO-IL-IN 127 HIGH 30%

*Note: Maximum SPC forecast categories through 20z Day 1

ESRL/GSD/AMBHRRR Deterministic Skill

In Outbreaks

Tornado PeriodsStronger Forcing 14-16 April 2011

CSI

25 dBZ, 40 km 40 dBZ, 40 km25 dBZ, 03 km 40 dBZ, 03 km

03 hr fcsts 06 hr fcsts


25 dBZ, 40 km 40 dBZ, 40 km25 dBZ, 03 km 40 dBZ, 03 km26-28 April 2011

CSI

Tornado PeriodsStronger Forcing03 hr fcsts 06 hr fcsts


25 dBZ, 40 km 40 dBZ, 40 km25 dBZ, 03 km 40 dBZ, 03 km22-25 May 2011

CSI

Tornado PeriodsStronger Forcing03 hr fcsts 06 hr fcsts


ESRL/GSD/AMBHRRR TL Ensemble

Probabilistic ComparisonIn Outbreaks

27 April 2011HTPF 13z + 09hr fcst

Valid 22z 27 April 20111630z SPC Tornado Probability

27 April 2011 Storm Reports

Tornado = Red DotsTornado Probability (%)

27 April 2011

Tornado Probability (%)Reflectivity (dBZ)

HTPF 13z + 09hr fcstValid 22z 27 April 2011

27 April 2011 Storm Reports

Tornado = Red Dots

Observed Reflectivity22z 27 April

22 May 2011HTPF 13z + 11hr fcstValid 00z 23 May 2011

1300z SPC Tornado Probability

22 May 2011 Storm Reports


22 May 2011



Tornado = Red Dots

HTPF 13z + 11hr fcstValid 00z 23 May 2011

Observed Reflectivity00z 23 May









With MUCAPE LPL < 50 mb AGL

23 May 2011



Tornado = Red Dots







24 May 2011




Tornado = Red Dots


Summary

50

HRRR Challenges from a WOF/HIP perspective

Reduce latency from 2 hrs to 1 hr, 30 min, etc…?Tradeoff between assimilating latest mesoscale observations (more latency) and some radar observations (less latency)

Model moisture (and other) bias dominates convective forecastbehavior: initial condition error, model error, both?

Mesoscale environment remains a strong driver ofstorm-scale predictability

Weaker (stronger) forcing and smaller (larger) favorableenvironments do translate to lower (higher) skill forecasts

Small (large) run-to-run variability doesn’t always translate to a higher (lower) skill forecast

Documents

ESRL/GSD/AMB Modeling System Overview