RUC/Rapid Refresh Development and Testing Including TAMDAR and Radar Reflectivity Impact Studies NOAA Earth System Research Lab (ESRL) Global Systems Division

RUC/Rapid Refresh Development and Testing Including TAMDAR

andRadar Reflectivity Impact StudiesNOAA Earth System Research Lab (ESRL)

Global Systems Division (GSD)Boulder, CO

NOAA/ESRL/GSDStan BenjaminSteve WeygandtJohn M. BrownTanya SmirnovaDezso DevenyiKevin BrundageGeorg GrellSteven PeckhamTom SchlatterTracy Lorraine SmithNCEP/EMC – Geoff Manikin

Major transitions:• RUC13 change package – ~Jan 2008

– radar reflectivity assimilation, TAMDAR, current status, testing

• RUC changes in current testing• Rapid Refresh WRF testing in 2007 - planned testing in 2007

- Current impl plan – FY09 – 4Q

RUC Hourly Assimilation Cycle

11 12 13 Time (UTC)

1-hrfcst

Background

Fields

Analysis

Fields

1-hrfcst

RUC 3dvar

Obs

1-hrfcst

3dvar

Obs

Cycle hydrometeor, soil temp/moisture/snow plus atmosphere state variables

Hourly obs in 2008 RUCData Type ~NumberRawinsonde (12h) 80NOAA profilers 30 VAD winds 110-130 PBL – prof/RASS ~25Aircraft (V,temp) 1400-4500 TAMDAR (V,T,RH) 0-1000Surface/METAR 1500-Surface/METAR 1500-1700 1700 Buoy/ship 100-150 GOES cloud winds 1000-2500 GOES cloud-top pres 10 km res GPS precip water ~300Mesonet (temp, dpt) ~7000Mesonet (wind) ~ 600METAR-cloud-vis-wx ~1500Radar / lightning 2km

RUC

RapidRefresh(2009)Hourly NWP Update for: - CONUS- AK/Can- Pac/Atl- Caribbean

Current RUC CONUS domain

Planned approx Rapid Refresh domain

NWP updated hourly w/ latest obs• Aviation / transportation• Severe weather• Decision support tools

RUC History – NCEP (NMC) implementations

1994 - First operational implementation of RUC- 60km resolution, 3-h cycle

1998 – 40km resolution, 1-h cycle, - cloud physics, land-sfc model

2002 – 20km resolution- addition of GOES cloud data in assimilation

2005 – 13km resolution, new obs (METAR clouds, GPS moisture), new model physics

2008 (Jan) – Assimilation of radar reflectivity, improved thunderstorm forecasting

2009 – WRF-based Rapid Refresh to replace RUCNOAA/GSD testing – precedes NCEP ops by 0.5-3 years

Jan 2008 Changes for oper RUC upgrade• Assimilation

• Use of radar reflectivity in RUC diabatic digital filter initialization in RUC model• Mesonet winds using mesonet provider uselist• TAMDAR aircraft observations

(TAMDAR impact para RUC tests at GSD)

• Model physics• RRTM longwave radiation• Mod to Grell-Devenyi – decrease areal coverage• Mod to RUC land-sfc model – fresh snow density

• Post-processing – add reflectivity fields

RUC change package – Jan2008 - continued

Model changes RRTM longwave radiation, replacing Dudhia LW (largely eliminates warm bias in RUC)• Mod to Grell-Devenyi convective scheme (reduce excessive areal coverage for light precip) Mod to snow component of RUC land-sfc model for snow density (decrease excessively cold 2m air temps over fresh snow cover at night)

RRTM Longwave Radiation in RUC UpgradeEffect on 2-m temperature forecasts

• Much decreased warm bias, esp. at nighttime1-month comparison14 May –13 June 07Eastern US only

RUC para – RRTM LW

RUC oper – Dudhia LW

2-m temp bias (obs – forecast)

COLD

W

ARM

12h

12h

3h

3h

0 3 6 9 12 15 18 21 UTC

9h fcst - Oper RUC 9h fcst – para RUC

Anx valid 09z

Better 2m temp forecast From para RUC w/ RRTM LW

9h fcst - Oper RUC 9h fcst – para RUC

Anx valid 09z

Better 2m temp forecast From para RUC w/ RRTM LW

Today

Data type used in the RUC model

Number (resolution) of observations

Frequency of data insertion

Rawinsonde 80 /12hNOAA/PBL wind profiler 30 + 25 /1hVAD winds 110 - 130 /1hAircraft (V, T) 1400 - 4500 /1hSurface / METAR 1500 - 1700 /1hBuoy / ship 100 - 150 /1hGOES precipitable water

1500 - 3000 /1h

GOES cloud drift winds 1000 - 2500 /1hGOES cloud-top pressure

(10-km resolution) /1h

SSM/I precipitable water

1000 - 4000 /6h

GPS precipitable water ~300 /1hMesonetwork data ~6000 /1hMETAR cloud visibility ~1500 /1hRadar / lightning (4-km resolution) /1hGOES / POES radiances WRF-Rapid Refresh + GSI / 1h

RUC cloud analysis since 2005 – Use of cloud / hydrometeor observations

to modify cycled cloud / hydrometeor fields

BackgroundCloud water + cloud ice

Cloud assessment(YES/NO/UNKNOWN)

from observations(METAR/sat/radar)

RUC change package – 2007 – one more thing

Assimilate mesonet winds from accepted provider uselist

• Allows about 600 additional wind observations to be used hourly in RUC• Primary mesonet providers (e.g., Citizens Weather, AWS) have common siting problems

• Mesonet winds turned off for RUC13 implementation in 2005

• New RUC treats each mesonet provider separately• Station-by-station reject list will allow use of many Citizens-Wx, AWS stations in futurePoster – Mesonet QC monitoring web site – Benj et al

http://ams.confex.com/ams/pdfpapers/124829.pdf

– Most significant weather problem for aviation operations.– Requirement for improved hourly-updated 2-8h forecast for air

traffic management.– Current situation

• Large uncertainty even for short lead time• Very small-scale, deterministic forecasts difficult

– Severe convective weather -- significant impact on human activities

The Thunderstorm Prediction Problem for Aviation and Severe Weather

• Two separate, but related problems:

– Convective initiation

– Convective evolution (including decay)

The Thunderstorm Prediction Problem


– Convective Initiation

– Convective evolution


Need very accurate forecast of mesoscale

environment




– Excellent near-surface physics

– High frequency assimilation of asynoptic observations (surface METAR and mesonet, wind profilers, aircraft)



environment




– Excellent near-surface physics

– High frequency assimilation of asynoptic observations (surface METAR and mesonet, wind profilers, aircraft)



environment

Nighttime convection often elevated – even harder

• WSR-88D provides invaluable observations• Much improved operational warning, nowcasting• Operational NWP community slow to utilize radar

reflectivity data in models

– Real-time Level II (3-d) data access issues

– Difficulties assimilating reflectivity

Once convection is ongoing…

Forward integration, full physics

Diabatic Digital Filter Initialization (DDFI)

-30 min -15 min Init +15 min

RUC model forecast

Backwards integration, no physics

Obtain initial fields with improved balance

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

Diabatic Digital Filter Initialization (DDFI)add assimilation of radar data

-30 min -15 min Init +15 min

RUC model forecast

Backwards integration, no physics

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

1. Force precipitation in areas with radar echoes– Specify 3D latent heat from reflectivity– Apply latent heat within forward integration

of diabatic digital filter initialization (DDFI)– Replace temperature tendency from cumulus

parameterization and explicit microphysics– Moisten echo region, do not add hydrometeors

2. Suppress convection in echo-free areas– Create convective suppression mask (> 300 mb

deep layer > 100 km from existing convection – Inhibit cumulus parameterization during DDFI and

1st 30 min. of model integration

RUC reflectivity assimilation procedure

1. Minimal shock to model– Coherent wind, temperature and moisture fields

evolve in response to heating within DDFI

2. Very little additional computer cost– DDFI already used to control noise

3. Independent of model or physics packages– Can be applied to Rapid Refresh WRF, other models

Advantages of radar assimilation procedure

RUC radar assimilation test case

NSSL radar reflectivity mosaic

Test case 00z 8 Jan 2007Experiment (EXP)

– LH temperature tendency in DDFI(no moistening, no suppression yet)

Control (CNTL)– Standard initialization

(no radar assimilation)

NSSL 3-km radar reflectivity (dbz)

K=15 LH temp. tend. (K / 15 min)

Contour interval = 0.5 K00z 8 Jan 2007

Reflectivity experiments within RUC

- CNTL standard initialization – no radar init

- EXPLH nudging within DDFIno adding hydrometeors from reflectivityno moistening in reflectivity region

Low-levelConvergence

K=15 U-comp. diff (EXP - CNTL)

K=35 U-comp. diff (EXP - CNTL)

Upper-levelDivergence

Contour interval = 0.2 m/s

1700 UTC 27 Jan 2004

NSSL mosaic

Z = 5 kft

NSSL mosaic

Z = 10 kft

NSSL mosaic

Z = 20 kft

“Pyramids of silence”complementing “cones of radar data”

Latent heating in diabatic forward DFI step specified only where 3-d radar data available

cint = 0.5 mm

EXP 45-60 min. prec.00z 3-km refl (dBZ)

NSSLmosaic

CNTL 45-60 min. prec.

cint = 0.5 mmcint = 0.5 mm

EXP 45-60 min. prec.







cint = 0.5 mm

EXP 115-120 min. prec.02z 3-km refl (dBZ)

NSSLmosaic

NSSL reflectivity

105-120 min. accum. precipitation

CNTL EXP

Contour interval = 0.5 mm 02z 8 Jan 2007

Radar obs – 00z 25 Mar 2007

With radar assimilation

Assimilation improvement most clear in reflectivity field (smeared in precipitation field)

Real-time parallel testing at GSD

(started February 2007)

Added simulated RUC radar reflectivity field

RUC 3-h forecasts valid 00z 25 Mar 2007

No radar assimilation

03z 1 Mar 2007

Obs. reflectivity 03z 1 Mar 2007

Analyzed700 mb

vert. vel.from RUC with andwithoutradar

assimilation

Real-time case from

03z 1 March2007

NSSLReflectivity

mosaic

0-h vert. vel.03z 1 Mar 2007

0-h vert. vel.

No radar assim

Radar assim

Obs. reflectivity 06z 1 Mar 2007

Radar assim

No radar assim 06z 1 Mar 2007

3-h fcstaccum.precip.

from RUC with andwithoutradar

assimilation

Real-time case from

03z 1 March2007

06z 1 Mar 2007

3-h precip. 3-h precip.

NSSLReflectivity

mosaic

Radar reflectivity assimilation

Part 2 – convection suppression• Define suppression areas as follows:

• No reflectivity > 20 dbZ within 100 km• Depth of radar data > 300 hPa• Complemented by GOES fully clear areas

No coverage Allow convection

Suppress convection

Accomplish in RUC model:Specify minimum cap depth as 0 hPa in DFI step and first 30 min in actual forecast

No coverage Allow convection

Suppress convection

Convective suppression example

Real-time case from12z 7 June

2007

NSSL reflectivity Suppression mask

NSSL 3-h precipitation

RadarAssimilationControl

convective suppression - How does it work? – Reduces latent heating, vert. motion in erroneous conv areas

Real-time 3-h forecasts valid 15z 7 June 2007 Valid 15z 7 June 2007

Convective suppression example

0900z

NSSL Q2 composite refl

RUC “analysis” composite refl(actually 1h fcst)

0900zTues 17 July 2007

0900z




Valid 1200zTues 17 July 2007

RUC 3h forecast composite refl


1200z

Precip – 3h –09-12zTues 17 July 2007

NSSL Q2 QPE

RUC 3h forecast with RADAR ASSIM


NSSL Q2 QPE



NSSL Q2 QPE

RUC 3h forecast without RADAR ASSIM


NSSL Q2 QPE

without RADAR ASSIM

RUC 3h forecasts

with RADAR ASSIM




1200z




1500z




1800z

RUC forecast unable to hold onto squall line- result of Grell-Dev limitations, not assim

Precip – 3h –1215zTues 17 July 2007

without RADAR ASSIM

RUC 3h forecasts

with RADAR ASSIM12-15z

NSSL Q2 QPE

Precip – 3h –15->18zTues 17 July 2007

NSSL Q2 QPE

without RADAR ASSIM

RUC 6h forecasts

with RADAR ASSIM1800z

Sfc Temp – 21zTues 17 July 2007

without RADAR ASSIM

RUC 9h forecasts

with RADAR ASSIM

2100z

Evaporative cooling- improved cold pool

Radar assim.

3-h fcst. precip. 12z 12 Feb 2007

No radar

assim.

Obs. reflectivity 11z 12 Feb 2007

3-h fcst. precip. 12z 12 Feb 2007

3-h fcstaccum.precip.

from RUC with andwithoutradar

assimilation

Real-time case from09z 12 Feb

2007

RUC Radar refl assim w/ DDFI• effective on winter and summer events• no added CPU

Radar assimilation impact on3-h precipitation skill scores

• Significant improvement in ETS and bias• Spring - daytime


• Summer - overnight


• 4 x 0-3h vs. 1x0-12h• Summer - daytime

WSI Nowrad 0500 UTC

23 Mar 2005Radar reflectivity (dbz)

NLDN

0500 UTC 23 Mar 2005(strikes/40 min/gridbox)

Lightning data

-------------------Radar dataLightning

data-----------------

------------------------Rainwater fromradar/lightning

data------------------------

0500 UTC 23 Mar 2005

---- one more time -----2007 Changes for oper RUC upgrade• Assimilation

• Use of radar reflectivity in RUC diabatic digital filter initialization in RUC model• Mesonet winds using mesonet provider uselist• TAMDAR aircraft observations

(TAMDAR impact para RUC tests at GSD)• Model physics

• RRTM longwave radiation• Mod to Grell-Devenyi – decrease areal coverage• Mod to RUC land-sfc model – fresh snow density

• Post-processing – add reflectivity fields

Verification regions for GSD-RUC TAMDAR impact

Large region (eastern half of US) -- 38 RAOB sites

Small region (Great Lakes) includes 14 RAOBs

AMDAR and TAMDAR

• “AMDAR” (Automated Meteorological Data and Recording) – are automatically sent from commercial aircraft, mostly large jets

• “TAMDAR” (Tropospheric AMDAR) – automatic reports from (currently) ~50 turboprops flying regionally in the US Midwest– Provided by AirDat LLC– Agreement between Northwest Airlines (Mesaba –

regional subsidiary) and AirDat LLC– New agreement between NWS/FAA and AirDat for

use of TAMDAR

Coverage is limited to major hubs below 20 Kft, (without TAMDAR)

Below 20 Kft, with TAMDAR – better regional coverage in the Midwest

TAMDAR Variables

• TAMDAR measures temperature and winds aloft, as does the rest of the AMDAR fleet

• In addition, TAMDAR measures– water vapor– turbulence (not discussed)– icing (not discussed)

Parallel real-time RUC cycles to monitor TAMDAR impact since 2005

• “dev2” – includes TAMDAR and all other data typically assimilated by the RUC

• “dev” – lacks only TAMDAR data• Both cycles use NAM boundary conditions• Both run at 20-km, but are otherwise similar to the

operational 13-km runs• Background fields are set equal every 48 h

Great Lakes Region includes 13 RAOBsEastern US Region includes 38 RAOBs

National Region is the RUC domain (CONUS and adjacent)

Results today are from the Great Lakes region, where most current TAMDAR-

equipped aircraft fly

TAMDAR – regional aircraft with V/T/RH obsGSD impact study with RUC parallel cycles

• 2005-2007 (ongoing)• 10-30% reduction in RH, temperature, wind fcst error w/ TAMDAR assimilation

3h Fcst errors – RUCdev (no TAMDAR), RUCdev2 (w/ TAMDAR)

noTAMwTAM

Temp RH

Wind

wTAM

wTAM

noTAM

noTAM

Temperature RMS error time series, 3-h forecasts, Great Lakes Region, surface to 500 mb

TAMDAR impact up to 0.2 K

Red: dev RMS error

Blue: dev2 RMS error

Black: difference

Temperature RMS error profile, 3-h forecasts, Great Lakes Region

TAMDAR impact max 0.4K at 900 mb -- Inversion level, cloud ceiling

For 4 months in Jan-May 2007

• Thus TAMDAR impact represents about 35% of the maximum expected 3-h T forecast error reduction at 900 mb.

Wind RMS error profile, 3-h forecasts, Great Lakes Region

TAMDAR impact:0.25 m/s at 700 mb

• Analysis fit to RAOBs is ~2.2 m/s• Thus, TAMDAR impact on 3-h wind forecasts represents a

15% reduction in 3-h wind forecast error at 700 mb

RH error time series, 3-h forecasts, Great Lakes Region, surface to 500 mb

TAMDAR impact up to

2% RH

RH RMS error profile, 3-h forecasts, Great Lakes Region

TAMDAR impact

~2 %RH below 550 mb

A look ahead (2)

• AirDat will install TAMDAR on additional fleets over the next several months

• Covering Alaska and the Western US• These fleets include some jet aircraft

– higher altitudes, speeds (implications??)– better heading => reduced wind errors

• GSD will evaluate the quality and impact of these data (with FAA funding)

• (Unfortunately, these new data will not be available beyond GSD, per AirDat)

Ed Szoke (GSD) TAMDAR evals - Overview

• TAMDAR soundings have been shown to be useful for forecasting

• Talks at the last SLS Conference and previous Annual Meetings• WFO Green Bay helps maintain the official NOAA TAMDAR web

page at http://www.crh.noaa.gov/tamdar/

• In this talk we focus on the impact on NWP:

• Evaluation of RUC precipitation forecasts for runs with and without TAMDAR for significant weather events– Mostly a subjective evaluation, but objective scoring for 2007 cases

http://www.crh.noaa.gov/tamdar/



Still one of the better cases for TAMDAR impact...4-5 Oct 2005: heavy precip in the Upper Midwest.

Flooding reported inMinnesota to northernWisconsin.

Case 1: 4 October 2005 – 2100 UTC Surface analyses and reflectivity

Very sharp cut off to theprecip in WIand a huge gradient witha 2-3” max.

NPVU estimated precipitation for 6-h ending 0000 UTC 5 October 2005

Both runs forecast too much precip in southern half of Wisconsin, but the RUC run with TAMDAR correctly forecasts more precip (small spots of >1.00”) across the northern half of the state.

RUC forecasts from the 4 October 2005 1800 UTC runs 6-h total precipitation ending 0000 UTC 5 October

No TAMDAR With TAMDAR

Sounding comparison: RUC 6-h forecasts with (labeled dev2) and without(labeled dev1, in black) TAMDAR, compared to the RAOB for Detroit (green)at 0000 UTC 5 Oct 05. Incorrect dry layer in the dev1 (noTAM) forecast.

Same comparison but for Peoria, Illinois. The RUC run with TAMDAR is closer to the RAOB especially at and below 700 mb.

Heavy precip continuesin the same areas

Case 1/part 2: 5 October 2005 – 0300 UTC Surface analyses and reflectivity

NPVU estimated precipitation for 6-h ending 0600 UTC 5 October 2005

For this period the RUC run that used the TAMDAR data is a much better forecast with a very sharp cut off to the precipitation in Wisconsin and a better location for the heavy precip.

RUC forecasts from the 5 October 2005 0000 UTC runs 6-h total precipitation ending 0600 UTC 5 October

No TAMDAR With TAMDARNo TAMDAR With TAMDAR

Case 4: 22 March 2007 – 0000 UTC Surface analyses and reflectivity Strong spring storm with lots of severe weather

22 March 2007 – 0300 UTC Surface analyses and reflectivity

SPC severe reports for 24-h ending 1200 UTC/22 March 2007

Some differences are seen – these are outlined in the forecasts The RUC forecast that uses TAMDAR is generally better except within the orange oval area, where no precipitation fell.

RUC forecasts from the 22 March 2007 0000 UTC runs 6-h total precipitation ending 0600 UTC 22 March

No TAMDAR With TAMDAR With TAMDARNo TAMDAR

Case 5: 21 June 2007 – 2100 UTC Surface analyses and reflectivity Strong convection with many reports of severe weather

22 June 2007 – 0000 UTC Surface analyses and reflectivity

SPC severe reports for 24-h ending 1200 UTC/22 June 2007

Main difference is the precipitation in IL and IN predicted by the RUC run without TAMDAR compared to almost nothing in the run with TAMDAR.

Verification showed that no precipitation fell in the IL/IN area.

RUC forecasts from the 21 June 2007 1800 UTC runs 6-h total precipitation ending 0000 UTC 22 June

No TAMDAR With TAMDAR

Sounding comparison for 6-h forecasts for RUC with TAMDAR (dev2) vs RUC without TAMDAR (dev) compared to the DVN RAOB at 0000 UTC 22 June 2007

Sounding comparison for 6-h forecasts for RUC with TAMDAR (dev2) vs RUC without TAMDAR (dev) compared to the ILX RAOB at 0000 UTC 22 June 2007

Summary• When we began to examine precipitation forecasts in late 2005 were impressed by the 4-5 October 2005 case with significantly better forecasts by the RUC run that used TAMDAR

– But that remains our best case

• More typically, we see much smaller impacts• These tend to favor the RUC run that uses TAMDAR, but not

always– And sometimes mixed...forecast better in some spots but not in

others

• Objective scoring of the precipitation forecasts that began in 2007 agrees with our overall subjective impression

– Longer-term statistics show relatively small differences generally favoring the RUC run that uses TAMDAR

– But on a case by case basis can see greater differences in the scores

Decreased vertical resolution decreases TAMDAR impact on 3-h T forecasts by

~30% at 750 mb

~10% at 900 mb

Effect of vertical resolution on TAMDAR 3-h Temperature forecast impact

Each curve shows the amount that TAMDAR reduces the RMS

error.

Low-res reduces the error less => less TAMDAR impact.

Current RUC CONUS domain

RUC

Rapid-Refresh(2008-09)

Continental situational awarenessmodelHourly NWP Update for: - CONUS- AK/Can- Pac/Atl- Caribbean

Planned Rapid Refresh domain

RUC to Rapid Refresh

• North American domain

(13km)

• GSI (Gridpoint Statistical

Interpolation)

• WRF model (ARW dynamic core

almost certainly)

• CONUS domain(13km)

• RUC 3dvar

• RUC model

Rapid Refresh Hourly Assimilation Cycle

11 12 13 Time (UTC)

1-hrfcst

Background

Fields

Analysis

Fields

1-hrfcst

GSI

Obs

1-hrfcst

GSI

Obs

Cycle hydrometeor, soil temp/moisture/snow plus atmosphere state variables

Hourly obs used in RRData Type ~NumberRawinsonde (12h) 80NOAA profilers 30 VAD winds 110-130 PBL – prof/RASS ~25Aircraft (V,temp) 1400-4500 TAMDAR (V,T,RH) 0-1000Surface/METAR 1500-Surface/METAR 1500-1700 1700 Buoy/ship 100-150 GOES cloud winds 1000-2500 GOES cloud-top pres 10 km res GPS precip water ~300Mesonet (temp, dpt) ~7000Mesonet (wind) ~ 600METAR-cloud-vis-wx ~1500Radar / lightning 2kmSat radiances – AMSU-A/B, GOESQuikSCAT

WRF physics options -- All available with both ARW and NMM cores w/ WRFv2.2 -- All combinations tested with WRF-RR core-test

• Phase 1 - Default NMM physics • Phase 2 - RUC-like physics

NAM-NMM RapidRefreshExplicit clouds Ferrier Thompson-

NCARSub-grid

convectionBetts-Miller-

JanjicGrell-Devenyi

Land-surface F77 version of Noah (“99”

LSM)

RUC-Smirnovaor Noah

Turbulent mixing

Mellor-Yamada-Janjic

Mellor-Yamada-Janjic

• 1-h cycling of atmospheric (including hydrometeor)and land surface model fields

• Update cycled fields with all available hourly observations

• Utilize GSI satellite radiance assimilation scheme

• Build in “RR-specific” components:1) ‘pre-forecast’ diabatic digital filter initiation (DDFI)2) cloud analysis (satellite, METAR, radar, LTG obs) 3) surface obs assimilation (BL depth, coast-lines)4) Force convection from radar, lightning data in model DDFI after GSI pre-processing

RR application of GSI assimilation

Example from the preliminary Rapid Refresh real time cycle

Analysis at 1200 UTC 29 May 2007 over RR domain. Wind field at model level 15 colored according to potential temperature. Each color represents a 5-K interval of potential temperature, with purple representing from 285-290K (north) and red representing from 330-335K (south).

12h forecast - 2m temperature

12z 12 May 2007

RapidRefresh

RUC

More preliminary RR results

Rapid Refresh Data Assimilation timeline

Fall 2006 – summer 2007 – Cycle WRF using GSI over RR domain

- Use of WRF version 1.2 (WRFSI)- Testing of new surface assimilation and

cloud analysis modules

Fall 2007 Cycling over NAmerica with all observations

- Update to new GSI, WRF versions; new computer- Use of NCEP prepbufr files, increase cycling frequency- Comparison with other systems, continue refinement

Fall/Winter 2007/08 Full system with RR modifications

- DDFI in place for chosen WRF model core- Detailed examination of cold season near surface aspects- Refinement of system toward operation skill

Spring/Summer 2008 Real-time and retro cycles

- Testing of DDFI radar data assimilation- Focus on performance for convective situations- Transfer code to NCEP

Winter 2008 - 09Testing of complete RR at NCEP and GSD

Summer/Fall 2009 Operational implementation at NCEP

Rapid Refresh Planned Timeline

Transitioning to operations (RUC, RR)

- Must run at NCEP- Must run within available computer

resourcesand time constraints (5 min – assim, 17 min- 12h fcst)

- Must be built into existing code infrastructure(e.g.: Build assimilation capability in GSI, develop probabilistic products within SREF framework)

Upcoming GSD tasks Develop Rapid Refresh – North

American 1h update 4-d assim/model – toward NextGen 4-d database

Tied with EMC more than before Test and recommend physics options Developed diabatic DFI (digital filter

initialization) in WRF-ARW to allow RR 1h cycle

GSI assimilation with RUC-specific enhancements

Work with EMC, NCEP centers, NWS, other RUC/FAA/AWRP users, DTC, WRF community on forecast evaluation and improvement

Major transition:Rapid Refresh planned implementation

2009Evaluation at NCEP - 2008

This is where you

folks come in!

FUTURE: High Resolution Rapid-Refresh (HRRR)

• Proposal for 2009-11 time frame• Nested high-resolution domain (2-4 km) within RR• Explicit depiction of convection (no cum. param.) • Hourly or sub-hourly observation updating

Need to initialize storm scale details…Use radial velocity (3DVAR, 4DVAR, retrieval techniques),reflectivity (polarimetric information), and lightning datato specify wind, temperature, and hydrometeors

Storm building, adjustment, and removal

HRRR-ARW 6h fcstradRUC IC

HRRR- ARW 6h fcstOper RUC IC

06z obs reflNSSL Q2 product

Results from sample real-time HRRR test

• Forecasts initialized 0000z 16 Aug 07• Radar-enhanced RUC critical for HRRR forecast

RUC/Rapid Refresh Development and Testing Including TAMDAR and

Radar Reflectivity Impact StudiesMajor transitions:

• RUC13 change package – ~Jan 2008– radar reflectivity assimilation- TAMDAR- Improved radiation, convection physics in RUC

• Rapid Refresh planned for FY09• WRF ARW, GSI, North America

• Ensemble Rapid Refresh • proposed by 2012, to use ESMF framework

• High-Res Rapid Refresh (HRRR) – proposed to NCEP by 2012

• 3km hourly updated 12h forecast• In testing at GSD• Covering NE Corridor

[email protected]://Ruc.noaa.gov 303-497-6387

mailto:[email protected]

http://ruc.noaa.gov/

Planned implementation of TAMDAR sensors by AirDAT LLC into Horizon and PenAir Saab 340s

First Alaska TAMDAR data- 12 June 2007

AMDAR-24h12-13 Mar 07

SATELLITE DATA EXPERIMENTS FOR RAPID REFRESHBoth HIRS and MSU -- Use of Community Radiative Transfer Model (CRTM)Preliminary experiments with NAM satellite radiance and bias files over CONUS domain using RUC background fields. Case of 11 April 2006, 1200 UTC.

Difference

satellite minus no-satellite data; specific humidity.

Model level=10.

Some Special Challenges – Aviation Forecasts with Expanded Domain

Arctic low stratus – will be difficult to predict explicitly -- but we will try

Sea ice – Leads, ponding, etc.

Taiga in spring—snow cover and frozen ground under warm forest canopy

Tundra in the land-surface model – prediction of surface conditions in the Far North

Tropical cyclones—initializing, track prediction, intensity

Sparse data over land – risk of “climate drift” in the model

Joint GSD-NCAR plans for HRRR model development

• High-Res Rapid Refresh (HRRR)• 2-3 km, hourly updating, assimilation of hourly radar reflectivity• Based off radar-assimilating Rapid Refresh (currently radar-assimilation RUC)

• Plans for FY08 1Q-2Q• GSD, NCAR

• Rerun cases and test periods summer 2007• 2 sources of external model grids

• GSD radar-assimilating RUC• NCEP operational RUC (no radar assim)

• 3 variations of 3-km WRF-ARW• ARW as is (already tested in real-time by GSD)• ARW with FDDA (NCAR lead on development)• ARW with radar-enhanced DFI (GSD lead)

Real-time HRRR for CoSPA for 3Q, 4Q FY08

• Real-time HRRR forecasts over regional domain over NE Corridor area for May-August period

– Forecasts out to 12h, reinitialized every 1-3h using radar-enhanced RUC or Rapid Refresh initial conditions

– 15-min output for selected 2-d fields including surface fields (2m temp/dewpoint, 10m winds), reflectivity, precipitation

– Run at GSD, backup at NCAR• Experimental HRRR output to MIT/LL, NCEP Storm Prediction

Center, AWC (possible), others

Other FY08 activities toward HRRR

• Case studies from summer 2007 cases– NCAR - lead, GSD collaborating

• Case study testing of revised radar assimilation methods• Development of simple forecast metrics for development

retrospective tests and case studies– NCAR and GSD

Documents

RUC/Rapid Refresh Development and Testing Including TAMDAR and Radar Reflectivity Impact Studies NOAA Earth System Research Lab (ESRL) Global Systems Division