Hee-Sang Lee and Seung-Woo Lee

24
Impact of ProbeX-IOP (KEOP) observations on the Impact of ProbeX-IOP (KEOP) observations on the predictive skill of heavy rainfall in the middle predictive skill of heavy rainfall in the middle part of Korea part of Korea Hee-Sang Lee and Seung-Woo Lee Hee-Sang Lee and Seung-Woo Lee Forecast Research Laboratory / National Institute of Forecast Research Laboratory / National Institute of Meteorological Research, KMA Meteorological Research, KMA National Institute of Meteorological Research National Institute of Meteorological Research

description

National Institute of Meteorological Research. Impact of ProbeX-IOP (KEOP) observations on the predictive skill of heavy rainfall in the middle part of Korea. Hee-Sang Lee and Seung-Woo Lee Forecast Research Laboratory / National Institute of Meteorological Research, KMA. Background. - PowerPoint PPT Presentation

Transcript of Hee-Sang Lee and Seung-Woo Lee

Page 1: Hee-Sang Lee and Seung-Woo Lee

Impact of ProbeX-IOP (KEOP) observations on the Impact of ProbeX-IOP (KEOP) observations on the predictive skill of heavy rainfall in the middle part of predictive skill of heavy rainfall in the middle part of

KoreaKorea

Hee-Sang Lee and Seung-Woo LeeHee-Sang Lee and Seung-Woo Lee

Forecast Research Laboratory / National Institute of Forecast Research Laboratory / National Institute of Meteorological Research, KMAMeteorological Research, KMA

National Institute of Meteorological ResearchNational Institute of Meteorological Research

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BackgroundBackground

KMA has been using the NCAR/PSU MM5 as a regional model KMA has been using the NCAR/PSU MM5 as a regional model for over 10 years.for over 10 years.

KMA considers the WRF model as a candidate of the operational KMA considers the WRF model as a candidate of the operational regional model.regional model.

Assessment of WRF model performance for very-short range Assessment of WRF model performance for very-short range forecasting of precipitation is demanded by forecasters.forecasting of precipitation is demanded by forecasters.

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12h Precip. ETS for 12h fcst(June, 2007)

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.1mm 5mm 15mm 25mm 50mm

Threshold Value

MM5- 30WRF- 10

12h Precip. Bias Score for 12h fcst(June, 2007)

00.20.40.60.8

11.21.41.61.8

2

0.1mm 5mm 15mm 25mm 50mm

Threshold Value

MM5- 30WRF- 10

MM5-30 vs WRF-10 kmMM5-30 vs WRF-10 km12h Precip. ETS for 24h fcst

(June, 2007)

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.1mm 5mm 15mm 25mm 50mm

Threshold Value

MM5- 30WRF- 10

12h Precip. Bias Score for 24h fcst(June, 2007)

00.20.40.60.8

11.21.41.61.8

2

0.1mm 5mm 15mm 25mm 50mm

Threshold Value

MM5- 30WRF- 10

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MM5- 30 km MM5- 30 km MM5- 10 km MM5- 10 km

MM5- 5 km MM5- 5 km WRF 10 km WRF 10 km

AWS observed rainfall AWS observed rainfall

WRF 3.3 km WRF 3.3 km

[2007. 7.3. 21 KST ~ 7. 4. 12 KST][2007. 7.3. 21 KST ~ 7. 4. 12 KST]

[2007. 7. 4. 00 KST ~ 12 KST][2007. 7. 4. 00 KST ~ 12 KST]

Predicted rainfall from two different regional modelsPredicted rainfall from two different regional models

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Observations : 4 July 2007Observations : 4 July 2007

No warning by this time in the routine forecasting.

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Observations : 4 July 2007Observations : 4 July 2007

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12-h rainfall amount 12-h rainfall amount (2007/07/04 00LST ~12LST)(2007/07/04 00LST ~12LST)

IR (2007/07/04 06LST)

SFC (2007/07/04 09LST)

Heavy rainfall event : 09LST 4 July 2007Heavy rainfall event : 09LST 4 July 2007

Mungyung 148.5 Mungyung 148.5 mm/12hmm/12h

Anyang 104 Anyang 104 mm/12hmm/12h

60 min. acc.60 min. acc.

15 min. acc.15 min. acc.

At early morning 4th July, a convective system associated with the Changma front that produced heavy rainfall over the southern part of Korea moved eastward, then local heavy rainfall occurred over the middle part of Korea.

Operational models did not capture this signals over this area.

CAPPI (2007/07/04 06LST)

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Observations : 9-12UTC 3 July 2007Observations : 9-12UTC 3 July 2007

111 ASOS111 ASOS

773 AWS data773 AWS data

19 Radiosondes19 Radiosondes

240 AMDAR240 AMDAR

451 AMDAR from Korean Airlines (KAL)451 AMDAR from Korean Airlines (KAL)

10 Wind profiler10 Wind profiler

5 SATEM5 SATEM

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Special observations for impact studiesSpecial observations for impact studies

HaenamHaenam

SokchoSokcho

MunsanMunsan

PohangPohang

BaengnyeongdBaengnyeongdoo

IeodoIeodo

GosanGosan

OsanOsan

HuksandoHuksando

Conventional Conventional

KEOPKEOP

Air ForceAir Force

GwangjuGwangju

ProbeXProbeX-2007 IOP-2007 IOP - - Observing period : Observing period :

2007/06/15 ~ 2007/07/152007/06/15 ~ 2007/07/15

- - Increasing time resolutionIncreasing time resolution : : 4 times/day 4 times/day (Baengnyeongdo, Sokcho, (Baengnyeongdo, Sokcho, Huksando, Pohang, Gosan) Huksando, Pohang, Gosan)

- - Increase space resolutionIncrease space resolution : : Additional enhanced Additional enhanced observation (Munsan, observation (Munsan, Haenam, Ieodo)Haenam, Ieodo)

Probex (PRedictability and Probex (PRedictability and

OBservation ExperimentOBservation Experiment

in Korea)in Korea)

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MM5-30 & KWRF-10 kmMM5-30 & KWRF-10 km KWRF 3.3 kmKWRF 3.3 km

Physical processesPhysical processes Domain 1 (10 km)Domain 1 (10 km) Domain 2 (3.3 km)Domain 2 (3.3 km) RemarksRemarks

DimensionsDimensions 574 X 514 (with 30 vertical levels)574 X 514 (with 30 vertical levels) 334 X 364 (with 30 vertical 334 X 364 (with 30 vertical levels)levels)

Run time on CRAY-X1ERun time on CRAY-X1E(1024CPUs / 18.4TFLOPS)(1024CPUs / 18.4TFLOPS)

Domain 1 : Domain 1 : 14 min.14 min. with 126 CPUswith 126 CPUsDomain 2 : 5Domain 2 : 50 min.0 min. with 64 CPUswith 64 CPUs

Time interval (Time interval (ΔΔt)t) 60 sec60 sec 20 sec20 sec

Cumulus Cumulus ParameterizationParameterization Kain-Fritsch (new Eta) schemeKain-Fritsch (new Eta) scheme NoneNone

MicrophysicsMicrophysics WSM6 / WSM5 / WSM3 / new EtaWSM6 / WSM5 / WSM3 / new Eta WSM 6-class schemeWSM 6-class scheme

PBLPBL YSU schemeYSU scheme YSU schemeYSU scheme

RadiationRadiation RRTM / Dudhia schemeRRTM / Dudhia scheme RRTM / Dudhia schemeRRTM / Dudhia scheme

Surface-LandSurface-Land Noah LSMNoah LSM Noah LSMNoah LSM

Initial and Boundary dataInitial and Boundary data GDAPST426 hybrid-sigma(0.28125GDAPST426 hybrid-sigma(0.28125oo)) WRF 10 kmWRF 10 km

Model domains and configurationsModel domains and configurations

Verification areaVerification area

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0000 0606 1212 1818 2424UTCUTC

Global (T426)

10 days forecast

CYCLE run

COLD run

3 days forecast

10 days forecast

60-h forecast

6-h forecast

60-h forecast

60-h forecast

Nestdown to WRF 3.3 km Nestdown to WRF 3.3 km

Experimental design Experimental design

3DVAR data assimilation3DVAR data assimilation

Nestdown to WRF 3.3 kmNestdown to WRF 3.3 km

3030 3636

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Experiment ID Assimilated observation data Remarks( Number of assimilated obs. )

CTL All available observations without KEOP soundings Operational, 1247

ALL All available observations including KEOP soundings 1249

OPR Conventional TEMP soundings 17

TMP Conventional TEMP + KEOP soundings 19

KOP KEOP soundings only 2

PRF Wind profiler data 10

ACS AMDAR data from FSL 240

KAL AMDAR data including KAL reports 451

KON KAL reports only 211

SFC SYNOP, SHIP, BUOY, AWS data 884

SYN SYNOP, SHIP, BUOY 111

AWS AWS 773

SAT SATEM, SATOB, QSCAT 5

Observations for impact studiesObservations for impact studies

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OBSOBS CTLCTL ALLALL

OPROPR TMPTMP IOPIOP

103103

T+12 acc rainfallT+12 acc rainfall

Munsan

Munsan

Munsan

The location of rainfall was slightly shifted toward observation when the IOP sounding (even in The location of rainfall was slightly shifted toward observation when the IOP sounding (even in one sounding at Munsan station) data was included.one sounding at Munsan station) data was included.

9898

104104

148.5148.5

100 km100 km

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OBSOBS PRFPRF ACSACS

KALKAL SFCSFC SYNSYN AWSAWS

SATSAT

T+12 acc rainfallT+12 acc rainfall

Sounding data shows positive impact on the improvement of rainfall than the surface observation data.Sounding data shows positive impact on the improvement of rainfall than the surface observation data.

The aircraft data from KAL shows most skillful forecasting of precipitation.The aircraft data from KAL shows most skillful forecasting of precipitation.

100 km100 km

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Sensitivity to boundary condition from global modelSensitivity to boundary condition from global model

FCST(C24H)FCST(C24H) ANAL_IOPANAL_IOP

OBSOBS ANALANALCTRL (operational)CTRL (operational)

6464

4343

9898

148.5148.5

104104

Since the BCs of WRF-0 are provided by the GDAPS, perfect BCs from global analyses Since the BCs of WRF-0 are provided by the GDAPS, perfect BCs from global analyses lead to an improvement of locations of heavy rainfall.lead to an improvement of locations of heavy rainfall.

100 km100 km

7676

6464

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CTRLCTRL COLDCOLD

C12HC12H C24HC24H

Sensitivity to the cycle with WRF-10Sensitivity to the cycle with WRF-10

The cycle plays an important role in the spin-up in precipitation process.The cycle plays an important role in the spin-up in precipitation process.

OBSOBS

100 km100 km

7676

1111

2929

6464

148.5148.5

104104

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Sensitivity to microphysics (WRF 10km) with ANAL_BCsSensitivity to microphysics (WRF 10km) with ANAL_BCs

WSM6WSM6OBSOBS WSM3WSM3

WSM5WSM5CTRL (WSM6)CTRL (WSM6)

9696 7474

42427676

148.5148.5

104104

100 km100 km ETA_NEW (Ferrier)ETA_NEW (Ferrier)

9494

Although the simulated rainfall amount was much smaller than the observed one, Although the simulated rainfall amount was much smaller than the observed one, ETA_NEW microphysics does better job in location of main rainfall area over the middle ETA_NEW microphysics does better job in location of main rainfall area over the middle part of Korea.part of Korea.

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Sensitivity to microphysics (WRF 3.3km)Sensitivity to microphysics (WRF 3.3km)

OBSOBS

4141

148.5148.5

104104

ETA_NEW (Ferrier)ETA_NEW (Ferrier)

In higher resolution experiment, the magnitude of maximum rainfall is larger than that in In higher resolution experiment, the magnitude of maximum rainfall is larger than that in lower resolution but no difference in phase.lower resolution but no difference in phase.

WSM6WSM6

9797

100 km100 km

WSM3WSM3

128128

WSM5WSM5

109109

9393

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The GA is a global optimization approach based on the Darwinian principles of natural selection. This method, developed from the concept of Holland [1975], aims to efficiently seek the extrema of complex function – see Goldberg [1989] for a detailed description.

Genetic Algorithm to optimize WRF-10 modelGenetic Algorithm to optimize WRF-10 model

Start

Initialization

Fitness Evaluation

Selection

Crossover

Mutation

Fitness Evaluation

Terminal condition

End

NO

YES

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Variance and length scale of background error (xVariance and length scale of background error (x11, ,

xx22, x, x33, x, x44, x, x55, l, l11, l, l22, l, l33, l, l44, l, l55))

Asymptotic mixing length in PBL(mAsymptotic mixing length in PBL(m11))

Clear air turbulence : 10 – 30 mClear air turbulence : 10 – 30 m

Cyclogenesis in upper troposphere : < 100mCyclogenesis in upper troposphere : < 100m

Closure assumption of KF (mClosure assumption of KF (m22))

In the Kain-Fritsch scheme the closure assumption is that convection In the Kain-Fritsch scheme the closure assumption is that convection consumes at least 90% of the environmental convective available consumes at least 90% of the environmental convective available potential energy (CAPE) over an advective time period ( 30 min ~ 1 potential energy (CAPE) over an advective time period ( 30 min ~ 1

hour) [hour) [Kain et al.Kain et al. 2003]. 2003].

96.002.0 2 m

20010 1 m

0.3,5.0 nn lx

Selection of ChromosomesSelection of Chromosomes

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The function to be optimized (i.e., Fitness) is defined by using a QPF skill score, the equitable treat score (ETS) [Schaefer, 1990],

Fitness = ,

i

iETS 100,,2,1 i

RHOF

RHETS

where i is the precipitation threshold in mm. Here, the ETS is defined as:

H : hitR : the expected number of hits in a random forecast F : rain forecast O : rain observation

NFOR /

Fitness functionFitness function

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Variance of control variables

var_scaling1 (x1, Ψ) var_scaling2 (x2,χ) var_scaling3 (x3,Tu) var_scaling4 (x4, qRH) var_scaling5 (x5,Pa)

1.32 2.68 1.34 0.96 2.36

Horizontal length scales

len_scaling1 (l1) len_scaling2 (l2) len_scaling3 (l3) len_scaling4 (l4) len_scaling5 (l5)

0.92 2.45 2.50 1.09 0.79

Physical parameters

asymptotic mixing length (m1) (30) reduction rate (m2) (0.95)

132.5 0.36

Evolution of chromosomesEvolution of chromosomes

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CTRLCTRL

GAGA

Preliminary results w/ and w/o GA in WRF-10Preliminary results w/ and w/o GA in WRF-10

Overall the tuned WRF by GA works for locations of heavy rainfall.Overall the tuned WRF by GA works for locations of heavy rainfall.

OBSOBS

100 km100 km

148.5148.5

104104 50.950.9

64.564.5

54.154.1

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SummarySummary

The assimilation of the intensive observations (KEOP-2007) with the The assimilation of the intensive observations (KEOP-2007) with the high resolution WRF model (3.3 km) and 3DVAR show a positive high resolution WRF model (3.3 km) and 3DVAR show a positive impact on the very-short range forecasting of heavy rainfall over Korea. impact on the very-short range forecasting of heavy rainfall over Korea.

Cycling processes to provide the background in 3DVAR play a crucial Cycling processes to provide the background in 3DVAR play a crucial role in spin-up of precipitation. role in spin-up of precipitation.

Improvement in boundary conditions from global model may lead to Improvement in boundary conditions from global model may lead to improvement in the forecast of heavy rainfall.improvement in the forecast of heavy rainfall.

Cloud microphysics plays an important role in the simulation of the Cloud microphysics plays an important role in the simulation of the heavy rainfall area in this case.heavy rainfall area in this case.