Numerical Weather Prediction:Status and prospects

APSDEU-6, 1-3 June 2005, Seoul, Rep. of Korea

Woo-Jin Lee

Numerical Weather Prediction Division

Korea Meteorological Administration

Model Analysis ResolutionLead time

(Days)Remark

  3dVar T426 (30km, 40 levels) 10Test

operation with tuning 

Global Spectral Model

3dVar T213 (55km, 30 levels) 10

(GDAPS) 3dVarT106 (110km, 30

levels)10 17 Ensemble

Regional Model

(RDAPS)3dOI/ 3dVar 30/ 10/ 5km (33 levels) 2 Triple Mesh

Typhoon Model (DBAR)

Bogus 20km (barotropic) 3 Typhoon Track

 Wave Model   0.25° 2 Asian

  1°× 1° 10 Global

Statistical Model   - 10 PPM and EPS

Models on operation at KMA

Items

The first proposal

Initial system(2004)

Final system(Oct 2005)

Model name X1-3/192-L X1E-8/960-L

MainSystem

The number of cabinets 3 7.5

NodesSystem 1 4

Computing 47 236

CPUsSystem 4 16

Computing 188 944

Single CPU performance 12.8Gflops 19.2Gflops

1 CPU Sustained performance 3.38 Gflops 4.63Gflops

Total Sustained Gflops 635.44 Gflops 4,370.72 Gflops

Total memory size 760 Gbytes 3776 Gbytes

Cray X1 supercomputer at KMA

Global model T213L30 for 1998-2004

3dOI 3dVar

RMSE of 500hPa Z North Hemisphere

0

20

40

60

80

100

120

98.

2 4 6 8 10

12

99.

2 4 6 8 10

12

00.

2 4 6 8 10

12

01.

2 4 6 8 10

12

02.

2 4 6 8 10

12

03.

2 4 6 8 10

12

04.

2 4 6 8 10

12

RM

SE

T106(1day) T106(3day) T106(5day)

T213(1day) T213(3day) T213(5day)

Global Regional

Model  T426L40/ T213L30 MM5 (30km version) MM5 (10km version)

Horizontal resolution

Inner loop: T106/ T63

Outer loop: T426/ T213

Lambert Conformal map projection, regular grids (190

by 171, 30km)

Lambert Conformal map projection, regular grids (160

by 178, 10km)

Vertical resolution

40/30 levels (0.4/ 10hPa) Sigma 33 levels (top at 50hPa)Sigma 33 levels (top at

50hPa)

Variables T,U,V,Ps,qv P,T,U,V,qv P,T,U,V,qv,qc,qr

Data source

SYNOP, SHIP, TEMP, PILOT, SATEM, SATOB, ACARS,

AMDAR, AIREP, QuikSCAT, ATOVS*

SYNOP, SHIP, TEMP, PILOT, SATEM, SATOB, ACARS,

AMDAR, AIREP, QuikSCAT, ATOVS*,

AWS

SYNOP, SHIP, TEMP,PILOT,

SATEM, SATOB, ACARS, AMDAR, AIREP*,

QuikSCAT, ATOVS*,

AWS

Radar (wind, reflectivity)*

 Update cycle 6 hourly 6 hourly 3 hourly

InitializationNon-linear normal mode

initializationDynamic nudging for prior 12

hoursIncremental Analysis Update (IAU) with 3 hour window

Status Operation Test operation Operation

3dVar at KMA

Songa Meari Maon Tokage

QuikSCAT seawinds on typhoon track

CNTL EXP

GOES-9 WV image 3 hr accumulated rain

Assl. NOAA 16 ATOVS, +12hr 3hr Precip. (valid time : 2004081006)

OBS at 2004/08/10/06UTC

N.H. 500GPH(2005/05/01~05/15)

00.10.20.30.40.50.60.70.80.9

1

1 2 3 4 5 6 7 8 9 10 11

예측시간

A.C

OR

MODISOPER

N.H. 500GPH(2005/05/01~05/15)

0

20

40

60

80

100

120

1 2 3 4 5 6 7 8 9 10 11

예측시간

RM

SE

MODISOPER

S.H. 500GPH(2005/05/01~05/15)

00.10.20.30.40.50.60.70.80.9

1

1 2 3 4 5 6 7 8 9 10 11

예측시간

A.C

OR

MODISOPER

S.H. 500GPH(2005/05/01~05/15)

020406080

100120140160180

1 2 3 4 5 6 7 8 9 10 11

예측시간

RM

SE

MODISOPER

• Used MODIS polar winds

Over ocean IR: above 700hPa WV: above 550hPa Over land IR,WV: above 400 ｈ Pa as ECMWF do.

• Data thinning 140km as ECMWF, still work on for improvement with QC

Before QC

MODIS polar wind

After QC

Radar Data Assimilation

• Status• S-band Reflectivity (Jin do, and Mt. Kwangdok)

• S-band Doppler wind & reflectivity (Gunsan and Pyungtaek)

• 3dVar 10km 3-hourly update

• Plan

• Extend to C-band reflectivity (5 sites, i.e., Gunsan, Is. Backryung, Donghae, Mt. Myunbong, Kosan)

9th April 2005

No Radar Radar

Unified 3dVar (U3dVar)

Motivation

- Common code share for global and regional DA (observations, preconditioning, background error statistics, minimization algorithm, observation operator etc)

Plan (2005)

- Background error tuning (theoretical and empirical approach)

- Improvement of observation data processing ( BUFR format, QC … )

- Introduction of satellite radiance / SSMI and GPS (2006)

- FGAT and outer loop for adaptive QC

- Test at operational frame

(T426L40 Global Model with 6hr cycle / 10km WRF regional Model with 3hr cycle)

Comparison of R3dVar, G3dVar and U3dVar

R3dVar G3dVar U3Dvar

Control variables (v)

Background E (B) NMC NMC NMC and ENS

Adaptive QC No No Yes

FGAT No Late 2005 Yes

Satellite Radiance Late 2005 Radiance End of 2005

Analysis Grid Grid Wave Grid

U transformation EOF

Recursive Filter

No vertical Transform

Wave to Grid

EOF

Spectral Power or Recursive Filter

Code f90 f77 F90 / MPI

Minimization QN QN QN and CG

qPu ,,, qTPsD uu ln,),(,, RHPsT uuu ,,,,

TUUB vUUUx hvp'

Summary of development planYear Data assimilation Global model Regional model Global Ensemble

2005Test of Unified 3dVar, and direct satellite assl.

of AMSU-A (AQUA)

Operation and tuning of high resolution versions, (Eulerian and/or semi Lagrangian T426L40)

Test operation of WRF (10km L33)

Test of LSM

Interface with U3dVar

Increasing members from 16 to 32

Stochastic forcing and rotation of bred vectors

2006

Unified 3dVar with

COSMIC GPS

AIRS, AMSU-B, AMSR-E

Explicit cloud and precipitation physics

Operation of extended domain WRF (10km)

Operation of coupled LSM/WRF

Increasing resolution to T213L40 with obs perturbations

2007Test of 4dVar or EnKF

Increasing vertical resolution to L70

Increase resolution to 5km L40

with radiation tuning

Increasing members from 32 to 50

2008Operation of 4dVar or EnKF

Next generation model

Coupled with ocean

Test of WRF (1 km L70)

for very short range forecast of severe weather

Tuning of physics

Wishes• Make more volume of satellite based observation

available through GTS and/or Internet

• Share forward operators (such as radiative transfer code) and quality control softwares

• Stimulate exchange of research findings on data assimilation with new satellite observations

• Encourage close communication between NWP community and satellite meteorology community

Thank You