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Numerical Model Management Office KMA

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Presentation on theme: "Numerical Model Management Office KMA"— Presentation transcript:

1 Numerical Model Management Office KMA
Centre report of KMA 29th WGNE meeting Melbourne MAR. 2014 Hoon Park Numerical Model Management Office KMA

2 Outlines Current status & update strategy of KMA NWP system
Upgrade NWP system in 2014 and upcoming plans Research activities in NWP at KMA

3 Status & upgrade strategy

4 KMA’s 3nd Supercomputer (current)
Computing System for Operation (20 Cabinets, 379Tflop/s) Ref HaeOn HaeDam Total Installation Year Core Number 45,120 90,240 Core Type AMD 2.1 GHz, 12 core Peak performance 379 TF 758TF Main Memory 60 TB 120TB Capacity of Disk 4 PB Capacity of Tape drive 8 PB OS Suse Linux 11 HaeOn Computing System for R&D and backup (20 Cabinets, 379Tflop/s) HaeDam HaeOn, HaeDam was ranked the 110th, 111th fastest supercomputer in the world (Nov. 2013) Ref. ( )

5 Operational NWP Systems
GLOBAL Resolution N512L70 (UM) (~25km / top = 80km) Target Length 288hrs (00/12UTC) 87hrs (06/18UTC) Initialization : Hybrid Ensemble 4DVAR Global EPS Resolution N320L70 (UM) (~40km/ top =80km) Target Length 288hrs IC : GDAPS # of Members : 24 Perturbation : ETKF, RP, SKEB2 E-ASIA UM 12kmL70 / WRF 10kmL40 Target Length 87hrs/72hrs (6 hourly) Initialization : 4DVAR / 3DVAR LOCAL Resolution 1.5kmL70 (UM) (744928 / top =39km) Target Length 36hrs Initialization : 3DVAR

6 Operational NWP Models (’13.6~)
Resolution Target Length Main target UM (Global) N512(25km) L70 12 days 87hours(06,18) Medium-range N320 L70 M24 Medium-range (EPS) UM (E.Asia) 12km L70 87 hours Short-range WRF (E.Asia) 10km L40 UM (Korea) 1.5km L70 36 hours Very short-range KLAPS (Korea) 5km 12 hours Wave Watch III 55km 12days Global 8km Northeast Asia 1km 72 hours Coastal ADAM (Dust & Aerosol) 30km Asia dust DBAR (Typhoon) 35km Track Tide/Storm Surge 9km Global E-Asia Local App. & Stat.

7 Hybrid 4dvar(1hr) 2km inner loop
Update plans for NWP system Year 2014 2015 2016 2017 computer 3rd 3rd to 4th 4th Global Deterministic 25km 70L Hybrid 4dVar 60km inner loop 17km70L 40km DA inner loop Global Ensemble 40km 70L 24M 6 hour cycle 25km 70L 24M Local (LDAPS) 1.5km 70L 3dVar(3hr) 3km inner loop 4dVar(1hr) Hybrid 4dVar(1hr) 1km 70L Hybrid 4dvar(1hr) 2km inner loop Ensemble 3km 70L 12M (Semi operation run) (Official operation run) 1.5km 70L 24M Undetermined Coupling with ocean wave, Asian dust model with global model

8 Update NWP system in 2013

9 NWP Changes in 2013 Global Data Assimilation and Prediction Syste (N512L70) Version changes UM : vn7.7 → vn7.9 VAR/OPS : vn27.2 →vn29.2 SURF: vn18.2 → vn18.5 Major change 4dVar → Hybrid Ensemble 4dVar Physics package upgrade (PS26 → PS28) Use Climatological Aerosols Data Set Add COMS CSR data

10 NWP Changes in 2013 Regional(East Asia) Data Assimilation and Prediction System(12kmL70) UM : vn7.7 → vn7.9 Physics package: PS27 → PS28 SURF: vn18.5 Ancillary Data Set update (CAP6.6 → CAP7.7) New soil hydraulic properties – wilting and critical points New soil thermal conductivity Local(Korea) Data Assimilation and Prediction System(1.5kmL70) UM : vn7.9 (1.5km L70 ) Physics package : PS27 → PS28 OPS : vn27.2 / VAR : vn27.2 → vn29.2 SURF: vn18.3 → vn18.5 Use Aerosol effect for Visibility with domestic emission data Latent heat nudging using Radar Data

11 Global Hybrid Ensemble 4DVAR
06 UTC 12 UTC 18 UTC 00 UTC Background ERLY LATE ERLY LATE ERLY LATE ERLY LATE GDAPS Initial T+0 Obs BERR 9h 288h 9h 288h ERLY ERLY (12d) ERLY ERLY (12d) EPS Changes in EPS : 2 times daily (00/12UTC) → 4 times daily (9 hours forecast at 06/18UTC) Use Hybrid background-error covariance (Climatological covariance : Ensemble covariance = 1.0 : 0.3) to reflect “Error of the day”

12 Impact of Hybrid Ensemble 4DVAR
Verification against Observation / Improvement over Non-hybrid D.A. [%] July~August 2012 December 2012 Positive Impact AVG AVG Verification Domain Verification Domain Verification against ECMWF Analysis (Z500) / Improvement over Non-hybrid D.A. [%] July~August 2012 December 2012 개선율식 필요 Positive Impact NH TR SH NML ASIA EASIA AVG NH TR SH NML ASIA EASIA AVG Verification Domain Verification Domain

13 Radiative Effect of Aerosol (Climatology)
Summer Continental Warm Bias

14 Operational Global Model Performance
GSM T213 GSM T106 GSM T426 UM N320 Model : UM N512 3DOI 3dVar 1dVar (TOVS) FGAT 4dVar D. A. : Hybrid 4dVar

15 The effect of New soil hydraulic properties
The corrected soil hydraulic properties data set added to RDAPS(12kmL70). The new soil properties shows wilting, critical point ↑ → soil moisture ↑ → surface temperature ↓ Decreased the warm bias in the RDAPS for winter time local time New soil properties Old soil properties Day Night OLD NEW Comparison of the soil properties

16 Visibility with Murk Aerosols (LDAPS)
Aerosol emission of CAPSS1 at NIER2 Resolution : 1km X 1km [ kg/year/km2 ] Type : NOx, SOx, VOC Coverage : South Korea 1 CAPSS : Clean Air Policy Support System 2 NIER : National Institute of Environmental Research INTEX-B (NASA/2006) Resolution : 0.5o0.5o Coverage : East Aisa Improved underestimation visibility for 1~5km Aerosols effect  : visual contrast(=0.05) air : scattering coefficient of clear air(=1.0E-5) r* : radius of total water concentration m : concentration of murk aerosol - L_MURK=F : 10 [g/kg] - L_MURK=T : 0.1~200 [g/kg] Murk Aerosols Visibility Relative Humidity NEW OLD

17 Plan for the new HPC introduction
HPC Plans - Installation of 1st stage system : ‘14 Q4 - Installation of final stage system : ‘15 Q4 - Expacted Rpeak : ~10PFlops (current HPC : 0.75PFlops) NWP Plans NWP system ‘15~’16 ‘17~’18 Global (Deterministic) ~17km ~12km Global (EPS) ~25km Local (Deterministic/EPS) 1.5~4km ~1km

18 Future Plans on NWP system
Model Implementation of New Dynamical Core (ENDGame) (’15) Increasing resolution of the global model(Ocean wave, dust) Development of Probabilistic (Ensemble) NWP Systems A-O coupling for NWP (extended medium-range prediction) Data assimilation Development / Implementation of new D.A. technique - Approach to use Ensemble information in D.A. Use of additional observation data - CSR, Ground GPS, observation from new satellites Ocean D.A ( For Seasonal and extended range (30 days)).

19 Seamless Prediction Approach
Complexity Joint Seasonal Prediction System Climate Research GAP Seasonal Prediction NWP Earth System 1day 3days 10days 1month 3months >year A-O Coupling 1km Target Length 10km Atmos.(+Sfc.) 100km LDAPS Resolution RDAPS GDAPS Global EPS

20 Seamless Prediction Approach
Complexity N320(~40km) UM (M24 EPS) + NEMO(0.25deg) 30-day prediction trial Climate Research Seasonal Prediction NWP Earth System 1day 3days 10days 1month 3months >year A-O Coupling 1km Target Length 10km Atmos.(+Sfc.) 100km Resolution Extension of target length using coupled NWP system and ensemble approach Spatio-temporally higher resolution prediction

21 Regional & Convective Scale Modelling
Seoul Incheon UM 1kmL70 for 17th Asian Game (Incheon, 2014) - UM vn7.9 → vn8.2 / 360(E-W)x324(N-S) - Hourly 3DVAR (2km inner loop) cycle / FGAT → 4DVAR? - LBC from LDAPS model - T+12H Incheon Int’l Airport

22 Local Ensemble & DA research

23 LENS The integration area covers the Korean peninsula including oceans and parts of adjacent countries such as China and Japan. About 3km horizontal grid spacing and 70 vertical levels of top 40km altitude are employed. Simple downscaling of global Ensemble prediction system (N400L70, ~32km) will be adapted for IC and BC. 1,869 km 2,013 km

24 Resolution & Num. of members
Preliminary FSS score(Le Duc et al., 2013) result from 3 rainfall cases. [0.1mm] [1.0mm] (3km 8) > (3km 12) > (2km 12) ~ (2km 8) ~ (3km 16) > (2km 16) > (1.5km 12) ~ (1.5km 16) > (1.5km 8) (3km 16) > (3km 12) > (2km 12) ~ (2km 16) > (2km 8) > (3km 8) > (1.5km 16) ~ (1.5km 12) > (1.5km 8) Spatial scale (neighborhood size) Spatial scale (neighborhood size) 3km 16 member shows best 3km 12 member selected to trial accounting computer resources and stable performance

25 Trial schedule of LENS 12~24 members for 2 days forecast
00 UTC 06 UTC 12 UTC 18 UTC Background ERLY LATE ERLY LATE ERLY LATE ERLY LATE GDAPS Hybrid Ensemble and 4dVar Initial T+0 Obs. BG_ERRs ERLY (12d) 288h ERLY 9h ERLY (12d) 288h ERLY 9h EPSG Downscaling Pert. IC (T+3) Pert. BC Pert. IC (T+3) Pert. BC T+48 LENS 03UTC 12~24 members for 2 days forecast T+48 15UTC Global ensemble prediction system(EPSG) provides perturbed initial and boundary conditions for LENS at T+3 forecast.

26 Application of Ensemble DA
LENS observation sensitivity using LETKF Spin-up UTC ~ UTC experiment UTC ~ UTC(8 cases) Sonde Surface Aircraft N. OBS 8192 15415 1390 Sensitivity Sensitivity/number 0.5634 Forecast error contribution :Forecast error contribution :N Obs :Sensitivity

27 Ocean DA and forecasting

28 Purpose and status Objective (application in KMA) History
Short-range global ocean forecasting Seasonal prediction in KMA (GloSea-5)  ocean initial fields Improvement of regional ocean forecasting in KMA  lateral condition History Introduction of NEMO-CICE and NEMOVAR from UK Met Office (2012.7) - Pre-operational version of codes Short-range hindcast simulation - start from 2010/06/10 (currently, running at 2010/08/ ) - using QCed obs. and NWP fluxes of UKMO Development of pre-processing system (2013.1~12.) - Observations: gathering observations and quality control (NEMOQC) - Fluxes: extraction from KMA NWP and interpolation to model (ORCA025) 그럼, 왜 전지구 해양순환예측시스템이 필요한가? 필요성, 목적, application을 동일하게

29 Hindcast Results 10/Jun/2010 ~ 15/Jun/2010 Comparison: SSH

30 Summary & Plan Implementation of NEMO/NEMOVAR at KMA is on going.
Next year, works on the post-processing will be conducted  we will move a pre-operational this Year. The assessment will also include inter-comparison with other reanalysis data, and comparison to independent data (e.g., surface drifter) The work on diagnosis of the NEMO/NEMOVAR will be started. KMA has a plan to replace a current regional ocean model (ROMS) by regional-NEMO/NEMOVAR system. (northwestern Pacific Ocean with 1/12 deg.)

31 Development at KIAPS

32 3D global hydrostatic model
Cubed Sphere horizontal grid (CAM-SE) Lorenz grid hybrid / Finite difference in vertical(70 layers) ne30np4(~ 1o×1o) Plug-in Selected physics modules & dynamic core in own model framework Develop suitable physics(convection, PBL) around 10 km resolution Jan mean zonal wind Jan mean precipitation

33 Developing Non-hydrostatic dynamic core
Develop 2-D slice model to test compressible non-hydrostatic equations Develop 3-D in 2014(IMEX, CG in horizontal, FE in vertical)

34 Result from OSSE exp. Using Ensemble DA
Data assimilation Develop basic components for DA Ensemble DA using LETKF on cubed sphere grid Minimization & variable conversion using spectral element method for variation method Developing 4DEnVar following 5 years using developed components Surface, sonde, AMSU-A, IASI, AIRS data processing developed U V T q No DA Sonde Sonde+AIRS Result from OSSE exp. Using Ensemble DA

35 Thank You for attention


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