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Centre report of KMA 29 th WGNE meeting Melbourne 10-13 MAR. 2014

Centre report of KMA 29 th WGNE meeting Melbourne 10-13 MAR. 2014. Hoon Park Numerical Model Management Office KMA. Outlines. Current status & update strategy of KMA NWP system Upgrade NWP system in 2014 and upcoming plans Research activities in NWP at KMA. Status & upgrade strategy.

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Centre report of KMA 29 th WGNE meeting Melbourne 10-13 MAR. 2014

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  1. Centrereport of KMA 29th WGNE meeting Melbourne 10-13 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 • Researchactivities in NWP at KMA

  3. Status & upgrade strategy

  4. KMA’s 3nd Supercomputer (current) HaeOn Computing System for R&D and backup (20 Cabinets, 379Tflop/s) Computing System for Operation (20 Cabinets, 379Tflop/s) HaeDam HaeOn, HaeDam was rankedthe 110th, 111th fastest supercomputer in the world(Nov. 2013) Ref. ( http://www.top500.org )

  5. Operational NWP Systems GLOBAL • Resolution • N512L70 (UM) • (~25km / top = 80km) • Target Length • 288hrs (00/12UTC) • 87hrs (06/18UTC) • Initialization : HybridEnsemble4DVAR 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~) Global E-Asia Local App. & Stat.

  7. Update plans for NWP system • 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 • Physicspackage: 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 ERLY ERLY ERLY LATE LATE LATE LATE GDAPS InitialT+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 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 T426 GSM T213 UM N512 GSM T106 UM N320 Model : 4dVar Hybrid 4dVar 1dVar (TOVS) 3dVar 3DOI D. A. : FGAT

  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 Comparison of the soil properties OLD Old soil properties NEW New soil properties local time Night Day

  16. Visibility withMurk 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 • Type : NOx, SOx, VOC • 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] Visibility Relative Humidity Murk Aerosols 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

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

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

  21. Regional & Convective Scale Modelling Seoul Incheon Incheon Int’l Airport 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

  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 00 UTC 06 UTC 12 UTC 18 UTC Background LATE LATE LATE LATE ERLY ERLY ERLY ERLY GDAPS Hybrid Ensemble and 4dVar • InitialT+0 • Obs. • BG_ERRs 9h 288h 9h 288h ERLY ERLY (12d) ERLY ERLY (12d) EPSG • Pert. IC (T+3) • Pert. BC • Pert. IC (T+3) • Pert. BC Downscaling T+48 03UTC LENS 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 2012080612 :Forecast error contribution :N Obs :Sensitivity

  27. Ocean DA and forecasting

  28. Purpose and status • Objective (application in KMA) • 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)

  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. 2012 mean zonal wind Jan. 2012 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. Data assimilation V U Sonde+AIRS No DA Sonde q T Result from OSSE exp. Using Ensemble DA • Develop basic components for DA • Ensemble DA using LETKF on cubed sphere grid • Minimization & variable conversion using spectral element method for variation method • Developing 4DEnVarfollowing 5 years using developed components • Surface, sonde, AMSU-A, IASI, AIRS data processing developed

  35. Thank You for attention

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