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MESOSCALE DATA ASSIMILATION FOR THE COSMO MODEL: STATUS AND PERSPECTIVES AT THE IMS

Massimo Bonavita , Lucio Torrisi, Antonio Vocino and Francesca Marcucci CNMCA Italian Meteorological Service Pratica di Mare, Rome, Italy. MESOSCALE DATA ASSIMILATION FOR THE COSMO MODEL: STATUS AND PERSPECTIVES AT THE IMS. 29° EWGLAM, Dubrovnik, 8-11 October 2007. Summary.

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MESOSCALE DATA ASSIMILATION FOR THE COSMO MODEL: STATUS AND PERSPECTIVES AT THE IMS

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  1. Massimo Bonavita, Lucio Torrisi, Antonio Vocino and Francesca Marcucci CNMCA Italian Meteorological Service Pratica di Mare, Rome, Italy MESOSCALE DATA ASSIMILATION FOR THE COSMO MODEL: STATUS AND PERSPECTIVES AT THE IMS 29° EWGLAM, Dubrovnik, 8-11 October 2007

  2. Summary • Current DAS configuration at the IMS • Recent changes in the DAS • Observation usage • Initialization for the COSMO Model: 3D-VARvsNudging • The quest for a ”flow-dependent” analysis 29° EWGLAM, Dubrovnik, 8-11 October 2007

  3. Domain size 769x513 Grid spacing 0.125° (14 Km)‏ Number of layers 40 Time step 150 sec Forecast range 72 hrs Initial time of model run 00/12 UTC L.B.C. IFS L.B.C. update frequency 3 hrs Initial state CNMCA 3D-VAR Initialization Digital Filter External analysis None Status Operational Hardware IBM P690 (ECMWF)‏ N° of processors used 32 (Model), 90 (Analysis) NWP-DAS at the IMS 29° EWGLAM, Dubrovnik, 8-11 October 2007

  4. NWP-DAS at the IMS • Data assimilation cycle: • 3D-VAR FGAT analysis step; • 3h refresh cycle; • Prognostic model: HRM hydrostatic model at 14 Km grid (0.125°) 29° EWGLAM, Dubrovnik, 8-11 October 2007

  5. NWP-DAS at the IMS 3h vs 6h DAS cycle

  6. NWP-DAS at the IMS FGAT vs OPE DAS cycle E-SAT/ST Meeting, Reading 14-15/05/2007

  7. NWP-DAS at the IMS 0.125° vs 0.25° DAS cycle E-SAT/ST Meeting, Reading 14-15/05/2007

  8. Observation usage Daily observation usage stats. SynopticAsynoptic • RAOB ~19000 - AIREP ~5500 • PILOT ~250 - AMDAR ~38000 • SYNOP ~5500 - ACAR ~8500 • SHIP,BUOY ~1200 - WIND PROF ~1200 • - QSCAT/ERS2 ~1800 • - ASCAT ~4000 • - AMV (MET9/MET7/MODIS)~14000 • - AMSU-A Rad. (NOAA1X) ~14000 • Synoptic Obs ~26000 AsynopticObs ~87000 • Total ~ 113000 obs/day 29° EWGLAM, Dubrovnik, 8-11 October 2007

  9. Observation usage • 1.Use of METOP data: a)AMSU-A rad.: extension of current NOAA1x • treatment, currently in passive monitoring • configuration • b) ASCAT winds: in place, impact and obs error • characteristics under investigation • c) GRAS Temperature/Spec. Hum. Profiles • 2.Use of hyper-spectral sounders data: • a) IASI L2 NRT products when available • b) AIRS L2 products give positive NWP impact (Riishojgaard et al., 2007) but NRT availability is unclear

  10. Initialization of COSMO Model • Initialization of COSMO Model at 7 Km resolution 29° EWGLAM, Dubrovnik, 8-11 October 2007

  11. Domain size 641 x 401 Grid spacing 0.0625 (7 km)‏ Number of layers 40 Time step 40 s Forecast range 72 hrs Initial time of model run 00 UTC Lateral bound. condit. IFS L.B.C. update freq. 3 hrs Interpolated 3D-VAR Initial state Initialization D.F.I. External analysis T,u,v, q, SP Special features Filtered topography Status Operational Hardware IBM P690 (ECMWF)‏ N° of processors 120 Initialization of COSMO Model Initial Conditions: Interpolated 14 Km 3D-VAR analysis

  12. Initialization of COSMO Model Initial Conditions: Nudging Data Assimilat. cycle

  13. 1000 400 500 700 850 150 200 250 300 925 100 2,5 2 1,5 1 0,5 0 1000 500 700 850 925 100 150 200 250 300 400 2 -0,5 1,5 -1 1 0,5 0 -0,5 -1 -1,5 COSMO-ME/COSMO-I7(LAMI)(7km) COSMO-ME vs COSMO-I7 Temp T+12 00run MAM COSMO-ME vs COSMO-I7 Temp T+24 00run MAM Mean Error (dot) and Mean Absolute Error (cont.)

  14. 1000 250 300 400 500 700 850 925 100 150 200 2 1,5 1000 500 700 850 925 100 150 200 250 300 400 2,5 1 2 0,5 1,5 0 1 -0,5 0,5 -1 0 -0,5 -1,5 -1 -1,5 COSMO-ME/COSMO-I7(LAMI)(7km) COSMO-ME vs COSMO-I7 Temp T+36 00run MAM COSMO-ME vs COSMO-I7 Temp T+48 00run MAM Mean Error (dot) and Mean Absolute Error (cont.)

  15. 100 100 150 150 200 200 250 250 300 300 400 400 500 500 700 700 850 850 925 925 1000 1000 -1 -0,5 0 0,5 1 1,5 2 2,5 3 3,5 4 -1 -0,5 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 COSMO-ME/COSMO-I7(LAMI)(7km) COSMO-ME vs COSMO-I7 Wmod T+12 00run MAM COSMO-ME vs COSMO-I7 Wmod T+24 00run MAM Mean Error (dot) and Mean Absolute Error (cont.)

  16. 1000 300 400 500 700 850 925 100 150 200 250 5 4,5 4 3,5 3 2,5 2 1,5 1 0,5 0 -0,5 -1 -1,5 COSMO-ME/COSMO-I7(LAMI)(7km) COSMO-ME vs COSMO-I7 Wmod T+36 00run MAM COSMO-ME vs COSMO-I7 Wmod T+48 00run MAM 100 150 200 250 300 400 500 700 850 925 1000 -1, -1 -0, 0 0, 1 1, 2 2, 3 3, 4 4, 5 5, 6 5 5 5 5 5 5 5 5 Mean Error (dot) and Mean Absolute Error (cont.)

  17. Initialization of COSMO Model • Interpolating a 3D-VAR analysis at 14 Km works well for the 7 Km COSMO Model • Significant improvements from 28 to 14 Km analysis: will investigate further resolution increase in 3DVAR DAS (hydrostatic limit) • Clear improvement over parallel COSMO implementation initialized with nudging. Not clear cut comparison, lack of explicit balance constraints in nudging could be an issue at 7 Km scale 29° EWGLAM, Dubrovnik, 8-11 October 2007

  18. Initialization of COSMO Model • Initialization of COSMO Model at 2.8 Km resolution 29° EWGLAM, Dubrovnik, 8-11 October 2007

  19. Initialization of COSMO Model • For the2.8Km version (COSMO-IT) an experiment was run comparing two identical model configurations: one initialized from interpolated 14 Km 3D-VAR, the other with Nudging data assimil. cycle

  20. Initialization of COSMO Model Convegno FAI, Ischia 14/06/2007

  21. Initialization of COSMO Model

  22. Initialization of COSMO Model

  23. Initialization of COSMO Model Convegno FAI, Ischia 14/06/2007

  24. Initialization of COSMO Model Convegno FAI, Ischia 14/06/2007

  25. Initialization of COSMO Model • Interpolating a 3D-VAR analysis at 14 Km does not provide balanced I.C. for 2.8 Km LM • Observation nudging is able to reduce/suppress precipitation spin-up present in the 3DVAR initialized version • After the first 6-9h skill scores of 3DVAR vs Nudging COSMO-IT are very similar: at 2-3 Km scale, nudging intrinsic balance constraints seems effective and the method looks competitive with 3D-Var • Currently, nudging initialization is employed in operational 2.8Km COSMO-IT 29° EWGLAM, Dubrovnik, 8-11 October 2007

  26. The quest for a flow dependent analysis • Extensive discussion inside COSMO community • Lack of resources/expertise to develop 4DVAR • EnKF approach is simpler and seems to be ripe for trial in operational environment (shown to outperform 3DVAR in perfect model simulations and, more recently in real world experiments) 29° EWGLAM, Dubrovnik, 8-11 October 2007

  27. The quest for a flow dependent analysis • Possible EnKF advantages for high resolution DAS: • Complex observation operators (i.e. precipitation) coped with automatically • Covariances are evolved indefinitely • Can be extended to assimilate asynchronous observations (4DEnKF) • Gives “optimal” initial perturbations for ensemble forecasting 29° EWGLAM, Dubrovnik, 8-11 October 2007

  28. The quest for a flow dependent analysis • Which EnKF version to use? Agreement on LETKF (Hunt et al. 2005) because: • Version of Ensemble Square Root Filter (EnSRF), avoids additional sampling error of perturbed observations • Avoids inefficient sequential analysis of observations of other EnSRF • Computationally efficient (computations performed in ensemble subspace) • Very efficient parallel implementation 29° EWGLAM, Dubrovnik, 8-11 October 2007

  29. The quest for a flow dependent analysis On the other hand: • Rank deficiency of sampled B matrix can be detrimental for affordable ensemble size. Observation localization can help, possible need of hybrid analysis step with 3DVAR • Effective treatment of model error still an issue 29° EWGLAM, Dubrovnik, 8-11 October 2007

  30. The quest for a flow dependent analysis At which resolution should the filter be used? Different ideas... • DWD has proposed the KEnDA project (COSMO project): Kilometer scale EnDA • Trying to tackle convection as an initial value problem too. • Running an ensemble DA and Forecast system at the Kilometer scale is very computationally expensive.. 29° EWGLAM, Dubrovnik, 8-11 October 2007

  31. The quest for a flow dependent analysis At which resolution should the filter be used? Different ideas... • At IMS we will not have the computing power of DWD for the foreseeable future! • Our forecasting target is the very short to extended short range, i.e. +3h->+72h • For non organized convection +3h is very long range forecasting • Convective systems whose life cycle and predictability extends beyond 3h can usually be modelled at the mesoscale (7-10 Km) 29° EWGLAM, Dubrovnik, 8-11 October 2007

  32. The quest for a flow dependent analysis MESO-DAPS project: Data Assimilation and Prediction System at the Mesoscale Main advantage of unified approach: “DA step samples initial uncertainties at correct spatial scales for subsequent ensemble forecast” 29th EWGLAM, Dubrovnik, 8-11 October 2007

  33. The quest for a flow dependent analysis MESO-DAPS project: • Based on LETKF (or LETKF-3DVAR hybrid approach) • 10-14 Km resolution of ensemble members • Will provide lateral and initial conditions for nested Km scale COSMO model (+3-24h) • Currently national project. Will be proposed to COSMO community if proven

  34. Thank you! 29° EWGLAM, Dubrovnik, 8-11 October 2007

  35. 3rd SRNWP Workshop on short-range EPS www.meteoam.it srepsws@meteoam.it Rome, 10-12 December 2007 Università Roma I “Sapienza”

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