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A new 4-dimensional variational data assimilation system for WRF

A new 4-dimensional variational data assimilation system for WRF. Juan Zhao , Bin Wang LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing. 2008-07-01. University Allied Workshop. Outline. Introduction to a new DA approach (HSP-4DVAR)

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A new 4-dimensional variational data assimilation system for WRF

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  1. A new 4-dimensional variational data assimilation system for WRF Juan Zhao , Bin Wang LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 2008-07-01 University Allied Workshop

  2. Outline • Introduction to a new DA approach (HSP-4DVAR) • Observing system simulation experiment (OSSE) • Summary University Allied Workshop

  3. Outline • Introduction to a new DA approach (HSP-4DVAR) • Observing system simulation experiment (OSSE) • Summary University Allied Workshop

  4. Introduction to HSP-4DVAR 4DVAR N*N The huge computing cost of the iterative procedure based on the adjoint technique greatly limits the wide applications of traditional 4DVAR ! Cost function of 4DVAR (incremental form): N-dimensional model space (N：106~108) Calculate by making the nonlinear optimal iteration: An effective and efficient 4DVAR adjoint (ECMWF,2002) University Allied Workshop

  5. Introduction to HSP-4DVAR HSP-4DVAR Historical Sample Projection (HSP)-4DVAR (Bin Wang et al, 2008) new cost function: m-dimensional sample space Abandon adjoint model Avoid making nonlinear optimal iteration m~102 calculate explicitly: ? University Allied Workshop

  6. Introduction to HSP-4DVAR Estimation of B matrix Utilize historical forecast samples to estimate B In model space In sample space University Allied Workshop

  7. Introduction to HSP-4DVAR Estimation of B matrix not full rank (rank = m - 1) underestimation of B University Allied Workshop

  8. Introduction to HSP-4DVAR Estimation of B matrix Take Xb as one of the samples ! full rank (rank = m) University Allied Workshop

  9. Introduction to HSP-4DVAR localization Purpose: to filter the false covariance between one point and another far point in B ( : Schur filtering operator) • Much more timesaving than EnKF localization Use the analysis as the only sample University Allied Workshop

  10. Introduction to HSP-4DVAR Analysis——in the middle of window new 4DVAR traditional 4DVAR 03 06 00 mean value theorem (Math) Xa Xa 3DVAR 03 06 00 Xa University Allied Workshop

  11. Outline • Introduction to a new DA approach(HSP-4DVAR) • Observing system simulation experiment (OSSE) • Summary University Allied Workshop

  12. OSSE—— experiment design Experiment design • Domain configuration: 189×89×29, 30km • TRUE—— forecasts from ECMWF global analysis (2.50×2.50) in the beginning of the assimilation window • CTL—— forecasts from background field; background field is produced from a 48h forecast with NCEP/NCAR reanalysis (10×10) at 48h prior to the beginning of the assimilation window • ASS—— forecasts from analysis field • Simulated obs: temperature (T) on model level 1, 10, 19, 28, interpolated from ‘TRUE’ University Allied Workshop

  13. OSSE—— experiment results Experiment results assimilation window -03 00 03 06 12 18 24 CTL ASS_middle (ASS) ASS_start University Allied Workshop

  14. OSSE—— experiment results 00h RMSE ASS : ASS_middle University Allied Workshop

  15. OSSE—— experiment results 03h RMSE University Allied Workshop

  16. OSSE—— experiment results 06h RMSE University Allied Workshop

  17. OSSE—— experiment results 12h RMSE University Allied Workshop

  18. OSSE—— experiment results 00h RMSE ASS_start = ASS_start — CTL ASS_middle = ASS_middle — CTL < 0 better > 0 worse

  19. OSSE—— experiment results 03h RMSE University Allied Workshop

  20. OSSE—— experiment results 06h RMSE University Allied Workshop

  21. OSSE—— experiment results 12h RMSE University Allied Workshop

  22. OSSE—— experiment results CTL 06h TRUE ASS precipitation ASS : ASS_middle University Allied Workshop

  23. OSSE—— experiment results CTL 12h TRUE ASS precipitation University Allied Workshop

  24. OSSE—— experiment results CTL 18h TRUE ASS precipitation University Allied Workshop

  25. OSSE—— experiment results CTL 24h TRUE ASS precipitation University Allied Workshop

  26. Outline • Introduction to a new DA approach(HSP-4DVAR) • Observing system simulation experiment (OSSE) • Summary University Allied Workshop

  27. Summary (1) • The new WRF HSP-4DVAR system performs well • abandon the adjoint technique • avoid making the nonlinear optimal iteration very time-saving • B is flow-dependent implicitly in the assimilation window explicitly from window to window • A promising approach to be applied in operational NWPs University Allied Workshop

  28. Summary (2) • Plans: • More experiments to test the new DA system (conventional and unconventional obs data) • Further improvement of B (analog prediction sample, EOF technique……) University Allied Workshop

  29. Thank you! Comments and questions are welcome! University Allied Workshop

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