Assimilation of Polarimetric Radar Data for Convective Storm using Ensemble Kalman Filter

1. Assimilation of simulated polarimetric radar data for a convective storm using the ensemble Kalman filter. Part I: Observation operators for reflectivity and polarimetric variables Reference: Jung Y., G. Zhang, and M. Xue, 2008: Assimilation of simulated polarimetric radar data for a convective storm using the ensemble Kalman filter. Part I: Observation operators for reflectivity and polarimetric variables. Mon. Wea. Rev., 136, 2228–2245. Speaker: Yi-Yun Chien Adviser: Prof. Ming-Jen Yang

2. OUTLINE • Keywords • Introduction • The model and convective-storm simulations • The observation operators • Applications to convective storms • Summary and conclusions

3. Keywords(1,2) • OSSEs (Observing System Simulation Experiments)觀測系統模擬實驗 • Radar simulator 雷達模擬器 for Dual-Polarmetric Radar RUN1: Generate a "nature" atmosphere IC: Sounding, etc. Observation operators Simulate observations (Radar simulator) Assess the impact of DA Data assimilation RUN2:Add perturbation

4. Keywords(3) • Melting ice (snow-hail) model 冰融化模型 Dry snow (Dry hail) Rain-snow mixture (Rain-hail mixture) qs(qh) qrs(qrh) MI model : Melting ice model

5. Introduction • The advantage of Data Assimilation (DA) • Problem1: Microphysics scheme in convective scale？Doppler radar: Vr and reflectivityPolarimetric Doppler radar: Zdr, Zdp, Kdp • Problem2:Mixed-phase hydrometeor => MI model

6. The model and convective-storm simulations • Advanced Regional Prediction System (ARPS) Xue et al. (2000; 2001; 2002) • Ice microphysics scheme -> Lin et al. (1983) • Output variables : u, v, w, p, θ, qv, qc, qi, qr, qs, qh, etc. • StormSquall-lineSupercell storm

7. The observation operators • The shape, orientation, and drop size distribution of hydrometeors • Melting ice (snow-hail) model • Observation operators

8. a. The shape, orientation, and drop size distribution of hydrometeors D:equivalent diameter(mm) By an equivalent model (Green 1975) Minor axis Major axis r≡ Canting angle:

9. a. The shape, orientation, and drop size distribution of hydrometeors x : hydrometeor type D: diameter λ : slope (Lin et al. 1983) (From Marshall and Palmer, 1948.)

10. b. Melting ice (snow-hail) model • Fraction F: fraction of rain-snow mixture Set Fmax = 0.5 Fqr : mixing ratio of rainwater in the mixture form (1 – Fqr) : mixing ratio of rainwater in the pure water form qrs=F(qr+qs) Snow melting fw = 0 fs = 1 fw = 1 fs = 0 • Dielectric constant Maxwell–Garnett mixing formula (Maxwell-Garnett 1904)

11. c. Observation operators x : hydrometeor type fa , fb : backscattering amplitudes ZVV ZHH (Radar Lab, NCU)

12. c. Observation operators Hydrometeor reflectivities Total reflectivities

13. (Zrnic, 1999) ZDR: differential reflectivity Zdp:reflectivity difference KDP :specific differential phase

14. Applications to convective storms a. Squall-line b. Supercell storm

15. a. Squall-line case

17. ZDR trough

20. LI : Linear interpolation model (Jung et al. 2005) MI : Melting ice model Convective precipitation region

21. Stratiform precipitation region

22. b. Supercell storm

24. qr ZH ZDR qs qh KDP

25. qr ZH ZDR qs qh KDP

26. Summary and conclusions • The purpose to develop radar operators:1. To assimilate the corresponding measurements into storm-scale numerical models2. To verify model predictions against radar observations • A new melting model:Assuming a function for water fraction based on known mixing ratios of rainwater, snow, and hail=> Improve microphysics schemes

27. Summary and conclusions • Convective-storm characteristics are well reproduced • Reflectivity is overestimated due to:1. Neglecting non-Raleigh scattering2. Fixed DSD intercept parameter of hail3. Lack of raindrop breakup

28. Questions ?

29. Keywords(1,2) • OSSEs (Observing System Simulation Experiments)觀測系統模擬實驗“將真實觀測到的環境場資訊，ex：sounding等，放到數值模式裡建立虛擬的真實大氣情況與(雷達)觀測資料。再配合實驗的目的修改模式或同化方法，重新預報，最後和虛擬真實大氣做比較，以瞭解各實驗的預報能力。” (黃,2007) • Radar simulator 雷達模擬器 for Dual-Polarmetric Radar

30. Keywords(1,2) Radar simulator Radar simulator (黃, 2007)

31. a. The shape, orientation, and drop size distribution of hydrometeors *Fit a polynomial function (Zhang et al. 2001) Minor axis Major axis D:equivalent diameter(mm) By an equivalent model (Green 1975) r≡ 31

32. c. Observation operators x : hydrometeor type fa , fb : backscattering amplitudes (function of fw)

33. Rain Minor-axis Major-axis Rain-snow Rain-hail Major-axis Major-axis Minor-axis Minor-axis c. Observation operators

35. Zdp Zhrain Zhrain+ice

36. ε: relative permittivity ε0: permittivity in vacuum p.10 Dielectric constant Maxwell–Garnett mixing formula (Maxwell-Garnett 1904)

37. Microphysics scheme: LFO83 (Lin,1983)

38. p.21-22 LI(linear interpolation) 100% dry hail 100% dry snow -2.5˚C -5˚C Linear change Linear change 2.5˚C 0˚C 100% wet hail 100% wet snow Function of temperature

39. Scattering http://hyperphysics.phy-astr.gsu.edu/Hbase/atmos/blusky.html#c4

40. Biggerstaff and Houze,(1993)