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A Radar Data Assimilation Experiment for COPS IOP 10 with the WRF 3DVAR System in a Rapid Update Cycle Configuration. Thomas Schwitalla Institute of Physics.

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Presentation on theme: "A Radar Data Assimilation Experiment for COPS IOP 10 with the WRF 3DVAR System in a Rapid Update Cycle Configuration. Thomas Schwitalla Institute of Physics."— Presentation transcript:

1 A Radar Data Assimilation Experiment for COPS IOP 10 with the WRF 3DVAR System in a Rapid Update Cycle Configuration. Thomas Schwitalla Institute of Physics and Meteorology University of Hohenheim

2 Motivation 29.07.201213th WRF Users Workshop 2012

3 Outline WRF model setup Radar data assimilation in the WRF model First radar assimilation experiment over France Summary Outlook 29.07.201213th WRF Users Workshop 2012

4 WRF model setup Convection permitting resolution of 3.6km – No cumulus scheme applied! 550*550*50 grid boxes Two-Moment microphysics DFI initialization Focus is set on events coming fromin from the Western Europe Direct initialization from ECMWF forecast or analysis on model levels CV6 Background error Matrix 29.07.201213th WRF Users Workshop 2012

5 29.07.201213th WRF Users Workshop 2012 29.07.2012 29.07.2012 Rapid Update Cycle approach with WRF Lateral boundary conditions from ECMWF analyses/forecast T T+0h ECMWF analysis + DFI T+3hT+6hT+9hT+12h 3DVAR Obs T + xx hours Free forecast Update low boundary Update lateral boundary conditions Forecast 00Z03Z06Z09Z12Z

6 Radar data coverage during COPS 29.07.201213th WRF Users Workshop 2012  15 Doppler radar in total  10 from France  5 from Germany  S- and C-Band radars  Scanning radius up to 250km  Range resolution 1km  R u max = 60m/s and 32m/s  3D volume data

7 Assimilation of radar data in WRF 29.07.201213th WRF Users Workshop 2012 Radial velocity assimilation: Terminal velocity v T represents the fall speed of rain. It depends on the rain water mixing ratio q r under the assumption of a laminar flow (R e ≈ 300). Reflectivities (dBZ) are assimilated applying the following operator: Derived from a Marshall-Palmer distribution with N 0 = 8*10 6 m -4

8 Quality control and data thinning 29.07.201213th WRF Users Workshop 2012 Raw observations amount is too large and data are noisy 1)According to quality flags, the raw observation is set to missing value 2)Calculation of a 3x3 average value 3)Calculation of variance for every raw observation 4)Variance rejection threshold 50dBZ² for reflectivity and 60m²/s² for radial velocity (Xiao, WRF Workshop 2008) 5)Additional smoothing along the ray and azimuth Applied filtering procedure for e.g. German radar data: Radial wind observation error = f(range) Reflectivity error set to 5dBZ Reflectivities are discarded above 4000m AGL and below 0°C Data thinning and filtering prior to its use in a data assimilation scheme

9 29.07.201213th WRF Users Workshop 2012 Assimilation of radial velocities only Good agreement throughout the complete RUC 03Z (second last RUC step)06Z, last RUC step

10 29.07.201213th WRF Users Workshop 2012 Assimilation of radial velocities only ObservationWith radar winds No radar Small but positive influence on the 3h precipitation forecast (Reduction of RMSE ~6%, correlation slightly improved)

11 29.07.201213th WRF Users Workshop 2012 Looks promising, but…. Assimilation of radial velocities only Last RUC step at 06UTC

12 29.07.201213th WRF Users Workshop 2012 Looks promising, but…. Assimilation of reflectivities in addition Can you spot the difference? Last RUC step at 06UTC

13 29.07.201213th WRF Users Workshop 2012 Looks promising, but…. Horizontal distribution of ZTD O-A No reflectivities

14 29.07.201213th WRF Users Workshop 2012 Looks promising, but…. Horizontal distribution of ZTD O-A With reflectivities

15 29.07.201213th WRF Users Workshop 2012 Looks promising, but…. Model imbalances despite DFI? - Hopefully not! Relative humidity set to 100% in the model? – Yes, set to 100% Deficits in cloud microphysics in 3DVAR scheme? – possible Too many observations used (approx. 5000)?

16 29.07.201213th WRF Users Workshop 2012  Overestimation of IWV  Assimilation of reflectivities leads to larger errors in the first few hours Looks promising, but….

17 Summary  Setup of a unique WRF Rapid Update Cycle over central Europe applying a convection permitting resolution  First steps to assimilate 3D volume radar data from two different networks with WRF over Europe  Results are promising, but still deficiencies due to model imbalances, deficits in clear air dynamics  Quality issues of reflectivities – bias correction required?  Problems with the humidity control variable q t in combination with the applied microphysics schemes? 29.07.201213th WRF Users Workshop 2012

18 Outlook  Harmonize radar data quality and interpolation procedures  OPERA European radar data base  Statistical evaluation of assimilating radar reflectivities  Check short-term forecasts inside RUC  Utilize polarization radar data (  CAOS)  Comparison of 3DVAR-RUC and 4DVAR (challenging….)  Testing (hybrid) ensemble data assimilation methods (EnKF, 3DVAR-ETKF, Ensemble-3DVAR)  Incorporate GPS slant total delays and/or more ZTD data if available to further improve the water vapor fields 29.07.201213th WRF Users Workshop 2012

19 Acknowledgements WRF team (especially Wei, Cindy, Xin and John) Galina Dick from GFZ Potsdam Klaus Stephan from the German Meteorological Service Olivier Caumont from Météo France ECMWF High Performance Computing Center Stuttgart (HLRS) 29.07.201213th WRF Users Workshop 2012

20 29.07.201213th WRF Users Workshop 2012 Thanks for your attention!

21 29.07.201213th WRF Users Workshop 2012 Results for COPS IOP10 performing a 3h RUC for 18 hours starting at 12Z, July 22, 2007

22 29.07.201213th WRF Users Workshop 2012 Radar data assimilation experiment for COPS IOP 10

23 Looks promising, but…. 29.07.201213th WRF Users Workshop 201216.04.2012 Institut für Physik und Meteorologie

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