A Radar Data Assimilation Experiment for COPS IOP 10 with the WRF 3DVAR System in a Rapid Update...

A Radar Data Assimilation Experiment for COPS IOP 10 with the WRF 3DVAR

System in a Rapid Update Cycle Configuration.

Thomas SchwitallaInstitute of Physics and Meteorology

University of Hohenheim

13th WRF Users Workshop 2012

Motivation

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Outline

• WRF model setup• Radar data assimilation in the WRF model• First radar assimilation experiment over France• Summary• Outlook

29.07.2012


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 from in from

the Western Europe• Direct initialization from ECMWF forecast

or analysis on model levels• CV6 Background error Matrix

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13th WRF Users Workshop 201229.07.2012

29.07.2012

Rapid Update Cycle approach with WRF

Lateral boundary conditions from ECMWF analyses/forecastT

T+0h

ECMWF analysis + DFI

T+3h T+6h T+9h T+12h

3DVAR 3DVAR 3DVAR 3DVAR

Obs Obs Obs Obs

T + xx hours

Free forecast

Update low boundary Update lateral boundary conditions

Forecast Forecast Forecast Forecast

00Z 03Z 06Z 09Z 12Z


Radar data coverage during COPS

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15 Doppler radar in total10 from France5 from Germany

S- and C-Band radarsScanning radius up to 250kmRange resolution 1kmRu

max= 60m/s and 32m/s3D volume data


Assimilation of radar data in WRF

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Radial velocity assimilation:

)( Ti

i

i

i

i

ir vw

r

zzv

r

yyu

r

xxv

Terminal velocity vT represents the fall speed of rain. It depends on the rain water mixing ratio qr under the assumption of a laminar flow (Re ≈ 300).

Reflectivities (dBZ) are assimilated applying the following operator:

3/1log5.171.43

mkg

qZ rair

Derived from a Marshall-Palmer distribution with N0 = 8*106m-4


Quality control and data thinning

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Raw observations amount is too large and data are noisy

1) According to quality flags, the raw observation is set to missing value2) Calculation of a 3x3 average value3) Calculation of variance for every raw observation4) 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 5dBZReflectivities are discarded above 4000m AGL and below 0°C

Data thinning and filtering prior to its use in a data assimilation scheme


Assimilation of radial velocities only

Good agreement throughout the complete RUC

03Z (second last RUC step)06Z, last RUC step


Assimilation of radial velocities onlyObservationWith radar windsNo radar

Small but positive influence on the 3h precipitation forecast(Reduction of RMSE ~6%, correlation slightly improved)


Looks promising, but….Assimilation of radial velocities only

Last RUC step at 06UTC


Looks promising, but….Assimilation of reflectivities in addition

Can you spot the difference?

Last RUC step at 06UTC


Looks promising, but….Horizontal distribution of ZTD O-A

No reflectivities


Looks promising, but….Horizontal distribution of ZTD O-A

With reflectivities


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)?


- Overestimation of IWV- Assimilation of reflectivities leads

to larger errors in the first few hours



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 qt in

combination with the applied microphysics schemes?

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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

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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)

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Thanks for your attention!


Results for COPS IOP10 performing a 3h RUC for 18 hours starting at 12Z, July 22, 2007


Radar data assimilation experiment for COPS IOP 10



29.07.2012 16.04.2012 Institut für Physik und Meteorologie

A Radar Data Assimilation Experiment for COPS IOP 10 with the WRF 3DVAR System in a Rapid Update...

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