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Development of a polarimetric radar simulator

Development of a polarimetric radar simulator. Clotilde Augros , Olivier Caumont, Pierre Tabary and Véronique Ducrocq Météo France Centre de Météorologie Radar ( CMR ) & Centre National de Recherches Météorologiques ( CNRM ). Context and motivation. NWP models

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Development of a polarimetric radar simulator

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  1. Development of a polarimetric radar simulator Clotilde Augros, Olivier Caumont, Pierre Tabary and Véronique Ducrocq Météo France Centre de Météorologie Radar (CMR) & Centre National de Recherches Météorologiques (CNRM)

  2. Context and motivation NWP models operating at a horizontal kilometric resolution, with explicit description of convection, rich microphysics, enhanced data assimilation capabilities (e.g. the French NWP system AROME) Polarimetric radars the new standard for operational weather radars (S / C / X) in the world Dual-pol radars provide additional variables (ZDR, DP, KDP, HV, …) which help unveiling the cold & warm microphysics inside precipitation systems

  3. Context and motivation NWP models operating at a horizontal kilometric resolution, with explicit description of convection, rich microphysics, enhanced data assimilation capabilities (e.g. the French NWP system AROME) Polarimetric radars the new standard for operational weather radars (S / C / X) in the world Dual-pol radars provide additional variables (ZDR, DP, KDP, HV, …) which help unveiling the cold & warm microphysics inside precipitation systems Development of a polarimetric radar simulator • Verify NWP models / Improve microphysical parametrization schemes • Pave the way towards assimilation of dual-pol variables into NWP • Help interpreting / understanding observed polarimetric signatures • Perform “laboratory experiments” on QPE, using the model as the reference – Test on wavelength, # radars, # tilts, …

  4. The French operational radar network at the end of 2013 27 radars overall 17 polarimetric 12 C-band 2 S-band 3 X-band (still under test) Dual-polarization is the new standard for operational radars in France and elsewhere

  5. The Météo France polarimetric (S/C/X) processing chain Processed Polarimetric Variables (Zh, Zhcorr, Zdrcorrdp, Kdp, hv) + Type Polarimetric PPIs (ZH, ZDR, DP, HV) + Z (Static) calibration of ZH & ZDR Non meteorological echo identification HV-based bright band identification DP offset removal and filtering KDP estimation DP-based attenuation correction Figueras i Ventura, J., and P. Tabary, 2013: The New French Operational Polarimetric Radar Rainfall Rate Product. J. Appl. Meteor. Climatol. doi:10.1175/JAMC-D-12-0179.1, in press. Hydrometeor classification

  6. Atmospheric model • Meso-NH model • Convective-scale atmospheric model developed by CNRM-GAME and LA • Nonhydrostatic dynamical model core, detailed moist physics, including a 1-moment bulk microphysics scheme (ICE 3) • 6 water species : • water vapor • rain • (dry) snow • graupel • cloud droplets • ice crystals No representation of hail / melting snow currently … Simulation domain Nîmes radar (S-band) 256 km range circle

  7. Polarimetric radar simulator - Main characteristics • Simulates beam bending and antenna’s radiation pattern • Simulates beam propagation (attenuation, differential attenuation, differential phase) and backscattering (reflectivity, differential reflectivity, backscatter differential phase) • Simulates Signal-to-Noise Ratio (SNR) diagnosis of extinct areas (important at X-band) Input : model prognostic variables (T°, qv, qr, qs, qg, qc, qi …) on a 3D grid Output : radar variables (VR, ZH, ZDR, HV, AH, ADP, DP, HV , KDP, …) interpolated onto radar PPIs Caumont, O., and Coauthors, 2006: A radar simulator for high resolution nonhydrostatic models. J. Atmos. Oceanic Technol., 23, 1049–1067.

  8. Polarimetric radar simulator – Hydrometeors representation • Particule size distribution : gamma particle size distributions consistent with MesoNH. N(D) is parametrized by the hydrometeor’s content M • Scattering : • Rayleigh or Mie scattering for spheres • T-matrix method for spheroids • No melting snow at the moment • Fixed fraction of liquid water for the graupel • No representation of hail (dry / melting, small / large)

  9. Case study – HyMeX Case – 24 September 2012 • A bow echo in south-eastern France observed during IOP6 of HYMEX • MesoNH simulation at 2.5 km horizontal resolution • Radar simulator: • T-matrix scattering for rain, graupel and snow and Mie for ice • Nimes radar : S-band • Extra measurements : • In-Situ Aircrafts measurements • Disdrometers, MRR • radiosoundings • balloons • research radar/lidar data … Reflectivity composite from 00 to 10 UTC

  10. Observations vs. Simulations : ZH & ZDR Reflectivity and differential reflectivity Observed variables (corrected for attenuation) Nîmes radar (S-band) Elevation=0.6° 24/09/2012 0300 UTC ZDR (dB) ZH (dBZ) 100 km Simulated variables ZDR (dB) ZH (dBZ)

  11. Observations vs. Simulations : DP & KDP Differential phase and specific differential phase Observed variables (corrected from attenuation) Nîmes radar (S-band) Elevation=0.6° 24/09/2012 0300 UTC KDP (° km-1) DP (°) Simulated variables 100 km KDP (° km-1) DP (°)

  12. Observations vs. Simulations : HV Nîmes radar (S-band) Elevation=0.6° 24/09/2012 - 0300 UTC Correlation coefficient 100 km Observed hv Simulated hv

  13. Observations vs. Simulations : Zhh and Kdp as a function of temperature 15 dBZ bias in snow/graupel/ice => model overestimation ? 0.5°/km bias for all temperatures => model overestimation ? =>underestimation of radar retrieved Kdp?

  14. Observations vs. Simulations : Zhh and Kdp as a function of temperature 15 dBZ bias in snow/graupel/ice => model overestimation ? 0.5°/km bias for all temperatures => model overestimation ? =>underestimation of radar retrieved Kdp?

  15. Observations vs. Simulations : Kdp as a function of Zhh in rain and snow => Overestimation bythemodel due to an inaccurate DSD ? => Underestimation of radar Kdp for the maximum values ?

  16. Future work • Carry on investigating the differences between radar and model • Use of DSD from disdrometers/MRR? • Radar/model comparisons at C and X-bands for this case and other cases • Test the sensitivity of the simulated polarimetric variables to the simulator parameters (dielectric function, oscillation, hydrometeors shapes) and try to adjust them in order to minimize the differences between observation and simulations • Compare the hydrometeor contents from the model with the hydrometeor types derived from the fuzzy-logic radar classification and try to use the model to help improve the radar classification • Final aim: assess how and in which conditions the polarimetric variables could be used for data assimilation in NWP models

  17. Any questions ?

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