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IODA-MED / HyMeX ST WV Meeting 16 May 2014

Comparisons between polarimetric radar observations and convective-scale simulations of HyMeX first special observing period. IODA-MED / HyMeX ST WV Meeting 16 May 2014. Clotilde Augros.

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IODA-MED / HyMeX ST WV Meeting 16 May 2014

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  1. Comparisons between polarimetric radar observations and convective-scale simulations of HyMeX first special observing period IODA-MED / HyMeX ST WV Meeting 16 May 2014 Clotilde Augros PhD student under the supervision of Olivier Caumont (CNRM/GMME/MICADO), Véronique Ducrocq (CNRM/GMME), Pierre Tabary (DSO/CMR) and Nicolas Gaussiat (DSO/CMR/DEP)

  2. Polarimetric radar dataPrincipleand French radar network Ø 4 Ø 3.68 Ø 2.9 Big drops are more oblate Ø 2.65 Ø 1.75 Ø 1.35 2 • Dual polarization • Simultaneous emission of 2 waves with horizontal and vertical polarization 13 operational polarimetric radars 11 C-band 2 S-band 3 X-band polarimetric radars « RHYTMME » + data from Mont Vial radar  All new/upgraded radars will be polarimetric

  3. Polarimetric dataWhat new information do they provide? 3 26/10/2012

  4. Polarimetric data and convective-scale NWP models 4 Convective-scale 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 Objectives of the study: • Develop a forward polarimetric radar observation operator: direct comparisons between radar and model • Evaluate the potential of polarimetric data for assimilation in Arome

  5. Plan Description of the polarimetric radar forward operator Radar/model subjective comparisons Montclar C-band radar, IOP6 HyMeX: 24/09/2012 Nîmes S-band radar, IOP6 HyMeX: 24/09/2012 Radar/model comparisons : membership functions Radar/model comparisons : CFAD Conclusions and outlook 5

  6. Description of the polarimetric radar forward operator Input : model prognostic variables (T°, qv, qr, qs, qg, qc, qi …) Output : model and radar variables (reflectivity and radial velocity) interpolated in the radar projection (PPI) + polarimetric radar variables (Zhh, Zdr, hv, dp , Kdp …) 6 • From the radar simulator from Caumont et al 2006 in Meso-NH research model • Parameters fixed by the microphysics schemeICE3 : PSD (gamma laws), density of snow/graupel/ice • « Free » parameters: dielectric constant, hydrometeor shape, orientation => Defined after a sensitivity study • Simulates beam propagation and backscattering • Simulates Signal-to-Noise Ratio (SNR) diagnosis of extinct areas (important at X-band)

  7. Radar/model subjective comparisons 7 C band 24/09/2012 (IOP 6 HyMeX)

  8. Radar/model subjective comparisons 8 C band 24/09/2012 (IOP 6 HyMeX)

  9. Radar/model subjective comparisons 9 C band 24/09/2012 (IOP 6 HyMeX)

  10. Radar/model subjective comparisons 10 S band 24/09/2012 (IOP 6 HyMeX)

  11. Radar/model subjective comparisons 11 S band 24/09/2012 (IOP 6 HyMeX)

  12. Radar/model subjective comparisons 12 S band 24/09/2012 (IOP 6 HyMeX)

  13. Radar/model subjective comparisons 13 S band 24/09/2012 (IOP 6 HyMeX)

  14. Radar/model subjective comparisons 14 S band 24/09/2012 (IOP 6 HyMeX)

  15. Radar/model comparisons : membership functions 15 Distribution of Zdr as a function of Zhh Rain Snow 24/09/2012 C-band Montclar S-band Nimes

  16. Radar/model comparisons : membership functions 16 Distribution of Kdp as a function of Zhh 24/09/2012 Rain Snow C-band Montclar S-band Nimes

  17. Radar/model comparisons : CFADMontclar (C-band) – 24/09/2012 17 Distribution of Zhh, Zdr and Kdp as a function of temperature in convective areas Radar Model Zhh Zdr Kdp

  18. Radar/model comparisons  : CFADNîmes (S-band) – 24/09/2012 18 Distribution of Zhh, Zdr and Kdp as a function of temperature in convective areas Radar Model Zhh Zdr Kdp

  19. Conclusions and outlook Main conclusions of radar/model comparisons for 24/09/2012 and 26/10/2012 Membership functions : good consistency between median Zdr and Kdp radar/model for a given Zhh. But high dispersion in radar data (natural variability of PSD + noise) CFAD of Zhh, Kdp and Zdr rather good consistency but varying with the case/radar Overestimation of snow/ice/graupel contents in some cases by the model?Underestimation of the maximum Zhh/Kdp in low levels (rain) Sharp transition between rain and snow in model But : uncertainties due to the methodology : all radar scans are not simultaneous => can impact vertical profiles + comparison of convective cells that do not necessarily have the same temporal evolution Paper in preparation for HyMeX special issue in QJRMS + presentation of results at ERAD and HyMeX conferences (September 2014) Outlook : toward the assimilation of polarimetric variables in Arome Literature review of the use of dual-pol variables for assimilation in NWP models Design of a methodology for the selection of polarimetric observations « useful » for assimilation Development of a new assimilation methodology using polarimetric data: to be defined this summer 19

  20. Merci !Vos questions sont bienvenues !

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