Comparisons between polarimetric radar observations and convective-scale simulations of HyMeX first special

observing period

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)

IODA-MED / HyMeX ST WV Meeting16 May 2014

Clotilde Augros

Polarimetric radar dataPrinciple and French radar network

13 operational polarimetric radars11 C-band2 S-band

3 X-band polarimetric radars « RHYTMME » + data from Mont Vial radar

All new/upgraded radars will be polarimetric

Dual polarization Simultaneous emission of 2 waves with horizontal and vertical polarization

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Ø 4 Ø 3.68 Ø 2.9

Big drops are more oblate

Ø 2.65 Ø 1.75 Ø 1.35

Polarimetric dataWhat new information do they provide?

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26/10/2012

Polarimetric data and convective-scale NWP models

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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

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

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

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Description of the polarimetric radar forward operator

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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 …)

From the radar simulator from Caumont et al 2006 in Meso-NH research model

Simulates beam propagation and backscattering

Simulates Signal-to-Noise Ratio (SNR) diagnosis of extinct areas (important at X-band)

Parameters fixed by the microphysics scheme ICE3 :

PSD (gamma laws), density of snow/graupel/ice

« Free » parameters:

dielectric constant, hydrometeor shape, orientation

=> Defined after a sensitivity study

Radar/model subjective comparisons

24/09/2012 (IOP 6 HyMeX)C band

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Radar/model subjective comparisons

24/09/2012 (IOP 6 HyMeX)

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C band

Radar/model subjective comparisons

24/09/2012 (IOP 6 HyMeX)

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C band

Radar/model subjective comparisons

24/09/2012 (IOP 6 HyMeX)

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S band

Radar/model subjective comparisons

S band24/09/2012 (IOP 6 HyMeX)

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Radar/model subjective comparisons

24/09/2012 (IOP 6 HyMeX)

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S band

Radar/model subjective comparisons

24/09/2012 (IOP 6 HyMeX)

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S band

Radar/model subjective comparisons

24/09/2012 (IOP 6 HyMeX)

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S band

24/09/2012

C-bandMontclar

S-bandNimes

Rain Snow

Radar/model comparisons : membership functionsDistribution of Zdr as a function of Zhh

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Radar/model comparisons : membership functions

24/09/2012

Distribution of Kdp as a function of Zhh

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C-bandMontclar

S-bandNimes

Rain Snow

Radar/model comparisons : CFADMontclar (C-band) – 24/09/2012

Radar

Model

Distribution of Zhh, Zdr and Kdp as a function of temperature in convective areas

Zhh Zdr Kdp

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Radar/model comparisons  : CFADNîmes (S-band) – 24/09/2012

Radar

Model

Zhh Zdr Kdp

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Distribution of Zhh, Zdr and Kdp as a function of temperature in convective areas

Conclusions and outlook

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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

Merci !

Vos questions sont bienvenues !