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 data
Principle and French radar network
 Dual polarization

Simultaneous emission of 2 waves with horizontal and vertical polarization
Ø4
Ø 3.68
Ø 2.9
Big drops are more oblate
Ø 2.65
Ø 1.75
Ø 1.35
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 data
What new information do they provide?
26/10/2012
4
Polarimetric data and convective-scale NWP models
Convective-scale NWP
models
operating at a horizontal
kilometric resolution, with
explicit description of
convection, rich microphysics,
enhanced data assimilation
capabilities
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
(e.g. the French NWP system
AROME)
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
6
Description of the polarimetric radar forward operator
 From the radar simulator from Caumont et al 2006 in Meso-NH research model
Input : model prognostic variables (T°, qv, qr, qs, qg, qc, qi …)
 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
Output : model and radar variables (reflectivity and radial velocity)
interpolated in the radar projection (PPI)
+ polarimetric radar variables (Zhh, Zdr, hv, dp , Kdp …)
 Simulates beam propagation and backscattering
 Simulates Signal-to-Noise Ratio (SNR) diagnosis of extinct
areas (important at X-band)
7
Radar/model subjective comparisons
C band
24/09/2012 (IOP 6 HyMeX)
8
Radar/model subjective comparisons
C band
24/09/2012 (IOP 6 HyMeX)
9
Radar/model subjective comparisons
C band
24/09/2012 (IOP 6 HyMeX)
10
Radar/model subjective comparisons
S band
24/09/2012 (IOP 6 HyMeX)
11
Radar/model subjective comparisons
S band
24/09/2012 (IOP 6 HyMeX)
12
Radar/model subjective comparisons
S band
24/09/2012 (IOP 6 HyMeX)
13
Radar/model subjective comparisons
S band
24/09/2012 (IOP 6 HyMeX)
14
Radar/model subjective comparisons
S band
24/09/2012 (IOP 6 HyMeX)
15
Radar/model comparisons : membership functions
Distribution of Zdr as a function of Zhh
Rain
Snow
24/09/2012
C-band
Montclar
Sband
Nimes
16
Radar/model comparisons : membership functions
Distribution of Kdp as a function of Zhh
Rain
Snow
24/09/2012
C-band
Montclar
Sband
Nimes
17
Radar/model comparisons : CFAD
Montclar (C-band) – 24/09/2012
Distribution of Zhh, Zdr and Kdp as a function of temperature in convective areas
Radar
Model
Zhh
Zdr
Kdp
18
Radar/model comparisons : CFAD
Nîmes (S-band) – 24/09/2012
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
Merci !
Vos questions sont bienvenues !