2 Towards a Better Use of Polarimetric Observations of Frozen and Freezing Precipitations with Application to Aircraft Icing Detection

Monday, 28 August 2017
Zurich DEFG (Swissotel Chicago)
Clotilde Augros, Météo France, Toulouse, France; and M. Lecocq, N. Yu, and N. Gaussiat

Handout (4.1 MB)

Polarimetric radars have become more and more popular in the past 10 years and are now deployed operationally in many developed countries (USA, UK, Germany, Japan, France, …). At Météo France, the use of polarimetric observations was proven to be very useful so far to discriminate non meteorological echoes, to correct for attenuation, to better estimate rainrate and to identify hydrometeor types. However, using differential reflectivity (Zdr) or specific differential phase shift (Kdp) to characterize cold micro-physical processes is still a challenge. These variables have generally low values above the melting level, and the accuracy of the operational measurements is too poor for localised estimations of Zdr and Kdp.

Nevertheless, previous studies have examined the polarimetric signatures of different cold microphysical processes. In particular, the polarimetric signatures encountered in the presence of supercooled liquid water (SLW) were investigated and led to the development of an icing hazard algorithm at NCAR (Ellis et al, 2012; Johnston et al, 2013; Serke et al, 2015). This algorithm includes several modules permitting the detection of freezing drizzle (Ikeda et al, 2009), SLW (Plummer et al, 2010), or mixed phase (Williams et al, 2011). Freezing drizzle regions are detected thanks to the spatial texture of reflectivity, which is suggested to be smoother in case of drizzle (with respect to snow). In the SLW module, the icing hazard is higher when Kdp and Zdr have very low values, following the conclusions of Plummer et al (2010) who found that the mean values of Kdp and Zdr were slightly greater in regions of ice-only compared to mixed-phase (supercooled liquid and ice particles). However, Williams et al (2011) suggest that the coexistence of SLW and ice particles can also be characterized by relatively large Kdp and Zdr values, if the crystals grow as dendrites. This is consistent with the study of Grazioli et al (2015), who explained that the presence of SLW layers (and riming) could be characterized by an enhancement of Zdr above the layer and by an increase of Kdp in this layer, due to the riming of supercooled drops on oblate crystals.

In that context, the objective of our study is to evaluate the potential of polarimetric observations for aircraft icing detection, and to develop our own icing detection algorithm adjusted to our radar observations. For that purpose, we have used a large data base of icing in-situ observations from two airlines (18 months of data) to calculate distributions of Zdr, Zhh, Kdp and other associated parameters (spatial textures, standard deviations) for icing versus non icing cases. Our first results show that Zdr values are lower in average in icing regions compared to non-icing ones, which is coherent with the findings from Plummer et al (2010). It is more difficult to use Kdp for icing hazard detection as Kdp distributions for icing and non-icing conditions tend to overlap. This could be partially due to the smoothing (6 km width filter) that is currently applied to estimate Kdp.

The global statistical analysis of the polarimetric parameters will be shown and the impact of an adaptive filter for the estimation of Kdp will be discussed. A case study will also be presented, with Zdr and Kdp peaks above the bright band, associated with icing conditions, which could be due to the riming of supercooled drops on oblate crystals, as observed by Williams et al (2011) and Grazioli et al (2015). Eventually, the performances of our icing detection algorithm will be presented and the influence of each variable will be discussed.


Ellis S., Serke D., Hubbert J., Albo D., Weekly A., and Politovich M., 2012: Towards the Detection of Aircraft Icing Conditions Using Operational Dual-polarimetric Radar, ERAD, Toulouse, France.

Johnston C., Serke D., Ellis S., Reehorst A., Hubbert J., Albo D., Weekley A., Adriaansen D., Elmore K., and Politovich M., 2013: Statistical analysis of a radar-based icing hazard algorithm, AMS ARAM Preprint, January 6-10, Austin, TX

Plummer D.M., Goeke S., Rauber R.M., and DiGirolamo L., 2010: Discrimination of mixed-versus ice-phase clouds using dual-polarization radar with application to detection of aircraft icing regions. J. Appl. Meteor. Clim., 49, 920-935.

Serke D., King M. and Reehorst A, 2015: Initial results from radiometer and polarized-radar-based icing algorithms compared to in-situ data, SAE Preprint, Prague, Czech Republic, June 22-25th.

Williams E.R., Smalley D.J., Donovan M.F., Hallowell R. G., Hood K. T., Bennett B. J. , Evaristo R., Stepanek A. , Bals-Elsholz T., Cobb J., and Ritzman J. M., 2011: Dual polarization radar winter storm studies supporting development of NEXRAD-based aviation hazard products. AMS 35th Conf. on Radar Meteorology, Pittsburgh, PA, 26-30 September.

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