Ori et al (2020)

Numerical weather prediction model output is compared with multi-frequency, Doppler, radar observations. The statistical comparison reveal discrepancies in the cloud structure that are suggesting the presence of some inaccuracies in the modeled ice properties


Davide Ori et al.



ACCEPTED FOR PUBLICATION on Quarterly of Royal Meteorologicl Society

Vertically pointing radar observations combining multiple frequencies and Doppler measurements have been recently shown to contain valuable information about ice particle growth processes, such as aggregation and riming. In this study, we use a two-months X, Ka, W-Band Doppler radar dataset of mid-latitude winter clouds to infer statistical growth signatures of ice and snow particles. The observational statistics are compared to forward simulated radar moments based on simulations of the campaign time period with a high-resolution version of the ICON model and a two-moment microphysical scheme.

The statistical comparison shows very good agreement of the simulated vertical structure of radar reflectivity and surface precipitation rate. The dual-wavelength ratios, which are closely related to the mean particle size, also show consistently a major increase at temperatures larger than -15$^\circ$C. However, at temperatures larger than -7$^\circ$C, ICON increasingly overestimates the mean particle size. The statistics of mean Doppler velocities also reveals that the model overestimates the terminal velocity of snow particles, especially at larger sizes. We discuss possible reasons for the identified discrepancies, such as an unrealistic temperature dependence of the sticking efficiency or the non-saturation of terminal velocities at larger sizes caused by the implemented power law relations. Our study exemplary demonstrates the importance of combining various radar techniques for identifying issues in simulated microphysical processes, which can otherwise be hidden due to compensating errors.

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