Retrieval of snowflake microphysical properties from multifrequency radar observations

Abstract

We have developed an algorithm that retrieves the size, number concentration and density of falling snow from multifrequency radar observations. This work builds on previous studies that have indicated that three-frequency radars can provide information on snow density, potentially improving the accuracy of snow parameter estimates. The algorithm is based on a Bayesian framework, using lookup tables mapping the measurement space to the state space, which allows fast and robust retrieval. In the forward model, we calculate the radar reflectivities using recently published snow scattering databases. We demonstrate the algorithm using multifrequency airborne radar observations from the OLYMPEX-RADEX field campaign, comparing the retrieval results to hydrometeor identification using ground-based polarimetric radar and also to collocated in situ observations made using another aircraft. Using these data, we examine how the availability of multiple frequencies affects the retrieval accuracy, and we test the sensitivity of the algorithm to the prior assumptions. The results suggest that multifrequency radars are substantially better than single-frequency radars at retrieving snow microphysical properties. Meanwhile, triplefrequency radars can retrieve wider ranges of snow density than dual-frequency radars and better locate regions of highdensity snow such as graupel, although these benefits are relatively modest compared to the difference in retrieval performance between dual-and single-frequency radars. We also examine the sensitivity of the retrieval results to the fixed a priori assumptions in the algorithm, showing that the multifrequency method can reliably retrieve snowflake size, while the retrieved number concentration and density are affected significantly by the assumptions.

The importance of particle size distribution shape for triple-frequency radar retrievals of the morphology of snow

“…These results indicate that, at least as the retrieval is configured here, triple-frequency radar measurements are insufficient to constrain a retrieval of the density factor. This is consistent with the results of Leinonen et al (2018), wherein the retrieved 20 prefactor of the particle mass-size relation was relatively insensitive to the triple-frequency radar measurements. Instead, the mean Doppler velocity provides an effective constraint on the density of rimed snow, as in Mason et al (2018).…”

“…Using groundbased triple-frequency radar measurements alongside in situ measurements of particle properties at the surface, we showed that including variations in the PSD shape permitted more accurate representations of the measured triple-frequency radar The potential to use advanced radar measurements to constrain ice particle properties in retrievals is of significant interest for reducing uncertainties in remote-sensed estimates of ice water content and snowfall, as well as improving understanding of the microphysics of ice and mixed-phase cloud. Two recent studies have used triple-frequency airborne radar measurements to constrain retrievals of ice particle density by modifying the prefactor of the mass-size distribution (Leinonen et al, 2018;Tridon et al, 2019); however, both studies found that triple-frequency radar retrievals were not substantially different from dual-frequency retrievals, suggesting that the problem was over-constrained. An alternative approach to estimating ice particle properties has been to use Doppler velocity as a constraint on particle density (Szyrmer and Zawadzki, 2014a;Mason et al, 2018).…”

“…The strong numerical and observational evidence that the triple-frequency radar signature reflects the density and structure of snow particles suggests the potential for retrievals in which some morphological parameters are constrained by triple-frequency radar measurements. Triple-frequency radar retrievals have been demonstrated in which the structure and density of ice particles 10 are allowed to vary (Leinonen et al, 2018;Tridon et al, 2019); however, it is not yet clear which ice particle properties are best constrained by the triple-frequency radar measurements; Leinonen et al (2018) found that a triple-frequency radar retrieval did not differ significantly from that of a dual-frequency retrieval, suggesting that the problem is over-constrained. To our knowledge, a triple-frequency Doppler retrieval of ice has not yet been described-this may have the advantages of estimating particle density constrained by Doppler velocity (as in Mason et al, 2018) and using triple-frequency radar signatures to 15 constrain some parameters of particle morphology.…”

“…In planning for satellite missions beyond EarthCARE (National Academies of Sciences Engineering and Medicine, 2018), the benefits of dual-frequency radar as a constraint on size and number concentration of hydrometeors has been wellestablished (e.g. Leinonen et al, 2018;Mason et al, 2017Mason et al, , 2018. As a constraint on the retrieval of particle density, triplefrequency radar has thus far provided relatively small advantages over dual-frequency radars (Leinonen et al, 2018;Tridon et al, 2019) when compared with Doppler velocity (Mason et al, 2018); however, we have demonstrated that triple-frequency 25 radar measurements can be used to constrain additional properties of the PSD to provide insights into ice and mixed-phase cloud microphysics.…”

The Microphysics of Stratiform Precipitation During OLYMPEX: Compatibility Between Triple‐Frequency Radar and Airborne In Situ Observations

“…By exploiting the frequency dependence of the interaction between hydrometeors and microwave radiation (Lhermitte, ), multifrequency radars have the potential to provide improved profiles of precipitation rates and of the microphysical properties of the ice and rain particle size distributions (PSDs). Previously, several multifrequency cloud radar techniques have been proposed to derive precipitating ice (Leinonen et al, ; Mason et al, ; Matrosov, ; Turk et al, ) and rain (Firda et al, ; Mason et al, ; Tridon et al, ) in stratiform systems, but few of them provide a simultaneous description of the ice and rain profile (Gaussiat et al, ; Grecu et al, ; ; Seto et al, ). Three points make such a retrieval challenging: The properties of ice crystals are extremely variable (size, shape, and structure), which makes their microwave scattering properties complex.…”