Preprints
https://doi.org/10.5194/amt-2021-227
https://doi.org/10.5194/amt-2021-227

  19 Aug 2021

19 Aug 2021

Review status: this preprint is currently under review for the journal AMT.

Triple frequency radar retrieval of microphysical properties of snow

Kamil Mroz1, Alessandro Battaglia2,1, Cuong Nguyen3, Andrew Heymsfield4, Alain Protat5, and Mengistu Wolde3 Kamil Mroz et al.
  • 1National Centre for Earth Observation, University of Leicester, Leicester, United Kingdom
  • 2Department of Environment, Land and Infrastructure Engineering, Politecnico di Torino, Turin, Italy
  • 3Flight Research Laboratory, National Research Council Canada, Ottawa, Canada
  • 4National Center for Atmospheric Research, Boulder, Colorado
  • 5Australian Bureau of Meteorology, Melbourne, Victoria, Australia

Abstract. An algorithm based on triple-frequency (X, Ka, W) radar measurements that retrieves the size, water content and degree of riming of ice clouds is presented. This study exploits the potential of multi-frequency radar measurements to provide information on bulk snow density that should underpin better estimates of the snow characteristic size and content within the radar volume. The algorithm is based on Bayes' rule with riming parameterized by the “fill-in” model. The radar reflectivities are simulated with a range of scattering models corresponding to realistic snowflake shapes. The algorithm is tested on multi-frequency radar data collected during the ESA-funded Radar Snow Experiment. During this campaign in-situ microphysical probes were mounted on the same airplane as the radars. This nearly perfectly collocated dataset of the remote and in-situ measurements gives an opportunity to derive a combined multi-instrument estimate of snow microphysical properties that is used for a rigorous validation of the radar retrieval. Results suggest that the triple-frequency retrieval performs well in estimating ice water content and mean-mass-weighted diameters obtaining root-mean-square-error of 0.13 and 0.15, respectively for log10 IWC and log10 Dm. The retrieval of the degree of riming is more challenging and only the algorithm that uses Doppler information obtains results that are highly correlated with the in-situ data.

Kamil Mroz et al.

Status: open (until 24 Sep 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2021-227', Anonymous Referee #1, 09 Sep 2021 reply
  • RC2: 'Comment on amt-2021-227', Anonymous Referee #2, 17 Sep 2021 reply

Kamil Mroz et al.

Kamil Mroz et al.

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Short summary
A method for estimating microphysical properties of ice clouds based on the radar measurements is presented. The algorithm exploits the information provided by differences in the radar response at different frequency bands in a relation to changes in the snow morphology. The inversion scheme is based on a statistical relation between the radar simulations and the properties of snow calculated from in cloud samplings.