Abstract

A method is developed to use both polarimetric and dual-frequency radar measurements to retrieve microphysical properties of falling snow. It is applied to the Ku- and Ka-band measurements of the NASA Dual-polarization, Dual-frequency Doppler Radar (D3R) obtained during the International Collaborative Experiment for PyeongChang Olympic and Paralympics (ICE-POP 2018) field campaign, and incorporates the Atmospheric Radiative Transfer Simulator (ARTS) microwave single scattering property database for oriented particles. The retrieval uses optimal estimation to solve for several parameters that describe the particle size distribution (PSD), relative contribution of pristine, aggregate, and rimed ice species, and the orientation distribution along an entire radial simultaneously. Examination of Jacobian matrices and averaging kernels show that the dual wavelength ratio (DWR) measurements provide information regarding the characteristic particle size, and to a lesser extent, the rime fraction and shape parameter of the size distribution, whereas the polarimetric measurements provide information regarding the mass fraction of pristine particles and their characteristic size and orientation distribution. Thus, by combining the dual-frequency and polarimetric measurements, some ambiguities can be resolved that should allow a better determination of the PSD and bulk microphysical properties (e.g., snowfall rate) than can be retrieved from single-frequency polarimetric measurements or dual-frequency, single-polarization measurements. The D3R ICE-POP retrievals were validated using Precipitation Imaging Package (PIP) and Pluvio weighing gauge measurements taken nearby at the May Hills ground site. The PIP measures the snow PSD directly, and its measurements can be used to derived the snowfall rate (volumetric and water equivalent), mean volume-weighted particle size, and effective density, as well as particle aspect ratio and orientation. Four retrieval experiments were performed to evaluate the utility of different measurement combinations: Ku-only, DWR-only, Ku-pol, and All-obs. In terms of correlation, the volumetric snowfall rate (r = 0.95) and snow water equivalent rate (r = 0.92) were best retrieved by the Ku-pol method, while the DWR-only method had the lowest magnitude bias for these parameters (−31 % and −8 %, respectively). The methods that incorporated DWR also had the best correlation to particle size (r = 0.74 and r = 0.71 for DWR-only and All-obs, respectively), although none of the methods retrieved density particularly well (r = 0.43 for All-obs). The ability of the measurements to retrieve mean aspect ratio was also inconclusive, although the polarimetric methods (Ku-pol and All-obs) had reduced biases and MAE relative to the Ku-only and DWR-only methods. The significant biases in particle size and snowfall rate appeared to be related to biases in the measured DWR, emphasizing the need for accurate DWR measurements and frequent calibration in future D3R deployments.

Highlights

  • Estimation of snowfall rates and other properties from weather radar is made difficult by many of the same challenges that exist for rainfall estimation, but additional factors further confound radar retrievals of snow

  • Efforts focused on using Z to estimate the intensity of snow precipitation measurements with assumed ice particle size distribution (PSD) forms (e.g., Marshall and Gunn, 1952)

  • We focus on the 231◦ RHI scans aimed towards the May Hills Supersite (MHS) 2 km downrange, which contained a wealth of ground instrumentation

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Summary

Introduction

Estimation of snowfall rates and other properties from weather radar is made difficult by many of the same challenges that exist for rainfall estimation (primarily, the discrepancy between the 6th moment dependence of radar reflectivity factor Z 30 and the 3rd-4th moment dependence of precipitation rate R), but additional factors further confound radar retrievals of snow. The D3R was part of an extensive network of ground-based remote sensing and in-situ instrumentation deployed during ICE-POP 2018, and formed a central observation point for measurements aligned perpendicular to the coastal mountain ranges of eastern South Korea This measurement strategy was devised to examine the distribution of precipitation from the coast to the mountains in different 85 winter synoptic weather situations and evaluate high-resolution numerical weather prediction in this complex topographic region (Lim et al, 2020). The objective of this study is to use the data collected by the D3R during ICE-POP 2018 develop a snow retrieval algorithm using realistic scattering models of pristine, aggregate, and rimed snow particles, to further our understanding of the complementary nature of the dual-frequency and polarimetric radar measurements and their utility regarding snow microphys ical characterization and QPE The output of this algorithm is intended to aid in identifying microphysical processes during ICE-POP events and provide snow QPE during the deployment.

Datasets
Particle Scattering Properties
3–94 GHz 190–270 K
Optimal estimation setup
Information Content Analysis
Snowfall rate and water equivalent
Findings
Conclusions
Full Text
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