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Discussion papers | Copyright
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 06 Aug 2018

Research article | 06 Aug 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

Dual-Wavelength Radar Technique Development for Snow Rate Estimation: A Case Study from GCPEx

Gwo-Jong Huang1,2, Viswanathan N. Bringi2, Andrew J. Newman3, GyuWon Lee1, Dmitri Moisseev4,5, and Branislav M. Notaros2 Gwo-Jong Huang et al.
  • 1Center for Atmospheric REmote sensing (CARE), Kyungpook National University, Daegu 41566, Rep. of Korea
  • 2Department of Electrical and Computer Engineering, Colorado State University, Fort Collins Colorado 80523, USA
  • 3Research Applications Lab, National Center for Atmospheric Research, Boulder, Colorado 80307, USA
  • 4Institute for Atmospheric and Earth System Research, University of Helsinki, 00560 Helsinki, Finland
  • 5Finnish Meteorological Institute, FI-00101 Helsinki, Finland

Abstract. Quantitative Precipitation Estimation (QPE) of snowfall has generally been expressed in power-law form between equivalent radar reflectivity factor (Ze) and liquid equivalent snow rate (SR). It is known that there is large variability in the pre-factor of the power law due to changes in particle size distribution (PSD), density, and fall velocity whereas the variability of the exponent is considerably smaller. The dual-wavelength radar reflectivity ratio (DWR) technique can improve SR accuracy by estimating one of the PSD parameters (characteristic diameter) thus reducing the variability due to the pre-factor. The two frequencies commonly used in dual-wavelength techniques are Ku- and Ka-bands. The basic idea of DWR is that the snow particle size-to-wavelength ratio is such as to fall in the Rayleigh region at Ku-band but in the Mie region at Ka-band.

We propose a method for snow rate estimation by using NASA D3R radar DWR and Ka-band reflectivity observations collected during a long-duration synoptic snow event on 30–31 January 2012 during the GCPEx (GPM Cold Season Precipitation Experiment). Since the particle mass can be estimated using 2D-video disdrometer (2DVD) fall speed data and hydrodynamic theory, we simulate the DWR and compare directly with D3R radar measurements. We also use the 2DVD-based mass to compute the 2DVD-based SR. Using three different mass estimation methods, we arrive at three respective sets of Z-SR and SR(Zh, DWR) relationships. We then use these relationships with D3R measurements to compute radar-based SR. Finally, we validate our method by comparing the D3R radar-retrieved SR with accumulated SR directly measured by a well-shielded Pluvio gauge for the entire synoptic event.

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Short summary
This paper proposes a method for snow rate (SR) estimation using observations collected by NASA dual-frequency dual-polarized (D3R) radar during the GPM Cold Season Precipitation Experiment (GCPEx). The new method utilizes dual-wavelength radar reflectivity ratio (DWR) and 2D-video disdrometer (2DVD) measurements, to improve SR estimation accuracy. It is validated by comparing the D3R radar-retrieved SR with accumulated SR directly measured by a Pluvio gauge for an entire GCPEx synoptic event.
This paper proposes a method for snow rate (SR) estimation using observations collected by NASA...