Dual-wavelength radar technique development for snow rate estimation: a case study from GCPEx

Huang, Gwo-Jong; Bringi, V. N.; Newman, Andrew J.; Lee, GyuWon; Moisseev, Dmitri; Notaroš, Branislav M.

doi:10.5194/amt-12-1409-2019

Cited by 15 publications

(10 citation statements)

References 50 publications

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“…Several studies suggested utilizing the dual-wavelength ratio (DWR) for improving the accuracy of radar-based quantitative precipitation estimation (QPE) for snowfall and for retrieving microphysical properties of ice hydrometeors values (e.g., Matrosov 1998;Liao et al 2005;Huang et al 2019). Some studies extended this by using triple-frequency measurements for deriving two different DWR values (e.g., Kneifel et al 2015;Chase et al 2018;Leinonen et al 2018).…”

Section: Introductionmentioning

confidence: 99%

“…Because DWR depends on hydrometeor shape (Matrosov 1993;Matrosov et al 2005), snowfall property retrieval techniques utilizing the DWR usually assume an average ice hydrometeor shape (e.g., Mason et al 2018;Huang et al 2019). The shape parameter is usually expressed as a particle aspect ratio, which is defined as a ratio of hydrometeor minor and major dimensions.…”

Section: Introductionmentioning

confidence: 99%

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Observational and Modeling Study of Ice Hydrometeor Radar Dual-Wavelength Ratios

Matrosov

Maahn

Boer

2019

Journal of Applied Meteorology and Climatology

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The influence of ice hydrometeor shape on the dual-wavelength ratio (DWR) of radar reflectivities at millimeter-wavelength frequencies is studied theoretically and on the basis of observations. Data from dual-frequency (Ka–W bands) radar show that, for vertically pointing measurements, DWR increasing trends with reflectivity Ze are very pronounced when Ka-band Ze is greater than about 0 dBZ and that DWR and Ze values are usually well correlated. This correlation is explained by strong relations between hydrometeor characteristic size and both of these radar variables. The observed DWR variability for a given level of reflectivity is as large as 8 dB, which is in part due to changes in mean hydrometeor shape as expressed in terms of the particle aspect ratio. Hydrometeors with a higher degree of nonsphericity exhibit lower DWR values when compared with quasi-spherical particles because of near-zenith reflectivity enhancements for particles outside the Rayleigh-scattering regime. When particle mass–size relations do not change significantly (e.g., for low-rime conditions), DWR can be used to differentiate between quasi-spherical and highly nonspherical hydrometeors because (for a given reflectivity value) DWR tends to increase as particles become more spherical. Another approach for differentiating among different degrees of nonsphericity for larger scatterers is based on analyzing DWR changes as a function of radar elevation angle. These changes are more pronounced for highly nonspherical particles and can exceed 10 dB. Measurements of snowfall spatiotemporally collocated with spaceborne CloudSat W-band radar and ground-based S-band operational weather radars also indicate that DWR values are generally smaller for ice hydrometeors with higher degrees of nonsphericity, which, for the same level of S-band reflectivity, exhibit greater differential reflectivity values.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Observational and Modeling Study of Ice Hydrometeor Radar Dual-Wavelength Ratios

Matrosov

Maahn

Boer

2019

Journal of Applied Meteorology and Climatology

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“…Radars can measure larger areas and thus provide more accurate QPE. There have been lots of snowfall rate estimations based on radar in the past (Bukovcic et al 2018;Hassan et al 2017;Huang et al 2010;Huang et al 2015;Huang et al 2019;Souverijns et al 2015;von Lerber et al 2017), and the majority of them use power-law relations between liquid water equivalent snowfall rate (S) and equivalent radar reflectivity factor (herein Z), = . Due to various reasons the prefactor and exponent vary greatly and cause large difference in snowfall estimation.…”

Section: Introductionmentioning

confidence: 99%

“…The use of DFR (the ratio of reflectivity at Ku-band and Ka-band) to estimate snowfall rate is considered here to reduce errors. Research using dual-frequency radar for snow quantitative precipitation estimation (QPE) is rare (Huang et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Snowfall Estimation Using Dual-wavelength Radar during the Pyeongchang 2018 Olympics and Paralympic Winter Games

Chandrasekar

Xiao

et al. 2021

Journal of the Meteorological Society of Japan

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Accurate estimation of snowfall rate during snowstorms is crucial. This estimate directly impacts the hydrological and atmospheric models. The density of snow plays a very important role in estimating the snowfall rate. In this paper, the density of snow is investigated during a huge snowstorm event during the International Collaborative Experiment held during the PyeongChang 2018 Olympics and Paralympic winter games (ICE-POP 2018). The density is calculated using the terminal velocities and diameters of the snow particles measured by a disdrometer. In this study, we not only use radar reflectivity factor (Z) for snowfall rate (S) estimation, but also use dual-frequency ratio (DFR). We derive S-Z and S-Z-DFR relations for snowfall estimation during this snowstorm event after considering the density of snow. The comparisons are performed between National Aeronautics and Space Administration (NASA) Dual-frequency Dualpolarization Doppler Radar (D3R) and precipitation gauges using these two power-law relations. The results show that the two relations for snowfall rate estimation agree well with gauges, but the S-Z-DFR method performs the best, which has a lower normalized standard error. The error in the snowfall rate estimates decreases as the time scale becomes large. This shows that the S-Z-DFR algorithm is a promising way for snowfall quantitative precipitation estimation (QPE) and can be used as a ground validation tool for Global Precipitation Measurement (GPM) snowfall production evaluations.

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“…many ice studies before. Matrosov (1998) developed a DWR method to estimate the snowfall rate R, supplementing experimental Ze-R relations with a retrieved median size, while in Huang et al (2019) the DWR was used for Quantitative 80 Precipitation Estimation (QPE) from the combination of Ku-and Ka-band which were accounted to be Rayleigh and Mie region, respectively, for the detected particles sizes. In other studies, such as Hogan and Illingworth (1999) and Hogan et al (2000), DWR from airborne and ground-based radars was used to estimate ice crystals sizes as well as IWC for cirrus clouds.…”

Section: Introductionmentioning

confidence: 99%

Retrievals of ice microphysics using dual-wavelength polarimetric radar observations during stratiform precipitation events

Tetoni

Ewald

Hagen

et al. 2021

Preprint

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Abstract. Ice growth processes within clouds affect the type as well as the amount of precipitation. Hence, the importance of an accurate representation of ice microphysics in numerical weather and numerical climate models has been confirmed by several studies. To better constrain ice processes in models, we need to study ice cloud regions before and during monitored precipitation events. For this purpose, two radar instruments facing each other were used to collect complementary measurements. The C-band POLDIRAD weather radar from the German Aerospace Center (DLR), Oberpfaffenhofen and the Ka-band MIRA-35 cloud radar from the Ludwig Maximilians University of Munich (LMU) were used to monitor stratiform precipitation in the vertical cross-section area between both instruments. The logarithmic difference of radar reflectivities at two different wavelengths (54.5 and 8.5 mm), known as dual-wavelength ratio, was exploited to provide information about the size of the detected ice hydrometeors, taking advantage of the different scattering behavior in the Rayleigh and Mie regime. Along with the dual-wavelength ratio, differential radar reflectivity measurements from POLDIRAD provided information about the apparent shape of the detected ice hydrometeors. Scattering simulations using the T-matrix method were performed for oblate and horizontally aligned prolate ice spheroids of varying shape and size using a realistic particle size distribution and a well-established mass-size relationship. The combination of dual-wavelength ratio, radar reflectivity and differential radar reflectivity measurements as well as scattering simulations was used for the development of a novel retrieval for ice cloud microphysics. The development of the retrieval scheme also comprised a method to estimate the hydrometeor attenuation in both radar bands. To demonstrate this approach, a feasibility study was conducted on three stratiform snow events which were monitored over Munich in January 2019. The ice retrieval can obtain ice particle shape, size and mass which are in line with differential radar reflectivity, dual-wavelength ratio and radar reflectivity observations when a suitable mass-size relation is used and when ice hydrometeors are assumed to be represented by oblate ice spheroids. A furthermore finding was the importance of the differential radar reflectivity for the particle size retrieval directly above the MIRA-35 cloud radar. Especially for that observation geometry, the simultaneous slantwise observation from the polarimetric weather radar POLDIRAD could reduce ambiguities in retrieval of the ice particle size by constraining the ice particle shape.

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Dual-wavelength radar technique development for snow rate estimation: a case study from GCPEx

Cited by 15 publications

References 50 publications

Observational and Modeling Study of Ice Hydrometeor Radar Dual-Wavelength Ratios

Observational and Modeling Study of Ice Hydrometeor Radar Dual-Wavelength Ratios

Snowfall Estimation Using Dual-wavelength Radar during the Pyeongchang 2018 Olympics and Paralympic Winter Games

Retrievals of ice microphysics using dual-wavelength polarimetric radar observations during stratiform precipitation events

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