Observed differences of triple-frequency radar signatures between snowflakes in stratiform and convective clouds

Yin, Mengtao; Liu, Guosheng; Honeyager, Ryan; Turk, F. Joseph

doi:10.1016/j.jqsrt.2017.02.017

Cited by 29 publications

(28 citation statements)

References 24 publications

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“…Comparing the results from Figure to past studies, the majority (63%) of OLYMPEX observations being found within the spheroidal‐behavior region of the DFR plane (Figures a and b) is consistent with prior airborne radar observations (Kulie et al, ) and spaceborne radar observations (Yin et al, ). This is expected when the particles in the PSD are scattering in the Rayleigh regime at all three frequencies (DFR Ku − Ka ≅ DFR Ka − W ).…”

Section: Resultssupporting

confidence: 90%

Evaluation of Triple‐Frequency Radar Retrieval of Snowfall Properties Using Coincident Airborne In Situ Observations During OLYMPEX

Chase

Finlon

Borque

et al. 2018

Geophysical Research Letters

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Scattering models of precipitation‐size ice particles have shown that aggregates and spheroidal particles occupy distinct regions of the Ku‐Ka‐W‐band dual‐frequency ratio (DFR) plane. Furthermore, past ground‐based observations suggest that particle bulk density and characteristic size can be retrieved from the DFR plane. This study, for the first time, evaluates airborne DFR observations with coincident airborne microphysical measurements. Over 2 hr of microphysical data collected aboard the University of North Dakota Citation from the Olympic Mountains Experiment are matched with Airborne Precipitation and cloud Radar Third Generation triple‐frequency radar observations. Across all flights, 31% (63%) of collocated data points show nonspheroidal (spheroidal) particle scattering characteristics. DFR observations compared with in situ observations of effective density and particle characteristic size reveal relationships that could potentially be used to develop quantitative dual‐ and triple‐frequency DFR ice property retrievals.

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Section: Resultssupporting

confidence: 90%

Evaluation of Triple‐Frequency Radar Retrieval of Snowfall Properties Using Coincident Airborne In Situ Observations During OLYMPEX

Chase

Finlon

Borque

et al. 2018

Geophysical Research Letters

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“…The selected frequencies are within ±1 GHz of X-, Ku-, Ka-, and W-band frequencies commonly used for the analysis of snowfall triple-frequency radar signatures (Leinonen et al, 2012;Kulie et al, 2014;Kneifel et al, 2015Kneifel et al, , 2016Yin et al, 2017).…”

Section: Snowfall Triple-frequency Radar Signaturesmentioning

confidence: 99%

“…7 covers a large part of all observed triple-frequency sig-natures in snowfall radar reflectivity measurements by Kulie et al (2014), Kneifel et al (2015), and Yin et al (2017). This modeled range also includes many of the triple-frequency radar signatures that Stein et al (2015) observed in their radar reflectivity measurements at 3, 35, and 94 GHz and modeled based on synthetic aggregate snowflakes generated according to W04.…”

Section: Snowfall Triple-frequency Radar Signaturesmentioning

confidence: 99%

Using snowflake surface-area-to-volume ratio to model and interpret snowfall triple-frequency radar signatures

2017

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Abstract. The snowflake microstructure determines the microwave scattering properties of individual snowflakes and has a strong impact on snowfall radar signatures. In this study, individual snowflakes are represented by collections of randomly distributed ice spheres where the size and number of the constituent ice spheres are specified by the snowflake mass and surface-area-to-volume ratio (SAV) and the bounding volume of each ice sphere collection is given by the snowflake maximum dimension. Radar backscatter cross sections for the ice sphere collections are calculated at X-, Ku-, Ka-, and W-band frequencies and then used to model triplefrequency radar signatures for exponential snowflake size distributions (SSDs). Additionally, snowflake complexity values obtained from high-resolution multi-view snowflake images are used as an indicator of snowflake SAV to derive snowfall triple-frequency radar signatures. The modeled snowfall triple-frequency radar signatures cover a wide range of triple-frequency signatures that were previously determined from radar reflectivity measurements and illustrate characteristic differences related to snow type, quantified through snowflake SAV, and snowflake size. The results show high sensitivity to snowflake SAV and SSD maximum size but are generally less affected by uncertainties in the parameterization of snowflake mass, indicating the importance of snowflake SAV for the interpretation of snowfall triplefrequency radar signatures.

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“…This variability is a source of significant uncertainty in radar retrievals. Nevertheless, dual-frequency methods have proved useful for snow retrievals (Hogan et al, 2000;Liao et al, 2005;Matrosov, 1993Matrosov, , 1998.Recently, experimental, modeling and theoretical studies have established that radars using three different frequencies can convey information about the snowflake density, in addition to the size (e.g Kneifel et al, 2011;Kulie et al, 2014;Leinonen et al, 2012;Stein et al, 2015;Yin et al, 2017). This can be understood in terms of the relationship between the frequency dependence of radar reflectivity, and the spatial correlation of the mass distribution of the snowflake (Leinonen et al, 2013).…”

mentioning

confidence: 99%

10th European Conference on Radar in Meteorology and Hydrology (ERAD 2018) : 1-6 July 2018, Ede-Wageningen, The Netherlands

Vos¹,

Leijnse²,

Uijlenhoet³

2018

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Observed differences of triple-frequency radar signatures between snowflakes in stratiform and convective clouds

Cited by 29 publications

References 24 publications

Evaluation of Triple‐Frequency Radar Retrieval of Snowfall Properties Using Coincident Airborne In Situ Observations During OLYMPEX

Evaluation of Triple‐Frequency Radar Retrieval of Snowfall Properties Using Coincident Airborne In Situ Observations During OLYMPEX

Using snowflake surface-area-to-volume ratio to model and interpret snowfall triple-frequency radar signatures

10th European Conference on Radar in Meteorology and Hydrology (ERAD 2018) : 1-6 July 2018, Ede-Wageningen, The Netherlands

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