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

Chase, Randy J.; Finlon, Joseph A.; Borque, Paloma; McFarquhar, Greg M.; Nesbitt, Stephen W.; Tanelli, Simone; Sy, Ousmane O.; Durden, Stephen L.; Poellot, Michael R.

doi:10.1029/2018GL077997

i

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

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2018
By Chase, Randy J. ; Finlon, Joseph A. ; Borque, Paloma ; ...

Details

Journal Title:

Geophysical Research Letters
Personal Author:

Chase, Randy J. ; Finlon, Joseph A. ; Borque, Paloma ; McFarquhar, Greg M. ; Nesbitt, Stephen W. ; Tanelli, Simone ; Sy, Ousmane O. ; Durden, Stephen L. ; Poellot, Michael R.
NOAA Program & Office:

NOAA Cooperative Institutes ; CIMMS (Cooperative Institute for Mesoscale Meteorological Studies) ; OAR (Oceanic and Atmospheric Research) ; NSSL (National Severe Storms Laboratory)
Description:

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.
Keywords:

Ice Clouds Remote Sensing Ice Clouds Remote Sensing
Source:

Geophysical Research Letters (2018) 45(11): 5752-5760.
DOI:

https://doi.org/10.1029/2018GL077997
Document Type:

Journal Article
Place as Subject:

North America
Rights Information:

Other
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Submitted
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urn:sha-512:bdc7966d263e4bce580d61a2cda6ed4602401d73c9f1f116f96816d9bcaa98a06a9cab6f326d6980cb5d9fc81f4c67a4237dc5664e9d744fef01b2f40476bfc5
Download URL:

https://repository.library.noaa.gov/view/noaa/25667/noaa_25667_DS1.pdf
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