Ice Hydrometeor Shape Estimations Using Polarimetric Operational and Research Radar Measurements

A polarimetric radar method to estimate mean shapes of ice hydrometeors was applied to several snowfall and ice cloud events observed by operational and research weather radars. The hydrometeor shape information is described in terms of their aspect ratios, r , which represent the ratio of particle...

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Published in:Atmosphere
Main Author: Sergey Y. Matrosov
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2020
Subjects:
Online Access:https://doi.org/10.3390/atmos11010097
https://doaj.org/article/c3f784476cfb4d90b8c259ba36dd8ba5
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spelling ftdoajarticles:oai:doaj.org/article:c3f784476cfb4d90b8c259ba36dd8ba5 2023-05-15T15:07:31+02:00 Ice Hydrometeor Shape Estimations Using Polarimetric Operational and Research Radar Measurements Sergey Y. Matrosov 2020-01-01T00:00:00Z https://doi.org/10.3390/atmos11010097 https://doaj.org/article/c3f784476cfb4d90b8c259ba36dd8ba5 EN eng MDPI AG https://www.mdpi.com/2073-4433/11/1/97 https://doaj.org/toc/2073-4433 2073-4433 doi:10.3390/atmos11010097 https://doaj.org/article/c3f784476cfb4d90b8c259ba36dd8ba5 Atmosphere, Vol 11, Iss 1, p 97 (2020) polarimetric radar depolarization ratio snowfall ice clouds hydrometeor shape Meteorology. Climatology QC851-999 article 2020 ftdoajarticles https://doi.org/10.3390/atmos11010097 2022-12-31T12:45:22Z A polarimetric radar method to estimate mean shapes of ice hydrometeors was applied to several snowfall and ice cloud events observed by operational and research weather radars. The hydrometeor shape information is described in terms of their aspect ratios, r , which represent the ratio of particle minor and major dimensions. The method is based on the relations between depolarization ratio (DR) estimates and aspect ratios. DR values, which are a proxy for circular depolarization ratio, were reconstructed from radar variables of reflectivity factor, Z e , differential reflectivity, Z DR , and copolar correlation coefficient ρ hv , which are available from radar systems operating in either simultaneous or alternate transmutation of horizontally and vertically polarized signals. DR- r relations were developed for retrieving aspect ratios and their sensitivity to different assumptions and model uncertainties were discussed. To account for changing particle bulk density, which is a major contributor to the retrieval uncertainty, an approach is suggested to tune the DR- r relations using reflectivity-based estimates of characteristic hydrometeor size. The analyzed events include moderate snowfall observed by an operational S-band weather radar and a precipitating ice cloud observed by a scanning K a -band cloud radar at an Arctic location. Uncertainties of the retrievals are discussed. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Atmosphere 11 1 97
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic polarimetric radar
depolarization ratio
snowfall
ice clouds
hydrometeor shape
Meteorology. Climatology
QC851-999
spellingShingle polarimetric radar
depolarization ratio
snowfall
ice clouds
hydrometeor shape
Meteorology. Climatology
QC851-999
Sergey Y. Matrosov
Ice Hydrometeor Shape Estimations Using Polarimetric Operational and Research Radar Measurements
topic_facet polarimetric radar
depolarization ratio
snowfall
ice clouds
hydrometeor shape
Meteorology. Climatology
QC851-999
description A polarimetric radar method to estimate mean shapes of ice hydrometeors was applied to several snowfall and ice cloud events observed by operational and research weather radars. The hydrometeor shape information is described in terms of their aspect ratios, r , which represent the ratio of particle minor and major dimensions. The method is based on the relations between depolarization ratio (DR) estimates and aspect ratios. DR values, which are a proxy for circular depolarization ratio, were reconstructed from radar variables of reflectivity factor, Z e , differential reflectivity, Z DR , and copolar correlation coefficient ρ hv , which are available from radar systems operating in either simultaneous or alternate transmutation of horizontally and vertically polarized signals. DR- r relations were developed for retrieving aspect ratios and their sensitivity to different assumptions and model uncertainties were discussed. To account for changing particle bulk density, which is a major contributor to the retrieval uncertainty, an approach is suggested to tune the DR- r relations using reflectivity-based estimates of characteristic hydrometeor size. The analyzed events include moderate snowfall observed by an operational S-band weather radar and a precipitating ice cloud observed by a scanning K a -band cloud radar at an Arctic location. Uncertainties of the retrievals are discussed.
format Article in Journal/Newspaper
author Sergey Y. Matrosov
author_facet Sergey Y. Matrosov
author_sort Sergey Y. Matrosov
title Ice Hydrometeor Shape Estimations Using Polarimetric Operational and Research Radar Measurements
title_short Ice Hydrometeor Shape Estimations Using Polarimetric Operational and Research Radar Measurements
title_full Ice Hydrometeor Shape Estimations Using Polarimetric Operational and Research Radar Measurements
title_fullStr Ice Hydrometeor Shape Estimations Using Polarimetric Operational and Research Radar Measurements
title_full_unstemmed Ice Hydrometeor Shape Estimations Using Polarimetric Operational and Research Radar Measurements
title_sort ice hydrometeor shape estimations using polarimetric operational and research radar measurements
publisher MDPI AG
publishDate 2020
url https://doi.org/10.3390/atmos11010097
https://doaj.org/article/c3f784476cfb4d90b8c259ba36dd8ba5
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_source Atmosphere, Vol 11, Iss 1, p 97 (2020)
op_relation https://www.mdpi.com/2073-4433/11/1/97
https://doaj.org/toc/2073-4433
2073-4433
doi:10.3390/atmos11010097
https://doaj.org/article/c3f784476cfb4d90b8c259ba36dd8ba5
op_doi https://doi.org/10.3390/atmos11010097
container_title Atmosphere
container_volume 11
container_issue 1
container_start_page 97
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