Supercooled Liquid Water Detection Capabilities from Ka-Band Doppler Profiling Radars: Moment-Based Algorithm Formulation and Assessment
The occurrence of supercooled liquid water in mixed-phase cloud (MPC) affects their cloud microphysical and radiative properties. The prevalence of MPCs in the mid- and high latitudes translates these effects to significant contributions to Earth’s radiative balance and hydrological cycle. The curre...
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Online Access: | http://hdl.handle.net/11583/2915934 https://doi.org/10.3390/rs13152891 |
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ftpoltorinoiris:oai:iris.polito.it:11583/2915934 2024-04-14T08:08:26+00:00 Supercooled Liquid Water Detection Capabilities from Ka-Band Doppler Profiling Radars: Moment-Based Algorithm Formulation and Assessment Petros Kalogeras Alessandro Battaglia Pavlos Kollias Kalogeras, Petro Battaglia, Alessandro Kollias, Pavlos 2021 http://hdl.handle.net/11583/2915934 https://doi.org/10.3390/rs13152891 eng eng MDPI info:eu-repo/semantics/altIdentifier/wos/WOS:000682202900001 volume:13 issue:15 firstpage:2891 numberofpages:23 journal:REMOTE SENSING http://hdl.handle.net/11583/2915934 doi:10.3390/rs13152891 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85111584943 info:eu-repo/semantics/openAccess info:eu-repo/semantics/article 2021 ftpoltorinoiris https://doi.org/10.3390/rs13152891 2024-03-21T16:38:59Z The occurrence of supercooled liquid water in mixed-phase cloud (MPC) affects their cloud microphysical and radiative properties. The prevalence of MPCs in the mid- and high latitudes translates these effects to significant contributions to Earth’s radiative balance and hydrological cycle. The current study develops and assesses a radar-only, moment-based phase partition technique for the demarcation of supercooled liquid water volumes in arctic, MPC conditions. The study utilizes observations from the Ka band profiling radar, the collocated high spectral resolution lidar, and ambient temperature profiles from radio sounding deployments following a statistical analysis of 5.5 years of data (January 2014–May 2019) from the Atmospheric Radiation Measurement observatory at the North Slope of Alaska. The ice/liquid phase partition occurs via a per-pixel, neighborhood-dependent algorithm based on the premise that the partitioning can be deduced by examining the mean values of locally sampled probability distributions of radar-based observables and then compare those against the means of climatologically derived, per-phase probability distributions. Analyzed radar observables include linear depolarization ratio (LDR), spectral width, and vertical gradients of reflectivity factor and radial velocity corrected for vertical air motion. Results highlight that the optimal supercooled liquid water detection skill levels are realized for the radar variable combination of spectral width and reflectivity vertical gradient, suggesting that radar-based polarimetry, in the absence of full LDR spectra, is not as critical as Doppler capabilities. The cloud phase masking technique is proven particularly reliable when applied to cloud tops with an Equitable Threat Score (ETS) of 65%; the detection of embedded supercooled layers remains much more uncertain (ETS = 27%). Article in Journal/Newspaper Arctic north slope Alaska PORTO@iris (Publications Open Repository TOrino - Politecnico di Torino) Arctic Remote Sensing 13 15 2891 |
institution |
Open Polar |
collection |
PORTO@iris (Publications Open Repository TOrino - Politecnico di Torino) |
op_collection_id |
ftpoltorinoiris |
language |
English |
description |
The occurrence of supercooled liquid water in mixed-phase cloud (MPC) affects their cloud microphysical and radiative properties. The prevalence of MPCs in the mid- and high latitudes translates these effects to significant contributions to Earth’s radiative balance and hydrological cycle. The current study develops and assesses a radar-only, moment-based phase partition technique for the demarcation of supercooled liquid water volumes in arctic, MPC conditions. The study utilizes observations from the Ka band profiling radar, the collocated high spectral resolution lidar, and ambient temperature profiles from radio sounding deployments following a statistical analysis of 5.5 years of data (January 2014–May 2019) from the Atmospheric Radiation Measurement observatory at the North Slope of Alaska. The ice/liquid phase partition occurs via a per-pixel, neighborhood-dependent algorithm based on the premise that the partitioning can be deduced by examining the mean values of locally sampled probability distributions of radar-based observables and then compare those against the means of climatologically derived, per-phase probability distributions. Analyzed radar observables include linear depolarization ratio (LDR), spectral width, and vertical gradients of reflectivity factor and radial velocity corrected for vertical air motion. Results highlight that the optimal supercooled liquid water detection skill levels are realized for the radar variable combination of spectral width and reflectivity vertical gradient, suggesting that radar-based polarimetry, in the absence of full LDR spectra, is not as critical as Doppler capabilities. The cloud phase masking technique is proven particularly reliable when applied to cloud tops with an Equitable Threat Score (ETS) of 65%; the detection of embedded supercooled layers remains much more uncertain (ETS = 27%). |
author2 |
Kalogeras, Petro Battaglia, Alessandro Kollias, Pavlos |
format |
Article in Journal/Newspaper |
author |
Petros Kalogeras Alessandro Battaglia Pavlos Kollias |
spellingShingle |
Petros Kalogeras Alessandro Battaglia Pavlos Kollias Supercooled Liquid Water Detection Capabilities from Ka-Band Doppler Profiling Radars: Moment-Based Algorithm Formulation and Assessment |
author_facet |
Petros Kalogeras Alessandro Battaglia Pavlos Kollias |
author_sort |
Petros Kalogeras |
title |
Supercooled Liquid Water Detection Capabilities from Ka-Band Doppler Profiling Radars: Moment-Based Algorithm Formulation and Assessment |
title_short |
Supercooled Liquid Water Detection Capabilities from Ka-Band Doppler Profiling Radars: Moment-Based Algorithm Formulation and Assessment |
title_full |
Supercooled Liquid Water Detection Capabilities from Ka-Band Doppler Profiling Radars: Moment-Based Algorithm Formulation and Assessment |
title_fullStr |
Supercooled Liquid Water Detection Capabilities from Ka-Band Doppler Profiling Radars: Moment-Based Algorithm Formulation and Assessment |
title_full_unstemmed |
Supercooled Liquid Water Detection Capabilities from Ka-Band Doppler Profiling Radars: Moment-Based Algorithm Formulation and Assessment |
title_sort |
supercooled liquid water detection capabilities from ka-band doppler profiling radars: moment-based algorithm formulation and assessment |
publisher |
MDPI |
publishDate |
2021 |
url |
http://hdl.handle.net/11583/2915934 https://doi.org/10.3390/rs13152891 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic north slope Alaska |
genre_facet |
Arctic north slope Alaska |
op_relation |
info:eu-repo/semantics/altIdentifier/wos/WOS:000682202900001 volume:13 issue:15 firstpage:2891 numberofpages:23 journal:REMOTE SENSING http://hdl.handle.net/11583/2915934 doi:10.3390/rs13152891 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85111584943 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.3390/rs13152891 |
container_title |
Remote Sensing |
container_volume |
13 |
container_issue |
15 |
container_start_page |
2891 |
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1796305869283000320 |