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...

Full description

Bibliographic Details
Published in:Remote Sensing
Main Authors: Petros Kalogeras, Alessandro Battaglia, Pavlos Kollias
Other Authors: Kalogeras, Petro, Battaglia, Alessandro, Kollias, Pavlos
Format: Article in Journal/Newspaper
Language:English
Published: MDPI 2021
Subjects:
Online Access:http://hdl.handle.net/11583/2915934
https://doi.org/10.3390/rs13152891
id ftpoltorinoiris:oai:iris.polito.it:11583/2915934
record_format openpolar
spelling 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
_version_ 1796305869283000320