{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T23:54:45Z","timestamp":1772150085594,"version":"3.50.1"},"reference-count":51,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2021,12,14]],"date-time":"2021-12-14T00:00:00Z","timestamp":1639440000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Hydrometeor classification remains a challenge in winter precipitation cloud systems. To address this issue, 42 snowfall events were investigated based on a multi-platform radar observation system (i.e., X-band dual-polarization radar, Ka-band millimeter wave cloud radar, microwave radiometer, airborne equipment, etc.) in the mountainous region of northern China from 2016 to 2020. A fuzzy logic classification method is proposed to identify the particle phases, and the retrieval result was further verified with ground-based radar observation. Moreover, the hydrometeor characteristics were compared with the numerical simulations to clarify the reliability of the proposed hydrometeor classification approach. The results demonstrate that the X-\/Ka- band radars are capable of identifying hydrometeor phases in winter precipitation in accordance with both ground observations and numerical simulations. Three particle categories, including snow, graupel and the mixture of snow and graupel are also detected in the winter precipitation cloud system, and there are three vertical layers identified from top to bottom, including the ice crystal layer, snow-graupel mixed layer and snowflake layer. Overall, this study has the potential for improving the understanding of microphysical processes such as freezing, deposition and aggregation of ice crystal particles in the winter precipitation cloud system.<\/jats:p>","DOI":"10.3390\/rs13245070","type":"journal-article","created":{"date-parts":[[2021,12,14]],"date-time":"2021-12-14T22:06:10Z","timestamp":1639519570000},"page":"5070","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Hydrometeor Classification of Winter Precipitation in Northern China Based on Multi-Platform Radar Observation System"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6290-5652","authenticated-orcid":false,"given":"Yichen","family":"Chen","sequence":"first","affiliation":[{"name":"Beijing Key Laboratory of Cloud, Precipitation and Atmospheric Water Resources (LCPW), Beijing Meteorological Bureau, Beijing 100089, China"},{"name":"Beijing Weather Modification Center, Beijing 100089, China"},{"name":"Field Experiment Base of Cloud and Precipitation Research in North China, China Meteorological Administration, Beijing 101200, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiang\u2019e","family":"Liu","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Cloud, Precipitation and Atmospheric Water Resources (LCPW), Beijing Meteorological Bureau, Beijing 100089, China"},{"name":"Beijing Weather Modification Center, Beijing 100089, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai","family":"Bi","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Cloud, Precipitation and Atmospheric Water Resources (LCPW), Beijing Meteorological Bureau, Beijing 100089, China"},{"name":"Beijing Weather Modification Center, Beijing 100089, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Delong","family":"Zhao","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Cloud, Precipitation and Atmospheric Water Resources (LCPW), Beijing Meteorological Bureau, Beijing 100089, China"},{"name":"Beijing Weather Modification Center, Beijing 100089, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"844","DOI":"10.1175\/2010JAMC2558.1","article-title":"S-band dual-polarization radar observations of winter storms","volume":"50","author":"Kennedy","year":"2011","journal-title":"J. Appl. Meteor. Climatol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"682","DOI":"10.1175\/JAMC-D-12-028.1","article-title":"Polarimetric signatures above the melting layer in winter storms: An observational and modeling study","volume":"52","author":"Kumjian","year":"2013","journal-title":"J. Appl. Meteor. Climatol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1147","DOI":"10.1175\/JAMC-D-12-055.1","article-title":"Polarimetric radar observations in the ice region of precipitating clouds at C-band and X-band radar frequencies","volume":"52","author":"Bechini","year":"2013","journal-title":"J. Appl. Meteor. Climatol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"828","DOI":"10.1175\/1520-0469(2001)058<0828:PSFICO>2.0.CO;2","article-title":"Polarimetric signatures from ice crystals observed at 95 GHz in winter clouds. Part I: Dependence on crystal form","volume":"58","author":"Wolde","year":"2001","journal-title":"J. Atmos. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/36.285183","article-title":"Polarimetric radar studies of atmospheric ice particles","volume":"32","author":"Vivekanandan","year":"1994","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1175\/1520-0450(1998)037<0125:PMFIWC>2.0.CO;2","article-title":"Polarimetric method for ice water content determination","volume":"37","author":"Ryzhkov","year":"1998","journal-title":"J. Appl. Meteor."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2549","DOI":"10.1175\/JAMC-D-12-0311.1","article-title":"A dual-polarization radar signature of hydrometeor refreezing in winter storms","volume":"52","author":"Kumjian","year":"2013","journal-title":"J. Appl. Meteor. Climatol."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Bringi, V.N., and Chandrasekar, V. (2001). Polarimetric Doppler Weather Radar: Principles and Applications, Cambridge University Press.","DOI":"10.1017\/CBO9780511541094"},{"key":"ref_9","first-page":"516","article-title":"An algorithm to deduce hydrometeor types and contents from multi-parameter radar data. Preprints, 26th Conf. on Radar Meteorology, Norman, OK","volume":"513","author":"Straka","year":"1993","journal-title":"Am. Meteor. Soc."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2500","DOI":"10.1175\/1520-0469(1994)051<2500:LCAPFI>2.0.CO;2","article-title":"Life cycle and precipitation formation in a hybrid-type hailstorm revealed by polarimetric and doppler radar measurements","volume":"51","author":"Holler","year":"1994","journal-title":"J. Atmos. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1175\/1520-0426(2000)017<0140:COHBOP>2.0.CO;2","article-title":"Classification of hydrometeors based on polarimetric Radar measurements: Development of fuzzy logic and neuro-fuzzy systems and in-situ verification","volume":"17","author":"Liu","year":"2000","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1882","DOI":"10.1175\/1520-0493(2001)129<1882:MOTRDO>2.0.CO;2","article-title":"Microphysics of the Rapid Development of Heavy Convective Precipitation","volume":"129","author":"Zeng","year":"2001","journal-title":"Mon. Weather Rev."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1175\/BAMS-86-6-809","article-title":"The Joint Polarization Experiment: Polarimetric rainfall measurements and hydrometeor classification","volume":"86","author":"Ryzhkov","year":"2005","journal-title":"Bull. Am. Meteor. Soc."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1175\/WAF956.1","article-title":"Validation of polarimetric hail detection","volume":"21","author":"Heinselman","year":"2006","journal-title":"Weather Forecast."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"730","DOI":"10.1175\/2008WAF2222205.1","article-title":"The hydrometeor classification algorithm for the polarimetric WSR-88D: Description and application to an MCS","volume":"24","author":"Park","year":"2009","journal-title":"Weather Forecast."},{"key":"ref_16","unstructured":"Apffel, K.R., Reynolds, A., and Zaff, D. (2021, December 04). Improving the Quantitative Precipitation Estimate for Hydrometeors Classified as Dry Snow by Polarimetric Radars. NOAA\/National Weather Service Eastern Regional Tech. Attachment, Available online: https:\/\/www.weather.gov\/media\/erh\/ta2015-06.pdf."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"841","DOI":"10.1175\/JAMC-D-19-0271.1","article-title":"The WSR-88D Inanimate Hydrometeor Class","volume":"59","author":"Kurdzo","year":"2020","journal-title":"J. Appl. Meteor. Climatol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"756","DOI":"10.1175\/WAF-D-10-05011.1","article-title":"The NSSL hydrometeor classification algorithm in winter surface precipitation: Evaluation and future development","volume":"26","author":"Elmore","year":"2011","journal-title":"Weather Forecast."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1457","DOI":"10.1175\/JTECH-D-13-00119.1","article-title":"A dual-polarization radar hydrometeor classification algorithm for winter precipitation","volume":"31","author":"Thompson","year":"2014","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1175\/1520-0450(1997)036<0322:IOHWEA>2.0.CO;2","article-title":"Identification of hydrometeors with elliptical and linear polarization Ka-band radar","volume":"36","author":"Reinking","year":"1997","journal-title":"J. Appl. Meteor."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"L22809","DOI":"10.1029\/2007GL031008","article-title":"A ground-based multiple remote-sensor cloud phase classifier","volume":"34","author":"Shupe","year":"2007","journal-title":"Geophys. Res. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1175\/2007JAMC1701.1","article-title":"Combined observational and model investigations of the Z-LWC 216 relationship in strato-cumulus clouds","volume":"47","author":"Khain","year":"2008","journal-title":"J. Appl. Met. Clim."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"4815","DOI":"10.1029\/2001JD001308","article-title":"On retrieving the microphysical properties of cirrus clouds using the moments of the millimeter-wavelength Doppler spectrum","volume":"107","author":"Mace","year":"2002","journal-title":"J. Geophys. Res."},{"key":"ref_24","first-page":"635","article-title":"The preliminary analyses of the cloud properties over the Tibetan Plateau from the field experiments in clouds precipitation with the vavious radars","volume":"73","author":"Liu","year":"2015","journal-title":"Acta Meteorol. Sin."},{"key":"ref_25","first-page":"134","article-title":"Preliminary analysis on the application of millimeter wave cloud radar on snow observation","volume":"42","author":"Chen","year":"2018","journal-title":"J. Atmos. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"13593","DOI":"10.5194\/acp-21-13593-2021","article-title":"Supercooled liquid water and secondary ice production in Kelvin\u2013Helmholtz instability as revealed by radar Doppler spectra observations","volume":"21","author":"Li","year":"2021","journal-title":"Atmos. Chem. Phys."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"e2020GL087499","DOI":"10.1029\/2020GL087499","article-title":"Two layers of melting ice particles within a single radar bright band: Interpretation and implications","volume":"47","author":"Li","year":"2020","journal-title":"Geophys. Res. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"9547","DOI":"10.5194\/acp-20-9547-2020","article-title":"Towards the connection between snow microphysics and melting layer: Insights from multifrequency and dual-polarization radar observations during BAECC","volume":"20","author":"Li","year":"2020","journal-title":"Atmos. Chem. Phys."},{"key":"ref_29","first-page":"245","article-title":"Analysis of snowfall\u2019s microphysical process from Doppler spectrum using Ka-band millimeter-wave cloud radar","volume":"38","author":"Li","year":"2019","journal-title":"J. Infrared. Millim. Waves"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1727","DOI":"10.1175\/JAS3904.1","article-title":"Modeling backscatter properties of snowfall at millimeter wavelengths","volume":"64","author":"Matrosov","year":"2007","journal-title":"J. Atmos. Sci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"769","DOI":"10.1175\/2007JAMC1768.1","article-title":"Snowfall Retrievals Using Millimeter-Wavelength Cloud Radars","volume":"47","author":"Matrosov","year":"2008","journal-title":"J. Appl. Meteor. Climatol."},{"key":"ref_32","unstructured":"Battan, L.J. (1973). Radar Observations of the Atmosphere, University of Chicago Press."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1510","DOI":"10.1175\/1520-0450(1998)037<1510:ADWRMT>2.0.CO;2","article-title":"A Dual-Wavelength Radar Method to Measure Snowfall Rate","volume":"37","author":"Matrosov","year":"1998","journal-title":"J. Appl. Meteor. Climatol."},{"key":"ref_34","first-page":"23","article-title":"Analysis of hydrometeor distribution characteristics in stratiform clouds using polarization radar","volume":"34","author":"He","year":"2010","journal-title":"J. Atmos. Sci."},{"key":"ref_35","first-page":"171","article-title":"Fuzzy Logic Method in Retrieval Atmospheric Cloud Particle Phases and Effect Analysis","volume":"41","author":"Wang","year":"2015","journal-title":"Meteor. Mon."},{"key":"ref_36","first-page":"226","article-title":"Assessment and Characteristics of MP-3000A Ground-Based Microwave Radiometer","volume":"41","author":"Han","year":"2015","journal-title":"Meteor. Mon."},{"key":"ref_37","first-page":"359","article-title":"Research on application of the mesoscale silver iodide seeding numerical model","volume":"79","author":"Liu","year":"2021","journal-title":"Acta Meteor. Sin."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1401","DOI":"10.1002\/jgrd.50115","article-title":"Evaluation of cloud microphysics schemes in simulations of a winter storm using radar and radiometer measurements","volume":"118","author":"Han","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_39","unstructured":"Takamichi, I., and Toshihisa, M. (2018). Advances in Clouds and Precipitation Modeling Supported by Remote Sensing Measurements. Remote Sensing of Clouds and Precipitation, Springer International Publishing."},{"key":"ref_40","first-page":"22","article-title":"Evaluating Simulated Raindrop Size Distributions and Ice Microphysical Processes with Polarimetric Radar Observations in a Meiyu Front Event Over Eastern China","volume":"126","author":"Gang","year":"2021","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1175\/JHM-D-19-0060.1","article-title":"Impact of Soil Moisture on Winter 2-m Temperature Forecasts in Northern China","volume":"21","author":"Zhong","year":"2020","journal-title":"J. Hydrometeor."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2318","DOI":"10.1175\/MWR3199.1","article-title":"A new vertical diffusion package with an explicit treatment of entrainment processes","volume":"134","author":"Hong","year":"2006","journal-title":"Mon. Weather Rev."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1175\/1520-0493(2001)129<0569:CAALSH>2.0.CO;2","article-title":"Coupling an advanced land surface\u2013hydrology model with the Penn State\u2013NCAR MM5 modeling system. Part I: Model implementation and sensitivity","volume":"129","author":"Chen","year":"2001","journal-title":"Mon. Weather Rev."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"16663","DOI":"10.1029\/97JD00237","article-title":"Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave","volume":"102","author":"Mlawer","year":"1997","journal-title":"J. Geophys. Res."},{"key":"ref_45","first-page":"104606","article-title":"A solar radiation parameterization (CLIRAD-SW) for atmospheric studies","volume":"40","author":"Chou","year":"1999","journal-title":"NASA Tech. Memo."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1665","DOI":"10.1175\/JAS3446.1","article-title":"A new double-moment microphysics parameterization for application in cloud and climate models. Part I: Description","volume":"62","author":"Morrison","year":"2005","journal-title":"J. Atmos. Sci."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"29823002","DOI":"10.1175\/MWR-D-11-00292.1","article-title":"Comparisons of single and double moment microphysics schemes in the simulation of a synoptic-scale snowfall event","volume":"140","author":"Molthan","year":"2012","journal-title":"Mon. Weather Rev."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"4197","DOI":"10.1002\/2017JD027734","article-title":"Sensitivity of a simulated squall line during Southern China Monsoon Rainfall Experiment to parameterization of microphysics","volume":"123","author":"Qian","year":"2018","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"e2019JD032279","DOI":"10.1029\/2019JD032279","article-title":"A modeling study of an atmospheric bore associated with a nocturnal convective system over China","volume":"125","author":"Zhang","year":"2020","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"105206","DOI":"10.1016\/j.atmosres.2020.105206","article-title":"Performance of the WRF Model in Simulating Intense Precipitation Events over the Hanjiang River Basin, China\u2014A Multi-Physics Ensemble Approach","volume":"248","author":"Yang","year":"2020","journal-title":"Atmos. Res."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"100013","DOI":"10.1016\/j.aosl.2020.100013","article-title":"Evaluating the performance of a WRF microphysics ensemble through comparisons with aircraft observations","volume":"14","author":"Yuan","year":"2021","journal-title":"Atmos. Ocean. Sci. Lett."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/24\/5070\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:47:50Z","timestamp":1760168870000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/24\/5070"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,14]]},"references-count":51,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2021,12]]}},"alternative-id":["rs13245070"],"URL":"https:\/\/doi.org\/10.3390\/rs13245070","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,14]]}}}