Abstract
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.
Highlights
The identification of hydrometeor particles in winter precipitation is critical for understanding microphysical processes in the cloud-precipitation system
Data inofthe vertical was interpolated to be the observed, and the spatial resolution datadirection in the vertical direction was intersame as millimeter wave cloud radar (MMCR), after which the data were unified to match the temporal resolution polated to be the same as MMCR, after which the XPOL data were unified to match the of MMCR.resolution of MMCR
The hydrometeor characteristics of winter precipitation in northern were investigated in 42 snowfall cases from 2016 to 2020, based on the multi-platform
Summary
The identification of hydrometeor particles in winter precipitation is critical for understanding microphysical processes in the cloud-precipitation system. For larger cloud particles, a dual-polarization radar, especially X-band ( XPOL), provides better detection in particle shape and spatial orientation as radar signals are dominated by the largest particles in the sampling volume To this end, relevant information about the distribution of sizes, orientations, shapes, and diversity of hydrometeors within a particular radar sample volume can be derived from differential reflectivity (ZDR ), correlation coefficient (ρ HV ), and the specific differential phase (K DP ) [8,9]. Since it is difficult to classify and verify the phases of various hydrometeor particles in winter precipitation cloud, especially on the radar beam level [18,19], a jointly multiplatform radar observation network, including ground-based equipment (e.g., XPOL, MMCR, microwave radiometer, etc.) and airborne sensors, was designed in this study. The vertical in situ measurement was performed with the Kingair aircraft across the observation range of MMCR, which helps obtain the hydrometeor particle images and meteorological elements within the ground radar’s observation range
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