Monday, 28 August 2023
Boundary Waters (Hyatt Regency Minneapolis)
In this study, we aimed to investigate snowfall characteristics and quantify winter precipitation in East China by analyzing data collected from a two-dimensional video disdrometer (2DVD), weighing precipitation gauges, an S-band Doppler weather radar, and a C-band dual-polarization Doppler radar during winter snowfall events in Nanjing from 2015 to 2019. We first examined the statistical characteristics of terminal velocity, density, and particle size distribution (PSD) of snowfall in Nanjing. Our findings revealed that the snow terminal velocity in this area was larger than that estimated using an empirical velocity-diameter relation reported in previous research. We classified two types of snowfall events based on terminal velocity, namely, high terminal velocity and low terminal velocity, which may be attributed to differences in snowflake types. The mean snow density calculated from our observations was greater than the result reported in literature, e.g., Brandes et al. (2007), when D0< 3.2 mm, which may be responsible for higher snowflakes terminal velocity.
Furthermore, based on observations from the dual-polarization radar, we analyzed the internal space vertical structure and growth mechanism of the ice-phase microphysical process of low and high terminal velocity snowfall events in 2016 (E16) and 2018 (E18). In both events, the dendritic-growth-layer (DGL) signature characterized by enhancements in differential reflectivity ZDR and specific differential phase KDP was observed. The KDP in the DGL, related to the total mass of horizontally-oriented ice particles, for snowfall nowcasting. The lagged correlation analysis revealed that the near-surface reflectivity factor (ZH), a proxy for snowfall intensity, could be predicted by KDP in the DGL with a 40-minute lead time and a correlation coefficient over 0.7 in E16. However, E18 had a worse nowcasting performance, with the maximum correlation coefficient being ~0.53, which could be attributed to its more complex ice microphysical structures and processes. Snow growth in E16 mainly occurred from the deposition in the DGL (mainly dendrites and plates) and aggregation below. In comparison, the snowstorm was deeper in E18, and the less oblate crystals (with larger aspect ratios) from above the DGL could grow and mix with the dendrites and plates in the DGL, weakening the correlation between the KDP and ice mass. Below the DGL, snow growth in E18 was contributed by aggregation and more active riming according to both radar and disdrometer observations, which further lowered the nowcasting performance of snowfall by the KDP in the DGL.
Finally, a power-law relationship between reflectivity factor and snowfall rate was derived from the 2DVD observations. The validation of the radar-derived snowfall estimates by weighing precipitation gauges revealed that the average mean absolute error (MAE) among the snowfall events in Nanjing was 16%. The MAE of low terminal velocity snowfall events was 23.3%, and that of high terminal velocity snowfall events was 8.9%.
Furthermore, based on observations from the dual-polarization radar, we analyzed the internal space vertical structure and growth mechanism of the ice-phase microphysical process of low and high terminal velocity snowfall events in 2016 (E16) and 2018 (E18). In both events, the dendritic-growth-layer (DGL) signature characterized by enhancements in differential reflectivity ZDR and specific differential phase KDP was observed. The KDP in the DGL, related to the total mass of horizontally-oriented ice particles, for snowfall nowcasting. The lagged correlation analysis revealed that the near-surface reflectivity factor (ZH), a proxy for snowfall intensity, could be predicted by KDP in the DGL with a 40-minute lead time and a correlation coefficient over 0.7 in E16. However, E18 had a worse nowcasting performance, with the maximum correlation coefficient being ~0.53, which could be attributed to its more complex ice microphysical structures and processes. Snow growth in E16 mainly occurred from the deposition in the DGL (mainly dendrites and plates) and aggregation below. In comparison, the snowstorm was deeper in E18, and the less oblate crystals (with larger aspect ratios) from above the DGL could grow and mix with the dendrites and plates in the DGL, weakening the correlation between the KDP and ice mass. Below the DGL, snow growth in E18 was contributed by aggregation and more active riming according to both radar and disdrometer observations, which further lowered the nowcasting performance of snowfall by the KDP in the DGL.
Finally, a power-law relationship between reflectivity factor and snowfall rate was derived from the 2DVD observations. The validation of the radar-derived snowfall estimates by weighing precipitation gauges revealed that the average mean absolute error (MAE) among the snowfall events in Nanjing was 16%. The MAE of low terminal velocity snowfall events was 23.3%, and that of high terminal velocity snowfall events was 8.9%.

