A contrastive analysis on the causes of two regional snowstorm processes influenced by the southern branch trough in Hunan in early 2022

In early 2022, there were four low‐temperature weather processes with rain and snow in Hunan Province, China. Two processes occurred on January 28–29 (referred to as the “0128” process) and February 6–7 (referred to as the “0206” process), and they have overlapping areas of heavy snowfall and high intensity of short‐term snowfall. Multi‐source observation data and the National Centers for Environmental Prediction (NCEP) reanalysis data are used to analyze the characteristics of circulation background and mesoscale. In addition, the causes of heavy snowfall processes under the influence of the southern branch trough are discussed based on the dual‐polarization radar products at Changsha station. The results show that two processes are characterized by the rapid phase transformation of rain and snow, concentrated snowfall periods, and heavy snowfall at night. The short‐term snowfall intensity of the “0206” process is greater than that of the “0128” process. The high‐latitude blocking high of the “0206” process is stronger than that of the “0128” process, and the water vapor transport of the southerly jet in low levels in the “0206” process is also stronger. The organized development of cold cloud clusters from the meso‐β scale to the meso‐α scale indicates that the snowfall intensifies, and the maximum blackbody temperature gradient corresponds well to the center of heavy snowfall. The propagation that is similar to the train effect is an important reason for the heavy snowfall process. The vertical variation of the ZH and the bright band of dual‐polarization parameters can determine the phase transformation between rain and snow. When the ZH and ZDR bright bands are 1–3 km away from the ground, the phase state is rain if the ZH near the ground is greater than 0 dBZ and the CC is close to 1; the phase state is the rain‐snow mixed phase if the CC is less than 0.95. When the bottom of the ZH bright band decreases, the CC/ZDR bright band disappears, the near‐surface CC is greater than 0.99 and the ZDR is less than 1 dB, the rain turns to snow. Compared with the “0128” process, the characteristics of the bright ring during the rainfall period of the “0206” process are more obvious, the precipitation intensity judged from the larger ZH and KDP is larger, and the phase transformation is faster due to more significant cooling effect caused by precipitation.

bright ring during the rainfall period of the "0206" process are more obvious, the precipitation intensity judged from the larger Z H and K DP is larger, and the phase transformation is faster due to more significant cooling effect caused by precipitation.

K E Y W O R D S
cause analysis, cold cloud evolution, polarization radar product features, snowstorm process

| INTRODUCTION
Snowstorms are one of the most important disaster weather phenomena in winter.In recent years, scholars at home and abroad have explored the causes of heavy snowfall weather from the aspects of circulation characteristics and atmospheric rivers, and they have made meaningful progress (Eldardiry et al., 2019;Goldenson et al., 2018;Porhemmat et al., 2020;Suriano et al., 2019;Varcie et al., 2022).Studies on several heavy snowfall events have shown that the snowstorm processes in eastcentral and southwestern China are often affected by the stable southern branch trough (SBT).For example, researchers analyzed the large-scale circulations of the historically rare low-temperature weather process with rain and snow in southern China in 2008, and they found that the strong Western Pacific subtropical high and the active SBT are the main causes of its persistence for up to 20 days (Wang et al., 2009;Yao et al., 2012;Zhou et al., 2008).From the extreme snowstorm in Hunan at the end of 2018, it was found that the abnormally stronger SBT compared with the same period of previous years was the most critical circulation background of heavy snowfall (Liu et al., 2020).
Since the evolution of cold cloud clusters during the snowfall process can better reflect the generation and development of mesoscale systems, scholars have carried out relevant exploration (Cao et al., 2011;Luobu et al., 2016;Ma et al., 2017;Shi, 2017;Wu et al., 2014;Yao et al., 2018a;Zhou et al., 2013).The results indicated that the evolution of the equivalent blackbody temperature (TBB) intensity is a good indicator for the forecast of the start time of heavy snowfall, and the center of heavy snowfall is consistent with the large-value area of the TBB of cold cloud clusters.Studies showed that for the extreme snowstorm process caused by a Jianghuai cyclone, heavy snowfall occurred in the enhancement stage of the TBB of comma-shaped cloud cluster, and the low-value center of the TBB coincided with the center of the snowstorm during the strongest snowfall period (Zhao et al., 2018).Each eastward movement of mesoscale cold clouds on shear lines and frontal zones corresponds to an intensification of snowfall, which directly leads to heavy snowfall (Gu & Wu, 2015;Liu et al., 2018).
Due to the high spatio-temporal resolutions of Doppler radars, they can provide more abundant atmospheric information and effectively detect the evolution of precipitation systems in combination with satellite cloud images, mostly applied in the forecast and early warning of various disastrous weather (Nan et al., 2018).However, scholars mainly carry out studies on quantitative snowfall estimation, and there are fewer studies on the phase transformation of rain and snow (Matrosov et al., 2009;Nakai et al., 2022;Tao et al., 2020;Yu et al., 2020).In recent years, Doppler radars have been gradually upgraded in China.Previous studies suggested that polarization radars show noticeable advantages in judging phase transformation (Bringi & Chandrasekar, 2005;Zheng et al., 2014) due to the obvious differences in the features (such as shape and size) of precipitation particles in different phases.Through the combined analysis of radar products such as correlation coefficient (CC) and differential reflectivity (Z DR ), it can also obtain information on the melting layer height (Shusse et al., 2019;Wu et al., 2018;Yang et al., 2019), and it can be found that the marked difference between the CC and specific differential phase (K DP ) indexes in rainfall and snowfall stages can not only effectively judge the phase transformation of rain and snow, but also identify the falling time of ice crystals or snow particles in advance.In addition, the precipitation particle classification product (HCL) also serves better for identifying the phase of precipitation particles (Li et al., 2018;Thériault et al., 2010;Yang et al., 2019;Yao et al., 2018b;Zheng et al., 2022).
Hunan Province is located in the south of the Yangtze River Basin in China, with mountainous and hilly landform (Figure 1).In early 2022, four low-temperature weather processes with rain and snow occurred in Hunan Province.From January 23 to February 22, the cumulative number of rain and snow days reached 23.2 days, which was 9.47 days more than the average value from 1961 to 2021 and set a historical record in the same period since 1961.Among them, two regional snowstorm weather processes occurred in north-central Hunan on January 28-29 (hereinafter referred to as the "0128" process) and February 6-7 (hereinafter referred to as the "0206" process), which are characterized by a short time interval between the processes, wide snowfall coverages and the overlapped areas with the heavy snowfall intensity and above, causing snow disasters in many cities (counties and districts).During the two snowstorm processes, the agricultural economic crops were seriously affected, and the direct economic losses caused by the "0206" process were more than 131 million Yuan.The two processes occurred under the influence of the SBT.In this study, the characteristics of meso-scale are discussed, and the analysis of applying dual-polarization radar products at Changsha station to research rainy and snowy weather is carried out to refine the technical indicators.This study aims to enhance the short-term and short-range forecast skills of the SBT snowstorms.

| DATA
Four types of data are selected in this research, namely the hourly rainfall observations from regional automatic meteorological stations and artificial intensified hourly observation data from 97 national standard meteorological stations in Hunan Province, the 6-hour National Centers for Environmental Prediction (NCEP) reanalysis data, and the dual-polarization weather radar products at Changsha station.The precipitation of the weather processes includes rainfall and snowfall, and the phase distribution is analyzed based on manual observation records.The area for calculating physical quantities is the range of 26.5 N-30 N, 108 E-114 E.  January 28-29, 2022 and (b) on February 6-8, 2022.The red contours represent the climate mean.The 500 hPa geopotential height and 850 hPa wind arrow (c) at 12:00 UTC on January 28 and (d) at 12:00 UTC on February 6.

| SNOWFALL WEATHER OVERVIEWS AND ATMOSPHERIC CIRCULATION BACKGROUND DURING THE TWO WEATHER PROCESSES
On January 28-29, 2022, a total of 63 counties and cities in north-central Hunan experienced sleet or snowfall.The maximum precipitation was 19.8 mm (Ningxiang station).At 06:00 on January 29, the snowfall range narrowed, and the weather process tended to end (Figure 2a).On February 6-7, a total of 57 counties and cities in the north-central regions of Hunan experienced sleet or snowfall.There were 24 stations monitoring snowstorms and one station monitoring heavy snowstorms, the maximum daily precipitation was 30.5 mm (Changsha station), and the maximum snow depth was 20 cm (Taojiang station) (Figure 2b).
In both processes, heavy snowfall was observed at Changsha station (Figure 3).The comparison suggests that at this station, the phase transformation of rain and snow is rapid, snowfall periods were concentrated, and the diurnal variations were noticeable with increased snowfall at night.The maximum 3-hour snowfall of the "0206" process was 13.8 mm (18:00-21:00 UTC on February 6).
The two snowstorm processes in early 2022 both occurred in the large-scale background with the eastward-moving SBT.From the 500 hPa average circulation field and circulation anomalies (Figure 4a, b), it can be found that the geopotential height anomalies in the Eurasian region always showed a "positive-negative" distribution from high latitudes to mid-low latitudes, indicating that the blocking high was stronger than the annual average value from 1961 to 2021.There were negative anomalies in the Yangtze River Basin and its south, and Hunan is in front of the SBT.These two strong largescale systems (blocking high and SBT) form a strong pressure gradient from north to south, which causes the high-level northwesterly airflow to maintain over Hunan for a long time.This is also a favorable circulation background for the occurrence of heavy snowfall.The comparison of 500 hPa circulation at the beginning of the strongest snowfall between the two processes shows that the 500 hPa blocking high was located east of the Balkhash Lake at 12:00 UTC on February 28 (Figure 4c).At 12:00 UTC on February 6, the blocking high controlling area was wider, extending from Balkhash Lake to Baikal Lake.The blocking high intensity of the "0206" process was 548 dagpm (Figure 4d), which was significantly stronger than that of the "0128" process.
Combined with the temporal evolution of the 850 hPa radial wind along 113 E (Figure 5), it can be found that before the snowfall of the "0128" process, there was an 8 m s À1 southerly wind center in South China, and the southerly airflow controlled most of Hunan Province.At 08:00 UTC on January 27, as the southerly wind area moved southward, the low-level shear line moved southward to central Hunan, providing dynamic conditions for snowfall.In terms of the "0206" process, At 12:00 UTC on February 6, the wind speed of the southerly jet core in South China was more than 14 m s À1 , the large-value area of the wind speed of southerly wind expanded northward to 35 N. From 12:00 UTC on February 6 to 12:00 UTC on February 7, the southerly wind in Hunan rapidly weakened, and the northerly airflow invaded Hunan.After 12:00 UTC on February 7, the whole Hunan region was controlled by the northerly wind.

| Cold cloud evolution
The two snowstorm processes occurred under the influence of the SBT, and the strongest snowfall areas were located in central-eastern Hunan.The response characteristics of the TBB field to the snowstorm area are obtained by analyzing the generation, development, and evolution of mesoscale cold cloud clusters.In this study, the scale-division standard of Orlanski (1975) is adopted.That is, the horizontal scale of 2-20 km is the meso-γ scale, 20-200 km is the meso-β scale, and 200-2000 km is the meso-α scale.
In the "0128" process, there were several scattered meso-β-scale cold clouds with the TBB ≤ À 20 C in north-central Hunan at 15:00 UTC on January 28, with the largest cold cloud cluster (diameter of about 120 km) in western Hunan (Figure 6a).At 18:00 UTC on January 28, the mid-level jet stream strengthened, the low-level shear line moved into Hunan, and the scattered cloud clusters began to merge in an organized manner.The cold clouds at the strongest convergence on the eastern section of the shear line expanded in size and developed into the meso-α-scale cold cloud cluster, with a length of about 380 km, a width of about 220 km, and TBB values of ≤À28 C (Figure 6b).At 23:00 UTC, the shear line moved eastward and lifted northward.The meso-α-scale cold cloud cluster with a TBB of ≤À28 C covered most of north-central Hunan, with a tight structure and a clear boundary.The maximum TBB gradient was in the area from western Changsha to Ningxiang (Figure 6c).It can be seen that the mesoscale cold cloud cluster with the TBB of ≤À28 C on the left side of the jet axis and on the shear line passed through the snowstorm area for six consecutive periods, and the propagation similar to the train effect was an important reason for the heavy snowfall processes.The period of the organized formation of the meso-α-scale cold cloud cluster from the meso-β scale was consistent with the period of the intensification of snowfall.
In the "0206" process, at 12:00 UTC on February 6, there were several isolated mesoscale cold clouds with TBB of ≤À32 C in the north of Hunan.A nearly northsouth low-trough cloud band moved closer to Hunan, which had a meso-β-scale development with TBB of ≤À36 C at 100 km in the movement direction of the low trough in west-central Hunan (Figure 6d).At 16:00 UTC on February 6, as the low trough moved into Hunan, the warm and humid airflow in the front of the trough converged with cold air, and four parallel-aligned mesoα-scale cold cloud clusters, with a length of about 500-600 km, a width of about 200-300 km and the TBB of ≤À40 C, appeared in the Yangtze River Basin and the regions south of it (Figure 6e), which have obviously enhanced convective characteristics.At 19:00 UTC on February 6 (Figure 6f), the cold advection at the rear of the trough strengthened the low trough.The combination and partial superposition of the B-shaped and C-shaped cloud bands organically formed a broad lowtrough cloud system with a length of about 1200 km and a width of about 400 km.In this broad low-trough cloud system, several meso-β-scale cloud clusters with TBB of <À48 C were embedded, showing a wedge-shaped northeast-southwest distribution.The merged cloud system had a tight structure and a clear boundary, the TBB gradient increased, and the maximum gradient of the contour lines at the edge of the cold cloud system with the TBB of ≤ À 50 C corresponds to the snowstorm area in eastern Hunan.Afterward, the cloud system moved out of Hunan, and the snowfall stopped.

| Dual-polarization radar characteristics of the snowfall processes
Studies have shown that dual-polarization radars can be used to determine the properties of precipitation particles in the atmosphere and classify the observations of precipitation particles in real-time (Ji et al., 2022;Li et al., 2018;Thériault et al., 2010;Wei et al., 2019;Yang et al., 2019;Yong & Wei, 2019).Its wide observation range, high spatio-temporal resolutions, and high timeliness can provide the relevant information of particles for forecasts, which is helpful for determining the type and intensity of rainfall and snowfall.The two weather processes with the phase transformation of rain and snow occurred at night, which led to the observation of the rain-snow phase transformation more difficult.In this study, we use the basic products from the Changsha dual-polarization radar to analyze the melting layer height, the phase transformation of precipitation particles, and the snowfall intensity, and aim to improve the monitoring and early warning ability of snowfall weather processes.
The bright band characteristics (large-value area) of horizontal reflectivity (Z H ) in the "0128" process are not prominent, and therefore the melting layer cannot be judged by analyzing the Z H alone.Dual-polarization products at a 2.4 elevation angle at 12:00 UTC on January 28 are shown in Figure 7.The Z H values vary from 30 to 50 dBZ (Figure 7a) and the Z DR is 1-3 dB (Figure 7b), slightly larger than that on both sides, at 40-50 km from the radar center.Figure 7c indicates that the CC in the above area is 0.85-0.95,lower than that on both sides, with relatively obvious bright ring characteristics in polarization.K DP is 0.1 -0.5 km À1 , without obvious bright band characteristics.
Figure 8 shows the radar product profiles along 260 azimuth from the area about 130 km away from the radar to the radar center.The results indicate that the Z H intensity is larger (exceeding 30 dBZ) at 2-3 km at 12:00 UTC, presenting vertical bright band characteristics (Figure 8a).The CC corresponding to the Z H bright band shows a low-value band of 0.85-0.95,and the Z DR has a relatively high-value band of 1-2.5 dB.As snowflakes further melt and break up, the decrease in particle size leads to lower Z H and Z DR .The melted particles are dominated by rain particles, so the CC increases to 0.99-1 in Changsha (Figure 8d, g).At 17:00 UTC, the particles increase as the echo moving eastward, the bright band characteristics of the Z H profile are more pronounced at 1.5-2.5 km (Figure 8b, e, h), and the bottom of the bright band descends.At this time, due to the increase in the number of particles, the ice particles are more likely to collide and merge during the melting process.Thus, the particles have a larger size and flat shape, resulting in an increase of Z DR and a more obvious Z DR bright band (≥1 dB).Due to the descent of the melting-layer bottom, the particles are not completely melted when fall to the ground.The particles are in a mixed phase of rain and snow, and the CC is 0.85-0.95.Afterward, ice crystals and snowflakes continue to pass through the melting layer, and their sinking and melting have a certain effect on the decrease of the temperature in different layers and near-surface temperature (Liu et al., 2021).Meanwhile, the melting layer height decreases further, and the whole-layer temperature is close to or less than 0 C. At 21:00 UTC, the range with the Z H ≥ 30 dBZ extends to the ground.Because the particles melt less in the falling process, the CC in the corresponding area near the radar center is greater than 0.99, and the Z DR from the surface to 3 km is less than 1 dB (Figure 8c, f, i).It can be concluded that the precipitation particles are dominated by snow particles at this time.The result indicates that the phase transformation of precipitation particles judged by the dual-polarization radar products is basically consistent with the actual situation.The change in the melting layer height indicates the change in temperature profile.When the echoes with ZH ≥ 30 dBZ extend to the near ground, the bright band characteristics of the dual-polarization parameters disappear, which means that the temperature of the whole layer drops to 0 C, and the precipitation phase transits to snow.
The radar echo characteristics of melting layer height obtained from the dual-polarization product and rainsnow phase transformation in the "0206" process differ from those in the "0128" process.Dual-polarization products at the 2.4 elevation angle at 17:00 UTC on February 6 are shown in Figure 8.There is a clear semiring-shaped bright band of the Z H (Figure 9a), and there are obvious bright rings of the CC and Z DR at the corresponding positions 40-50 km away from the radar center.The inner refers to the side close to the radar, and the outer refers to the side away from the radar.Compared with the "0128" process, the inner side of the bright ring of the CC (Figure 9b) and Z DR (Figure 9c) in the "0206" process is closer to the radar center, but the outer position of the bright ring is in a similar position.Therefore, compared with the "0128" process, the melting layer of the "0206" process is thicker, and its bottom is lower.These results are consistent with the temperature stratification distribution of the Changsha sounding data.The maximum value of Z H of the "0206" process is substantially higher than that of the "0128" process.At 20:00 UTC, due to the strengthening of the southerly jet, the center intensity of the Z H is more than 50 dBZ, and the K DP values are also greater than that of the "0128" process, with a center value of 0.5 -1.1 km À1 (Figure 9d).In addition, the atmospheric water vapor increases, and the 0 C level height decreases obviously.In this case, the higher Z H and the larger K DP imply that the cooling effect caused by the falling and drag effect of a large amount of precipitation particles is more pronounced, and the phase transformation of rain and snow is more rapid.

| CONCLUSIONS
Based on the multi-source observation data and the NCEP reanalysis data in Hunan in 2022, this paper statistically analyzes the characteristics of mesoscale and dualpolarization radar products in two regional snowstorm processes.The main conclusions of this study are as follows.
The persistent influence of mesoscale cloud clusters with the "train effect" was an important cause of the two snowstorm processes.In the strongest snowfall stage of the two processes, the meso-β scale cold clouds developed into meso-α scale clouds, the cold cloud area expanded and the TBB continuously decreased (such as the decrease of TBB from À20 C to À28 C at 23:00 UTC on January 28 and the decrease in TBB from À40 C to À50 C at 19:00 UTC on February 6), which indicates the strengthening of snowfall.The maximum gradient of TBB corresponds well to the central area of heavy snowfall.
F I G U R E 9 Same as Figure 7, but for 17:00 UTC on February 6, 2022.
Analyzing the dual-polarization radar products, such as the CC and the Z DR , we find that when the Z H bright band characteristics are not obvious, the CC has a low-value band of 0.85-0.95,and the Z DR has a high-value band of 1-3 dB, showing bright ring characteristics that can be used as the basis for identifying the melting layer.The vertical thickness variation of the bright ring can determine the thickness of the melting layer.The three conditions, namely the decrease in the melting layer height, the near-surface CC greater than 0.99, and the Z DR less than 1 dB can identify the phase transformation of rain to snow.Compared with the "0128" process, the characteristics of the bright ring during the rainfall period of the "0206" process were more obvious, the vertical thickness of the bright ring was larger, the melting layer height was thicker, the precipitation intensity judged from the larger Z H and K DP was larger, and the phase transformation of rain and snow was faster due to more obvious cooling effect.

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I G U R E 3 Time series (mm) of the 3-hour accumulated rainfall and snowfall at Changsha station in both weather processes (a) from 12:00 UTC on January 28 to 06:00 UTC on January 29, 2022, and (b) from 09:00 UTC on February 6 to 06:00 UTC on February 7, 2022.F I G U R E 4 The average (black contours; dagpm) and anomaly fields (colored area; dagpm) of the 500 hPa geopotential height (a) on

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I G U R E 5 The profile of the 850 hPa radial wind along 113 E. The black box denotes the north-south boundary of Hunan Province.

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I G U R E 7 (a) Horizontal reflectivity (Z H ), (b) differential reflectivity (Z DR ), and (c) zero-lag correlation coefficient (CC) from Changsha radar at the 2.4 elevation angle at 12:00 UTC on January 28, 2022.