Method for judging freezing rain and snowfall in winter

Abstract

The invention discloses a method for judging freezing rain and snowfall in winter, and relates to the technical field of meteorology. The method comprises the following steps: acquiring research samples of observation data of a ground automatic weather station, a sounding radar and a wind profile radar in winter, preprocessing the observation data of the ground automatic weather station, the sounding radar and the wind profile radar, and extracting physical quantity parameters; statistical analysis is carried out on the ground air temperature of 2 meters, the air temperature of 700 hundred Pa, the air temperature of 500 hundred Pa, the potential thickness between 500 hundred Pa and 700 hundred Pa, the height of a 0-degree layer, the cloud top temperature, and the vertical speed, the horizontal wind speed and the horizontal wind direction distribution characteristics at five heights (150 meters, 390 meters, 750 meters, 1350 meters and 2430 meters), the temperature of a specific layer is combined with the vertical speed of rainfall particles, and the optimal freezing rain and snowfall judgment indexes are established. And the capability of discriminating freezing rain and snowfall can be improved.

Description

Technical Field

[0001] This invention relates to the field of meteorological technology, specifically to a method for identifying freezing rain and snowfall in winter. Background Technology

[0002] In winter, Guizhou often experiences precipitation, freezing rain, and snow. Mixed precipitation in winter is a challenge for weather forecasting, and the combination of freezing rain and snow can easily lead to freezing weather, which has a significant impact on transportation, agricultural production, communication facilities, power transmission, energy supply, and people's lives.

[0003] Numerous scholars have utilized ground-based, radiosonde, and reanalysis data to study precipitation phases such as rainfall, freezing rain, and snow, primarily focusing on single precipitation phases or multi-phase precipitation identification indicators (rainfall-sleet-snowfall). For example, Jing Hao et al., in their study of winter precipitation phases in Beijing and surrounding areas, used cloud top temperature and the height of the 0°C layer as key factors for phase discrimination. Their results showed that a cloud top temperature ≤ -14°C is a crucial threshold for determining the presence of sufficient iso-ice phase particles (snowflakes) within the cloud, a necessary condition for snowfall. Sleet or rainfall is more likely to occur when cloud top temperatures are between -14°C and -4°C. Wind profiler radar can detect the terminal velocity of precipitation particles and the vertical velocity of airflow. Kong Zhaolin et al. used wind profiler radar to define the terminal velocities of rainfall and snowfall particles, but this was not reflected in the multi-phase precipitation discrimination indicators for winter. Wu Guhui et al.'s analysis of the low-temperature rain and snow weather in Guizhou in 2011 concluded that cloud top temperature is closely related to precipitation phase, and that snowfall requires low cloud top temperatures. However, they did not clearly define the corresponding indicators of cloud top temperature for freezing rain and snowfall in Guizhou. Furthermore, due to the highly complex vertical distribution of temperature and humidity in the atmosphere, and the influence of different precipitation phases on the underlying surface such as topography, current technologies still suffer from low accuracy in distinguishing between freezing rain and snowfall.

[0004] Therefore, this invention proposes a method for identifying freezing rain and snowfall in winter, thereby improving the accuracy of identifying freezing rain and snowfall in Guizhou. Summary of the Invention

[0005] (a) Technical problems to be solved

[0006] To address the shortcomings of existing technologies, this invention acquires research samples of observation data from winter automatic weather stations, radiosondes, and wind profiler radar. It preprocesses these data and extracts physical parameters. Statistical analysis is then conducted on the distribution characteristics of ground-based air temperature at 2 meters, 700 hPa, 500 hPa, geopotential thickness between 500 hPa and 700 hPa, 0-degree layer height, cloud top temperature, and vertical velocity, horizontal wind speed, and horizontal wind direction at five altitudes (150 meters, 390 meters, 750 meters, 1350 meters, and 2430 meters). By combining specific layer temperatures with the vertical velocity of precipitation particles, an optimal discrimination index for freezing rain and snowfall is established, thereby improving the ability to distinguish between freezing rain and snowfall.

[0007] (II) Technical Solution

[0008] To achieve the above objectives, the present invention provides the following technical solution: a method for identifying freezing rain and snowfall in winter, comprising the following steps:

[0009] S1: Acquire ground-based automatic weather station observation data, radiosonde observation data, and wind profiler radar observation data for the target area during winter to form a research sample set;

[0010] S2: Preprocess the various types of observation data in the research sample set and extract the physical quantity parameters used for discrimination;

[0011] S3: Based on the extracted physical quantity parameters, statistically analyze the distribution characteristics of each physical quantity parameter under freezing rain and snowfall events respectively;

[0012] S4: Based on the distribution characteristics and combined with the geographical and climatic characteristics of the target area, establish a discrimination index for freezing rain and snowfall;

[0013] S5: For the weather process to be identified, acquire the corresponding real-time observation data, extract the physical quantity parameters on which the identification index is based, and output the identification result of freezing rain or snowfall according to the identification index.

[0014] Preferably, in step S2, the physical quantity parameters extracted from the observation data of the ground automatic weather station are the air temperature at 2 meters above the ground. The physical quantity parameters extracted from the radiosonde observation data include: specific layer temperatures at 700 hPa and 500 hPa, geopotential heights at 700 hPa and 500 hPa, 0-degree layer height, and cloud top temperature. The physical quantity parameters extracted from the wind profiler radar observation data include at least five vertical velocity, horizontal wind speed, and horizontal wind direction parameters at different altitudes.

[0015] Preferably, the 0-degree layer height is the difference between the geopotential height of the lowest 0-degree layer at the sounding detection altitude and the altitude.

[0016] Preferably, the cloud top temperature is calculated as follows: the temperature and dew point temperature are extracted from the sounding research sample, and the temperature whose difference between the two is less than 3°C is taken as the cloud top temperature.

[0017] Preferably, the distribution characteristics statistically analyzed in step S3 include: the distribution characteristics of ground temperature at 2 meters above ground level during freezing rain and snowfall, the distribution characteristics of geopotential thickness between 500 hPa and 700 hPa during freezing rain and snowfall, the distribution characteristics of the 0-degree layer height during freezing rain and snowfall, the distribution characteristics of cloud top temperature during freezing rain and snowfall, and the distribution characteristics of vertical velocity, horizontal wind speed, and horizontal wind direction during freezing rain and snowfall at at least 5 different altitudes.

[0018] Preferably, the height in the physical quantity parameters and distribution characteristics is set to 5, and is set to 150 meters, 390 meters, 750 meters, 1350 meters and 2430 meters respectively.

[0019] Preferably, in step S4, when the target area is the entire province, the discrimination index for freezing rain and snowfall is:

[0020] When the air temperature at 2 meters above the ground is less than or equal to 0°C, the cloud top temperature is greater than or equal to -9°C, and the vertical velocity at 1350 meters is less than or equal to 0.6 m / s, it is judged as freezing rain;

[0021] Snowfall is defined as the temperature at 2 meters above the ground being less than 1°C, the temperature at the cloud top being less than or equal to -12°C, and the vertical velocity at 1350 meters being greater than 0.6 m / s.

[0022] Preferably, in step S4, when the target area is central Guizhou, the criteria for distinguishing between freezing rain and snowfall are:

[0023] Freezing rain is defined as the temperature at 2 meters above the ground being less than or equal to 0°C, the temperature at 700 hPa being greater than -3°C, and the geopotential thickness between 500 hPa and 700 hPa being greater than or equal to 263 dagpm.

[0024] (III) Beneficial Effects

[0025] Compared with existing technologies, this invention provides a method for distinguishing freezing rain and snowfall in winter, which has the following beneficial effects: This invention obtains research samples of observation data from ground automatic weather stations, radiosondes, and wind profiler radar in winter, preprocesses the observation data from ground automatic weather stations, radiosondes, and wind profiler radar, and extracts physical quantity parameters; statistically analyzes the distribution characteristics of vertical velocity, horizontal wind speed, and horizontal wind direction at five altitudes (150m, 390m, 750m, 1350m, and 2430m) for ground air temperature at 2m, 700hPa, 500hPa, geopotential thickness between 500hPa and 700hPa, 0-degree layer height, cloud top temperature, and at five altitudes (150m, 390m, 750m, 1350m, and 2430m), and combines the temperature of a specific layer with the vertical velocity of precipitation particles to establish the optimal discrimination index for freezing rain and snowfall, which can improve the ability to distinguish between freezing rain and snowfall. Attached Figure Description

[0026] Figure 1 This is a flowchart of the method for distinguishing between freezing rain and snowfall according to the present invention;

[0027] Figure 2 This is a schematic diagram of the method for determining the 0-degree layer height and cloud top temperature according to the present invention;

[0028] Figure 3 For the present invention T 2m T 700 T 500 H 500~700 Box plot of 0-degree layer height and cloud top temperature;

[0029] Figure 4 This is a statistical chart showing the horizontal wind direction, horizontal wind speed, and vertical velocity at different altitudes during freezing rain and snowfall processes, as presented in this invention.

[0030] Figure 5 This invention provides temperature and humidity profile maps for Guiyang at 20:00 on February 22, 2024, and 08:00 on February 23, 2024, and for Weining at 20:00 on February 25, 2024, and 08:00 on February 26, 2024.

[0031] Figure 6 The wind profile radar maps for horizontal and vertical wind speeds during freezing rain in Guiyang on February 23, 2024, and snowfall in Weining from 20:00 on January 25 to 19:00 on January 26, 2025, are for this invention. Detailed Implementation

[0032] To better understand the purpose, structure, and function of this invention, and to improve the accuracy of distinguishing between freezing rain and snowfall in Guizhou, a method for distinguishing between freezing rain and snowfall in winter according to this invention will be described in further detail.

[0033] refer to Figure 1-6 This invention: A flowchart of a method for identifying freezing rain and snowfall, as shown below. Figure 1 As shown, the process of the freezing rain and snowfall discrimination method includes: acquiring data, extracting physical quantity parameters, statistically analyzing physical quantity characteristics, establishing discrimination indicators for freezing rain and snowfall, and verifying discrimination indicators.

[0034] Data Acquisition:

[0035] From January 2022 to March 2025, 19 freezing rain and snowfall events were identified in Guizhou Province. These events were: January 8-17, 2022; January 26-29, 2022; January 31-February 4, 2022; February 19-23, 2022; November 30, 2022; December 1-18, 2022; December 25-31, 2022; January 1-5, 2023. 3.01.14-25, 2023.02.03-28, 2023.12.15-19, 2024.01.21-28, 2024.02.01-08, 2024.02.22-03.01, 2024.12.21-25, 2025.01.07-09, 2025.01.25-26, 2025.02.05-09, 2025.3.15-19. Data from three radiosonde observations at 08:00 and 20:00 across the province, as well as observations from 14 wind profiler radars and the corresponding national automatic weather stations, were used. Based on the occurrence of freezing rain and snowfall at 08:00 and 20:00, ground, radiosonde, and wind profiler radar observations were selected for these times. The results for freezing rain were: 57 radiosonde observations, 72 ground observations, and 53 wind profiler radar observations. For snowfall, only 18 radiosonde observations were available. Therefore, in addition to the 08:00 and 20:00 data, observations from other periods of the snowfall process were also selected, resulting in 49 ground observations and 42 wind profiler radar observations. The selected freezing rain and snowfall data were divided into statistical and test samples, as shown in Table 1.

[0036]

[0037] Table 1

[0038] Extracting physical quantity parameters:

[0039] The study sampled ground-based, radiosonde, and wind profiler radar observations, processed and extracted 21 physical parameters, including the ground air temperature at 2 meters (T). 2m ), 700 hPa temperature (T) 700 ), 500 hPa temperature (T) 500 The potential thickness (H) between 500 hPa and 700 hPa 500~700 The data includes the following parameters: 0-degree altitude, cloud top temperature, vertical velocity, horizontal wind speed, and horizontal wind direction at five altitudes: 150m, 390m, 750m, 1350m, and 2430m. The 0-degree altitude is the difference between the geopotential height of the lowest 0-degree layer and the altitude. The cloud top temperature is the temperature whose difference from the dew point temperature is less than 3°C. A schematic diagram illustrating the methods for determining the 0-degree altitude and cloud top temperature is shown below. Figure 2 .

[0040] Statistical analysis of physical quantity characteristics:

[0041] Figure 3 T corresponds to freezing rain and snowfall. 2m T 700 T 500 H 500~700 Box plot of 0-degree layer height and cloud top temperature.

[0042] Snowfall T 2m The maximum value is 0.9℃. The 90th percentiles of freezing rain and snowfall are below -0.5℃ and 0.1℃, respectively, with medians of -1.3℃ and -1.8℃. The 10% to 90% percentiles completely overlap. 2m A single indicator cannot distinguish between freezing rain and snowfall.

[0043] Freezing rain and snowfall T 700 The maximum values ​​are 7℃ and -3℃, respectively, and the medians are 0.2℃ and -7℃, respectively. The 90th percentile for freezing rain is below 3℃, and the 10th percentile is below -3℃. The 90th percentile for snowfall is below -3℃. Freezing rain and snowfall do not overlap in the 10th to 90th percentiles. If T 700 Temperatures above -3℃ are considered freezing rain, reaching 96% in central regions and only 37% in western regions.

[0044] Freezing rain and snowfall T 500 The maximum values ​​are 1℃ and -11℃, respectively, and the medians are -8℃ and -15℃, respectively. The 10th percentile of freezing rain is below -14℃, and the 90th percentile of snowfall is below -13℃. There is a significant overlap between the two in the 10th and 90th percentiles, which is not conducive to distinguishing between freezing rain and snowfall.

[0045] Freezing rain and snowfall H 500~700 The medians are 265 dagpm and 260 dagpm, respectively. The 10th percentile for freezing rain is less than 263 dagpm, and the 90th percentile for snowfall is less than 262 dagpm. There is no overlap between the 10th and 90th percentiles. If H 500~700 A reading of ≥263 dagpm indicates freezing rain, with the central region reaching 93% and the western region only 57%.

[0046] The 90th percentile of freezing rain is below 1.2 km, with a median and mean of 0.9 km, and the 10th percentile descends to the ground. Snowfall has the highest 0-degree layer height at approximately 0.1 km, with 80% reaching the ground. If freezing rain and snow are distinguished by the 0-degree layer grounding, 28% of freezing rain will be identified as snowfall.

[0047] The minimum cloud top temperature for freezing rain is -9℃, the median is -1℃, the maximum temperature for snowfall is -12℃, and the 90th percentile is below -16℃. The cloud top temperatures for freezing rain and snowfall do not overlap at all.

[0048] Figure 4 This chart shows the horizontal wind direction, horizontal wind speed, and vertical velocity at different altitudes during freezing rain and snowfall. During freezing rain, the horizontal wind direction at 150m and 390m was basically the same. In the western region, easterly and southeasterly winds were dominant, while in Guiyang, northerly and northeasterly winds were dominant. At 750m, southwesterly winds accounted for only 30% of the total sample. At 1350m, southwesterly and westerly winds were dominant in the western region, while in Guiyang, southwesterly winds were dominant. The horizontal wind speed at 150m was less than 6m / s, with an average wind speed of about 3m / s. The horizontal wind speed at 1350m was higher, with an average wind speed of 17m / s. The wind speed in Weining was relatively consistent, while it fluctuated more significantly in Puan and Guiyang. Overall, the vertical velocities at 150m and 390m were basically consistent across all stations, with 97% ranging from 0.1 to 0.9 m / s and an average of about 0.5 m / s. At 750m, the vertical velocities were between 0.1 and 0.8 m / s, accounting for 81% of the total sample. The maximum vertical velocity at 1350m was 0.6 m / s, but this occurred only once, mainly between -0.2 and 0.2 m / s, with -0.2 to 0 m / s accounting for 69% of the total sample. This indicates that the descending airflow weakened significantly at 1350m.

[0049] During the snowfall process, the horizontal wind direction at 150m and 390m was relatively consistent, mainly northeasterly and northerly. However, in Weining and Shuicheng, southeasterly winds accounted for about 40% of the total samples at the two stations. At 2430m, the wind direction was mainly southwesterly. At 150m, the horizontal wind speed was greater than 5m / s in 66% of the total samples, with an average speed of 6m / s. The horizontal wind speed gradually increased from 390m to 2430m, with the average wind speed increasing from 6.6m / s to 14.2m / s. Overall, the vertical velocity at different altitudes was basically consistent across all stations, with 91% of the samples having a vertical velocity between 0.7 and 2.2m / s. Below 750m, the vertical velocity was less than or equal to 0.9m / s in 23% of the samples. At 1350m, the vertical wind speed was between 0.7 and 2.2m / s in 91% of the samples, and at 2430m, the vertical wind speed was between 0.7 and 2.2m / s in 85% of the samples, indicating that below 2430m, descending airflow still dominated.

[0050] The horizontal wind speeds of freezing rain and snowfall overlap significantly at different altitudes, and the vertical speeds below 750m also overlap significantly between 0.5 and 0.9 m / s, but at 1350m, their vertical speed overlap rate is only 5%.

[0051] Establish indicators for distinguishing between freezing rain and snowfall:

[0052] When freezing rain occurs, T 2m Less than or equal to 0℃, T 2m The maximum snowfall temperature was 0.9℃. 2m ≤0 and T 2m<1 can be used as a preliminary criterion for judging freezing rain and snowfall respectively; during freezing rain, the cloud top temperature is ≥-9℃, and during snowfall, the cloud top temperature is ≤-12℃. The cloud top temperatures during freezing rain and snowfall do not overlap at all. When the cloud top temperature is ≥-9℃, it can be judged as freezing rain; when the cloud top temperature is ≤-12℃, it can be judged as snowfall. 700 >-3℃ and H 500~700 In central Guizhou, a wind speed of ≥263 dagpm indicates a greater than 93% probability of freezing rain. Therefore, these two indicators are used to determine freezing rain in central Guizhou. Horizontal wind speeds for freezing rain and snowfall show significant overlap at altitudes of 150m, 390m, 750m, 1350m, and 2430m. Below 750m, vertical wind speeds for freezing rain and snowfall also show significant overlap between 0.7 and 0.9 m / s. The overlap rate of vertical wind speeds for freezing rain and snowfall at 1350m is only 5%. Therefore, the vertical wind speed at 1350m is used as an indicator for determining freezing rain and snowfall. Specific indicators are shown in Table 2.

[0053] It should be noted that due to the limited number of snowfall cases at 08:00 and 20:00 during Guiyang radiosonde in 2022-2025, this embodiment does not include snowfall data for the central region. 700 and H 500~700 The physical quantity index provides judgment and verification, which is represented by "x" in the table;

[0054]

[0055] Table 2

[0056] Indicators for distinguishing between freezing rain and snowfall:

[0057] The physical quantity T for the freezing rain process, applicable to the entire province, was tested using the test samples in Table 1. 2m ≤-0.3℃, cloud top temperatures are all above or equal to -7℃, snowfall process T 2m ≤0.4℃, cloud top temperature below or equal to -15.6℃, T 2m Both the cloud top temperature test samples and the physical quantity judgment index for freezing rain and snowfall were within the range. In the test samples for freezing rain and snowfall at a vertical velocity of 1350m, one sample each appeared that deviated from the judgment index, indicating an accuracy of approximately 90%. This method is suitable for judging the physical quantity of freezing rain in central regions: T. 700 >-3℃ and H 500~700 A value of ≥263 dagpm indicates a 70% probability of freezing rain.

[0058] Combining freezing rain and snowfall indicators, this study analyzes a freezing rain and snowfall event. From February 22nd to 27th, 2024, low-temperature freezing weather occurred in central and eastern Guizhou. Freezing rain was observed at the Guiyang vertical observation station, mainly occurring in the early morning and evening. The temperature and humidity profiles of the Guiyang radiosonde at 20:00 on February 22nd and 08:00 on February 23rd were... Figure 5The cloud top temperatures were 5.6℃ and 1℃, respectively, and the 700hPa temperature was 5℃. 500~700 The values ​​were 269.7 dagpm and 270.1 dagpm, respectively, both meeting the criteria for freezing rain in the central region. The cold pads were both below 800 hPa, the cloud tops were above the 0-degree layer, there was no melting layer, and the clouds contained liquid water droplets. The water droplets formed freezing rain as they fell due to the action of the underlying cold pads.

[0059] From January 25th to 26th, 2025, low temperatures and snow occurred in central and western Guizhou Province. The snowfall mainly occurred on the 26th, and on the same day, four ground-based remote sensing vertical observation stations in Weining, Puan, Bijie, and Shuicheng observed snowfall. The T... 2m The maximum temperature was 0.8℃, which is lower than the temperature during snowfall. 2m The index of <1℃, the temperature and humidity profile of Weining radiosonde at 20:00 on January 25, 2025 and 08:00 on January 26, 2025 ( Figure 1 At 20:00 on the 25th, the 0-degree layer descended to the ground, with a cloud top temperature of -11.5℃. Ice crystals, snowflakes, and supercooled water were present in the clouds. At this time, no snowfall was observed on the ground. At 08:00 on the 26th, the 0-degree layer reached the ground, with a cloud top temperature of -20.5℃. The cloud top temperature was significantly lower than the snowfall judgment index of -12℃, and snowfall occurred on the ground.

[0060] Figure 6 The wind profile radar maps show the horizontal and vertical wind speeds for freezing rain in Guiyang on February 23, 2024, and snowfall in Weining from 20:00 on January 25 to 19:00 on January 26, 2025. Below 1000m, the vertical wind speeds for freezing rain and snowfall show significant overlap between 0.7 and 0.8 m / s. The maximum vertical speed for freezing rain at 1350m is 0.2 m / s, while the vertical speed for snowfall at 1350m is mainly between 0.7 and 1.9 m / s. This aligns with the criteria for judging freezing rain and snowfall at 1350m.

[0061] It is understood that the present invention has been described through some embodiments, and those skilled in the art will recognize that various changes or equivalent substitutions can be made to these features and embodiments without departing from the spirit and scope of the invention. Furthermore, under the teachings of the present invention, these features and embodiments can be modified to adapt to specific situations and materials without departing from the spirit and scope of the invention. Therefore, the present invention is not limited to the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the protection scope of the present invention.

Claims

1. A method for identifying freezing rain and snowfall in winter, characterized in that, Includes the following steps: S1: Acquire ground-based automatic weather station observation data, radiosonde observation data, and wind profiler radar observation data for the target area during winter to form a research sample set; S2: Preprocess the various types of observation data in the research sample set and extract the physical quantity parameters used for discrimination; S3: Based on the extracted physical quantity parameters, statistically analyze the distribution characteristics of each physical quantity parameter under freezing rain and snowfall events respectively; S4: Based on the distribution characteristics and combined with the geographical and climatic characteristics of the target area, establish a discrimination index for freezing rain and snowfall; S5: For the weather process to be identified, acquire the corresponding real-time observation data, extract the physical quantity parameters on which the identification index is based, and output the identification result of freezing rain or snowfall according to the identification index.

2. The method for identifying freezing rain and snowfall in winter according to claim 1, characterized in that, In step S2, the physical parameters extracted from the observation data of the ground automatic weather station are the air temperature at 2 meters above the ground. The physical parameters extracted from the radiosonde observation data include: specific layer temperatures at 700 hPa and 500 hPa, geopotential heights at 700 hPa and 500 hPa, 0-degree layer height, and cloud top temperature. The physical parameters extracted from the wind profiler radar observation data include at least five vertical velocity, horizontal wind speed, and horizontal wind direction parameters at different altitudes.

3. The method for identifying freezing rain and snowfall in winter according to claim 2, characterized in that, The 0-degree layer height is the difference between the geopotential height of the lowest 0-degree layer at the sounding altitude and the altitude.

4. The method for identifying freezing rain and snowfall in winter according to claim 3, characterized in that, The cloud top temperature is calculated as follows: the temperature and dew point temperature are extracted from the sounding research sample, and the temperature with a difference of less than 3°C is taken as the cloud top temperature.

5. The method for identifying freezing rain and snowfall in winter according to claim 4, characterized in that: The distribution characteristics statistically analyzed in step S3 include: the distribution characteristics of ground temperature at 2 meters during freezing rain and snowfall, the distribution characteristics of geopotential thickness between 500 hPa and 700 hPa during freezing rain and snowfall, the distribution characteristics of the 0-degree layer height during freezing rain and snowfall, the distribution characteristics of cloud top temperature during freezing rain and snowfall, and the distribution characteristics of vertical velocity, horizontal wind speed, and horizontal wind direction during freezing rain and snowfall at at least 5 different altitudes.

6. The method for identifying freezing rain and snowfall in winter according to claim 5, characterized in that, The physical quantity parameters and distribution characteristics include five height settings, which are 150 meters, 390 meters, 750 meters, 1350 meters, and 2430 meters respectively.

7. The method for identifying freezing rain and snowfall in winter according to claim 6, characterized in that, In step S4, when the target area is the entire province, the criteria for distinguishing between freezing rain and snowfall are: When the air temperature at 2 meters above the ground is less than or equal to 0°C, the cloud top temperature is greater than or equal to -9°C, and the vertical velocity at 1350 meters is less than or equal to 0.6 m / s, it is judged as freezing rain; Snowfall is defined as the temperature at 2 meters above the ground being less than 1°C, the temperature at the cloud top being less than or equal to -12°C, and the vertical velocity at 1350 meters being greater than 0.6 m / s.

8. The method for identifying freezing rain and snowfall in winter according to claim 6, characterized in that, In step S4, when the target area is central Guizhou, the criteria for distinguishing between freezing rain and snowfall are: Freezing rain is defined as the temperature at 2 meters above the ground being less than or equal to 0°C, the temperature at 700 hPa being greater than -3°C, and the geopotential thickness between 500 hPa and 700 hPa being greater than or equal to 263 dagpm.

Images