Method and system for evaluating distribution and intensity of freezing rain disasters in hilly areas

Abstract

The invention discloses a method and a system for evaluating distribution and intensity of freezing rain disasters in hilly areas. The evaluation method adopted by the invention comprises the following steps: collecting meteorological reanalysis grid point data with fine vertical layering in a freezing rain event influence period, calculating freezing rain occurrence altitudes and potential freezing rain amounts of different grid points in the hilly area hour by hour, and downscaling to fine grid points; the method comprises the following steps: taking the potential freezing rain amount of a fine grid point at a certain moment when the altitude is lower than the ground elevation as the freezing rain amount of the grid point at the moment, and then accumulating the freezing rain amounts at all moments by fine grids to obtain the accumulated freezing rain amount of all the fine grids in an influence time period, thereby determining the freezing rain disaster distribution of the hilly and mountainous areas; and determining a freezing rain risk level by combining the obtained freezing rain disaster information of the partial region. The problem that freezing rain disaster assessment is difficult due to serious shortage of glaze data and incomplete freezing rain disaster information in existing hilly areas is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of meteorological disaster prevention and reduction, and specifically relates to a method and system for evaluating the distribution and intensity of freezing rain disasters in hilly areas. Background Art

[0002] Freezing rain is liquid precipitation in the form of supercooled water droplets. When it falls on an object with a surface temperature of 0°C or below, it immediately freezes (known in meteorology as rime). Once it occurs, freezing rain often has a serious impact on traffic. Severe freezing rain can paralyze traffic, damage power lines and towers, and topple trees, flowers, and plants. The impact is often much more serious than that of snow or ice pellets of the same level. In southern China, there is a freezing rain belt that stretches from Guizhou, Hunan, Jiangxi, and Zhejiang from west to east, with freezing rain frequency decreasing from high to low. This freezing rain belt can extend northward to Sichuan, Chongqing, Hubei, Anhui, and Henan, and southward to Yunnan, Guangxi, Guangdong, and northern Fujian. Its southern edge aligns with the direction of the southern mountain ranges of my country. Guizhou, located in the western section of the freezing rain belt, is situated on a plateau, and its abundant data on rime days and freezing rain damage is sufficient for freezing rain disaster impact assessments. Meteorological stations in provinces with flat terrain in the eastern section of the freezing rain belt can also observe rime and other freezing rain-related data. However, in the hilly areas of the central and eastern sections of the freezing rain belt, the terrain is highly rugged, and there are fewer meteorological stations in the mountains. Rime data is severely lacking, making it difficult to obtain freezing rain damage, leading to a significant underestimation of freezing rain in hilly areas. For example, in Zhejiang Province, of the province's 73 conventional meteorological stations, 68 are located at elevations below 200 meters, 3 are between 200 and 300 meters, and 2 are between 400 and 500 meters. Yet, approximately 23% of the province is mountainous, with elevations between 500 and 1923 meters. During the freezing rain in late February 2024, rime and ice covered power transmission lines in many areas of Zhejiang Province. Areas like Siming Mountain in Ningbo and Anji in Huzhou even saw severe ice coverage exceeding 30 mm. However, during this period, no meteorological stations recorded any number of days with rime. Besides records of icing on transmission lines, there was also little survey data on freezing rain damage. Similar phenomena were also common in hilly and mountainous areas of Jiangxi, Anhui, Guangxi, and Guangdong provinces. This suggests that the number of days with rime fails to reflect the true extent of freezing rain in hilly and mountainous areas. Furthermore, freezing rain often occurs in mountainous areas, making comprehensive freezing rain damage data difficult to obtain, significantly hindering the overall assessment of freezing rain disasters in hilly areas.

[0003] The mountainous areas are heavily covered in ice, yet the weather station is lacking rime. This discrepancy stems from the local stratification structure. Changsha has a typical three-layer structure: "cold-warm-cold." The bottom layer, where the weather station is located, is a cold layer, and freezing rain falls directly to the ground as rime. Hangzhou, on the other hand, has a four-layer structure: "warm-cold-warm-cold." The bottom layer, where the weather station is located, is a warm layer, and freezing rain falls to the ground as precipitation. However, the mountainous areas near Hangzhou share similar stratification characteristics to Changsha. Freezing rain falls below the mountainous areas, forming rime, which then forms ice on power lines. Because freezing rain in Hunan, Hubei and other places represented by Changsha is more easily captured by meteorological stations, and the center of the warm layer when freezing rain occurs in these provinces is mostly located at 700hPa, and the center of the cold layer is mostly located at 850hPa, the inversion layer range formed by the 850hPa and 700hPa layers is often used in business as the main feature of the occurrence of freezing rain; and the analysis of freezing rain stratification found that the freezing rain process caused by the encounter of warm and humid air currents from different sources with cold air has different warm layer centers and cold layer centers, and even changes dynamically according to the strength of the warm and cold air. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to overcome the difficulty in assessing freezing rain disasters in hilly areas due to the severe shortage of rime data and insufficient freezing rain disaster information. A method and system for assessing the distribution and intensity of freezing rain disasters in hilly areas are provided. The method estimates the amount of freezing rain based on the relative humidity at the height where freezing rain occurs, and constructs an assessment index that can quantify the distribution and intensity of freezing rain disasters to assess the distribution and intensity of freezing rain disasters in hilly areas, thereby providing a scientific basis for preventing freezing rain disasters in hilly areas.

[0005] To this end, the present invention adopts the following technical solution: a method for evaluating the distribution and intensity of freezing rain disasters in hilly areas, comprising:

[0006] First, the impact period of a freezing rain event was determined based on rime data from meteorological stations. Meteorological reanalysis grid data with fine vertical stratification at 5-25 km intervals were collected during the impact period. The freezing rain occurrence altitude and potential freezing rain amount at different grid points in hilly areas were calculated hourly, and then downscaled to fine grid points with a grid interval of less than 2.5 km.

[0007] Then, the potential freezing rain amount at a certain fine grid point at a certain moment, where the altitude at which freezing rain occurs is lower than the ground elevation, is taken as the freezing rain amount at that grid point at that moment. Then, the freezing rain amount at all moments is accumulated on each fine grid to obtain the cumulative freezing rain amount of all fine grids during the affected period, thereby determining the distribution of freezing rain disasters in hilly and mountainous areas.

[0008] Finally, the freezing rain risk level was determined based on the available freezing rain disaster data in some areas, and a quantitative assessment of the intensity of freezing rain disasters in the entire hilly area was conducted.

[0009] Furthermore, the method of determining the impact period of a freezing rain event based on rime data from meteorological stations is as follows: for hilly areas, data on the number of days with rime observed by conventional meteorological stations in the area are collected; rime data observed by meteorological stations below 800m above sea level are selected from the collected data on the number of days with rime, and the impact period of a freezing rain event is determined according to the two standards of severe freezing rain events and local freezing rain events.

[0010] Furthermore, the severe freezing rain event is a freezing rain process in which the number of stations with daily rime rain exceeds 70 and multiple stations have freezing rain lasting for more than 3 days; the local freezing rain event is a freezing rain process in which the number of stations with daily rime rain exceeds 5 and at least 3 stations have freezing rain lasting for more than 2 days.

[0011] Furthermore, the meteorological reanalysis grid data with fine vertical stratification of 5-25 km grid spacing during the impact period are collected, specifically: according to the impact period of the freezing rain event, meteorological reanalysis data with 5-25 km grid spacing and DEM data with 90 m grid spacing are downloaded from relevant websites.

[0012] Furthermore, the hourly calculation of the freezing rain occurrence altitude and potential freezing rain amount at different grid points in hilly areas is as follows: based on the typical temperature stratification characteristics of "cold-warm-cold" freezing rain, grid points that meet the freezing rain occurrence threshold conditions are identified hourly during the impact period of the freezing rain event, marked as 1, and the lower limit height of the bottom cold layer is recorded as the freezing rain occurrence altitude H1, and those that do not meet the conditions are recorded as 0; for the grid points marked as 1, the potential freezing rain amount of the grid points is determined based on the relative humidity rh at the freezing rain occurrence altitude H1.

[0013] Furthermore, the formula for determining the potential freezing rain amount at a grid point based on the relative humidity rh at the freezing rain occurrence altitude H1 is as follows:

[0014]

[0015] Wherein, the value range of x is 0.1mm to 0.3mm.

[0016] Furthermore, the specific process of obtaining the cumulative freezing rain amount of all fine grids during the impact period is as follows:

[0017] The hourly estimated potential freezing rain amount and freezing rain occurrence altitude data H1 are downscaled to fine grid points within 2.5 km in hilly areas to obtain the freezing rain amount and freezing rain occurrence altitude data H2 at the fine grid points. Accordingly, the DEM is resampled to a grid interval within 2.5 km, and the ground elevation of each grid point is recorded as H3.

[0018] According to the grid points where the potential freezing rain amount is greater than 0.0 mm, the difference between H3 and H2 is calculated. If H2-H3≥0, the freezing rain amount of the grid point is assigned to 0.0 mm. Otherwise, the potential freezing rain amount of the grid point is the freezing rain amount of the corresponding fine grid point. The judgment of all grid points in the study area is completed as the hourly freezing rain amount of each fine grid point at the corresponding moment; the judgment of the remaining moments is completed in the same way. Finally, the freezing rain amount of all moments is accumulated for each fine grid point to obtain the cumulative freezing rain amount of all fine grids in the affected period during a freezing rain event, thereby determining the distribution of freezing rain disasters in hilly and mountainous areas.

[0019] Furthermore, the freezing rain risk levels are as follows: Level 1 is slight icing, with freezing rain amount <5mm; Level 2 is obvious icing, with freezing rain amount between [5mm, 15mm); Level 3 is heavy icing, with freezing rain amount between [15mm, 25mm); Level 4 is severe icing, with freezing rain amount ≥25mm.

[0020] Furthermore, a spatial distribution map is drawn based on the freezing rain risk level at each grid point to determine the impact range and intensity distribution of a freezing rain event.

[0021] The present invention also provides an evaluation system for the distribution and severity of freezing rain disasters in hilly areas, which is used in the above-mentioned evaluation method for the distribution and severity of freezing rain disasters in hilly areas, and includes:

[0022] Calculation unit: Based on rime data from weather stations, the impact period of a freezing rain event is determined. Meteorological reanalysis grid data with fine vertical stratification at 5-25 km intervals are collected during the impact period. The freezing rain occurrence altitude and potential freezing rain amount at different grid points in hilly areas are calculated hourly, and then downscaled to fine grid points with a grid interval of less than 2.5 km.

[0023] Cumulative freezing rain amount acquisition unit: used to take the potential freezing rain amount at a certain fine grid point at a certain moment when the freezing rain appears at an altitude lower than the ground elevation as the freezing rain amount at that grid point at that moment, and then accumulate the freezing rain amount at all moments for each fine grid to obtain the cumulative freezing rain amount of all fine grids in the affected period;

[0024] Quantitative assessment unit: used to determine the freezing rain risk level based on the available freezing rain disaster data in some areas, and to conduct a quantitative assessment of the intensity of freezing rain disasters in the entire hilly area.

[0025] Compared with the existing technology, the present invention has the following beneficial effects: the present invention combines DEM data of hilly and mountainous areas and detailed freezing rain disaster information of some areas, proposes a freezing rain risk index for quantitatively measuring the impact of freezing rain disasters, evaluates the distribution and intensity of freezing rain disasters in the entire hilly area, and provides a scientific basis for preventing freezing rain disasters in hilly areas; the present invention solves the problem of difficulty in assessing freezing rain disasters in hilly areas due to a serious shortage of rime data and insufficient freezing rain disaster data. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for the embodiments.

[0027] Figure 1 This is a flow chart of a method for evaluating the distribution and intensity of freezing rain disasters in hilly areas according to the present invention;

[0028] Figure 2 This is a statistical chart of the number of weather stations that observed rime every day in the hilly area in late February 2024 in a specific embodiment of the present invention;

[0029] Figure 3 The cumulative number of days with rime at the weather station from February 21 to 26, 2024, and the distribution map of icing accident points on power transmission lines in Zhejiang Province in a specific embodiment of the present invention are shown;

[0030] Figure 4 This is a typical freezing rain stratification distribution characteristic diagram in January 2008 in a specific embodiment of the present invention;

[0031] Figure 5 The spatial distribution map of freezing rain amount from February 21 to 26, 2024, estimated according to the method of the present invention (the numbers are the number of days with rime rain at the weather station);

[0032] Figure 6 This is a comparative analysis chart of icing accident points and freezing rain amounts in Zhejiang Province from February 21 to 26, 2024, in a specific embodiment of the present invention;

[0033] Figure 7 A spatial distribution map of freezing rain risk levels from February 21 to 26, 2024, drawn according to the method of the present invention;

[0034] Figure 8 This is a composition diagram of a method for evaluating the distribution and intensity of freezing rain disasters in hilly areas according to the present invention. DETAILED DESCRIPTION

[0035] The present invention will be further described below with reference to the accompanying drawings.

[0036] Example 1

[0037] This embodiment provides a method for evaluating the distribution and intensity of freezing rain disasters in hilly areas. Figure 1 As shown, the steps are as follows:

[0038] First, the impact period of a freezing rain event was determined based on the rime data from meteorological stations. Meteorological reanalysis grid data with a fine vertical stratification of 25 kilometers were collected during the impact period. The altitude at which freezing rain would occur and the potential amount of freezing rain at different grid points in hilly areas were calculated hourly.

[0039] The method for determining the impact period of a freezing rain event based on rime data from weather stations is as follows: for hilly areas (109°E-123°E, 24°N-35°N), data on the number of days with rime observed by conventional weather stations in the area are collected; rime data observed by weather stations below 800 meters above sea level are selected from the collected rime data, and the impact period of a freezing rain event is determined according to two criteria: severe freezing rain events and localized freezing rain events. A severe freezing rain event is defined as a freezing rain process with more than 70 stations experiencing rime per day, and with multiple stations experiencing rime for more than three days; a localized freezing rain event is defined as a freezing rain process with more than five stations experiencing rime per day (with the stations being close to each other), and with at least three stations experiencing rime for more than two days.

[0040] The meteorological reanalysis grid data with fine vertical stratification during the impact period are collected, specifically: according to the impact period of the freezing rain event, meteorological reanalysis data are downloaded from relevant websites (ERA5 of the European Center for Medium-Range Weather Forecasts is used here, with a grid spacing of 25 kilometers, a time resolution of 1 hour, 37 vertical layers, and a data range of (109°E-123°E, 24°N-35°N)), and DEM data with a grid spacing of 90 meters are downloaded from relevant websites.

[0041] The hourly calculation of the freezing rain occurrence altitude and potential freezing rain amount at different grid points in hilly areas is specifically as follows: based on the typical temperature stratification characteristics of "cold-warm-cold" freezing rain, grid points that meet the freezing rain occurrence threshold conditions are identified hourly during the impact period of the freezing rain event, marked as 1, and the lower limit height of the bottom cold layer is recorded as the freezing rain occurrence altitude H1, and those that do not meet the conditions are recorded as 0; for the grid points marked as 1, the potential freezing rain amount of the grid points is determined based on the relative humidity rh at the freezing rain occurrence altitude H1.

[0042] The formula for determining the potential freezing rain amount at a grid point based on the relative humidity rh at the freezing rain occurrence altitude H1 is as follows:

[0043]

[0044] In the formula, the value of x ranges from 0.1 mm to 0.3 mm, which is determined according to the freezing rain disaster situation and can be adjusted after more detailed freezing rain disaster data are available.

[0045] The specific process of obtaining the cumulative freezing rain amount of all fine grids during the affected period is as follows:

[0046] The hourly estimated potential freezing rain amount and freezing rain occurrence altitude data H1 are downscaled to the fine grid points of 2.5 km grid spacing in the hilly area to obtain the freezing rain amount and freezing rain occurrence altitude data H2 at the fine grid points. Accordingly, the DEM is resampled to the 2.5 km grid spacing, and the ground elevation of each grid point is recorded as H3;

[0047] According to the grid points where the potential freezing rain amount is greater than 0.0 mm, the difference between H3 and H2 is calculated. If H2-H3≥0, the freezing rain amount of the grid point is assigned to 0.0 mm. Otherwise, the potential freezing rain amount of the grid point is the freezing rain amount of the corresponding fine grid point. The judgment of all grid points in the study area is completed as the hourly freezing rain amount of each fine grid point at the corresponding moment; the judgment of the remaining moments is completed in the same way. Finally, the freezing rain amount of all moments is accumulated for each fine grid point to obtain the cumulative freezing rain amount of all fine grids in the affected period during a freezing rain event, thereby determining the distribution of freezing rain disasters in hilly and mountainous areas.

[0048] Finally, the available freezing rain disaster data were combined to classify the freezing rain risk levels and conduct a quantitative assessment of the severity of freezing rain disasters in hilly areas.

[0049] The freezing rain risk levels are as follows: Level 1 is slight icing, with freezing rain <5mm; Level 2 is obvious icing, with freezing rain between [5mm, 15mm); Level 3 is heavy icing, with freezing rain between [15mm, 25mm); Level 4 is severe icing, with freezing rain ≥25mm.

[0050] A spatial distribution map is drawn based on the freezing rain risk level at each fine grid point to determine the impact range and intensity distribution of a freezing rain event.

[0051] In order to test the actual effect of the method described in the present invention, this embodiment selects a large-scale severe freezing rain event that occurred in a hilly area from February 21 to 26, 2024.

[0052] Step 1: Collect data on the number of days with rime rain observed at weather stations (below 800 m above sea level) in the hilly area (109°E-123°E, 24°N-35°N) in late February 2024, such as Figure 2 As shown in the figure, from the 21st to the 25th, there were more than 70 days of rime at stations for five consecutive days, which is considered a severe large-scale freezing rain event. Since rime was still observed at more than 10 weather stations on the 26th (rime in the later stages of the freezing rain process is mostly distributed in the southern hilly and mountainous areas), the freezing rain impact period is set as February 21st to 26th. The spatial distribution of the cumulative number of rime days at each weather station from the 21st to the 26th is plotted, as shown in the figure below. Figure 3 The figure also shows data collected from Zhejiang Province on freezing rain and icing disasters affecting power transmission lines. The lack of corresponding data on days with rime and rain for freezing rain and icing disasters in Zhejiang Province suggests that freezing rain in hilly and mountainous areas is severely underestimated.

[0053] Step 2: Download ERA5 meteorological reanalysis data from the European Centre for Medium-Range Weather Forecasts website. The data period is 144 hours, from 08:00 on February 21, 2024, to 08:00 on February 27, 2024. It covers the area (109°E-123°E, 24°N-35°N) and has 37 vertical layers. Meteorological elements include temperature (t), relative humidity (r), and altitude (z). Download DEM data with a 90-meter grid spacing from the Xingtu Cloud open platform.

[0054] Step 3: Start the freezing rain amount estimation based on the downloaded reanalysis data. The typical stratification distribution during freezing rain is as follows: Figure 4 As shown in the figure, the specific calculation method is to calculate whether each grid point meets the cold-warm-cold stratification from the bottom layer vertically upward, and set certain thresholds for the thickness of the intermediate warm layer and the bottom cold layer. The minimum threshold for the bottom cold layer thickness is 400m, and the upper threshold for the cold layer thickness is 3000m. The threshold for the thickness of the intermediate warm layer is also set to be greater than 400m, and the upper threshold for the warm layer thickness is 3600m. Each grid point is calculated based on the set thresholds. If the conditions are met, the grid point is considered to have freezing rain conditions at that moment. During the period affected by the freezing rain event, the grid points that meet the freezing rain conditions are calculated hour by hour, marked as 1, and the altitude at which the freezing rain occurred is recorded. If the conditions are not met, it is marked as 0.

[0055] Step 4: For the grid point marked as 1, determine the potential freezing rain amount (icerain) at that grid point based on the relative humidity (rh) at the altitude where freezing rain occurs (see Equation 1 for details).

[0056] Step 5: The hourly estimated coarse grid potential freezing rain amount and freezing rain occurrence altitude data H1 are downscaled to the hilly area to obtain fine grid (2.5 km grid spacing or higher grid spacing) potential freezing rain amount and freezing rain occurrence altitude data H2. Correspondingly, the DEM is resampled to the same grid spacing, and the DEM of each grid point is recorded as H3.

[0057] Step 6: Calculate the difference between H2 and H3 based on the grid points where the potential freezing rain amount at the fine grid points is greater than 0.0 mm: If H2-H3 ≥ 0, the estimated value of the freezing rain amount at the grid point is reassigned to 0.0 mm; otherwise, the potential freezing rain amount at the grid point is the freezing rain amount at the fine grid point. The judgment of all grid points in the study area is completed as the hourly freezing rain amount of each fine grid point at that moment. The judgment of all moments from February 21 to 26, 2024 is also completed in this way. Finally, the judgment results of all moments are accumulated at each fine grid point to obtain the total freezing rain amount of all fine grid points in the hilly area ( Figure 5As can be seen from the figure, the calculated cumulative freezing rain distribution has a good correspondence with the distribution of rime days observed by the meteorological stations in the figure. Hunan, Hubei, Anhui and Zhejiang provinces all experienced freezing rain of more than 30mm, and are the provinces most severely affected by this freezing rain disaster. The following uses the icing disaster of power transmission lines in Zhejiang Province to verify the estimated results, and draws a comparative analysis chart of icing accident points and freezing rain in Zhejiang Province ( Figure 6 Most icing accident points have a good correspondence with the 25mm freezing rain amount distribution, but some points do not (the low grid spacing of the reanalysis data leads to errors in the calculation results, which is reasonable. Thick ice is also common in some micro-topography areas prone to icing). This shows that the freezing rain amount distribution calculated by the method of the present invention can well display the distribution and intensity of a freezing rain disaster.

[0058] Step 7: Since the above freezing rain amount analysis results are calculated using meteorological data, there is a certain deviation from the actual freezing rain amount, and the magnitude of freezing rain cannot well reflect the impact of freezing rain disasters. Here, a comprehensive analysis of freezing rain amount and freezing rain disaster situation is combined to convert freezing rain amount into freezing rain risk level ( Figure 7 As can be seen from the figure, Hunan, Hubei, Anhui, and Zhejiang were the provinces most severely affected by icing during this icing event, which is basically consistent with the icing disaster situation. Hunan, Hubei, and Anhui all experienced large areas of heavy and severe icing risk, while heavy and severe icing in Zhejiang Province occurred in more scattered areas, indicating that the hilly characteristics of Zhejiang Province were more significantly affected than those of other provinces. It also shows that the method based on the present invention can better reflect the distribution and intensity of freezing rain risks in hilly areas.

[0059] Example 2

[0060] This embodiment provides an evaluation system for the distribution and intensity of freezing rain disasters in hilly areas, which is used to implement the evaluation method for the distribution and intensity of freezing rain disasters in hilly areas described in Example 1. Figure 8 As shown, it consists of a calculation unit, a cumulative freezing rain amount acquisition unit and a quantitative evaluation unit.

[0061] The calculation unit determines the impact period of a freezing rain event based on rime data from a weather station, collects meteorological reanalysis grid data with a fine vertical stratification of 25 kilometers (or smaller grid spacing) during the impact period, calculates the freezing rain occurrence altitude and potential freezing rain amount at different grid points in hilly areas on an hourly basis, and downscales the data to fine grid points of 2.5 kilometers (or smaller grid spacing).

[0062] The cumulative freezing rain amount acquisition unit is used to take the potential freezing rain amount at a certain fine grid point at a certain moment when the freezing rain occurs at an altitude lower than the ground elevation as the freezing rain amount of the fine grid point at that moment, and then accumulate the freezing rain amount at all moments for each fine grid to obtain the cumulative freezing rain amount of all fine grids in the affected period.

[0063] The quantitative assessment unit is used to divide the freezing rain risk level into the available freezing rain disaster data and to perform a quantitative assessment on the severity of freezing rain disasters in hilly areas.

[0064] It should be noted that the various units in the above-mentioned evaluation system for the distribution and intensity of freezing rain disasters in hilly areas can be implemented in whole or in part by software, hardware, and a combination thereof. The above-mentioned units can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned various units. Regarding the specific definition of an evaluation system for the distribution and intensity of freezing rain disasters in hilly areas, please refer to the definition of an evaluation method for the distribution and intensity of freezing rain disasters in hilly areas (i.e., Example 1) above. The two have the same functions and effects and will not be repeated here.

[0065] It is obvious that those skilled in the art can easily make various modifications to the above embodiments and apply the general principles described herein to other embodiments without requiring creative effort. Therefore, the present invention is not limited to the above embodiments, and improvements and modifications made by those skilled in the art based on the disclosure of the present invention should fall within the scope of protection of the present invention.

Claims

1. A method for evaluating the distribution and intensity of freezing rain disasters in hilly areas, characterized in that: First, the impact period of a freezing rain event was determined based on rime data from meteorological stations. Meteorological reanalysis grid data with fine vertical stratification at 5-25 km intervals were collected during the impact period. The freezing rain occurrence altitude and potential freezing rain amount at different grid points in hilly areas were calculated hourly, and then downscaled to fine grid points with a grid interval of less than 2.5 km. Then, the potential freezing rain amount at a certain fine grid point at a certain moment, where the altitude at which freezing rain occurs is lower than the ground elevation, is taken as the freezing rain amount at that grid point at that moment. Then, the freezing rain amount at all moments is accumulated on each fine grid to obtain the cumulative freezing rain amount of all fine grids during the affected period, thereby determining the distribution of freezing rain disasters in hilly and mountainous areas. Finally, the freezing rain risk level was determined based on the available freezing rain disaster data in some areas, and a quantitative assessment of the intensity of freezing rain disasters in the entire hilly area was conducted.

2. The evaluation method according to claim 1, wherein: The method of determining the impact period of a freezing rain event based on rime data from meteorological stations is as follows: for hilly areas, data on the number of days with rime observed by conventional meteorological stations in the area are collected; rime data observed by meteorological stations below 800m above sea level are selected from the collected data on the number of days with rime, and the impact period of a freezing rain event is determined according to the two standards of severe freezing rain events and local freezing rain events.

3. The evaluation method according to claim 2, wherein: The severe freezing rain event refers to a freezing rain process in which the number of stations with daily rime rain exceeds 70 and multiple stations have freezing rain lasting for more than 3 days; the local freezing rain event refers to a freezing rain process in which the number of stations with daily rime rain exceeds 5 and at least 3 stations have freezing rain lasting for more than 2 days.

4. The evaluation method according to claim 1, wherein: The meteorological reanalysis grid data with fine vertical stratification and 5-25 km grid spacing are collected during the impact period. Specifically, according to the impact period of the freezing rain event, meteorological reanalysis data with 5-25 km grid spacing and DEM data with 90 m grid spacing are downloaded from relevant websites.

5. The evaluation method according to claim 1, wherein: The hourly calculation of the freezing rain occurrence altitude and potential freezing rain amount at different grid points in hilly areas is specifically as follows: based on the typical "cold-warm-cold" freezing rain temperature stratification characteristics, grid points that meet the freezing rain occurrence threshold conditions are identified hourly during the freezing rain event impact period, marked as 1, and the lower limit height of the lowest cold layer is recorded as the freezing rain occurrence altitude H1; those that do not meet the threshold conditions are recorded as 0; for the grid points marked as 1, the potential freezing rain amount of the grid points is determined based on the relative humidity rh at the freezing rain occurrence altitude H1.

6. The evaluation method according to claim 5, characterized in that The formula for determining the potential freezing rain amount at a grid point based on the relative humidity rh at the freezing rain occurrence altitude H1 is as follows: Wherein, the value range of x is 0.1mm to 0.3mm.

7. The evaluation method according to claim 5, characterized in that The specific process of obtaining the cumulative freezing rain amount of all fine grids during the affected period is as follows: The hourly estimated potential freezing rain amount and freezing rain occurrence altitude data H1 are downscaled to fine grid points within 2.5 km in hilly areas to obtain the freezing rain amount and freezing rain occurrence altitude data H2 at the fine grid points. Accordingly, the DEM is resampled to fine grid points with the same grid spacing, and the ground elevation of each grid point is recorded as H3. According to the grid points where the potential freezing rain amount is greater than 0.0 mm, the difference between H3 and H2 is calculated. If H2-H3≥0, the freezing rain amount of the grid point is assigned a value of 0.0 mm. Otherwise, the potential freezing rain amount of the grid point is the freezing rain amount of the corresponding fine grid point. The judgment of all grid points in the study area is completed as the hourly freezing rain amount of each fine grid point at the corresponding time. The judgment of the remaining moments is completed in the same way. Finally, the freezing rain amount at all moments is accumulated at each fine grid point to obtain the cumulative freezing rain amount of all fine grids in the affected period during a freezing rain event, thereby determining the distribution of freezing rain disasters in hilly and mountainous areas.

8. The evaluation method according to claim 1, wherein: The freezing rain risk levels are as follows: Level 1 is slight icing, with freezing rain <5mm; Level 2 is obvious icing, with freezing rain between [5mm, 15mm); Level 3 is heavy icing, with freezing rain between [15mm, 25mm); Level 4 is severe icing, with freezing rain ≥25mm.

9. The evaluation method according to claim 8, characterized in that A spatial distribution map is drawn based on the freezing rain risk level at each grid point to determine the distribution range and intensity of a freezing rain event.

10. An evaluation system for the distribution and intensity of freezing rain disasters in hilly areas, used to implement the evaluation method according to any one of claims 1 to 9, characterized in that: include: Calculation unit: Based on rime data from weather stations, the impact period of a freezing rain event is determined. Meteorological reanalysis grid data with fine vertical stratification at 5-25 km intervals are collected during the impact period. The freezing rain occurrence altitude and potential freezing rain amount at different grid points in hilly areas are calculated hourly, and then downscaled to fine grid points with a grid interval of less than 2.5 km. Cumulative freezing rain amount acquisition unit: used to take the potential freezing rain amount at a certain grid point at a certain moment when the freezing rain appears at an altitude lower than the ground elevation as the freezing rain amount at that grid point at that moment, and then accumulate the freezing rain amount at all moments for each fine grid to obtain the cumulative freezing rain amount of all fine grids in the affected period; Quantitative assessment unit: used to determine the freezing rain risk level based on the available freezing rain disaster data in some areas, and to conduct a quantitative assessment of the intensity of freezing rain disasters in the entire hilly area.

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