An objective identification method for strong precipitation events forced by weak weather based on visualized information

Abstract

The application discloses a weak weather forcing heavy precipitation event objective identification method based on visual information, and comprises the following steps: obtaining data and visual information thereof, analyzing and utilizing the information to exclude the influence area of strong weather systems such as tropical cyclones, vortices, shear lines and fronts; further determining the area and time affected by the weak weather forcing in the research area, and identifying the corresponding heavy precipitation event; the application effectively continues the traditional prediction experience, and provides support for the mechanism research and prediction technology development of the weak weather forcing heavy precipitation event.

Description

TECHNICAL FIELD

[0001] The present application relates to the meteorological technical field, and in particular to a weak weather forcing heavy precipitation event objective identification method based on visual information. BACKGROUND

[0002] Precipitation research is of great significance for disaster prevention and mitigation. Under normal circumstances, strong precipitation events are often accompanied by obvious strong weather systems, such as fronts or vortices. However, when the weather system is not obvious, i.e. under the condition of weak weather forcing, the occurrence of heavy precipitation is rare. Therefore, the strong precipitation event under the condition of weak weather forcing is easy to be missed, which affects the timeliness of disaster prevention and mitigation, and may cause casualties and economic losses.

[0003] The identification of strong precipitation events under weak weather forcing usually relies on the subjective judgment of forecasters, which is based on the occurrence of strong precipitation events in a certain area without the influence of obvious or strong weather systems (such as tropical cyclones, fronts, vortices, shear lines, etc.). However, subjective identification is not only time-consuming and laborious, but also difficult to standardize, so it is urgent to develop an objective identification method to solve this problem.

[0004] Existing objective identification methods are inconsistent with the subjective judgment of forecasters. These methods usually only focus on a single physical quantity, ignoring the weather system characteristics relied on by subjective identification; in addition, existing methods regard strong precipitation events as independent grid events, without reflecting the spatio-temporal distribution characteristics of strong precipitation events consistent with subjective cognition. Therefore, an objective identification method for strong precipitation events under weak weather forcing based on subjective experience is urgently needed to continue traditional forecasting experience and provide support for future mechanism research and forecasting technology development for a large number of strong precipitation events under weak weather forcing. SUMMARY

[0005] The purpose of the present application is to provide an objective identification method for strong precipitation events under weak weather forcing based on visual information, which solves the problem that existing methods usually only focus on a single physical quantity, ignoring the weather system characteristics relied on by subjective identification, and solves the problem that existing methods regard strong precipitation events as independent grid events, without reflecting the spatio-temporal distribution characteristics of strong precipitation events consistent with subjective cognition.

[0006] Technical scheme: the objective identification method for strong precipitation events under weak weather forcing based on visual information provided by the present application comprises the following steps:

[0007] (1) obtaining data and its visual information acquisition and analysis;

[0008] (2) determining the position of the tropical cyclone center by using the tropical cyclone path data;

[0009] (3) Using the visualization information of equivalent potential temperature gradient, relative vorticity and thermal front parameter to determine the weather scale frontal influence area;

[0010] (4) Using the visualization information of relative vorticity and wind field, and using the density-based clustering method and skeleton extraction method to determine the weather scale shear line influence area;

[0011] (5) Using the visualization information of geopotential height to determine the weather scale vortex influence area;

[0012] (6) Taking the union of the influence areas of various weather systems at the same time, and taking the union of the influence areas of weather systems in the same day to determine the strong weather forcing influence area of the day, and finally taking the complement of the strong weather forcing influence area to determine the weak weather forcing influence area of the day;

[0013] (7) According to the hourly precipitation, the location and number of precipitation stations, strong precipitation events are determined, and if the strong precipitation event only occurs in the weak weather forcing influence area, it is identified as a weak weather forcing strong precipitation event.

[0014] Further, step (1) is as follows: obtaining precipitation, tropical cyclone path, 850 hPa equivalent potential temperature gradient size , thermal front parameter , wind (u, v), relative vorticity , and 500 hPa, 850 hPa and 925 hPa geopotential height data, and visualizing 500 hPa, 850 hPa and 925 hPa geopotential height and 850 hPa TFP; wherein the geopotential height interval is 2 dagpm, and only TFP=0 is plotted; output the position information of each contour point variable c, judge whether the first and last points of the contour are in the same position, if they are in the same position, it is a closed contour, if they are not in the same position, it is a non-closed contour; calculate the length of the contour; calculate the area of the closed contour; judge whether the grid points on a closed contour are inside other closed contours, and judge whether a closed contour is inside another closed contour.

[0015] Further, in step (2), the area within 1000 km of the tropical cyclone center is the tropical cyclone influence area.

[0016] Further, step (3) is as follows: remove and , select the contour line with a length of more than 1000 km, which is not closed and TFP=0, and determine the area within 200 km of the contour line as the weather scale frontal influence area.

[0017] Further, step (4) is as follows: using 850 hPa wind field to calculate relative vorticity , at the grid point, according to the wind direction to determine that it meets one of the three situations:

[0018] a1: and ;

[0019] a2: , and ;

[0020] a3: and , where the subscript i is eastwardly displaced by 1 grid point, and the subscript j is northwardly displaced by 1 grid point.

[0021] Further, according to the position of the cut edge point, using the density-based clustering method to merge the shear points into several groups, screening out the group with the distance between the two farthest grid points exceeding 500 km, using the skeleton extraction method to determine the main line, and finally determining the area within 200 km of the main line as the weather scale shear line influence area.

[0022] Further, step (5) is as follows: using 500 hPa, 850 hPa and 925 hPa potential height field, visualizing the isopleth information of the potential height field with an interval of 2 dagpm, merging the closed isopleths in a nested relationship into the same set, and determining the area surrounded by the isopleth set with the outermost closed isopleth surrounding an area exceeding 196000 km 2 as the weather scale vortex influence area.

[0023] Further, step (6) is as follows: taking the union of the influence areas of various weather systems at the same time, taking the union of the weather system influence areas of the same day, i.e. the strong weather forcing influence area of the day, and if the strong weather forcing influence area is less than 50% of the area of the research area, identifying the research area of the day as a weak weather forcing influence area.

[0024] Further, step (7) is as follows: using precipitation data to determine the grid point set with the maximum hourly precipitation reaching 20 mm, the distance being less than 100 km and the precipitation period overlapping, identifying a spatiotemporal continuous heavy precipitation event when the number of grid points in the set exceeds 3, determining the time of the earliest precipitation in the grid point set as the starting time of the event, and the time of the latest precipitation as the ending time of the event; if the entire heavy precipitation event only occurs on a weak weather forcing day, it is identified as a weak weather forcing heavy precipitation event.

[0025] ​​​The electronic device provided by the application comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, and the computer program realizes the objective identification method of the strong precipitation event forced by weak weather based on visual information according to any one of the application when loaded into the processor.

[0026] The storage medium provided by the application stores a computer program, and the computer program realizes the objective identification method of the strong precipitation event forced by weak weather based on visual information according to any one of the application when executed by a processor.

[0027] Beneficial effects: Compared with the prior art, the application has the following obvious advantages: the objective method is used to identify the strong precipitation event forced by weak weather based on subjective identification experience, which not only continues the artificial identification idea, but also avoids the problem that subjective identification is time-consuming and difficult to standardize, and aims to efficiently identify the strong precipitation event forced by weak weather, thereby providing strong support for future statistical research, mechanism analysis and forecast technology development of a large number of strong precipitation events forced by weak weather. BRIEF DESCRIPTION OF DRAWINGS

[0028] Figure 1 is a flowchart of the application;

[0029] Figure 2 is a daily change of the total number of times of the strong precipitation event forced by weak weather in the period from 2000 to 2022. DETAILED DESCRIPTION

[0030] The technical solutions of the application will be further described below with reference to the drawings.

[0031] The embodiment of the application provides an objective identification method of a strong precipitation event forced by weak weather based on visual information, as shown in Figure 1 , comprising the following steps:

[0032] The research area of the embodiment of the application is SEC in the southeast of China, and the research period is June-August in 2000-2022.

[0033] Step 1: data acquisition and acquisition and analysis of visual information: acquire precipitation, tropical cyclone path, 850hPa equivalent potential temperature gradient size , thermal front parameter (Thermal Frontal Parameter, ), wind (u, v) and relative vorticity and 925 hPa, and TFP at 850 hPa (only plot TFP=0) are visualized respectively, and the output visualization information variable c contains the variable value represented by each contour line, the position of the point on each contour line, etc. Based on this, (a) judge whether the first and last grid points of the contour line are at the same position, if they are at the same position, it is a closed contour line, if they are not at the same position, it is a non-closed contour line, (b) calculate the length of the contour line, (c) calculate the area of the closed contour line, (d) judge whether the grid points on a closed contour line are inside other closed contour lines, so as to judge whether a closed contour line is inside another closed contour line (nested relationship).

[0034] In this example, the precipitation data is CMORPH satellite precipitation estimation data, and the tropical cyclone path data comes from the Best Track dataset BST of the Tropical Cyclone Data Center; the temperature field, specific humidity field, wind field, and geopotential height field data at each height layer come from the ERA5 reanalysis data.

[0035] The time resolution of the BST dataset is sometimes every 6 hours, and sometimes every 3 hours, while the ERA5 and CMORPH datasets are every hour. For convenience of processing, assuming that the movement of the tropical cyclone center within 6 hours and 3 hours is a uniform straight line, interpolate the BST to every hour, so that the time resolution of each dataset is consistent. Since ERA5 does not have P = 850 hPa air temperature (unit: K) T, specific humidity q (unit: kg / kg) can be used to calculate. First, use q to calculate the water vapor pressure , based on e, the dew point temperature can be calculated; then use T to calculate the latent heat of condensation ratio ; based on q, e, , T and L, the equivalent potential temperature can be calculated. Thus, TFP can be calculated using . Wind field data can be used for diagnosis.

[0036] The visualization process of this example is implemented using Matlab. Taking the visualization of the geopotential height at 850 hPa as an example, the Matlab code is as follows:

[0037] [c, ~] = contour(longitude, latitude, geopotential_850hPa, 'LevelList', 0:2:1200);

[0038] Where, c is the output visualization information variable, longitude and latitude are the longitude and latitude respectively, geopotential_850hPa is the 850 hPa geopotential height (unit: dagpm), and the parameter LevelList is set to 0:2:1200, which means that an isopleth is drawn every 2 dagpm interval, and the isopleth information is contained in c.

[0039] Step 2: Determine the tropical cyclone center position using tropical cyclone path data, and then determine the area within 1000 km of the tropical cyclone center as the tropical cyclone influence area.

[0040] Step 3: Remove and areas, filter out isopleths with a length of more than 1000 km, which are not closed and TFP=0, and determine the area within 200 km of the isopleth as the weather scale frontal influence area.

[0041] Step 4: Calculate the relative vorticity using the 850 hPa wind field, and determine the grid point that meets one of the three conditions as a cyclonic shear point based on the wind direction at the grid point:

[0042] a1: and ;

[0043] a2: , and ;

[0044] a3: and , where subscript is 1 grid point east of i, is 1 grid point north of j, as a cyclonic shear point.

[0045] Then, according to the position of the shear edge point, use the density-based clustering method to merge the shear points into several groups, then filter out the group with the longest distance between the two farthest grid points of more than 500 km, and then use the skeleton extraction method to determine the main trunk line of these groups, and finally determine the area within 200 km of the main trunk line as the weather scale shear line influence area.

[0046] Step 5: Use the 500 hPa, 850 hPa and 925 hPa geopotential height fields, and visualize the isopleth information of the geopotential height field with an interval of 2 dagpm, and merge closed isopleths in a nested relationship into the same set, and in the closed isopleth set with isopleth values decreasing towards the center, determine the area surrounded by the isopleth set with the outermost closed isopleth with an area of more than 196000 km 2 (diameter about 500 km) as the weather scale vortex influence area.

[0047] Step 6: Take the union of the influence areas of various weather systems at the same time, and take the union of the influence areas of weather systems on the same day, that is, the strong weather forced influence area of the day, if the strong weather forced influence area is less than 50% of the SEC area, then the study area on the day is identified as weak weather forced.

[0048] Step 7: Using precipitation data, determine the grid set of the maximum hourly precipitation reaching 20mm, the distance less than 100km and the precipitation period overlapping, when the number of grid points in the set exceeds 3, it is identified as a spatiotemporal continuous heavy rainfall event, and then the earliest precipitation time in the grid set is determined as the starting time of the event, and the latest precipitation time is determined as the ending time of the event. If the entire heavy rainfall event only occurs on a weak weather forced day, it is identified as a weak weather forced heavy rainfall event.

[0049] As shown in Figure 2 1550 weak weather forced heavy rainfall events were identified from 2000 to 2022, the starting time mainly occurred from 14:00 to 18:00, all more than 150 events, among which 212 events reached the peak from 16:00 to 17:00. However, there were fewer weak weather forced heavy rainfall events at night and in the morning from 22:00 to 10:00, all less than 20 events, among which 2 events reached the minimum at 06:00.

[0050] The embodiment of the application also provides an electronic device, which comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the computer program realizes the weak weather forced heavy rainfall event objective identification method based on visual information according to any one of the embodiments when loaded into the processor.

[0051] The embodiment of the application also provides a storage medium, which stores a computer program, and the computer program realizes the weak weather forced heavy rainfall event objective identification method based on visual information according to any one of the embodiments when executed by a processor.

Claims

1. A method for objectively identifying a weak weather forced heavy precipitation event based on visualized information, characterized in that, The method comprises the following steps: (1) Acquisition and analysis of data and its visualization information; specifically as follows: acquisition of precipitation, tropical cyclone path, and equivalent potential temperature at 850 hPa. gradient magnitude Thermal front parameters Wind (u,v), relative vorticity The geopotential heights at 500 hPa, 850 hPa, and 925 hPa are plotted, along with the TFP at 850 hPa. The geopotential heights at 500 hPa, 850 hPa, and 925 hPa are visualized, as is the TFP at 850 hPa. The geopotential heights are plotted at intervals of 2 dagpm, with only TFP=0 plotted. The output visualization variable 'c' represents the position information of points on each contour line. The system determines whether the first and last grid points of a contour line are in the same position; if they are, it is a closed contour line; otherwise, it is an open contour line. The system calculates the length of the contour lines, calculates the area of ​​closed contour lines, and determines whether a grid point on a closed contour line is inside another closed contour line, and whether one closed contour line is inside another closed contour line. (2) determining the center position of the tropical cyclone by using the tropical cyclone path data; and taking the region within 1000 km of the center of the tropical cyclone as the tropical cyclone influence region; (3) Using the visualization information of equivalent potential temperature gradient, relative vorticity and thermal front parameter to determine the weather scale front influence area; Specifically as follows: removing the area of and , screening the isoline of TFP=0 with length more than 1000km, and determining the area within 200km from the isoline as the weather scale front influence area; (4) determining the weather scale shear line influence region by using the visualization information of the relative vorticity and the wind field, and using the density-based clustering method and the skeleton extraction method; (5) determining the weather scale vortex influence region by using the visualization information of the potential height; (6) taking the union of the influence regions of various weather systems at the same time, taking the union of the influence regions of the weather systems on the same day, determining the strong weather forcing influence region on the day, and finally taking the complement of the strong weather forcing influence region to determine the weak weather forcing influence region on the day; (7) determining the strong precipitation event according to the hourly precipitation, the location and the number of the precipitation stations, and identifying the weak weather forcing strong precipitation event if the strong precipitation event only occurs in the weak weather forcing influence region.

2. The method of claim 1, wherein the method is characterized in that, Step (4) is specifically as follows: relative vorticity is calculated using the 850 hPa wind field , at the grid points, according to the wind direction, one of the three situations is determined: ​ a1: and ; a2: , and ; a3: and where the footnotes is 1 grid point east of i, is 1 grid point north of j, the cyclonic shear point; According to the location of the edge cutting point, the edge cutting points are merged into several groups by using the density-based clustering method, the group with the distance between the farthest two grid points exceeding 500 km is screened out, the skeleton extraction method is used to determine the main line, and finally the region within 200 km of the main line is determined as the weather scale shear line influence region.

3. The method of claim 1, wherein the method is characterized by, Step (5) is specifically as follows: using 500 hPa, 850 hPa and 925 hPa potential height field, interval 2 dagpm visualizes the contour information of potential height field, combines the closed contours of nested relationship into the same set, in the closed contour set with centripetal decreasing contour value, determines the area surrounded by the outermost closed contour as the area surrounded by the contour set with the area exceeding 196000km 2 of the weather scale vortex influence area.

4. The method of claim 1, wherein the method is characterized by, Step (6) is specifically as follows: taking the union of the influence regions of various weather systems at the same time, taking the union of the influence regions of the weather systems on the same day, i.e. the strong weather forcing influence region on the day, and identifying the weak weather forcing influence region on the day if the strong weather forcing influence region is less than 50% of the area of the research region.

5. The method of claim 1, wherein the method is characterized by, Step (7) is specifically as follows: determining the grid point set with the maximum hourly precipitation reaching 20 mm, the distance being less than 100 km and the precipitation time period being overlapped, identifying the time and space continuous strong precipitation event if the number of grid points in the set exceeds 3, determining the starting time of the event as the time when the precipitation occurs earliest in the grid point set, and determining the ending time of the event as the time when the precipitation ends latest; and identifying the weak weather forcing strong precipitation event if the entire strong precipitation event only occurs in the weak weather forcing influence day.

6. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The computer program is loaded into the processor to realize the weak weather forcing strong precipitation event objective identification method based on the visualization information according to any one of claims 1-5.

7. A storage medium storing a computer program, characterized by The computer program is executed by the processor to realize the weak weather forcing strong precipitation event objective identification method based on the visualization information according to any one of claims 1-5.

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