A method for downburst identification based on near-ground divergence characteristics

Abstract

The present invention proposes a method for identifying downbursts based on near-ground divergence characteristics, comprising: step 1, obtaining horizontal wind field grid data (gridData); step 2, constructing a region block (block) with ideal divergence characteristics; step 3, comparing a region within the horizontal wind field grid data (gridData) with the region block (block) with ideal divergence characteristics; step 4, obtaining the difference between the region and the region block; and step 5, identifying downbursts based on the difference obtained in step 4. The method can use near-ground horizontal wind field data obtained by laser wind radar scanning to identify divergence characteristics and thus downbursts, and can also obtain data on the downburst's center point, range, and intensity.

Description

Technical Field

[0001] The present invention relates to the technical field of meteorological identification, and in particular to a method for realizing downburst identification based on near-ground divergence characteristics. Background Art

[0002] When a convective storm develops to a mature stage, the cold downdrafts in the thunderstorm clouds reach a considerable intensity, forming outflows when they reach the ground, and bringing thunderstorm winds. This local strong downdraft that causes disastrous winds on the ground is called a downburst. A downburst can cause strong wind shear near the ground, posing a great threat to the safety of aircraft takeoff and landing.

[0003] Generally speaking, downbursts are divided into two categories: microdownbursts and macrodownbursts. A microdownburst refers to a downburst with a horizontal divergence scale of less than 4 km and a duration of no more than 10 minutes; a macrodownburst refers to a downburst with a scale greater than or equal to 4 km and a duration of more than 10 minutes. Since microdownbursts are more harmful, research on microdownbursts is more in-depth. A large number of observational facts show that microdownbursts are mainly formed by the downward collapse of cold and heavy cloud tops in thunderstorm clouds.

[0004] Based on the different formation mechanisms of downbursts, there is also a way to distinguish downbursts into two categories: dry downbursts and wet downbursts. The former often occurs in severe storms, mainly because ice crystals in the clouds sink into a drier environment and quickly evaporate, resulting in a strong sinking cold air mass, which then sinks to the near-ground layer and radiates around. The latter is believed to be caused by cold sinking air currents in heavy rainfall. The former has little or no precipitation on the ground, while the latter occurs in heavy rainfall.

[0005] Based on the hazards of downbursts, it is necessary to effectively identify downbursts.

[0006] For example, the Chinese invention patent application document with the number CN202110111297.9 discloses a downburst identification method based on the near-ground divergence field, which includes the following steps:

[0007] S01. Extract radial velocity and reflectivity factor data of all echoes within the detection range of Doppler weather radar and perform quality control on radar data.

[0008] S02. For the convection echo obtained in step S01, extract the multi-elevation radial velocity data thereof, and calculate the multi-elevation divergence field using the linear least squares method;

[0009] S03, for the multi-elevation divergence field calculated in step S02, using the set multiple thresholds, including the distance range threshold and the reflectivity factor threshold, to perform preliminary screening to obtain the multi-elevation divergence field to be identified for use in the next step;

[0010] S04. Using the previously collected and collated dataset of typical historical Doppler weather radar observations, calculate the multi-elevation divergence field of typical historical downbursts according to steps S01-S03 above, and obtain the convergence-divergence threshold value through threshold processing as a basis for judging downbursts.

[0011] S05. The multi-elevation divergence fields of the convective echoes selected in step S03 are tested as follows: the elevation divergence field of the lowest layer is tested, and the maximum value of the divergence in the divergence field within the convective echo range is extracted. If the maximum divergence meets the corresponding divergence threshold extracted in step S04, convergence identification is then performed on the divergence fields of the middle and high layers. If a convergence field is identified in the middle and high layers, the probability of a downburst is determined to be high. If no convergence field is identified in the middle and high layers, the probability of a downburst is determined to be relatively low.

[0012] S06. If the maximum divergence value extracted at the lowest elevation angle in step S05 does not meet the divergence threshold extracted in step S04, then the maximum divergence value in the divergence field of the upper layer of the lowest elevation angle is extracted to determine whether the maximum divergence value is greater than the corresponding divergence divergence threshold extracted in step S04. If the maximum elevation angle divergence value of the upper layer of the lowest elevation angle meets the corresponding divergence divergence threshold extracted in step S04, then convergence identification is performed on the divergence field of the middle and high layers. If the convergence field is identified in the middle and high layers, the probability of a downburst is determined to be high. If the convergence field is not identified in the middle and high layers, the probability of a downburst is determined to be low. If the maximum elevation angle divergence value of the second layer does not meet the corresponding divergence divergence threshold extracted in step S04, it is determined to be a non-downburst.

[0013] Although the existing technology discloses a downburst identification method based on the near-ground divergence field, in actual application, due to the complexity of the actual wind field, mid- and high-level convergence may not be detected. Therefore, this method may have misjudgments when using mid- and high-level convergence to judge the probability of a downburst. At the same time, when calculating the multi-elevation divergence field, the size of the selected area is determined according to the length of several radial and tangential grid points in polar coordinates. That is, the farther the area is from the radar, the larger it is, so there is an error in the calculated divergence.

[0014] In view of the above-mentioned technical problems existing in the prior art, the present invention provides a method for identifying downbursts based on near-ground divergence characteristics. Summary of the Invention

[0015] The present invention proposes a method for downburst identification based on near-ground divergence characteristics.

[0016] The present invention adopts the following technical solutions:

[0017] A method for downburst identification based on near-ground divergence characteristics comprises:

[0018] Step 1, obtain horizontal wind field grid data gridData;

[0019] Step 2: construct a block with ideal divergence characteristics;

[0020] Step 3: Compare a certain area in the horizontal wind field grid data gridData with a block of areas with ideal divergence characteristics;

[0021] Step 4, obtaining the difference between a certain area and the block;

[0022] Step 5: Identify the downburst based on the difference between the area obtained in step 4 and the block.

[0023] Furthermore, in step 1, the radial data of the horizontal wind field near the ground is obtained by performing a low-elevation-angle PPI (Plan Position Indicator) scan using a laser wind measuring radar, and the horizontal wind field grid data gridData is obtained by interpolating the radial data.

[0024] Furthermore, the horizontal wind field grid data gridData includes grid point coordinates (i, j), wind speed speed and wind direction angle.

[0025] Furthermore, in step 2, the block is an n×n block, where n is an odd number. The center point of the block is used as the origin of a plane rectangular coordinate system. A coordinate system is established to obtain the coordinates (x, y) of each point. The wind direction angle value of each point block (x, y) in the block is calculated as follows:

[0026] block(x, y)=(180+PolarAngle(x, y))mod 360...(1);

[0027] Where mod represents the modular operation, which takes the remainder after division by 360 and limits the angle value to between 0 and 360. PolarAngle(x,y) is a function that calculates the angle value of a point (x,y) in a rectangular coordinate system in a polar coordinate system.

[0028] Furthermore, in step 4, after obtaining the wind direction angle value of each point block(x,y) in the block, a feature search is performed on the horizontal wind field grid data gridData. For any point gridData(i,j) in the horizontal wind field grid data gridData, the difference between the area centered at point gridData(i,j) and the block is calculated using the following formula:

[0029]

[0030] Among them, angle(i+x,j+y) represents the wind direction angle value of gridData(i+x,j+y), (i,j) is the coordinate value of gridData and its value is fixed, (x,y) is the coordinate value of block and its value is all coordinate values ​​of block except (0,0), m=n*n-1, gridData(i,j) and block(0,0) do not participate in the calculation, AngleInterval() is the shortest angle interval between two angles and its value is a positive number, diff(i,j) is the angle of all points corresponding to the area and the area block after removing the center point The average value of the difference. When any gridData(i+x,j+y) exceeds the grid data range or the data at this point is invalid, diff(i,j) will no longer be calculated. At the same time, when speed(i+x,j+y) is less than a given minimum speed threshold minSpeedThreshold, it will also no longer be calculated. speed(i+x,j+y) represents the wind speed of gridData(i+x,j+y), where (i,j) is the coordinate value of gridData and its value is fixed, (x,y) is the coordinate value of block and its value is all coordinate values ​​of block except (0,0).

[0031] Furthermore, in step 5, a downburst data set downBursts is set, and each downburst data set downBurst in the set includes the downburst center point centerPoint, the maximum speed point maxSpeedPoint, the average speed avgSpeed ​​in the area, the maximum speed maxSpeed ​​in the extended area, the area range range and the difference value diff. The difference value threshold diffThreshold is set. When diff(i,j) is less than diffThreshold and the value of diff(i,j) is the smallest among all points in the area with (i,j) as the center point, the point is identified as the downburst center point, and a corresponding downBurst is constructed and added to downBursts. The centerPoint and diff are known, the initial range is the default minimum range of 5, and the maximum range can be obtained by calculation. After the range is determined, the maxSpeedPoint, avgSpeed ​​and maxSpeed ​​are obtained by calculation.

[0032] Furthermore, in step 5, set the area range range to 5, set n to n1, where n1 = n + 2, and obtain a new area block block and the corresponding new difference value diff. If diff is less than diffThreshold, range is equal to n1. At the same time, the value of n1 is added to 2 and the calculation is repeated until the difference value diff is greater than diffThreshold, or range is greater than the given maximum range maxRange. No further calculation is performed, and the obtained area range range is the maximum range where the divergence feature exists.

[0033] Furthermore, in step 5, the average speed is calculated based on the range. avgSpeed ​​is the average speed of all points in the range except the center point, so:

[0034]

[0035] Set an enlargeRange, and expand the size of enlargeRange outward on the basis of the regional range range. Find the maxSpeed ​​and the corresponding maxSpeedPoint in this enlarged area. If the maxSpeed ​​is less than the given maximum speed threshold maxSpeedThreshold, then remove the downBurst corresponding to the centerPoint from downBursts.

[0036] Compared with the prior art, the present invention has the following advantages:

[0037] The method for identifying downbursts based on near-ground divergence characteristics described in the present invention can use near-ground horizontal wind field data obtained by laser wind radar scanning to identify divergence characteristics and thus identify downbursts, and can obtain data on the center point, range and intensity of the downburst. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is a schematic diagram of the divergence feature described in an embodiment of the present invention;

[0039] Figure 2 It is a flowchart of a method for realizing downburst identification based on near-ground divergence characteristics according to an embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention is further described in detail below with reference to the accompanying drawings and specific implementation methods. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other unless there is a conflict.

[0041] Example

[0042] like Figure 1 As shown in FIG, the main idea of ​​the method for realizing downburst identification based on near-ground divergence characteristics is to judge whether the wind direction in a region of the near-ground horizontal wind field presents divergence characteristics. In the figure, the circle is the center point of the downburst, the square is the point with the maximum speed, the solid circle with the center point of the downburst as the center is the range of the downburst, and the dotted circle with the center point of the downburst as the center is the outward expansion range. It can be seen from the figure that the wind vector in the red solid circle presents a more obvious divergence characteristic, and the wind speed between the two circles is also faster. The downburst can be identified by these characteristics. If there is a divergence characteristic, a downburst occurs in this area. Figure 2 As shown in FIG, the method for realizing downburst identification based on near-ground divergence characteristics is as follows: first, a laser wind measuring radar is used to perform a low-elevation PPI scan near the ground to obtain radial data of the near-ground horizontal wind field, and then the horizontal wind field grid data gridData is obtained by interpolation, including the grid point coordinates (i, j), wind speed speed and wind direction angle. In order to identify the divergence characteristics from gridData, it is necessary to compare it with the regional block block with ideal divergence characteristics. The smaller the difference between a certain area in gridData and the block, the more likely the area is to be divergent. The block is a block of size n×n, where n is an odd number. The center point of the block is used as the origin of the plane rectangular coordinate system. The coordinate system is established and the coordinates (x, y) of each point are obtained. The calculation formula of the wind direction angle value of each point block (x, y) is as follows:

[0043] block(x,y)=(180+PolarAngle(x,y))mod 360;

[0044] PolarAngle(x,y) is a function that calculates the angle of a point (x,y) in a rectangular coordinate system in a polar coordinate system. Because the polar coordinate system and the wind direction coordinate system are different, the angle must be converted to obtain the wind direction. 180 is added to the obtained angle value, and a modulo operation is performed to limit the value to within 360. The final result is the wind direction angle at that point. Because the center point of ideal divergence has no direction, the value of block(0,0) is meaningless.

[0045] After obtaining the wind direction angle value of each point block(x,y), perform feature search on gridData. For any point gridData(i,j), the difference between the area centered at gridData(i,j) and the block is calculated as follows:

[0046]

[0047] Where m = n*n-1, gridData(i,j) and block(0,0) are not included in the calculation, AngleInterval() is the shortest angle interval between two angles and its value is a positive number, diff(i,j) is the average of the angle differences of all points corresponding to the two areas after excluding the center point. If any gridData(i+x,j+y) exceeds the grid data range or the data of the point is invalid, diff(i,j) will not be calculated. At the same time, if speed(i+x,j+y) is less than a given minimum speed threshold minSpeedThreshold, it will not be calculated either.

[0048] Suppose there is a downburst data set downBursts. Each downburst data set in the set contains data such as the downburst center point centerPoint, the maximum speed point maxSpeedPoint, the average speed avgSpeed ​​in the area, the maximum speed maxSpeed ​​in the extended area, the area range range and the difference value diff. These values ​​can be used for further analysis to ensure the accuracy of downburst identification.

[0049] Given a difference value threshold diffThreshold, if diff(i,j) is less than diffThreshold and the value of diff(i,j) is the smallest among all points in the area centered at (i,j), then the point is identified as the downburst center point, and a corresponding downBurst is constructed and added to downBursts. The centerPoint and diff are already known, and the other values ​​need to be calculated separately.

[0050] In this embodiment, the value of n is 5 in the actual calculation. This is because when the value is 3, the value of diff(i, j) cannot effectively distinguish whether there is a divergence feature. When the value is 5, it can be distinguished and the amount of calculation is minimized. However, this can only determine whether the divergence center point is within the area, but cannot determine the range of the divergence. Therefore, after obtaining downBurst, the range value needs to be calculated. Set the range to 5, set n to n+2, and then calculate the new block and the corresponding new diff. If diff is less than diffThreshold, range is equal to the new n, and the value of n is added by 2 and the calculation is repeated until diff is greater than diffThreshold, or range is greater than the given maximum range maxRange, then no further calculation is performed. The final range is the maximum range with a divergence feature. After obtaining the range, the average speed can be calculated. avgSpeed ​​is the average speed of all points except the center point in the area with range as the range:

[0051]

[0052] Given an enlargeRange, expand the size of enlargeRange outward based on range, find maxSpeed ​​and the corresponding maxSpeedPoint in this enlarged area, and if maxSpeed ​​is less than the given maximum speed threshold maxSpeedThreshold, remove the downBurst corresponding to centerPoint from downBursts.

[0053] The present invention is not limited to the above-described embodiments. The above-described embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims.

Claims

1. A method for downburst identification based on near-ground divergence characteristics, characterized in that: include: Step 1: Use a laser wind radar to perform a low-elevation PPI scan to obtain radial data of the horizontal wind field near the ground, and obtain horizontal wind field grid data gridData by interpolating the radial data; Step 2: construct a block with ideal divergence characteristics; Step 3: Compare a certain area in the horizontal wind field grid data gridData with a block of areas with ideal divergence characteristics; Step 4, obtaining the difference between the certain area and the block; Step 5: Identify downbursts based on the difference obtained in step 4: suppose there is a downburst data set downBursts, where each downburst data set downBurst in the set contains the downburst center point centerPoint, the maximum speed point maxSpeedPoint, the average speed avgSpeed ​​in the area, the maximum speed maxSpeed ​​in the extended area, the area range range, and the difference value diff. Suppose the difference value threshold diffThreshold. If diff(i,j) is less than diffThreshold, and the value of diff(i,j) is the smallest among all points in the area with (i,j) as the center point, then the point is identified as the downburst center point, and a corresponding downBurst is constructed and added to downBursts.

2. The method for downburst identification based on near-ground divergence characteristics according to claim 1, characterized in that: The horizontal wind field grid data gridData includes the grid point coordinates (i, j), wind speed speed and wind direction angle.

3. The method for downburst identification based on near-ground divergence characteristics according to claim 1, characterized in that: In step 2, the block is an n×n block, where n is an odd number. The center point of the block is used as the origin of a plane rectangular coordinate system. A coordinate system is established to obtain the coordinates (x, y) of each point. The wind direction angle value of each point (x, y) in the block is calculated as follows: ……（1）； Where mod represents the modular operation, which takes the remainder after division by 360 and limits the angle value to between 0 and 360. PolarAngle(x,y) is a function that calculates the angle value of a point (x,y) in a rectangular coordinate system in a polar coordinate system.

4. The method for downburst identification based on near-ground divergence characteristics according to claim 3 is characterized in that: In step 4, after obtaining the wind direction angle value of each point block(x,y) in the block, a feature search is performed on the horizontal wind field grid data gridData. For any point gridData(i,j) in the horizontal wind field grid data gridData, the difference between the area centered at point gridData(i,j) and the block is calculated as follows: ……（2）； Among them, angle(i+x,j+y) represents the wind direction angle value of gridData (i+x,j+y), (i,j) is the coordinate value of gridData and its value is fixed, (x,y) is the coordinate value of block and its value is all coordinate values ​​of block except (0,0), m=n*n-1, gridData(i,j) and block(0,0) do not participate in the calculation, AngleInterval() is the shortest angle interval between two angles and its value is a positive number, diff(i,j) is the average of the angle differences between the area and all points corresponding to the area block after excluding the center point. If any gridData(i+x,j+y) exceeds the grid data range or the data of the point is invalid, diff(i,j) is no longer calculated.

5. The method for downburst identification based on near-ground divergence characteristics according to claim 1, characterized in that: In step 5, set the area range range to 5, set n to n1, where n1=n+2, and obtain the new area block block and the corresponding new difference value diff. If diff is less than diffThreshold, range is equal to n1, and the value of n1 is added to 2 and the calculation is repeated until the difference value diff is greater than diffThreshold, or range is greater than the given maximum range maxRange. In this case, no further calculation is performed, and the obtained area range range is the maximum range with divergence features.

6. The method for downburst identification based on near-ground divergence characteristics according to claim 5, characterized in that: In step 5, the average speed is calculated based on the range. avgSpeed ​​is the average speed of all points in the range except the center point. Then: ……（3）； Set an enlargeRange, and expand the size of enlargeRange outward on the basis of the regional range range. Find the maxSpeed ​​and the corresponding maxSpeedPoint in this enlarged area. If the maxSpeed ​​is less than the given maximum speed threshold maxSpeedThreshold, remove the downBurst corresponding to the centerPoint from downBursts.

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