Precipitation estimation method and device based on weather radar network hybrid scanning

Abstract

The present invention provides a precipitation estimation method and device based on weather radar networking hybrid scanning. The method comprises: constructing an initial data grid according to the projection mode, networking range and resolution of radar networking precipitation estimation, and constructing an elevation data grid according to the terrain elevation data of the radar networking area with the same projection mode, networking range and resolution; converting the coordinates of the initial data grid into longitude and latitude coordinates, calculating the intersection height of the geocentric line of the longitude and latitude coordinates of the initial data grid and the elevation scanning data of each radar in the radar networking area; selecting the range between the intersection heights and the preset near-surface height in the corresponding elevation data grid according to the intersection heights corresponding to each radar H The latest scan data is used as the scan data of the initial data grid for precipitation assessment. The present invention improves the precipitation estimation capability of the weather radar network.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a precipitation estimation method and device based on weather radar networking hybrid scanning. Background Art

[0002] At present, the implementation methods of precipitation estimation in weather radar networks are mainly based on two types: first calculating the precipitation estimation products of each radar station and then networking and integrating them, and first networking and integrating and then calculating the precipitation estimation products. The first type first calculates the precipitation estimation products of each radar station participating in the network, which is to network and integrate the precipitation estimation products of each single station according to the spatial position. When fusing precipitation data, the maximum value or average value algorithm is used to process the overlapping areas of radar detection. The second type first networks and integrates radar data, and then inverts precipitation estimation methods through the fused data.

[0003] The existing weather radar network precipitation estimation methods have the following main shortcomings. First, when calculating the single-station precipitation estimation product, the area near the radar center is affected by the current urban development, especially the X-band small radars are mostly located in the city. Although the elevation angle data is used, it may still be affected by terrain factors such as ground pollution and obstruction, which will cause deviations in precipitation estimation. In addition, with the diversification of the current radar volume scanning mode, the radar volume scanning elevation angle is also changing, and the fixed hybrid scanning reflectivity HSR (Hybrid Scan Reflectivity) processing method is not applicable. At the same time, in the current weather radar network precipitation implementation method, the single-station precipitation estimation product is calculated first, and then the precipitation data is fused. For the processing of the radar scanning overlapping area, whether the maximum value or average value processing method is used, the precipitation estimation value obtained is most likely obtained by the effective scanning data of the non-closest surface, and the precipitation estimation result will be biased. In particular, when there is a zero-degree layer area in the mixed scanning of the radar single-station precipitation estimation, the precipitation overestimation problem in the zero-degree layer will cause a large deviation.

[0004] Second, precipitation is estimated after the network radar data is fused, and data is selected in the overlapping observation area of ​​multiple radars. First, the radar lowest layer elevation scanning data in the overlapping area is easily affected by the blocking factors such as terrain and buildings, resulting in the radar network precipitation estimation precipitation being significantly underestimated compared with the actual observation. Secondly, the precipitation estimation product inverted by the maximum value data of the radar reflectivity factor in the overlapping area is greatly affected by different seasons. For example, in summer, the radar strong centroid echo height is usually around 8 km in strong convection, and the precipitation or hail is affected by the evaporation of hot air during the falling process, and the intensity is significantly weakened, resulting in the estimated precipitation being significantly overestimated compared with the actual observation. In spring and autumn, under the influence of the zero-degree layer, the inverted precipitation estimate will also be overestimated than the actual. Thirdly, selecting the radar reflectivity factor data at a preset height in the overlapping area to invert the precipitation estimation product is equivalent to using CAPPI (reflectivity factor of 360-degree scanning of radar at a specific height) data, that is, a layer of plane data at a fixed height, which is the altitude. Since the inverted precipitation estimate is closer to the actual situation when the data is closer to the surface, the terrain difference will cause the selected height to not fully meet the near-ground data. Summary of the invention

[0005] The present invention provides a precipitation estimation method and device based on weather radar networking hybrid scanning, which are used to solve the defect of deviation in precipitation estimation of weather radar networking hybrid scanning in the prior art, and to improve the precipitation estimation capability of weather radar networking.

[0006] The present invention provides a precipitation estimation method based on weather radar network hybrid scanning, comprising:

[0007] According to the projection mode, networking range and resolution of radar network precipitation estimation, an initial data grid is constructed, and according to the terrain elevation data of the radar network area, an elevation data grid is constructed with the same projection mode, networking range and resolution;

[0008] Convert the coordinates of the initial data grid into longitude and latitude coordinates, and calculate the intersection height of the geocentric line of the longitude and latitude coordinates of the initial data grid and the elevation scanning data of each radar in the radar networking area;

[0009] According to the intersection heights corresponding to the radars, the scanning data whose range between the intersection heights and the nearest preset near-surface height H in the corresponding elevation data grid is selected as the scanning data of the initial data grid for precipitation assessment.

[0010] According to a precipitation estimation method based on weather radar network hybrid scanning provided by the present invention, the scanning data corresponding to the nearest intersection height is used as the scanning data of the initial data grid for precipitation evaluation, including:

[0011] In the case that the latest scanning data is dual-polarization radar scanning data, all dual-polarization quantities of the latest scanning data are used as scanning data of the initial data grid for precipitation assessment.

[0012] According to a precipitation estimation method based on weather radar network hybrid scanning provided by the present invention, the method comprises: selecting scanning data whose scanning position is closest to a preset near-surface height H in the corresponding elevation data grid according to the intersection height corresponding to each radar as scanning data of the initial data grid for precipitation evaluation, including:

[0013] In the case where the most recent scanning data is single polarization radar scanning data, it is determined whether there is dual polarization radar scanning data in the range between the intersection heights and intersecting with the redundant selection range HT / 2 to H + T / 2, where T is the data redundancy thickness;

[0014] If dual-polarization radar scanning data exists, using the dual-polarization radar scanning data as scanning data of the initial data grid for precipitation assessment;

[0015] If the dual-polarization radar scanning data does not exist, the single-polarization radar scanning data is used as the scanning data of the initial data grid for precipitation assessment.

[0016] According to a precipitation estimation method based on weather radar network hybrid scanning provided by the present invention, the range between the intersection heights and the scanning data closest to the preset near-surface height H in the corresponding elevation data grid are selected as the scanning data of the initial data grid for precipitation evaluation, including:

[0017] In the case where the scanning data of the initial data grid is single polarization radar scanning data, precipitation assessment is performed based on the single polarization radar scanning data using the Z / R relationship.

[0018] According to a precipitation estimation method based on weather radar network hybrid scanning provided by the present invention, the range between the intersection heights and the scanning data closest to the preset near-surface height H in the corresponding elevation data grid are selected as the scanning data of the initial data grid for precipitation evaluation, including:

[0019] In a case where the scanning data of the initial data grid is dual-polarization radar scanning data, precipitation assessment is performed using a quantitative precipitation estimation algorithm according to the dual-polarization radar scanning data.

[0020] According to a precipitation estimation method based on weather radar network hybrid scanning provided by the present invention, the precipitation assessment is performed using a quantitative precipitation estimation algorithm according to the dual-polarization radar scanning data, comprising:

[0021] When the radar reflectivity factor in the dual-polarization radar scanning data is greater than a first preset threshold value and the radar differential propagation phase shift rate is greater than a second preset threshold value, determining that the precipitation type is non-liquid precipitation, and calculating the precipitation rate according to the radar reflectivity factor;

[0022] When the radar reflectivity factor is less than or equal to a first preset threshold, or the radar differential propagation phase shift rate is less than or equal to a second preset threshold, the precipitation type is determined to be liquid precipitation, and the precipitation rate is calculated according to the radar differential propagation phase shift rate.

[0023] According to a precipitation estimation method based on weather radar network hybrid scanning provided by the present invention, the radar reflectivity factor Z is calculated by the following formula: H Calculate the precipitation rate R:

[0024] ;

[0025] According to the radar differential propagation phase shift rate K, the following formula is used DP Calculate the precipitation rate R:

[0026] .

[0027] The present invention also provides a precipitation estimation device based on weather radar networking and hybrid scanning, comprising:

[0028] A construction module is used to construct an initial data grid according to the projection mode, networking range and resolution of radar network precipitation estimation, and to construct an elevation data grid according to the terrain elevation data of the radar network area with the same projection mode, networking range and resolution;

[0029] A calculation module, used for converting the coordinates of the initial data grid into longitude and latitude coordinates, and calculating the intersection height of the geocentric line of the longitude and latitude coordinates of the initial data grid and the elevation scanning data of each radar in the radar networking area;

[0030] The selection module is used to select the scanning data closest to the preset near-surface height H in the corresponding elevation data grid and the range between the intersection heights corresponding to each radar as the scanning data of the initial data grid for precipitation assessment.

[0031] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the precipitation estimation method based on hybrid scanning of a weather radar network as described in any one of the above is implemented.

[0032] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the precipitation estimation method based on hybrid scanning of a weather radar network as described in any one of the above is implemented.

[0033] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned precipitation estimation methods based on weather radar network hybrid scanning.

[0034] The precipitation estimation method and device based on weather radar network hybrid scanning provided by the present invention introduce terrain elevation data on the basis of radar networking, obtain multi-height layer data of networked radar hybrid scanning based on terrain, construct an initial data grid based on the networked observation of multiple radars, select a near-surface range according to the terrain data to mix the networked radar scanning data, realize the selection of near-surface data in the overlapping observation area of ​​multiple radars, estimate precipitation based on the effective scanning data of the adjacent surface under the terrain, the networked hybrid scanning data can effectively avoid the influence of ground object occlusion, and the data selection is not limited by the radar volume scanning method. Through the setting of the near-surface range, the idea of ​​the nearest effective scanning data of the surface can be applied in the entire range of the radar networking area, thereby optimizing the selection of application data of the precipitation estimation algorithm and improving the precipitation estimation capability of the weather radar network. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 It is a schematic diagram of the VCP21 volume scanning mode in the precipitation estimation method based on weather radar networking hybrid scanning provided by the present invention;

[0037] Figure 2 This is one of the flow charts of the precipitation estimation method based on weather radar network hybrid scanning provided by the present invention;

[0038] Figure 3 It is a schematic diagram of terrain grid elevation in the precipitation estimation method based on weather radar network hybrid scanning provided by the present invention;

[0039] Figure 4 It is a schematic diagram of the intersection points of all elevation scanning data of multiple radars in the precipitation estimation method based on weather radar network hybrid scanning provided by the present invention;

[0040] Figure 5It is a schematic diagram of hybrid scanning data of near-surface radar networks of different terrains in the precipitation estimation method based on hybrid scanning of weather radar networks provided by the present invention;

[0041] Figure 6 This is the second flow chart of the precipitation estimation method based on weather radar network hybrid scanning provided by the present invention;

[0042] Figure 7 It is a schematic diagram of the process of dual-polarization radar precipitation intensity estimation in the precipitation estimation method based on weather radar networking hybrid scanning provided by the present invention;

[0043] Figure 8 It is a structural schematic diagram of a precipitation estimation device based on weather radar networking hybrid scanning provided by the present invention;

[0044] Fig. 9 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Heavy precipitation affects all aspects of life and social economy, such as agriculture, hydropower generation, and outdoor travel. The continuous occurrence of heavy precipitation may lead to various disasters such as urban waterlogging, landslides, and mud-rock flows. As an effective monitoring method for severe weather processes, Doppler weather radar has high temporal and spatial resolution and has broad application prospects in quantitative precipitation monitoring and short-term forecasting.

[0047] Single-station radar is greatly affected by factors such as observation range, clutter interference, terrain obstruction and equipment maintenance during detection, especially in low-altitude areas. The influence of the earth's curvature and terrain causes the radar signal to be unable to effectively cover the ground precipitation area at long distances.

[0048] With the high-quality development of meteorology, the number of meteorological radars is increasing. In order to overcome the limitations of a single radar, multi-radar networking technology has been widely studied and applied. By deploying multiple radars in an area and observing together, wider spatial coverage and more comprehensive data acquisition can be achieved. This networking method can effectively make up for the shortcomings of a single radar in terms of spatial resolution, coverage and timeliness.

[0049] The calculation of precipitation estimation products of radar single station is mainly based on hybrid scanning method, and its main idea is to select effective scanning data of the nearest neighboring surface that excludes the influence of ground objects. Taking VCP21 volume scanning as an example, 3.4º data is used in the range of 0-20.35km, and 2.4º, 1.5º, and 0.5º scanning data are used in the range of 20.35-35.15km, 35.15-50km, and beyond 50km, respectively. Among them, Figure 1 (a) is the elevation side view of VCP21 in volume scanning mode. Figure 1 (b) is a schematic diagram of single-station hybrid scanning.

[0050] After the network radar data is fused, precipitation estimation is performed. There are many methods for selecting data in the overlapping observation area of ​​multiple radars, usually the following: 1. Select the radar reflectivity factor (Z) of the lowest radar elevation scan of the observation radar in the overlapping area. H )(dBZ) data; 2. Select the radar reflectivity factor (Z H )(dBZ) maximum value data; 3. Select the radar reflectivity factor (Z) of a preset height in the overlapping area H )(dBZ) data; 4. Select the maximum radar reflectivity factor (Z) between the center of two or more radar beams, the bottom layer and the top layer in the overlapping area. H )(dBZ) data.

[0051] Taking the terrain elevation map of a certain area as an example, it can be seen that the northern region has a lower altitude, while the central and southern regions are basically above 600 m, and some areas are above 1000 m. If the network radar selects data below 600 m above sea level, the precipitation estimation error in the central and southern regions will be extremely large, and if the network data above 1000 m above sea level is selected to invert the precipitation estimation, the error in the northern region will be large, so it is not possible to always select the near-surface radar network data. Finally, the maximum radar reflectivity factor between the bottom and high layers of the beam center of two or more radars in the overlapping area is also affected by the terrain, and it is impossible to select near-surface data under terrains of different altitudes, resulting in overestimation of precipitation estimation.

[0052] Combine the following Figure 2 A precipitation estimation method based on weather radar network hybrid scanning of the present invention is described, comprising:

[0053] Step 301, constructing an initial data grid according to the projection mode, networking range and resolution of radar network precipitation estimation, and constructing an elevation data grid according to the terrain elevation data of the radar network area with the same projection mode, networking range and resolution;

[0054] Select the projection mode of radar network precipitation estimation products. The projection mode of weather radar network products is generally Mercator projection. In this projection mode, construct the initial data grid of network precipitation rate according to the network range and resolution.

[0055] Obtain the terrain elevation data of the networking area, and construct the elevation data grid of the networking area with the same projection method, resolution and range as the network precipitation rate. Figure 3 As shown, different grid points use different colors to represent different height values.

[0056] Step 302, converting the coordinates of the initial data grid into longitude and latitude coordinates, and calculating the intersection height of the geocentric line of the longitude and latitude coordinates of the initial data grid and the elevation scanning data of each radar in the radar networking area;

[0057] The coordinates of the initial data grid constructed under the projection system are converted into longitude and latitude coordinates. For the longitude and latitude coordinates of each initial data grid, the intersection height of its geocentric line and all elevation scanning data of each radar in space is calculated, such as Figure 4 shown.

[0058] Step 303, according to the intersection heights corresponding to each radar, select the scanning data whose range between the intersection heights and the nearest preset near-surface height H in the corresponding elevation data grid as the scanning data of the initial data grid for precipitation assessment.

[0059] Select near-surface height data. Assuming the near-surface height above the terrain height is H and the data redundancy thickness is T, the redundancy selection range is HT / 2 to H + T / 2.

[0060] According to the preset near-surface height H and the intersection height corresponding to each radar, the mixed scanning data of the networked radars of the initial data grid is selected. When selecting scanning data, the principle is to be closest to the preset near-surface height H. The preset near-surface height H selects the optimal value based on the elevation data of the detection area.

[0061] Figure 5 This is a schematic diagram of the undulating terrain. The upper gray layer is used to filter out the near-surface height under different terrains. The networked radar obtains this gray near-surface data through hybrid scanning for precipitation estimation inversion.

[0062] The maximum and minimum intersection heights of the geocentric line of the latitude and longitude coordinates of the initial data grid and the elevation scan data of each radar can be determined. The difference between the maximum intersection height and the minimum intersection height is divided by 2 to obtain the middle height within the range between the intersection heights. The difference between the middle height and the preset near-surface height H, as well as the difference between the maximum intersection height, the minimum intersection height and the preset near-surface height H are calculated, and the radar scan data whose weighted sum of the three differences is less than the specified value is used as the scan data of the initial data grid for precipitation assessment.

[0063] For example, assuming that the preset near-surface height H is Figure 4 The height h i+3 , the minimum intersection height of radar 1 is h i , the maximum intersection height is h i+2 , the middle height is h i+1 The minimum intersection height of radar 2 and radar 3 is h i , the maximum intersection height is h i+7 , the middle height is h i+3 Finally, the scanning data of radar 2 and radar 3 are selected as the scanning data of the initial data grid.

[0064] This embodiment introduces terrain elevation data on the basis of radar networking, obtains multi-height layer data of networked radar hybrid scanning based on terrain, constructs an initial data grid based on the networked observation of multiple radars, selects the near-surface range according to the terrain data to mix the networked radar scanning data, realizes the selection of near-surface data in the overlapping observation area of ​​multiple radars, and estimates the precipitation based on the effective scanning data of the adjacent surface under the terrain. The networked hybrid scanning data can effectively avoid the influence of ground obstruction. At the same time, the data selection is not limited by the radar volume scanning method. Through the setting of the near-surface range, the idea of ​​the nearest effective surface scanning data can be applied in the entire range of the radar networking area, thereby optimizing the selection of application data of the precipitation estimation algorithm and improving the precipitation estimation capability of the weather radar network.

[0065] Based on the above embodiment, the method of using the scan data corresponding to the height of the nearest intersection as the scan data of the initial data grid to perform precipitation assessment in this embodiment includes:

[0066] In the case that the latest scanning data is dual-polarization radar scanning data, all dual-polarization quantities of the latest scanning data are used as scanning data of the initial data grid for precipitation assessment.

[0067] If scanning data of multiple radars are selected as scanning data of the initial data grid, the dual-polarization radar scanning data is preferentially selected as scanning data of the initial data grid for precipitation assessment.

[0068] If the most recent scan data is dual-polarization radar scan data, then the initial data grid may store all dual-polarization quantities of the most adjacent scan data in a one-dimensional manner.

[0069] On the basis of the above embodiment, the method of this embodiment, according to the intersection heights corresponding to each radar, selects the scanning data whose scanning position is closest to the preset near-surface height H in the corresponding elevation data grid as the scanning data of the initial data grid for precipitation assessment, including:

[0070] In the case where the most recent scanning data is single polarization radar scanning data, it is determined whether there is dual polarization radar scanning data in the range between the intersection heights and intersecting with the redundant selection range HT / 2 to H + T / 2, where T is the data redundancy thickness;

[0071] If dual-polarization radar scanning data exists, using the dual-polarization radar scanning data as scanning data of the initial data grid for precipitation assessment;

[0072] If the dual-polarization radar scanning data does not exist, the single-polarization radar scanning data is used as the scanning data of the initial data grid for precipitation assessment.

[0073] Single polarization weather radar transmits a single polarization wave, usually a horizontal polarization wave, and can obtain reflectivity factor (Z), Doppler velocity (V) and velocity spectrum width (W) parameters. Dual polarization weather radar is an upgrade of single polarization radar, which transmits horizontal and vertical polarization electromagnetic waves at the same time. In addition to obtaining single polarization reflectivity factor (Z), Doppler velocity (V) and velocity spectrum width (W) parameters, it can also obtain dual polarization parameters such as cocorrelation coefficient (CC), differential reflectivity (ZDR), differential phase shift (PhiDP), differential phase shift ratio (KDP), etc.

[0074] If the most recent scanning data are all single polarization radar scanning data, then a search is performed to determine whether there is dual polarization scanning data whose range between the minimum intersection height and the maximum intersection height intersects with the redundant selection range.

[0075] If dual-polarization radar scanning data exists, the single-polarization radar scanning data is replaced by the dual-polarization radar scanning data searched within the redundant selection range, and the initial data grid records the dual-polarization radar scanning data.

[0076] If dual polarization radar scan data does not exist, this initial data grid records single polarization radar scan data.

[0077] After selecting and processing the data of all grids in the constructed initial data grid, the precipitation rate is calculated. When calculating the precipitation rate, the data of each grid point is traversed. After obtaining the precipitation rate of the single-time network radar hybrid scanning data, the cumulative precipitation estimate is obtained through time accumulation, and the network precipitation estimation product is generated. The complete process of the precipitation estimation method based on weather radar network hybrid scanning is as follows: Figure 6 shown.

[0078] Based on the above embodiment, in this embodiment, the method of selecting the range between the intersection heights and the scan data closest to the preset near-surface height H in the corresponding elevation data grid as the scan data of the initial data grid for precipitation assessment includes:

[0079] In the case where the scanning data of the initial data grid is single polarization radar scanning data, precipitation assessment is performed based on the single polarization radar scanning data using the Z / R relationship.

[0080] When calculating the precipitation rate, traverse the data of each grid point and distinguish between single-polarization and double-polarization data. If the scan data of the initial data grid is single-polarization radar scan data, directly apply the Z / R relationship to calculate the precipitation rate.

[0081] Based on the above embodiment, in this embodiment, the method of selecting the range between the intersection heights and the scan data closest to the preset near-surface height H in the corresponding elevation data grid as the scan data of the initial data grid for precipitation assessment includes:

[0082] In the case where the scanning data of the initial data grid is dual-polarization radar scanning data, precipitation assessment is performed using a quantitative precipitation estimation algorithm (Quantitative Precipitation Estimation, QPE) according to the dual-polarization radar scanning data.

[0083] Based on the above embodiments, Figure 7 As shown, in this embodiment, the method of performing precipitation assessment using a quantitative precipitation estimation algorithm according to the dual-polarization radar scanning data includes:

[0084] When the radar reflectivity factor in the dual-polarization radar scanning data is greater than a first preset threshold value and the radar differential propagation phase shift rate is greater than a second preset threshold value, determining that the precipitation type is non-liquid precipitation, and calculating the precipitation rate according to the radar reflectivity factor;

[0085] When the radar reflectivity factor is less than or equal to a first preset threshold, or the radar differential propagation phase shift rate is less than or equal to a second preset threshold, the precipitation type is determined to be liquid precipitation, and the precipitation rate is calculated according to the radar differential propagation phase shift rate.

[0086] Among them, the radar reflectivity factor (Z H )(dBZ) is a unit that represents the echo intensity of precipitation targets. It is related to the size, number and phase of precipitation particles in the unit volume of the precipitation target.

[0087] Dual polarization radar differential propagation phase shift rate (K DP ) represents the propagation phase difference between the horizontal channel and the vertical channel per unit distance, which is the differential propagation phase shift (φ DP ) of the export volume.

[0088] If the scan data of the initial data grid is dual-polarization radar scan data, the quantitative precipitation estimation algorithm is used for precipitation assessment, such as Figure 7 First, the phase classification of the networked mixed scanning data is calculated; then, according to the phase type of precipitation particles in the networked mixed scanning data, the precipitation type is roughly divided into liquid and non-liquid; finally, according to the radar differential propagation phase shift rate K DP and radar reflectivity factor Z H Select different precipitation rate calculation formulas.

[0089] Based on the above embodiments, Figure 7 As shown, in this embodiment, the radar reflectivity factor Z is calculated by the following formula: H Calculate the precipitation rate R:

[0090] ;

[0091] According to the radar differential propagation phase shift rate K, the following formula is used DP Calculate the precipitation rate R:

[0092] .

[0093] The advantages of the present invention mainly include: first, by acquiring near-surface radar reflectivity factor data related to the terrain through a networked radar hybrid scanning method, the influence of terrain undulation on the data is solved, and effective near-surface scanning data is acquired; second, the method is not limited by the radar scanning method and the radar band, that is, when a multi-band radar is networked for detection, all adjacent surface scanning data in the networking area can be acquired for precipitation estimation; third, a reasonable data selection method is designed for single-polarization and dual-polarization radars; fourth, the near-surface data constructed by radar network hybrid scanning can also be used as the basis for inversion of a series of products such as phase classification.

[0094] The precipitation estimation device based on weather radar networking hybrid scanning provided by the present invention is described below. The precipitation estimation device based on weather radar networking hybrid scanning described below and the precipitation estimation method based on weather radar networking hybrid scanning described above can be referenced to each other.

[0095] like Figure 8 As shown, the device includes a construction module 901, a calculation module 902 and a selection module 903, wherein:

[0096] The construction module 901 is used to construct an initial data grid according to the projection mode, networking range and resolution of the radar network precipitation estimation, and to construct an elevation data grid according to the terrain elevation data of the radar network area with the same projection mode, networking range and resolution;

[0097] The calculation module 902 is used to convert the coordinates of the initial data grid into longitude and latitude coordinates, and calculate the intersection height of the geocentric line of the longitude and latitude coordinates of the initial data grid and the elevation scanning data of each radar in the radar networking area;

[0098] The selection module 903 is used to select the scanning data closest to the preset near-surface height H in the corresponding elevation data grid according to the intersection heights corresponding to each radar as the scanning data of the initial data grid for precipitation assessment.

[0099] This embodiment introduces terrain elevation data on the basis of radar networking, obtains multi-height layer data of networked radar hybrid scanning based on terrain, constructs an initial data grid based on the networked observation of multiple radars, selects the near-surface range according to the terrain data to mix the networked radar scanning data, realizes the selection of near-surface data in the overlapping observation area of ​​multiple radars, and estimates the precipitation based on the effective scanning data of the adjacent surface under the terrain. The networked hybrid scanning data can effectively avoid the influence of ground obstruction. At the same time, the data selection is not limited by the radar volume scanning method. Through the setting of the near-surface range, the idea of ​​the nearest effective surface scanning data can be applied in the entire range of the radar networking area, thereby optimizing the selection of application data of the precipitation estimation algorithm and improving the precipitation estimation capability of the weather radar network.

[0100] Fig. 9 An example of a physical structure diagram of an electronic device is shown in FIG. Fig. 9As shown, the electronic device may include: a processor (processor) 1010, a communication interface (Communications Interface) 1020, a memory (memory) 1030 and a communication bus 1040, wherein the processor 1010, the communication interface 1020, and the memory 1030 communicate with each other through the communication bus 1040. The processor 1010 can call the logic instructions in the memory 1030 to execute the precipitation estimation method of weather radar networking hybrid scanning, which includes: constructing an initial data grid according to the projection method, networking range and resolution of radar networking precipitation estimation, and constructing an elevation data grid according to the terrain elevation data of the radar networking area with the same projection method, networking range and resolution; converting the coordinates of the initial data grid into longitude and latitude coordinates, and calculating the intersection height of the geocentric line of the longitude and latitude coordinates of the initial data grid and the elevation scanning data of each radar in the radar networking area; according to the intersection height corresponding to each radar, selecting the range between the intersection heights and the scanning data closest to the preset near-surface height H in the corresponding elevation data grid as the scanning data of the initial data grid for precipitation assessment.

[0101] In addition, the logic instructions in the above-mentioned memory 1030 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0102] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the precipitation estimation method based on weather radar networking hybrid scanning provided by the above-mentioned methods, the method including: constructing an initial data grid according to the projection method, networking range and resolution of radar networking precipitation estimation, and constructing an elevation data grid according to the terrain elevation data of the radar networking area with the same projection method, networking range and resolution; converting the coordinates of the initial data grid into longitude and latitude coordinates, and calculating the intersection height of the geocentric line of the longitude and latitude coordinates of the initial data grid and the elevation scanning data of each radar in the radar networking area; according to the intersection height corresponding to each radar, selecting the scanning data closest to the preset near-surface height H in the corresponding elevation data grid as the scanning data of the initial data grid for precipitation assessment.

[0103] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the precipitation estimation method based on weather radar networking hybrid scanning provided by the above-mentioned methods, the method comprising: constructing an initial data grid according to the projection method, networking range and resolution of radar networking precipitation estimation, and constructing an elevation data grid according to the terrain elevation data of the radar networking area with the same projection method, networking range and resolution; converting the coordinates of the initial data grid into longitude and latitude coordinates, and calculating the intersection height of the geocentric line of the longitude and latitude coordinates of the initial data grid and the elevation scanning data of each radar in the radar networking area; according to the intersection height corresponding to each radar, selecting the scanning data closest to the preset near-surface height H in the corresponding elevation data grid as the scanning data of the initial data grid for precipitation assessment.

[0104] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0105] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0106] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A precipitation estimation method based on weather radar network hybrid scanning, characterized in that: include: According to the projection mode, networking range and resolution of radar network precipitation estimation, an initial data grid is constructed, and according to the terrain elevation data of the radar network area, an elevation data grid is constructed with the same projection mode, networking range and resolution; Convert the coordinates of the initial data grid into longitude and latitude coordinates, and calculate the intersection height of the geocentric line of the longitude and latitude coordinates of the initial data grid and the elevation scanning data of each radar in the radar networking area; According to the intersection heights corresponding to each radar, the range between the intersection heights and the preset near-surface height in the corresponding elevation data grid are selected. H The most recent scan data is used as the scan data of the initial data grid for precipitation assessment; According to the intersection height corresponding to each radar, the scanning position and the preset near-surface height in the corresponding elevation data grid are selected. H The most recent scan data is used as the scan data for the initial data grid for precipitation assessment, including: In the case where the most recent scan data is single polarization radar scan data, determining the redundant selection range H - T / 2 to H + T Whether there is dual polarization radar scanning data within the range between the intersection heights and intersecting with it within / 2, T is the data redundancy thickness; If dual-polarization radar scanning data exists, using the dual-polarization radar scanning data as scanning data of the initial data grid for precipitation assessment; If the dual-polarization radar scanning data does not exist, the single-polarization radar scanning data is used as the scanning data of the initial data grid for precipitation assessment.

2. The precipitation estimation method based on weather radar network hybrid scanning according to claim 1 is characterized in that: According to the intersection height corresponding to each radar, the scanning position and the preset near-surface height in the corresponding elevation data grid are selected. H The most recent scan data is used as the scan data for the initial data grid for precipitation assessment, including: In the case that the latest scanning data is dual-polarization radar scanning data, all dual-polarization quantities of the latest scanning data are used as scanning data of the initial data grid for precipitation assessment.

3. The precipitation estimation method based on weather radar network hybrid scanning according to claim 1 is characterized in that: The range between the selected intersection heights and the preset near-surface height in the corresponding elevation data grid H The most recent scan data is used as the scan data for the initial data grid for precipitation assessment, including: In the case where the scanning data of the initial data grid is single polarization radar scanning data, precipitation assessment is performed based on the single polarization radar scanning data using the Z / R relationship.

4. The precipitation estimation method based on weather radar network hybrid scanning according to claim 1 is characterized in that: The range between the selected intersection heights and the preset near-surface height in the corresponding elevation data grid H The most recent scan data is used as the scan data for the initial data grid for precipitation assessment, including: In a case where the scanning data of the initial data grid is dual-polarization radar scanning data, precipitation assessment is performed using a quantitative precipitation estimation algorithm according to the dual-polarization radar scanning data.

5. The precipitation estimation method based on weather radar network hybrid scanning according to claim 4 is characterized in that: The step of performing precipitation assessment using a quantitative precipitation estimation algorithm according to the dual-polarization radar scanning data comprises: When the radar reflectivity factor in the dual-polarization radar scanning data is greater than a first preset threshold value and the radar differential propagation phase shift rate is greater than a second preset threshold value, determining that the precipitation type is non-liquid precipitation, and calculating the precipitation rate according to the radar reflectivity factor; When the radar reflectivity factor is less than or equal to a first preset threshold, or the radar differential propagation phase shift rate is less than or equal to a second preset threshold, the precipitation type is determined to be liquid precipitation, and the precipitation rate is calculated according to the radar differential propagation phase shift rate.

6. The precipitation estimation method based on weather radar network hybrid scanning according to claim 5 is characterized in that: The radar reflectivity factor is calculated by the following formula Z H Calculating precipitation rate R : ； The radar differential propagation phase shift rate is calculated by the following formula: K DP Calculating precipitation rate R : 。 7. A precipitation estimation device based on weather radar network hybrid scanning, characterized in that: include: A construction module is used to construct an initial data grid according to the projection mode, networking range and resolution of radar network precipitation estimation, and to construct an elevation data grid according to the terrain elevation data of the radar network area with the same projection mode, networking range and resolution; A calculation module, used for converting the coordinates of the initial data grid into longitude and latitude coordinates, and calculating the intersection height of the geocentric line of the longitude and latitude coordinates of the initial data grid and the elevation scanning data of each radar in the radar networking area; The selection module is used to select the range between the intersection heights and the preset near-surface height in the corresponding elevation data grid according to the intersection heights corresponding to each radar. H The most recent scan data is used as the scan data of the initial data grid for precipitation assessment; The selection module is specifically used for: In the case where the most recent scan data is single polarization radar scan data, determining the redundant selection range H - T / 2 to H + T Whether there is dual polarization radar scanning data within the range between the intersection heights and intersecting with it within / 2, T is the data redundancy thickness; If dual-polarization radar scanning data exists, using the dual-polarization radar scanning data as scanning data of the initial data grid for precipitation assessment; If the dual-polarization radar scanning data does not exist, the single-polarization radar scanning data is used as the scanning data of the initial data grid for precipitation assessment.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the precipitation estimation method based on weather radar network hybrid scanning as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the precipitation estimation method based on weather radar network hybrid scanning as described in any one of claims 1 to 6 is implemented.

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