A horizontal wind field inversion method and device based on radial velocity of wind profile radar

Abstract

This invention discloses a method and apparatus for horizontal wind field inversion based on the radial velocity of a wind profiler radar, relating to the field of wind profiler radar technology. The method includes: reading the radial velocity data of the wind profiler radar beams in each direction; rearranging and splicing the radial velocity data of each beam in a preset order to form a beam radial velocity profile; sequentially performing data identification, one-dimensional median filtering, and one-dimensional moving average filtering on the beam radial velocity profile to ensure data consistency; performing spatiotemporal continuity processing, followed by time-consistent averaging; and obtaining the inverted horizontal wind field based on the spatial geometric relationship between the wind field and the radial velocity data of each beam, according to the processed radial velocity data of each beam. This invention solves the problem of low accuracy in horizontal wind field inversion in existing technologies.

Description

Technical Field

[0001] This invention relates to the field of wind profiler radar technology, and in particular to a method and apparatus for horizontal wind field inversion based on the radial velocity of wind profiler radar. Background Technology

[0002] Wind profiler radar is one of the key detection devices in the ground-based remote sensing vertical observation system of meteorological departments. It mainly uses the scattering effect of atmospheric turbulence on electromagnetic waves for detection. It can provide real-time distribution of meteorological elements such as atmospheric horizontal wind field, vertical velocity, and atmospheric refractive index structure constant with altitude in a 24-hour unattended manner. It has the characteristics of high spatiotemporal resolution, good continuity, and strong real-time performance. It can also adapt to harsh environments and is an important supplement to the current conventional weather balloon wind measurement system.

[0003] Currently, the data integrity and quality of wind profiler radar in complex weather environments still need further improvement, especially in signal processing and data quality control. Due to the weak atmospheric turbulence signal, electromagnetic waves are easily affected by attenuation, scattering, and noise interference during propagation, resulting in a low signal-to-noise ratio and seriously affecting the accuracy of meteorological signals. Therefore, it is particularly important to conduct research on data processing and quality control methods for wind profiler radar.

[0004] In existing technologies, wind profiler radars typically employ a five-beam detection method, including a vertically upward zenith measurement beam and four tilted beams (pointing east, south, west, and north, respectively). Due to the weak turbulence echo signal, the radar may be subject to various interferences during detection, leading to contamination or even unusable measurement data from some beams. Therefore, some wind field inversion techniques utilize three-beam measurements to calculate the wind field. However, the three-beam measurement method requires high detection quality for each beam, and errors are easily amplified during calculation, resulting in abnormal wind speed and direction calculations, thus affecting the accuracy of wind field inversion. Summary of the Invention

[0005] In view of this, the present invention provides a method and apparatus for horizontal wind field inversion based on radial velocity of wind profiler radar, aiming to optimize the quality of wind profiler radar data, improve the inversion accuracy of horizontal wind field, and provide more accurate wind field observation products for wind profiler radar data users.

[0006] This invention proposes a method for horizontal wind field inversion based on the radial velocity of a wind profiler radar, the method comprising:

[0007] Read the radial velocity data of the wind profiler radar beams in each direction, rearrange the radial velocity data of the beams in each direction according to a preset order, and stitch together the radial velocity data of the beams in each direction at different altitudes to form a beam radial velocity profile.

[0008] The beam radial velocity profile data is sequentially identified, filtered by one-dimensional median, and filtered by one-dimensional moving average to ensure consistency.

[0009] Radial data of beams in each direction at each altitude are extracted to form a three-dimensional array, and spatiotemporal continuity processing is performed, followed by time-consistent averaging.

[0010] Based on the spatial geometric relationship between the wind field and the radial velocity data of beams in each direction, the inverted horizontal wind field is obtained from the processed radial velocity data of beams in each direction.

[0011] Furthermore, in the aforementioned horizontal wind field inversion method based on the radial velocity of the wind profile radar, the steps of sequentially performing data identification, one-dimensional median filtering, and one-dimensional moving average filtering on the beam radial velocity profile to achieve data consistency processing include:

[0012] A quality control code is set to indicate whether the radial velocity data is accurate, based on the principle of symmetry between the radial velocities of two sets of beams at the same altitude and their vertical velocities.

[0013] One-dimensional median filtering is performed on beam data in each direction in ascending order of low value, and the quality control code indicating whether the radial velocity data is accurate is incorporated into the filtering process.

[0014] After one-dimensional median filtering is performed on the radial velocities of all beams, the quality control code of the radial velocity data is updated.

[0015] One-dimensional moving average filtering is performed on beam data in each direction in ascending order, and the quality control code indicating whether the radial velocity data is accurate is incorporated into the filtering process.

[0016] After the radial velocities of all beams have undergone one-dimensional moving average filtering, the quality control code of the radial velocity data is updated.

[0017] Furthermore, in the aforementioned horizontal wind field inversion method based on the radial velocity of wind profiler radar, the step of performing one-dimensional median filtering on the beam data in each direction in ascending order, and incorporating the quality control code indicating the accuracy of the radial velocity data into the filtering process, includes:

[0018] When filtering the data corresponding to the quality control code indicating inaccurate radial velocity data and calculating the median, only the data of the quality control code indicating accurate radial velocity data are considered.

[0019] Furthermore, in the aforementioned horizontal wind field inversion method based on the radial velocity of wind profiler radar, the step of setting a quality control code indicating the accuracy of the radial velocity data according to the symmetry principle of the radial velocities of the two sets of beams at the same height with respect to the vertical velocity includes:

[0020] If the radial velocities of two beams at the same altitude have opposite signs, and the absolute value of the sum of the radial velocities of the two beams at the same altitude is less than the first preset value, then a quality control code representing accurate radial velocity data is set.

[0021] If the absolute value of the sum of the radial velocities of the two beams at the same altitude is greater than the second preset value, or the absolute value of one of them is greater than the third preset value, then a quality control code representing inaccurate radial velocity data is set.

[0022] Furthermore, the above-mentioned horizontal wind field inversion method based on the radial velocity of wind profiler radar, wherein the steps of extracting radial data of each beam at each height to form a three-dimensional array, performing spatiotemporal continuity processing, and then performing time-consistent averaging processing include:

[0023] The resulting three-dimensional array is subjected to two-dimensional median filtering in the time and height dimensions to perform spatiotemporal continuity processing;

[0024] Specifically, by determining whether the difference between the radial velocity at a certain altitude layer at a certain moment and the observed values ​​at adjacent moments and altitude layers exceeds a preset threshold, it is determined whether to use the median for replacement.

[0025] Furthermore, in the above-mentioned horizontal wind field inversion method based on wind profiler radar radial velocity, the step of performing time-consistent averaging includes:

[0026] Radial data with similar values ​​at a single height and a single beam within a preset time period are grouped together to form a set.

[0027] Find the target set with the largest sample size, and average the data in the target set to obtain the average observation value for the corresponding preset time period.

[0028] Furthermore, in the above-mentioned horizontal wind field inversion method based on the radial velocity of wind profiler radar, the step of obtaining the inverted horizontal wind field based on the spatial geometric relationship between the wind field and the radial velocity data of each directional beam, and according to the processed radial velocity data of each directional beam, includes:

[0029] ;

[0030] ;

[0031] ;

[0032] ;

[0033] ;

[0034] ;

[0035] in, For horizontal wind speed, The wind direction is horizontal. , , , These represent the radial velocities measured by the wind profiler radar in the east, west, north, south, and central directions, respectively. The tilt angle of the oblique beam. This is the azimuth correction value.

[0036] Another object of the present invention is to provide a horizontal wind field inversion device based on the radial velocity of a wind profiler radar, the device comprising:

[0037] The acquisition module is used to read the radial velocity data of the wind profiler radar beams in each direction, rearrange the radial velocity data of the beams in each direction according to a preset order, and stitch together the radial velocity data of the beams in each direction at different altitudes to form a beam radial velocity profile.

[0038] The identification module is used to sequentially identify the data of the beam radial velocity profile, perform one-dimensional median filtering and one-dimensional moving average filtering to ensure the consistency of the beam radial velocity profile data.

[0039] The quality control module is used to extract radial data of beams in each direction at each height to form a three-dimensional array, and then perform spatiotemporal continuity processing, followed by time-consistent averaging.

[0040] The inversion module is used to obtain the inverted horizontal wind field based on the spatial geometric relationship between the wind field and the radial velocity data of each beam.

[0041] Another object of the present invention is to provide a readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described above.

[0042] Another object of the present invention is to provide an electronic device including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of the method described above.

[0043] This invention reads the radial velocity data of the beams in each direction from a wind profiler radar, rearranges the radial velocity data of the beams in each direction according to a preset order, and splices and organizes the radial velocity data of the beams in each direction at different altitudes to form a beam radial velocity profile.

[0044] The radial velocity profile of the beam is sequentially processed by data identification, one-dimensional median filtering, and one-dimensional moving average filtering to ensure data consistency. Radial data of each beam at each altitude is extracted to form a three-dimensional array, which is then processed for spatiotemporal continuity and followed by time-consistent averaging. Based on the spatial geometric relationship between the wind field and the radial velocity data of each beam, the horizontal wind field is inverted from the processed radial velocity data of each beam. This effectively improves the quality of wind profile radar data, eliminates noise and outliers in the data, and provides more accurate wind field inversion results. Attached Figure Description

[0045] Figure 1 This is a flowchart of the horizontal wind field inversion method based on the radial velocity of wind profiler radar in the first embodiment of the present invention;

[0046] Figure 2 This is a schematic diagram of the three-dimensional space of the beams in the five-beam wind profiler radar in a horizontal wind field inversion method based on the radial velocity of the wind profiler radar in one embodiment of the present invention.

[0047] Figure 3 In one embodiment of the present invention, the east, south, west, and north beams of the five-beam wind profiler radar in the horizontal wind field inversion method based on radial velocity of wind profiler radar are... x, y Projection onto a plane;

[0048] Figure 4 This is a structural block diagram of the horizontal wind field inversion device based on the radial velocity of a wind profiler radar in the third embodiment of the present invention.

[0049] The following detailed description, in conjunction with the accompanying drawings, will further illustrate the present invention. Detailed Implementation

[0050] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Several embodiments of the invention are illustrated in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0051] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0053] Example 1

[0054] Please see Figure 1 The figure shows a horizontal wind field inversion method based on the radial velocity of a wind profiler radar in the first embodiment of the present invention, the method including steps S10 to S13.

[0055] Step S10: Read the radial velocity data of the wind profiler radar beams in each direction, rearrange the radial velocity data of the beams in each direction according to a preset order, and stitch together the radial velocity data of the beams in each direction at different altitudes to form a beam radial velocity profile.

[0056] In this step, the radial velocity data detected by the radar on each directional beam is first read, and then the data of these different directional beams are rearranged in a pre-set order to unify the format. At the same time, for each directional beam, the radial velocity data distributed at different altitudes are connected and integrated to finally form a complete radial velocity profile of each directional beam that varies with altitude.

[0057] In this embodiment of the invention, the wind profiler radar employs a five-beam wind profiler radar, including a vertically upward zenith measurement beam and four tilted beams pointing east, south, west, and north, respectively. In specific implementation, the radial velocity data of the five beams of the wind profiler radar is first read. Based on the beam sequence indicator in the document, the data is rearranged in the order of center, east, west, north, and south, and the radial velocity data of low, medium, and high modes are stitched together according to altitude level (from low to high). For data in overlapping areas, the higher mode data is selected, ultimately forming a complete five-beam radial velocity profile. This operation ensures the structural rationality of the data and lays the foundation for subsequent processing. For example, data within a certain time period can be selected according to actual needs, such as the radial velocity data of each beam in each direction at the current moment and within the previous 30 minutes.

[0058] Step S11: The beam radial velocity profile data is sequentially identified, one-dimensional median filtering is performed, and one-dimensional moving average filtering is performed to ensure consistency of the beam radial velocity profile data.

[0059] The radial velocity profiles of the five beams undergo consistency processing. Specifically, based on the symmetry principle of the radial velocities at the same altitude (east-west and north-south) with respect to the vertical velocity, quality control codes are set to indicate the accuracy of the radial velocity data. This allows for data identification and targeted processing of different data types. The data mainly includes two categories: accurate and inaccurate. Inaccurate data can be further divided into unclear status, missing values, and erroneous values. For each data type, a corresponding quality control code can be assigned, for example, "0" indicates unclear status, "1" indicates missing value, "2" indicates correct value, and "3" indicates erroneous value.

[0060] Taking the radial velocities of two beams in the east-west direction as an example, the rules for judging "good" (accurate) data are as follows: the two beams have opposite signs, and the absolute value of their sum is ≤2.0 m / s. The rules for judging "bad" (inaccurate) data are as follows: the absolute value of their sum is ≥6.0 m / s, or the absolute value of one of them is ≥10.0 m / s. In addition, it can also identify whether data is missing, and data with an unclear status other than accurate, erroneous, and missing data. In this way, a quality control code is assigned to each data point. The purpose of setting quality control codes is to prevent erroneous values ​​from affecting subsequent filtering processes.

[0061] Subsequently, one-dimensional median filtering was performed on the radial velocity. Specifically, one-dimensional median filtering (window size 1×3) was applied to the radial velocity of a single beam at a single time interval. The filtering process only performed on data whose quality control code was not "2". When calculating the median, only data with a quality control code of "2" were considered to improve the smoothness and consistency of the data. The filtering threshold was set to 1 m / s, and the quality control code of the data was updated.

[0062] Next, a one-dimensional moving average filter (window size 1×5) is applied to the radial velocity of a single beam at a single time interval. Only data with a quality control code other than "2" are considered for filtering to further reduce noise and ensure data accuracy. The filtering threshold is set to 2 m / s, and the quality control code of the data is updated.

[0063] Step S12: Extract the radial data of each beam at each altitude to form a three-dimensional array, perform spatiotemporal continuity processing, and then perform time-consistent averaging.

[0064] The purpose of this step is to perform spatiotemporal continuity checks and time-consistency averaging on the beam observation data from the wind profiler radar, further eliminating outliers and improving data smoothness and consistency. The basic idea of ​​spatiotemporal continuity processing is to perform two-dimensional median filtering on the radial velocity data of a specific beam in both the "time dimension" (different moments) and the "height dimension" (different altitude levels). Specifically, by judging the difference between the radial velocity at a certain altitude level at a given moment and the observation values ​​at adjacent moments and altitude levels, if it exceeds a preset threshold (i.e., the data is spatiotemporally discontinuous), the median of the surrounding data is used to replace the outlier, thereby ensuring the continuity of the data in both the time series and vertical height.

[0065] For each beam of data, a two-dimensional median filter is applied to the three-dimensional array formed in the time and height dimensions. The filter window size is 5×5, the threshold is set to 2 m / s, and only data with a quality control code of "0" or "2" are considered. After two-dimensional median filtering is completed for all beams, the quality control code of the data is updated.

[0066] Understandably, in practice, the window size is 5×5. That is, for each "time-height" point to be processed, take 5 consecutive time points around it (such as the current time and 2 time points before and after) and 5 consecutive height layers (such as the current height and 2 height layers above and below), forming a 5×5 rectangular window. The data within the window is used to calculate the median.

[0067] If the difference between the radial velocity at the current "time-elevation" point and the window value exceeds 2 m / s (i.e., spatial discontinuity), then the window value is used to replace the data.

[0068] The median calculation is based on the following criteria: only data with a control code of "0" (unknown status) and "2" (correct value) are considered. Data with a control code of "1" and "3" are excluded because these data are unreliable and are not included in the median calculation to avoid interfering with the results.

[0069] Step S13: Based on the spatial geometric relationship between the wind field and the radial velocity data of each direction beam, the inverted horizontal wind field is obtained according to the processed radial velocity data of each direction beam.

[0070] In this embodiment of the invention, a five-beam detection method is adopted, in which one beam is perpendicularly pointed to the zenith for measurement, and the other four beams are tilted at the four directions of east, south, west and north respectively, and the azimuth angles between adjacent beams are orthogonal.

[0071] However, due to potential antenna installation and calibration errors in wind profiler radars, as well as inherent biases in the radar system itself, these four tilting beams may not necessarily point due east, due south, due west, or due north. Therefore, azimuth correction values ​​must be considered during wind field inversion to correct for these errors and ensure the accuracy of wind speed and direction data.

[0072] Based on this, embodiments of the present invention provide a formula for calculating horizontal wind after considering azimuth correction values, such as... Figures 2 to 3 As shown, the actual wind (the quantity to be determined) at a certain altitude is denoted as... The radial velocities measured by the wind profiler radar in the east, west, north, south, and center directions (positive towards the radar, negative away from the radar) are respectively , , , , The azimuth correction value is (Clockwise deviation is positive, counterclockwise deviation is negative). , These respectively represent winds blowing from east to west and winds blowing from north to south.

[0073] Assuming the east, south, west, and north beams are in The projections on the plane are pairwise orthogonal. Based on the spatial geometric relationship between the actual wind field and the radial velocities measured on the five beams, the following relationship can be obtained:

[0074] ;

[0075] ;

[0076] ;

[0077] ;

[0078] ;

[0079] We can obtain:

[0080] ;

[0081]

[0082] when Time, record:

[0083] ;

[0084]

[0085] We can obtain:

[0086] ;

[0087] ;

[0088] This leads to the formula for calculating horizontal wind after considering azimuth correction. Vertical velocity can be calculated using the formula... Directly obtained. Horizontal wind speed. and horizontal wind direction It is calculated by the following formula:

[0089] ;

[0090] ;

[0091] Among them, wind direction In meteorology, wind direction refers to the direction from which the wind blows. Its angle is the angle traversed when rotating clockwise from due north towards the direction the wind is blowing. The range of values ​​is... .

[0092] After the above steps, the horizontal wind field can be obtained by inverting the radial velocity of the five beams of the wind profiler radar.

[0093] In summary, the horizontal wind field inversion method based on radial velocity of wind profiler radar in the above embodiments of the present invention reads the radial velocity data of the wind profiler radar beams in each direction, rearranges the radial velocity data of each beam in each direction according to a preset order, and splices and organizes the radial velocity data of each beam at different heights to form a beam radial velocity profile. The beam radial velocity profile is then subjected to data identification, one-dimensional median filtering, and one-dimensional moving average filtering to ensure data consistency. Radial data of each beam at each height is extracted to form a three-dimensional array, and spatiotemporal continuity processing is performed, followed by time-consistent averaging. Based on the spatial geometric relationship between the wind field and the radial velocity data of each beam, the inverted horizontal wind field is obtained from the processed radial velocity data of each beam. This method effectively improves the quality of wind profiler radar data, eliminates noise and outliers in the data, and provides more accurate wind field inversion results. It solves the problem of low accuracy in wind field inversion results in the prior art.

[0094] Example 2

[0095] This embodiment also proposes a horizontal wind field inversion method based on the radial velocity of a wind profiler radar. The difference between the horizontal wind field inversion method based on the radial velocity of a wind profiler radar in this embodiment and the horizontal wind field inversion method based on the radial velocity of a wind profiler radar in Embodiment 1 is as follows:

[0096] The steps for performing time-consistent averaging include:

[0097] Radial data with similar values ​​at a single height and a single beam within a preset time period are grouped together to form a set.

[0098] Find the target set with the largest sample size, and average the data in the target set to obtain the average observation value for the corresponding preset time period.

[0099] The core idea of ​​the time-consistent averaging algorithm is to perform a consistency check on the radial data at a single height of a single beam in the time dimension. Data with similar values ​​are grouped together to form a set. Then, the set with the largest sample size is identified, and the data in this set is averaged to obtain the observation average for that time period. Choosing an appropriate averaging time is crucial. The longer the averaging time, the more obvious the smoothing effect and the better the wind continuity, but it may also smooth out changes such as wind shear that occur in a short period of time. In this embodiment of the invention, averaging over 15 to 30 minutes for boundary layer wind profiler radar and averaging over 30 to 60 minutes for tropospheric wind profiler radar are generally considered to be suitable time ranges. This embodiment of the invention sets the averaging time to 30 minutes.

[0100] Suppose that within a 30-minute time period, there are 6 radial velocity values ​​at a specific altitude for a certain beam that have a quality control code of "0" or "2". First, for the th radial velocity value (=1, 2, …, 6), we first calculate its... The number of other radial velocity values ​​within the interval ( The quality control code is calculated as follows: (1) the average radial velocity within that interval. Then, the average radial velocity corresponding to the maximum value is taken as the quality control result for the current moment, and it must be the closest to the current moment. This invention sets the value to 2.0 m / s. After all beams have completed time consistency processing, the quality control code of the data is updated.

[0101] This method effectively removes outliers, significantly reduces errors caused by abnormal values, and replaces them with a reasonable mean, thereby improving the accuracy and stability of wind field inversion results.

[0102] In summary, the horizontal wind field inversion method based on radial velocity of wind profiler radar in the above embodiments of the present invention reads the radial velocity data of the wind profiler radar beams in each direction, rearranges the radial velocity data of each beam in each direction according to a preset order, and splices and organizes the radial velocity data of each beam at different heights to form a beam radial velocity profile. The beam radial velocity profile is then subjected to data identification, one-dimensional median filtering, and one-dimensional moving average filtering to ensure data consistency. Radial data of each beam at each height is extracted to form a three-dimensional array, and spatiotemporal continuity processing is performed, followed by time-consistent averaging. Based on the spatial geometric relationship between the wind field and the radial velocity data of each beam, the inverted horizontal wind field is obtained from the processed radial velocity data of each beam. This method effectively improves the quality of wind profiler radar data, eliminates noise and outliers in the data, and provides more accurate wind field inversion results. It solves the problem of low accuracy in wind field inversion results in the prior art.

[0103] Example 3

[0104] Please see Figure 4 The image shows a horizontal wind field inversion device based on the radial velocity of a wind profiler radar proposed in the third embodiment of the present invention. The device includes:

[0105] The acquisition module 100 is used to read the radial velocity data of the wind profiler radar beams in each direction, rearrange the radial velocity data of the beams in each direction according to a preset order, and stitch together the radial velocity data of the beams in each direction at different altitudes to form a beam radial velocity profile.

[0106] The identification module 200 is used to sequentially identify the data of the beam radial velocity profile, perform one-dimensional median filtering and one-dimensional moving average filtering to perform consistency processing on the data of the beam radial velocity profile.

[0107] The quality control module 300 is used to extract radial data of beams in each direction at each height to form a three-dimensional array, and to perform spatiotemporal continuity processing, followed by time-consistent averaging.

[0108] The inversion module 400 is used to obtain the inverted horizontal wind field based on the spatial geometric relationship between the wind field and the radial velocity data of each directional beam, and based on the processed radial velocity data of each directional beam.

[0109] The functions or operation steps implemented by the above modules are largely the same as those in the above method embodiments, and will not be repeated here.

[0110] Example 4

[0111] In another aspect, the present invention provides a readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the steps of the method described in any one of Embodiments 1 to 2 above.

[0112] Example 5

[0113] In another aspect, the present invention provides an electronic device, the electronic device including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of any one of the methods described in Embodiments 1 to 2 above.

[0114] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0115] Those skilled in the art will understand that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequential list of executable instructions for implementing logical functions, and can be embodied in any computer-readable storage medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable storage medium" can mean any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0116] More specific examples (a non-exhaustive list) of computer-readable storage media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable storage media can even be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0117] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0118] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0119] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A method for inverting horizontal wind fields based on radial velocity from a wind profiler radar, characterized in that, The method includes: Read the radial velocity data of the wind profiler radar beams in each direction, rearrange the radial velocity data of the beams in each direction according to a preset order, and stitch together the radial velocity data of the beams in each direction at different altitudes to form a beam radial velocity profile. The beam radial velocity profile data is sequentially identified, filtered by one-dimensional median, and filtered by one-dimensional moving average to ensure consistency. Radial data of beams in each direction at each altitude are extracted to form a three-dimensional array, and spatiotemporal continuity processing is performed, followed by time-consistent averaging. Based on the spatial geometric relationship between the wind field and the radial velocity data of beams in each direction, the inverted horizontal wind field is obtained from the processed radial velocity data of beams in each direction. The steps of sequentially performing data identification, one-dimensional median filtering, and one-dimensional moving average filtering on the beam radial velocity profile to achieve data consistency processing include: A quality control code is set to indicate whether the radial velocity data is accurate, based on the principle of symmetry between the radial velocities of two sets of beams at the same altitude and their vertical velocities. One-dimensional median filtering is performed on beam data in each direction in ascending order of low value, and the quality control code indicating whether the radial velocity data is accurate is incorporated into the filtering process. After one-dimensional median filtering is performed on the radial velocities of all beams, the quality control code of the radial velocity data is updated. One-dimensional moving average filtering is performed on beam data in each direction in ascending order, and the quality control code indicating whether the radial velocity data is accurate is incorporated into the filtering process. After the radial velocities of all beams have undergone one-dimensional moving average filtering, the quality control code of the radial velocity data is updated.

2. The horizontal wind field inversion method based on wind profiler radar radial velocity according to claim 1, characterized in that, The step of performing one-dimensional median filtering on beam data in each direction in ascending order of low to high, and incorporating the quality control code indicating the accuracy of radial velocity data into the filtering process, includes: When filtering the data corresponding to the quality control code indicating inaccurate radial velocity data and calculating the median, only the data of the quality control code indicating accurate radial velocity data are considered.

3. The horizontal wind field inversion method based on wind profiler radar radial velocity according to claim 2, characterized in that, The step of setting a quality control code to indicate the accuracy of radial velocity data based on the principle of symmetry between the radial velocities of two sets of beams at the same height and their vertical velocities includes: If the radial velocities of two beams at the same altitude have opposite signs, and the absolute value of the sum of the radial velocities of the two beams at the same altitude is less than the first preset value, then a quality control code representing accurate radial velocity data is set. If the absolute value of the sum of the radial velocities of the two beams at the same altitude is greater than the second preset value, or the absolute value of one of them is greater than the third preset value, then a quality control code representing inaccurate radial velocity data is set.

4. The horizontal wind field inversion method based on wind profiler radar radial velocity according to claim 3, characterized in that, The steps of extracting radial data of beams in each direction at each altitude to form a three-dimensional array, performing spatiotemporal continuity processing, and then performing time-consistent averaging include: The resulting three-dimensional array is subjected to two-dimensional median filtering in the time and height dimensions to perform spatiotemporal continuity processing; Specifically, by determining whether the difference between the radial velocity at a certain altitude layer at a certain moment and the observed values ​​at adjacent moments and altitude layers exceeds a preset threshold, it is determined whether to use the median for replacement.

5. The horizontal wind field inversion method based on wind profiler radar radial velocity according to claim 4, characterized in that, The steps for performing time-consistent averaging include: Radial data with similar values ​​at a single height and a single beam within a preset time period are grouped together to form a set. Find the target set with the largest sample size, and average the data in the target set to obtain the average observation value for the corresponding preset time period.

6. The horizontal wind field inversion method based on wind profiler radar radial velocity according to claim 5, characterized in that, The step of obtaining the inverted horizontal wind field based on the spatial geometric relationship between the wind field and the radial velocity data of each beam includes: ； ； ； ； ； ； in, For horizontal wind speed, The wind direction is horizontal. , , , These represent the radial velocities measured by the wind profiler radar in the east, west, north, south, and central directions, respectively. The tilt angle of the oblique beam. This is the azimuth correction value.

7. A horizontal wind field inversion device based on radial velocity of wind profiler radar, characterized in that, The apparatus for implementing the horizontal wind field inversion method based on wind profiler radar radial velocity as described in any one of claims 1 to 6, comprises: The acquisition module is used to read the radial velocity data of the wind profiler radar beams in each direction, rearrange the radial velocity data of the beams in each direction according to a preset order, and stitch together the radial velocity data of the beams in each direction at different altitudes to form a beam radial velocity profile. The identification module is used to sequentially identify the data of the beam radial velocity profile, perform one-dimensional median filtering and one-dimensional moving average filtering to ensure the consistency of the beam radial velocity profile data. The quality control module is used to extract radial data of beams in each direction at each height to form a three-dimensional array, and then perform spatiotemporal continuity processing, followed by time-consistent averaging. The inversion module is used to obtain the inverted horizontal wind field based on the spatial geometric relationship between the wind field and the radial velocity data of each beam.

8. A readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the method as described in any one of claims 1 to 6.

9. An electronic device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor, when executing the program, implements the steps of the method as described in any one of claims 1 to 6.

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