A radar estimated precipitation and rain gauge observed precipitation fusion method and system

Abstract

The present application relates to a kind of radar estimation precipitation and rain gauge observation precipitation fusion method and system, comprising the following steps: according to raindrop spectrum data, determine A coefficient and b coefficient;According to A coefficient, b coefficient and radar reflectivity factor, determine the initial radar QPE corresponding to each weather radar in precipitation field;Get the rain gauge observation value and initial radar QPE in different preset distance range of grid point;According to the rain gauge observation value and initial radar QPE in different preset distance range of grid point, determine the calibration factor corresponding to each preset distance range;According to the calibration factor corresponding to each preset distance range, obtain first fusion QPE;According to rain gauge observation value and first fusion QPE, determine rain gauge observation interpolation and first fusion QPE interpolation;According to rain gauge observation interpolation and first fusion QPE interpolation, determine second fusion QPE.The problem that using rain gauge is prone to blind area, and using weather radar has the problem that accuracy is not as good as rain gauge is solved.

Description

A method and system for fusing radar-estimated precipitation with rain gauge-observed precipitation Technical Field

[0001] This invention relates to the field of meteorological operational technology, and in particular to a method and system for fusing radar-estimated precipitation with rain gauge-observed precipitation. Background Technology

[0002] With the continuous development of meteorological operational technologies, the number of observation equipment is also constantly increasing. Taking rainfall observation as an example, there are currently over 70,000 rain gauge stations nationwide, and approximately 2,100 in Chongqing. In Chongqing alone, this equates to about one rain gauge station every 39 km², or about one every 6 km. This rain gauge density is sufficient to observe precipitation generated by the vast majority of weather systems. However, rain gauges only represent point-based observations, and some localized heavy rainfall generated by small- to medium-scale weather events may not be observed by rain gauges. Such localized heavy rainfall often causes disasters or casualties. Weather radar can provide high-resolution precipitation estimation products, offering a valuable supplement to rain gauge observations. Weather radars can achieve a horizontal resolution of 1 km x 1 km, which is 39 times the density of rain gauges, with some X-band radars reaching 30 x 30 m. However, radar-estimated precipitation (QPE) has certain errors due to variations in the raindrop spectrum, and its accuracy is lower than that of rain gauges. Summary of the Invention

[0003] To overcome the problem that rain gauges are prone to blind spots and that weather radar is less accurate than rain gauges, this invention provides a method and system for fusing radar-estimated precipitation with rain gauge-observed precipitation.

[0004] In a first aspect, to solve the above-mentioned technical problems, the present invention provides a method for fusing radar-estimated precipitation with rain gauge-observed precipitation, the method comprising the following steps:

[0005] Based on the raindrop spectrum data, the A coefficient and b coefficient are determined. The raindrop spectrum data is the acquisition parameter of the raindrop spectrometer. The A coefficient and b coefficient are used to fit the relationship between the initial radar QPE and the radar reflectivity factor.

[0006] Based on the A coefficient, b coefficient, and radar reflectivity factor, the initial radar QPE corresponding to each weather radar in the precipitation field is determined. The initial radar QPE is the precipitation intensity estimated by the weather radar.

[0007] For each grid point in the precipitation field, the rain gauge observations and initial radar QPE of the grid point are obtained within different preset distance ranges, and each grid point corresponds to at least one weather radar.

[0008] For each grid point in the precipitation field, the calibration factor corresponding to each preset distance range is determined based on the rain gauge observations and the initial radar QPE of the grid point within different preset distance ranges.

[0009] Based on the calibration factors corresponding to each preset distance range, the initial radar QPE of each grid point in the precipitation field is calibrated to obtain the first fused QPE corresponding to each grid point in the precipitation field.

[0010] For each grid point in the precipitation field, the rain gauge observation interpolation and the first fused QPE interpolation are determined based on the rain gauge observations and the first fused QPE.

[0011] For each grid point within the precipitation field, the second fused QPE is determined based on the rain gauge observation interpolation and the first fused QPE interpolation.

[0012] The beneficial effects of the radar-estimated precipitation and rain gauge observation fusion method provided by this invention are as follows: An initial radar QPE corresponding to each radar is determined using the A coefficient, b coefficient, and radar reflectivity factor. A calibration factor is then determined based on rain gauge observations at grid points within different preset distance ranges and the initial radar QPE. The initial radar QPE is then calibrated using the calibration factor to obtain a first fused QPE. The first fused QPE and rain gauge observations are then interpolated onto the grid points of the precipitation field to obtain rain gauge observation interpolations and the first fused QPE interpolation value. Finally, a second fused QPE is determined based on the rain gauge observation interpolation value and the first fused QPE interpolation value. This application uses a combination of rain gauge observations and initial radar QPE, which not only ensures the advantage of weather radar in terms of observation range but also calibrates the weather radar observation data using rain gauge observations. This solves the problem that rain gauges are prone to blind spots, while weather radar is less accurate than rain gauges.

[0013] Based on the above technical solution, the method for fusing radar-estimated precipitation and rain gauge-observed precipitation of the present invention can be further improved as follows.

[0014] Furthermore, the aforementioned raindrop spectral data includes radar reflectivity factor, raindrop diameter of the raindrop spectrometer, number of fall velocity channels of the raindrop spectrometer, sampling time of the raindrop spectrometer, sampling area of ​​the raindrop spectrometer, raindrop number concentration, number of raindrops per unit volume and unit diameter in the diameter channel of the raindrop spectrometer, number of raindrops in the diameter channel and velocity channel of the raindrop spectrometer, and spacing of the diameter channel in the raindrop spectrometer.

[0015] Based on raindrop spectral data, determine the A coefficient and b coefficient, including:

[0016] Based on the radar reflectivity factor, raindrop diameter of the raindrop spectrometer, number of terminal velocity channels of the raindrop spectrometer, sampling time of the raindrop spectrometer, sampling area of ​​the raindrop spectrometer, raindrop number concentration, number of raindrops per unit volume and unit diameter in the diameter channel of the raindrop spectrometer, number of raindrops in the diameter channel and velocity channel of the raindrop spectrometer, and spacing of the diameter channels in the raindrop spectrometer, the coefficients A and b are determined using the first formula, where the first formula is:

[0017]

[0018]

[0019]

[0020] ;

[0021] in, Radar reflectivity factor Indicates the diameter of the raindrop. This represents the raindrop number concentration, and M represents the number of terminal velocity channels. Indicates diameter Channel and speed The number of raindrops on the channel, where T represents the sampling time and S represents the sampling area. Indicates diameter The spacing of the channels, The value represents the rainfall intensity, A represents the A coefficient, and b represents the b coefficient.

[0022] The beneficial effect of adopting the above-mentioned further scheme is that the A coefficient and b coefficient are determined by the first formula, which can then be used to fit the relationship between the initial radar QPE and the radar reflectivity factor.

[0023] Furthermore, for each grid point within the precipitation field, based on the rain gauge observations and initial radar QPE within different preset distance ranges, the calibration factor corresponding to each preset distance range is determined, including:

[0024] For each grid point within the precipitation field, based on the rain gauge observations and the initial radar QPE within the j-th preset distance range of the grid point, the calibration factor corresponding to the j-th preset distance range is determined using the second formula, where the second formula is:

[0025] ;

[0026] in, This represents the calibration factor corresponding to the j-th preset distance range. This represents the number of rain gauges within the j-th preset distance range. This represents the i-th rain gauge observation within the j-th preset distance range. This represents the i-th initial radar QPE within the j-th preset distance range.

[0027] The advantage of adopting the above-mentioned further scheme is that the calibration factor is determined by the second formula, so as to calibrate the initial radar QPE by the calibration factor.

[0028] Furthermore, based on the calibration factor, the initial radar QPE for each grid point within the precipitation field is calibrated to obtain the first fused QPE corresponding to each grid point within the precipitation field, including:

[0029] For each grid point in the precipitation field, if there are at least two identical initial radar QPEs within multiple preset distance ranges, the calibration factor corresponding to each preset distance range is taken as the first target factor. Based on any one of the at least two identical initial radar QPEs and each first target factor, the first fused QPE is obtained.

[0030] For each grid point in the precipitation field, count the radar rain gauge pairs within each preset distance range, select any preset distance range as the target distance range, if there are more than a preset number of radar rain gauge pairs within the target distance range, then take the calibration factor corresponding to each preset distance range corresponding to the radar rain gauge pairs that are more than the preset number as the second target factor, and obtain the first fused QPE based on the initial radar QPE and each second target factor, wherein an initial radar QPE and a rain gauge observation value constitute a radar rain gauge pair;

[0031] For each grid point in the precipitation field, select any preset distance range as the target distance range. If there are fewer than the preset number of radar rain gauge pairs within the target distance range, then the initial radar QPE is used as the first fused QPE.

[0032] The beneficial effects of adopting the above-mentioned further scheme are as follows: if there are at least two identical initial radar QPEs within multiple preset distance ranges, then a first fused QPE is obtained based on any one of the at least two identical initial radar QPEs and each first target factor; if there are more than a preset number of radar rain gauge pairs within the target distance range, then a first fused QPE is obtained based on the initial radar QPE and each second target factor; if there are fewer than a preset number of radar rain gauge pairs within the target distance range, then the initial radar QPE is used as the first fused QPE.

[0033] Furthermore, the method also includes:

[0034] For each grid point in the precipitation field, obtain the inverse square weight of each rain gauge observation value within the preset radius of the grid point and the preset radius.

[0035] For each grid point within the precipitation field, based on rain gauge observations and the first fused QPE, determine the rain gauge observation interpolation and the first fused QPE interpolation, including:

[0036] For each grid point within the precipitation field, based on the inverse square weight of each rain gauge observation within the preset radius of the grid point, the rain gauge observation value, and the first fused QPE, the rain gauge observation interpolation and the first fused QPE interpolation are determined using the third formula, whereby:

[0037]

[0038]

[0039] ;

[0040] in, This indicates the interpolation of rain gauge observations. Indicates the first fused QPE interpolation, This indicates the number of rain gauge stations within a preset radius. Indicates the preset radius. This represents the inverse square weight of the k-th observed rainfall within the preset radius relative to the square of the preset radius. This represents the observed rainfall at the k-th rain gauge station within the preset radius. This represents the first fusion QPE corresponding to the k-th rain gauge station within the preset radius.

[0041] The beneficial effect of adopting the above-mentioned further scheme is that the rain gauge observation interpolation and the first fused QPE interpolation are obtained through the third formula, so that the rain gauge observation and the initial radar QPE can be fused a second time through the rain gauge observation interpolation and the first fused QPE interpolation.

[0042] Furthermore, for each grid point within the precipitation field, the second fused QPE is determined based on the rain gauge observation interpolation and the first fused QPE interpolation, including:

[0043] For each grid point within the precipitation field, the second fused QPE is determined using the fourth formula based on rain gauge observation interpolation, the first fused QPE interpolation, and the first fused QPE. The fourth formula is as follows:

[0044] ;

[0045] in, Indicates the second fused QPE, First Fusion QPE.

[0046] The beneficial effect of adopting the above-mentioned further scheme is that the second fused QPE not only integrates the first fused QPE, but also integrates the rain gauge observation interpolation and the first fused QPE interpolation. Therefore, the second fused QPE can not only reflect the rainwater distribution characteristics of the precipitation field, but also be consistent with the rain gauge observation values, and has high accuracy.

[0047] Secondly, the present invention provides a system for fusing radar-estimated precipitation with rain gauge-observed precipitation, comprising:

[0048] The coefficient acquisition module is used to determine the A coefficient and b coefficient based on the raindrop spectrum data. The raindrop spectrum data is the acquisition parameter of the raindrop spectrometer. The A coefficient and b coefficient are used to fit the relationship between the initial radar QPE and the radar reflectivity factor.

[0049] The initial radar QPE acquisition module is used to determine the initial radar QPE corresponding to each radar in the precipitation field based on the A coefficient, b coefficient and radar reflectivity factor. The initial radar QPE is the rainfall intensity estimated by the weather radar.

[0050] The first acquisition module is used to acquire the rain gauge observations and initial radar QPE of each grid point within the precipitation field at different preset distance ranges.

[0051] The calibration factor acquisition module is used to determine the calibration factor corresponding to each preset distance range for each grid point in the precipitation field, based on the rain gauge observations and the initial radar QPE of the grid point in different preset distance ranges.

[0052] The first fused QPE acquisition module is used to calibrate the initial radar QPE of each grid point in the precipitation field according to the calibration factor corresponding to each preset distance range, so as to obtain the first fused QPE corresponding to each grid point in the precipitation field.

[0053] The second acquisition module is used to determine the rain gauge observation interpolation and the first fused QPE interpolation for each grid point in the precipitation field based on the rain gauge observation value and the first fused QPE.

[0054] The second fused QPE acquisition module is used to determine the second fused QPE for each grid point in the precipitation field based on the rain gauge observation interpolation and the first fused QPE interpolation.

[0055] Thirdly, the present invention also provides an electronic device, including a memory, a processor, and a program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of the above-described method for fusing radar-estimated precipitation with rain gauge-observed precipitation.

[0056] Fourthly, the present invention also provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores instructions that, when executed on a terminal device, cause the terminal device to perform the steps of the above-described method for fusing radar-estimated precipitation with rain gauge-observed precipitation. Attached Figure Description

[0057] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0058] Figure 1 is a flowchart illustrating a method for fusing radar-estimated precipitation with rain gauge-observed precipitation according to an embodiment of the present invention.

[0059] Figure 2 shows the rainfall map interpolated from rain gauge observations;

[0060] Figure 3 shows the rainfall map after superimposing the rain gauge observations with the first fused QPE;

[0061] Figure 4 shows the rainfall map after superimposing the rain gauge observations with the second fused QPE;

[0062] Figure 5 shows the difference between the second fused QPE and the rain gauge observation interpolation;

[0063] Figure 6 shows a scatter plot of precipitation and rain gauge precipitation from the first fused QPE;

[0064] Figure 7 shows a scatter plot of precipitation from the second fused QPE and rain gauge precipitation;

[0065] Figure 8 is a schematic diagram of a radar-estimated precipitation and rain gauge-observed precipitation fusion system according to an embodiment of the present invention. Detailed Implementation

[0066] The following embodiments are further explanations and supplements to the present invention and do not constitute any limitation on the present invention.

[0067] The following describes, with reference to the accompanying drawings, a method and system for fusing radar-estimated precipitation and rain gauge-observed precipitation according to an embodiment of the present invention.

[0068] As shown in Figure 1, an embodiment of the present invention provides a method for fusing radar-estimated precipitation with rain gauge-observed precipitation. This method can be applied to terminal devices. In this application, the terminal device is used as the execution subject to describe the solution. The terminal device can be a computer, server, etc., used to execute a method for fusing radar-estimated precipitation with rain gauge-observed precipitation.

[0069] Specifically, a method for fusing radar-estimated precipitation with rain gauge-observed precipitation includes the following steps:

[0070] S1. Based on the raindrop spectrum data, determine the A coefficient and b coefficient. The raindrop spectrum data is the acquisition parameter of the raindrop spectrometer. The A coefficient and b coefficient are used to fit the relationship between the initial radar QPE and the radar reflectivity factor.

[0071] S2. Based on the A coefficient, b coefficient and radar reflectivity factor, determine the initial radar QPE corresponding to each weather radar in the precipitation field. The initial radar QPE is the precipitation intensity estimated by the weather radar.

[0072] S3, for each grid point in the precipitation field, acquire the rain gauge observations and initial radar QPE of the grid point within different preset distance ranges;

[0073] S4. For each grid point in the precipitation field, determine the calibration factor corresponding to each preset distance range based on the rain gauge observations and the initial radar QPE of the grid point within different preset distance ranges.

[0074] S5. According to the calibration factors corresponding to each preset distance range, the initial radar QPE of each grid point in the precipitation field is calibrated to obtain the first fused QPE corresponding to each grid point in the precipitation field.

[0075] S6. For each grid point in the precipitation field, determine the rain gauge observation interpolation and the first fused QPE interpolation based on the rain gauge observation and the first fused QPE.

[0076] S7. For each grid point in the precipitation field, determine the second fused QPE based on the rain gauge observation interpolation and the first fused QPE interpolation.

[0077] Optionally, in this embodiment, all data related to weather radar can be denoised, and rain gauges can be processed for climate thresholds and spatiotemporal consistency detection to remove outliers.

[0078] Optionally, the initial radar QPE is the rainfall intensity estimated by the weather radar. One of the main functions of weather radar is to provide quantitative precipitation estimation with high spatiotemporal resolution, which is a supplement to conventional rain gauge precipitation observations. Especially in mountainous areas where rain gauges are relatively sparsely deployed, the weather radar can calculate the initial radar QPE through the ZR relationship. The estimated value of the initial radar QPE at the corresponding point of the rain gauge often has a certain error with the rain gauge observation value, but the greater advantage of the initial radar QPE is that it better represents the surface distribution characteristics of precipitation.

[0079] In addition, a rain gauge is sometimes called a rain gauge station, which is a device or equipment used to observe precipitation (referring to rain or snow). The data observed by the rain gauge station is the rain gauge observation value.

[0080] In addition, in the ZR relationship, Z represents the radar reflectivity factor, with units of mm. 6 / m 3, where is the 6th moment of the raindrop spectrum, and R represents the rainfall intensity in mm / h. Both radar reflectivity factor and rainfall intensity are related to the raindrop spectrum. The radar reflectivity factor is proportional to the 6th moment of the raindrop spectrum, and the rainfall intensity is proportional to approximately the 3.67th moment of the raindrop spectrum. Therefore, a direct relationship can be established between the radar reflectivity factor and rainfall intensity, i.e., the commonly used ZR relationship. However, the key to the ZR relationship is determining its coefficients A and b, i.e., coefficients A and b. Due to the differences in raindrop spectra under different regions, seasons, and precipitation clusters, the coefficients A and b are unstable. Based on this, the coefficients A and b of the rainfall field in this embodiment can be determined using the following method based on local historical raindrop spectrum data:

[0081] Raindrop spectral data includes radar reflectivity factor, raindrop diameter of raindrop spectrometer, number of fall velocity channels of raindrop spectrometer, sampling time of raindrop spectrometer, sampling area of ​​raindrop spectrometer, raindrop number concentration, number of raindrops per unit volume and unit diameter in diameter channel of raindrop spectrometer, number of raindrops in diameter channel and velocity channel of raindrop spectrometer, and spacing of diameter channel in raindrop spectrometer;

[0082] Based on raindrop spectral data, determine the A coefficient and b coefficient, including:

[0083] Based on the radar reflectivity factor, raindrop diameter of the raindrop spectrometer, number of terminal velocity channels of the raindrop spectrometer, sampling time of the raindrop spectrometer, sampling area of ​​the raindrop spectrometer, raindrop number concentration, number of raindrops per unit volume and unit diameter in the diameter channel of the raindrop spectrometer, number of raindrops in the diameter channel and velocity channel of the raindrop spectrometer, and spacing of the diameter channels in the raindrop spectrometer, the coefficients A and b are determined using the first formula, where the first formula is:

[0084]

[0085]

[0086]

[0087] ;

[0088] in, Radar reflectivity factor Indicates the diameter of the raindrop. This represents the raindrop number concentration, and M represents the number of terminal velocity channels. Indicates diameter Channel and speed The number of raindrops on the channel, where T represents the sampling time and S represents the sampling area. Indicates diameter The spacing of the channels, The value represents the rainfall intensity, A represents the A coefficient, and b represents the b coefficient.

[0089] Optionally, once the A coefficient and b coefficient are determined, the initial radar QPE corresponding to each weather radar within the precipitation field can be calculated using the ZR relationship between the A coefficient and b coefficient, as shown in the following formula:

[0090]

[0091] ;

[0092] in, Let R represent the radar reflectivity factor, R represent the initial radar QPE, A represent the A coefficient, and b represent the b coefficient. This indicates that the radar reflectance factor is based on commonly used radar reflectance factors. The radar reflectivity factor required for this embodiment is obtained through conversion.

[0093] Optionally, the precipitation field can be divided into multiple regions using a grid. With one grid point as the center and a preset distance range as the radius, multiple initial radar QPEs and rain gauge observations can be covered. As mentioned above, there is a certain error between the initial radar QPE and the rain gauge observations. Therefore, it is necessary to calibrate the initial radar QPE within the preset distance range using the rain gauge observations.

[0094] Optionally, for each grid point within the precipitation field, based on the rain gauge observations and initial radar QPE within different preset distance ranges, the calibration factor corresponding to each preset distance range is determined, including:

[0095] For each grid point within the precipitation field, based on the rain gauge observations and the initial radar QPE within the j-th preset distance range of the grid point, the calibration factor corresponding to the j-th preset distance range is determined using the second formula, where the second formula is:

[0096] ;

[0097] in, This represents the calibration factor corresponding to the j-th preset distance range. This represents the number of rain gauges within the j-th preset distance range. This represents the i-th rain gauge observation within the j-th preset distance range. This represents the i-th initial radar QPE within the j-th preset distance range.

[0098] Optionally, the initial radar QPE for each grid point within the precipitation field is calibrated according to the calibration factor to obtain the first fused QPE corresponding to each grid point within the precipitation field, including:

[0099] 1) For each grid point in the precipitation field, if there are at least two identical initial radar QPEs within multiple preset distance ranges, the calibration factor corresponding to each preset distance range is taken as the first target factor. Based on any one of the at least two identical initial radar QPEs and each first target factor, the first fused QPE is obtained.

[0100] For example, the preset range includes ≥60.0mm, 55.0-59.9mm, 50.0-54.9mm and 45.0-49.9mm. Among them, 55.0-59.9mm and 50.0-54.9mm contain the same initial radar QPE a and b, where a=b. Then, the calibration factors corresponding to 55.0-59.9mm and 50.0-54.9mm are taken as the first target factors, which are c and d respectively. The first fused QPE in 55.0-59.9mm and 50.0-54.9mm is equal to (a*c+a*d) / 2.

[0101] 2) If condition 1) is not met, for each grid point in the precipitation field, count the radar rain gauge pairs within each preset distance range, select any preset distance range as the target distance range, if there are more than a preset number of radar rain gauge pairs within the target distance range, then take the calibration factor corresponding to each preset distance range corresponding to the radar rain gauge pairs that are more than the preset number as the second target factor, and obtain the first fused QPE based on the initial radar QPE and each second target factor, wherein an initial radar QPE and a rain gauge observation value constitute a radar rain gauge pair;

[0102] For example, if there are no identical initial radar QPEs in multiple preset ranges, and there are only 2 radar rain gauge pairs in the preset range of 55.0-59.9mm and only 1 radar rain gauge pair in the range of 50.0-54.9mm, then the 2 radar rain gauge pairs in the range of 55.0-59.9mm are merged into the range of 50.0-54.9mm (high range merged into low range). At this time, there are more than 3 preset number of radar rain gauge pairs in the range of 50.0-54.9mm as the target range. Then the calibration factor corresponding to 50.0-54.9mm is used as the second target factor, and the first fused QPE is equal to the initial radar QPE * the second target factor.

[0103] 3) If neither condition 1) nor condition 2) is satisfied, for each grid point in the precipitation field, select any preset distance range as the target distance range. If there are fewer than the preset number of radar rain gauge pairs within the target distance range, then the initial radar QPE is used as the first fused QPE.

[0104] For example, if there are no identical initial radar QPEs in multiple preset distance ranges, and there is only one radar rain gauge pair in the preset distance range of 55.0-59.9mm and only one radar rain gauge pair in the preset distance range of 50.0-54.9mm, then their respective initial radar QPEs are retained.

[0105] Optionally, the calibrated first fused QPE and rainfall observations can be re-interpolated back into the precipitation field to achieve secondary fusion of the first fused QPE and rainfall observations, and further estimate the precipitation intensity.

[0106] Optionally, the method further includes:

[0107] For each grid point in the precipitation field, obtain the inverse square weight of each rain gauge observation value within the preset radius of the grid point and the preset radius.

[0108] For each grid point within the precipitation field, based on rain gauge observations and the first fused QPE, determine the rain gauge observation interpolation and the first fused QPE interpolation, including:

[0109] For each grid point within the precipitation field, based on the inverse square weight of each rain gauge observation within the preset radius of the grid point, the rain gauge observation value, and the first fused QPE, the rain gauge observation interpolation and the first fused QPE interpolation are determined using the third formula, whereby:

[0110]

[0111]

[0112] ;

[0113] in, This indicates the interpolation of rain gauge observations. Indicates the first fused QPE interpolation, This indicates the number of rain gauge stations within a preset radius. Indicates the preset radius. This represents the inverse square weight of the k-th observed rainfall within the preset radius relative to the square of the preset radius. This represents the observed rainfall at the k-th rain gauge station within the preset radius. This represents the first fusion QPE corresponding to the k-th rain gauge station within the preset radius.

[0114] Optionally, for each grid point within the precipitation field, the second fused QPE is determined based on the rain gauge observation interpolation and the first fused QPE interpolation, including:

[0115] For each grid point within the precipitation field, the second fused QPE is determined using the fourth formula based on rain gauge observation interpolation, the first fused QPE interpolation, and the first fused QPE. The fourth formula is as follows:

[0116] ;

[0117] in, Indicates the second fused QPE, First Fusion QPE.

[0118] Optionally, in the fourth formula, the first fused QPE combines the initial radar QPE and rain gauge observations, which can very well represent the rainfall intensity distribution characteristics of the precipitation field, while the rain gauge observation interpolation can reflect the true rain gauge values ​​in the precipitation field. This represents the error between the first fused QPE and the first fused QPE interpolation. This error is added to the rain gauge observation interpolation to correct the error in the true value of the rain gauge in the precipitation field.

[0119] Optionally, one specific application of this embodiment:

[0120] A regional rainstorm that occurred in Chongqing in 2018 was selected as an example. First, the data from rain gauges and weather radar were denoised. The rain gauge rainfall was subjected to quality control such as climate threshold and spatiotemporal consistency checks. The weather radar data was selected using the SWAN mosaic reflectivity factor product, which has already undergone quality control such as denoising and removal of ground features.

[0121] Secondly, the initial radar QPE was calculated. The A coefficient and b coefficient of the ZR relationship were obtained by fitting raindrop spectrum data from the Shapingba station in Chongqing. The values ​​were 446.3 and 1.3, respectively. The initial radar QPE was calculated through the ZR relationship. Next, the first fused QPE was obtained by combining the initial radar QPE with the quality-controlled rain gauge data. Then, the first fused QPE value corresponding to the rain gauge station was interpolated with the rain gauge observation value and added to the precipitation field. Finally, the precipitation was fused again to obtain the second fused QPE.

[0122] Figures 2-5 show the merged precipitation at one time point during a regional rainstorm that occurred in Chongqing in 2018. Figure 2 shows the precipitation map interpolated from rain gauge observations, Figure 3 shows the precipitation map after superimposing the rain gauge observations onto the first merged QPE, Figure 4 shows the precipitation map after superimposing the rain gauge observations onto the second merged QPE, and Figure 5 shows the difference between the second merged QPE and the rain gauge interpolated data. As can be seen from Figures 2-5, there are certain differences in the distribution of precipitation between the individual rain gauge interpolated data and the first and second merged QPEs, especially in the areas of heavy precipitation centers. From the distribution of rain gauge stations, the rain gauge density did not detect some small- to medium-scale heavy precipitation centers, which were highlighted by the merged precipitation (see heavy precipitation above 40 mm / h in Figures 3 and 4), as can also be seen in the heavy precipitation above 40 mm / h in Figure 5.

[0123] Figures 6 and 7 are scatter plots of precipitation from the first and second fused QPEs, respectively, and rain gauge observations. In both Figures 6 and 7, the horizontal axis represents the rain gauge observations (unit: mm / h). The vertical axis in Figure 6 represents the first fused QPE, and the vertical axis in Figure 7 represents the second fused QPE. The scatter plots in Figure 6 are mainly distributed around and to the sides of y=x (the solid line in the figure), and are relatively evenly distributed. This indicates that the first fused QPE and the rain gauge observations are generally consistent, which to some extent also suggests that the first fused QPE... The combined QPE can already reflect the precipitation distribution characteristics, but there is still a certain error between the observed values ​​and the actual values ​​at the rain gauge observation points. This error is resolved by further fusion, as shown in Figure 7. The second fused QPE is significantly consistent with the rain gauge observation values ​​at the rain gauge stations. In this way, the fused precipitation combines the advantages of radar surface observations and rain gauge point observations. It can better reflect the distribution characteristics of precipitation estimated by weather radar on the surface, while ensuring the observation accuracy of rain gauges at the points. This is of positive significance for improving the monitoring capability of small and medium-scale precipitation, especially the monitoring capability of local heavy precipitation.

[0124] As shown in Figure 8, an embodiment of the present invention provides a fusion system for radar-estimated precipitation and rain gauge-observed precipitation, comprising:

[0125] The coefficient acquisition module 201 is used to determine the A coefficient and b coefficient based on the raindrop spectrum data. The raindrop spectrum data is the acquisition parameter of the raindrop spectrometer. The A coefficient and b coefficient are used to fit the relationship between the initial radar QPE and the radar reflectivity factor.

[0126] The initial radar QPE acquisition module 202 is used to determine the initial radar QPE corresponding to each radar in the precipitation field based on the A coefficient, b coefficient and radar reflectivity factor. The initial radar QPE is the rainfall intensity estimated by the weather radar.

[0127] The first acquisition module 203 is used to acquire, for each grid point in the precipitation field, the rain gauge observation value and the initial radar QPE of the grid point within different preset distance ranges;

[0128] The calibration factor acquisition module 204 is used to determine the calibration factor corresponding to each preset distance range for each grid point in the precipitation field based on the rain gauge observation values ​​and the initial radar QPE of the grid point in different preset distance ranges.

[0129] The first fused QPE acquisition module 205 is used to calibrate the initial radar QPE of each grid point in the precipitation field according to the calibration factor corresponding to each preset distance range, so as to obtain the first fused QPE corresponding to each grid point in the precipitation field.

[0130] The second acquisition module 206 is used to determine the rain gauge observation interpolation and the first fused QPE interpolation for each grid point in the precipitation field based on the rain gauge observation value and the first fused QPE.

[0131] The second fused QPE acquisition module 207 is used to determine the second fused QPE for each grid point in the precipitation field based on the rain gauge observation interpolation and the first fused QPE interpolation.

[0132] Optionally, the system may also include:

[0133] The raindrop spectrum data acquisition module is used to acquire radar reflectivity factor, raindrop diameter of raindrop spectrometer, number of fall velocity channels of raindrop spectrometer, sampling time of raindrop spectrometer, sampling area of ​​raindrop spectrometer, raindrop number concentration, number of raindrops per unit volume and unit diameter in diameter channel of raindrop spectrometer, number of raindrops in diameter channel and velocity channel of raindrop spectrometer, and spacing of diameter channel in raindrop spectrometer;

[0134] The coefficient acquisition module 201 is also used for:

[0135] Based on the radar reflectivity factor, raindrop diameter of the raindrop spectrometer, number of terminal velocity channels of the raindrop spectrometer, sampling time of the raindrop spectrometer, sampling area of ​​the raindrop spectrometer, raindrop number concentration, number of raindrops per unit volume and unit diameter in the diameter channel of the raindrop spectrometer, number of raindrops in the diameter channel and velocity channel of the raindrop spectrometer, and spacing of the diameter channels in the raindrop spectrometer, the coefficients A and b are determined using the first formula, where the first formula is:

[0136]

[0137]

[0138]

[0139] ;

[0140] in, Radar reflectivity factor Indicates the diameter of the raindrop. This represents the raindrop number concentration, and M represents the number of terminal velocity channels. Indicates diameter Channel and speed The number of raindrops on the channel, where T represents the sampling time and S represents the sampling area. Indicates diameter The spacing of the channels, The value represents the rainfall intensity, A represents the A coefficient, and b represents the b coefficient.

[0141] Optionally, the calibration factor acquisition module 204 is also used for:

[0142] For each grid point within the precipitation field, based on the rain gauge observations and the initial radar QPE within the j-th preset distance range of the grid point, the calibration factor corresponding to the j-th preset distance range is determined using the second formula, where the second formula is:

[0143] ;

[0144] in, This represents the calibration factor corresponding to the j-th preset distance range. This represents the number of rain gauges within the j-th preset distance range. This represents the i-th rain gauge observation within the j-th preset distance range. This represents the i-th initial radar QPE within the j-th preset distance range.

[0145] Optionally, the first fused QPE acquisition module 205 acquires the first fused QPE through the first unit, wherein the first unit is specifically used for:

[0146] For each grid point in the precipitation field, if there are at least two identical initial radar QPEs within multiple preset distance ranges, the calibration factor corresponding to each preset distance range is taken as the first target factor. Based on any one of the at least two identical initial radar QPEs and each first target factor, the first fused QPE is obtained.

[0147] For each grid point in the precipitation field, count the radar rain gauge pairs within each preset distance range, select any preset distance range as the target distance range, if there are more than a preset number of radar rain gauge pairs within the target distance range, then take the calibration factor corresponding to each preset distance range corresponding to the radar rain gauge pairs that are more than the preset number as the second target factor, and obtain the first fused QPE based on the initial radar QPE and each second target factor, wherein an initial radar QPE and a rain gauge observation value constitute a radar rain gauge pair;

[0148] For each grid point in the precipitation field, select any preset distance range as the target distance range. If there are fewer than the preset number of radar rain gauge pairs within the target distance range, then the initial radar QPE is used as the first fused QPE.

[0149] Optionally, the system may also include:

[0150] The weight acquisition module is used to acquire the inverse square weight of each rain gauge observation value within a preset radius of the grid point in the precipitation field.

[0151] The second acquisition module 206 is further configured to, for each grid point within the precipitation field, determine the rain gauge observation interpolation and the first fused QPE interpolation using a third formula, based on the inverse square weight of each rain gauge observation value to the preset radius within the preset radius of the grid point, the rain gauge observation value, and the first fused QPE. The third formula is as follows:

[0152]

[0153]

[0154] ;

[0155] in, This indicates the interpolation of rain gauge observations. Indicates the first fused QPE interpolation, This indicates the number of rain gauge stations within a preset radius. Indicates the preset radius. This represents the inverse square weight of the k-th observed rainfall within the preset radius relative to the square of the preset radius. This represents the observed rainfall at the k-th rain gauge station within the preset radius. This represents the first fusion QPE corresponding to the k-th rain gauge station within the preset radius.

[0156] Optionally, the second acquisition module 206 is also used for:

[0157] For each grid point within the precipitation field, the second fused QPE is determined using the fourth formula based on rain gauge observation interpolation, the first fused QPE interpolation, and the first fused QPE. The fourth formula is as follows:

[0158] ;

[0159] in, Indicates the second fused QPE, First Fusion QPE.

[0160] An electronic device according to an embodiment of the present invention includes a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, it implements some or all of the steps of the above-described intelligent data collection and push method based on supply chain management.

[0161] The electronic device can be a computer, and its program is computer software. The parameters and steps of the electronic device of the present invention can be referred to the parameters and steps in the embodiment of the data intelligent collection and push method based on supply chain management in the above text, and will not be repeated here.

[0162] Those skilled in the art will recognize that this invention can be implemented as a system, method, or computer program product. Therefore, this disclosure can be embodied in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, the invention can also be implemented as a computer program product contained in one or more computer-readable media, which contains computer-readable program code. Computer-readable storage media can be, for example, but not limited to—electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof.

[0163] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present 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. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0164] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for fusing radar-estimated precipitation with rain gauge-observed precipitation, characterized in that, The method includes the following steps: determining A coefficients and b coefficients based on raindrop spectrum data, where the raindrop spectrum data is the acquisition parameters of a raindrop spectrometer, and the A coefficients and b coefficients are used to fit the relationship between the initial radar QPE and the radar reflectivity factor; determining the initial radar QPE corresponding to each weather radar within the precipitation field based on the A coefficients, the b coefficients, and the radar reflectivity factor, where the initial radar QPE is the rainfall intensity estimated by the weather radar; for each grid point within the precipitation field, acquiring the rain gauge observation values ​​and the initial radar QPE of the grid point within different preset distance ranges, where each grid point corresponds to at least one weather radar; for each grid point within the precipitation field, determining a calibration factor corresponding to each preset distance range based on the rain gauge observation values ​​and the initial radar QPE of the grid point within different preset distance ranges; and calibrating the initial radar QPE of each grid point within the precipitation field based on the calibration factors corresponding to each preset distance range. The process includes obtaining a first fused QPE corresponding to each grid point within the precipitation field; for each grid point within the precipitation field, determining the rain gauge observation interpolation and the first fused QPE interpolation based on the rain gauge observation value and the first fused QPE; for each grid point within the precipitation field, determining a second fused QPE based on the rain gauge observation interpolation and the first fused QPE interpolation; and further including: for each grid point within the precipitation field, obtaining the inverse square weight of each rain gauge observation value within a preset radius of the grid point to the preset radius; the determination of the rain gauge observation interpolation and the first fused QPE interpolation for each grid point within the precipitation field, based on the rain gauge observation value and the first fused QPE, includes: for each grid point within the precipitation field, determining the rain gauge observation interpolation and the first fused QPE interpolation based on the inverse square weight of each rain gauge observation value within a preset radius of the grid point, the rain gauge observation value, and the first fused QPE, using a third formula, wherein the third formula is: ;in, This indicates the interpolation of rain gauge observations. Indicates the first fused QPE interpolation, This indicates the number of rain gauge stations within a preset radius. Indicates the preset radius. This represents the inverse square weight of the k-th observed rainfall within the preset radius relative to the square of the preset radius. This represents the observed rainfall at the k-th rain gauge station within the preset radius. The first fused QPE corresponds to the k-th rain gauge station within a preset radius; the determination of the second fused QPE for each grid point within the precipitation field, based on the rain gauge observation interpolation and the first fused QPE interpolation, includes: for each grid point within the precipitation field, determining the second fused QPE using a fourth formula based on the rain gauge observation interpolation, the first fused QPE interpolation, and the first fused QPE, wherein the fourth formula is: ;in, Indicates the second fused QPE, First Fusion QPE.

2. The method according to claim 1, characterized in that, The raindrop spectral data includes radar reflectivity factor, raindrop diameter of the raindrop spectrometer, number of fall velocity channels of the raindrop spectrometer, sampling time of the raindrop spectrometer, sampling area of ​​the raindrop spectrometer, raindrop number concentration, number of raindrops per unit volume and unit diameter in the diameter channel of the raindrop spectrometer, number of raindrops in the diameter channel and velocity channel of the raindrop spectrometer, and spacing of the diameter channels in the raindrop spectrometer. The determination of coefficients A and b based on raindrop spectral data includes: determining coefficients A and b using a first formula based on the radar reflectivity factor, raindrop diameter of the raindrop spectrometer, number of terminal velocity channels of the raindrop spectrometer, sampling time of the raindrop spectrometer, sampling area of ​​the raindrop spectrometer, raindrop number concentration, number of raindrops per unit volume and unit diameter in the diameter channel of the raindrop spectrometer, number of raindrops in the diameter channel and velocity channel of the raindrop spectrometer, and spacing of the diameter channels of the raindrop spectrometer. The first formula is: ； ;in, Radar reflectivity factor Indicates the diameter of the raindrop. This represents the raindrop number concentration, and M represents the number of terminal velocity channels. Indicates diameter Channel and speed The number of raindrops on the channel, where T represents the sampling time and S represents the sampling area. Indicates diameter The spacing of the channels, The value represents the rainfall intensity, A represents the A coefficient, and b represents the b coefficient.

3. The method according to claim 2, characterized in that, For each grid point within the precipitation field, based on the rain gauge observations and the initial radar QPE within different preset distance ranges of the grid point, a calibration factor corresponding to each preset distance range is determined, including: for each grid point within the precipitation field, based on the rain gauge observations and the initial radar QPE within the j-th preset distance range of the grid point, a calibration factor corresponding to the j-th preset distance range is determined using a second formula, wherein the second formula is: ;in, This represents the calibration factor corresponding to the j-th preset distance range. This represents the number of rain gauges within the j-th preset distance range. This represents the i-th rain gauge observation within the j-th preset distance range. This represents the i-th initial radar QPE within the j-th preset distance range.

4. The method according to claim 2, characterized in that, The step of calibrating the initial radar QPE for each grid point within the precipitation field according to the calibration factor to obtain the first fused QPE corresponding to each grid point within the precipitation field includes: for each grid point within the precipitation field, if there are at least two identical initial radar QPEs within multiple preset distance ranges, then the calibration factor corresponding to each preset distance range is used as the first target factor, and the first fused QPE is obtained based on any one of the at least two identical initial radar QPEs and each of the first target factors; for each grid point within the precipitation field, the radar rain gauge pairs within each preset distance range are counted, and any preset distance range is selected as the target distance. If there are more than a preset number of radar rain gauge pairs within the target distance range, then the calibration factors corresponding to each preset distance range corresponding to the greater than preset number of radar rain gauge pairs are used as second target factors. Based on the initial radar QPE and each of the second target factors, a first fused QPE is obtained, wherein one initial radar QPE and one rain gauge observation value constitute one radar rain gauge pair. For each grid point in the precipitation field, any preset distance range is selected as the target distance range. If there are less than a preset number of radar rain gauge pairs within the target distance range, then the initial radar QPE is used as the first fused QPE.

5. A system for fusing radar-estimated precipitation with rain gauge-observed precipitation, characterized in that, include: The coefficient acquisition module is used to determine the A coefficient and b coefficient based on raindrop spectrum data, where the raindrop spectrum data is the acquisition parameter of the raindrop spectrometer, and the A coefficient and b coefficient are used to fit the relationship between the initial radar QPE and the radar reflectivity factor; the initial radar QPE acquisition module is used to determine the initial radar QPE corresponding to each radar in the precipitation field based on the A coefficient, the b coefficient and the radar reflectivity factor, where the initial radar QPE is the rainfall intensity estimated by the weather radar. The first acquisition module is used to acquire, for each grid point in the precipitation field, the rain gauge observation value of the grid point within a different preset distance range and the initial radar QPE; The calibration factor acquisition module is used to determine the calibration factor corresponding to each preset distance range for each grid point in the precipitation field based on the rain gauge observation value and the initial radar QPE of the grid point in different preset distance ranges; the first fused QPE acquisition module is used to calibrate the initial radar QPE of each grid point in the precipitation field based on the calibration factor corresponding to each preset distance range to obtain the first fused QPE corresponding to each grid point in the precipitation field. The second acquisition module is used to determine the rain gauge observation interpolation and the first fusion QPE interpolation for each grid point in the precipitation field based on the rain gauge observation value and the first fusion QPE; the second fusion QPE acquisition module is used to determine the second fusion QPE for each grid point in the precipitation field based on the rain gauge observation interpolation and the first fusion QPE interpolation; and for each grid point in the precipitation field, to acquire the inverse square weight of each rain gauge observation value within a preset radius of the grid point and the preset radius. The step of determining the rain gauge observation interpolation and the first fused QPE interpolation for each grid point within the precipitation field, based on the rain gauge observations and the first fused QPE, includes: for each grid point within the precipitation field, determining the rain gauge observation interpolation and the first fused QPE interpolation using a third formula based on the inverse square weight of each rain gauge observation to the preset radius within the preset radius of the grid point, the rain gauge observations, and the first fused QPE, wherein the third formula is: ;in, This indicates the interpolation of rain gauge observations. Indicates the first fused QPE interpolation, This indicates the number of rain gauge stations within a preset radius. Indicates the preset radius. This represents the inverse square weight of the k-th observed rainfall within the preset radius relative to the square of the preset radius. This represents the observed rainfall at the k-th rain gauge station within the preset radius. The first fused QPE corresponds to the k-th rain gauge station within a preset radius; the determination of the second fused QPE for each grid point within the precipitation field, based on the rain gauge observation interpolation and the first fused QPE interpolation, includes: for each grid point within the precipitation field, determining the second fused QPE using a fourth formula based on the rain gauge observation interpolation, the first fused QPE interpolation, and the first fused QPE, wherein the fourth formula is: ;in, Indicates the second fused QPE, First Fusion QPE.

6. An electronic device comprising a memory, a processor, and a program stored in the memory and running on the processor, characterized in that, When the processor executes the program, it implements the steps of the method for fusing radar-estimated precipitation and rain gauge-observed precipitation as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a terminal device, cause the terminal device to perform the steps of the method for fusing radar-estimated precipitation and rain gauge-observed precipitation as described in any one of claims 1 to 4.

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