Method, device, electronic device and medium for reconstructing three-dimensional cloud body by fusion of satellite, ground and cloud

Abstract

The present disclosure discloses a method, device, electronic device and medium for reconstructing a three-dimensional cloud body by integrating satellite, ground and cloud. The method for reconstructing a three-dimensional cloud body by integrating satellite, ground and cloud comprises: obtaining ground-based cloud observation data of at least three cloud radars; obtaining multi-channel scanning imaging radiometer data and cloud detection product data of geostationary meteorological satellites; performing spatiotemporal matching of the ground-based cloud observation data, the multi-channel scanning imaging radiometer data and the cloud detection product data to obtain satellite-ground matching data; inverting the cloud top height of the satellite in a preset area around each cloud radar installation point based on the satellite-ground matching data to obtain the cloud top height of the cloud radar networking area; obtaining the cloud bottom height of the cloud radar networking area based on the ground-based cloud observation data; obtaining the three-dimensional cloud body boundary based on the cloud top height and the cloud bottom height; and obtaining a reconstructed three-dimensional cloud body based on the reflectivity factor profile and radial velocity profile in the ground-based cloud observation data.

Description

Technical Field

[0001] The present invention relates to the field of atmospheric detection and atmospheric remote sensing, and in particular to a method, device, electronic equipment and medium for reconstructing a three-dimensional cloud body by integrating satellite, ground and cloud. Background Art

[0002] One way to obtain cloud observation data is through large-area remote sensing observations by meteorological satellites, especially geostationary meteorological satellites, which remain in a constant relative position to the earth, and can achieve high-frequency continuous observations of the same location on the earth. Meteorological satellites can obtain information on cloud distribution, cloud amount, cloud shape, etc. over a large area. They can also use the characteristics of the cloud's infrared radiation being related to temperature to further invert cloud top height information based on satellite infrared cloud images. However, since satellite observation data is affected by many factors such as the earth's atmosphere, surface, position of the sun, and the working status of onboard instruments, and the intensity of cloud infrared radiation is related to factors such as cloud density, cloud top height, and cloud thickness, the cloud top height directly inverted by satellites sometimes has large errors.

[0003] Another way to obtain cloud observation data is through single-point observation of ground-based clouds, such as laser ceilometers, all-sky imagers, millimeter-wave cloud radars, etc. Among them, millimeter-wave cloud radars work in the Ka (35GHz) band and use the scattering characteristics of hydrometeors on millimeter waves to penetrate thicker clouds and obtain basic information such as echo intensity, radial velocity, and velocity spectrum width inside the cloud body. Further processing can obtain cloud top height and cloud base height products. However, the data obtained from single-point observation of ground-based clouds have the characteristics of more "point" products, fewer "surface" products, and a single vertical product. These characteristics limit the effectiveness of comprehensive observations. Summary of the invention

[0004] The embodiments of the present disclosure provide a method, device, electronic device and medium for reconstructing a three-dimensional cloud body by integrating satellite, ground and cloud.

[0005] In a first aspect, an embodiment of the present disclosure provides a method for reconstructing a three-dimensional cloud body by integrating satellite, ground and cloud.

[0006] The method for reconstructing a three-dimensional cloud body by integrating satellite, ground and cloud includes:

[0007] Acquiring ground-based cloud observation data from at least three cloud radars, wherein the at least three cloud radars are networked at a preset station spacing;

[0008] Based on the acquired ground-based cloud observation data, the cloud top height, cloud bottom height, reflectivity factor profile and radial velocity profile of each cloud radar installation point are obtained;

[0009] Acquire multi-channel scanning imaging radiometer data and cloud detection product data from geostationary meteorological satellites;

[0010] Performing temporal and spatial matching on the ground-based cloud observation data, the multi-channel scanning imaging radiometer data and the cloud detection product data to obtain satellite-ground matching data;

[0011] Based on the satellite-ground matching data, the cloud top height of the satellite in the preset area around each cloud radar installation point is inverted to obtain the cloud top height of the preset area around each cloud radar installation point, and further obtain the cloud top height of the cloud radar networking area;

[0012] The cloud base height of each cloud radar is interpolated to obtain the cloud base height of the cloud radar network area;

[0013] Matching the cloud base height and cloud top height of the cloud radar network area to obtain a three-dimensional cloud body boundary;

[0014] Based on the cloud radar reflectivity factor profile and the radial velocity profile, surface interpolation is performed on each vertical height layer to fill the three-dimensional cloud body to obtain a reconstructed three-dimensional cloud body, wherein the height of each vertical height layer is determined by the vertical distance resolution of the cloud radar.

[0015] According to an embodiment of the present disclosure, the cloud top height, cloud bottom height, reflectivity factor profile and radial velocity profile of each cloud radar installation point vertically above the ground-based cloud observation data obtained include:

[0016] Acquiring cloud radar power spectrum data from the ground-based cloud observation data;

[0017] Obtain a main peak of the power spectrum according to the position, width and amplitude of the peak body in the power spectrum data, and obtain a reflectivity factor and a radial velocity according to the main peak of the power spectrum;

[0018] Acquire power spectrum data at each vertical height layer, and obtain a vertical reflectivity factor profile and a radial velocity profile according to the power spectrum data at each vertical height layer;

[0019] The cloud top height and cloud bottom height in the vertical direction are obtained according to the reflectivity factor profile and the radial velocity profile.

[0020] According to an embodiment of the present disclosure, performing spatiotemporal matching on the ground-based cloud observation data, the multi-channel scanning imaging radiometer data and the cloud detection product data to obtain satellite-ground matching data includes:

[0021] The M minutes before and after the satellite observation time is used as the ground-based cloud observation data time window;

[0022] Determine the proportion of cloud-free time within the time window based on the cloud detection product data;

[0023] When the proportion of cloud-free time in the time window is less than a first preset threshold, according to the location information of the cloud radar installation point, the pixel point closest to the satellite is searched for matching to obtain spatial matching data;

[0024] The cloud top height and cloud bottom height of the cloud radar are normalized respectively within the time window, and then the normalized data are matched with the space matching data to obtain the satellite-ground matching data, wherein M is a positive integer.

[0025] According to an embodiment of the present disclosure, the cloud top height inversion of the satellite in the preset area around each cloud radar installation point based on the satellite-ground matching data is implemented to obtain the cloud top height of the preset area of ​​each cloud radar installation point, including:

[0026] The cloud top height of the cloud radar in the time window is normalized to obtain the normalized cloud top height H of the matching pixel point. a ;

[0027] Get the thermal infrared channel data Z from the multi-channel scanning imaging radiometer data of the matching pixel point a ;

[0028] Based on the formula Get the satellite-ground-cloud fusion factor of the cloud radar at the observation time corresponding to the time window

[0029] Based on the formula Get the cloud top height H of other pixels around the cloud radar installation point at the time of observation by the satellite ij , where i and j are the row and column numbers of the locations of other satellite pixels;

[0030] Based on the cloud top heights of the pixels around all cloud radar installation points at the time of the observation, the cloud top heights of the preset areas of the cloud radar installation points are obtained;

[0031] Among them, the preset area is a circular area with the cloud radar installation point as the center and the first preset distance as the radius.

[0032] According to an embodiment of the present disclosure, combining the cloud top heights of the preset areas of the cloud radar installation points to obtain the cloud top height of the cloud radar networking area includes:

[0033] When there is overlap between the preset areas of the cloud radar installation points, it is determined that the average of the cloud top heights of the preset areas of the cloud radar installation points constituting the overlap is the cloud top height of the overlapping area.

[0034] According to an embodiment of the present disclosure, when there are multiple layers of clouds in the vertical observation direction of the cloud radar, the cloud top height, cloud bottom height, reflectivity factor profile and radial velocity profile in the vertical overhead space of the cloud radar installation point are determined based on the observation data of the topmost cloud whose thickness is greater than a second preset threshold.

[0035] According to an embodiment of the present disclosure, the interpolation refers to interpolation performed with satellite spatial resolution as a grid point.

[0036] According to an embodiment of the present disclosure, it also includes taking extreme values ​​of the reflectivity factor and radial velocity of the three-dimensional cloud body to obtain a combined reflectivity factor and combined radial velocity of the cloud radar networking area, wherein the extreme values ​​of the reflectivity factor and radial velocity of the three-dimensional cloud body are, the maximum value of the reflectivity factor, and the minimum value of the radial velocity.

[0037] In a second aspect, an apparatus for reconstructing a three-dimensional cloud body by integrating satellite, ground and cloud is provided in an embodiment of the present disclosure.

[0038] The device for reconstructing a three-dimensional cloud body by integrating satellite, ground and cloud includes:

[0039] A first acquisition module, the first acquisition module is configured to acquire ground-based cloud observation data of at least three cloud radars, and obtain a cloud top height, a cloud bottom height, a reflectivity factor and a radial velocity profile of a vertical overhead space of each cloud radar installation point based on the acquired ground-based cloud observation data, wherein the at least three cloud radars are networked at a preset station spacing;

[0040] A second acquisition module is configured to acquire multi-channel scanning imaging radiometer data and cloud detection product data of geostationary meteorological satellites;

[0041] a space-time matching module configured to perform space-time matching on the ground-based cloud observation data, the multi-channel scanning imaging radiometer data and the cloud detection product data to obtain satellite-ground matching data;

[0042] An inversion module is configured to realize the inversion of the cloud top height of the satellite in the preset area around each cloud radar installation point based on the satellite-ground matching data, obtain the cloud top height of the preset area of ​​each cloud radar installation point, and further obtain the cloud top height of the cloud radar networking area;

[0043] A determination module is configured to interpolate the cloud base height of each cloud radar to obtain the cloud base height of the cloud radar networking area;

[0044] The reconstruction module is configured to match the cloud base height and cloud top height of the cloud radar networking area to obtain a three-dimensional cloud body boundary; based on the cloud radar reflectivity factor profile and radial velocity profile, perform surface interpolation at each vertical height layer to fill the three-dimensional cloud body to obtain a reconstructed three-dimensional cloud body, wherein the height of each vertical height layer is determined by the vertical distance resolution of the cloud radar.

[0045] In a third aspect, an embodiment of the present disclosure provides an electronic device, including a memory and a processor, wherein the memory is used to store one or more computer instructions that support a data processing device to execute the above-mentioned satellite-ground-cloud fusion reconstruction three-dimensional cloud body method, and the processor is configured to execute the computer instructions stored in the memory. The electronic device may also include a communication interface for the electronic device to communicate with other devices or a communication network.

[0046] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium for storing computer instructions used by a data processing device, which includes computer instructions involved in the data processing device for executing the above-mentioned method for reconstructing a three-dimensional cloud body by fusion of satellites, ground and clouds.

[0047] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects:

[0048] The method for reconstructing three-dimensional cloud bodies by integrating satellite, ground and cloud provided in the embodiments of the present disclosure effectively combines the characteristics of large-scale observation of geostationary meteorological satellites and high-precision observation of ground-based cloud radars, and performs spatiotemporal matching and data fusion of the two, so as to quickly and accurately realize three-dimensional stereoscopic reconstruction of clouds in the cloud radar networking area, thereby improving the speed and accuracy of three-dimensional cloud body reconstruction; the reconstructed three-dimensional cloud body can provide a variety of products such as cloud top height, cloud bottom height and three-dimensional cloud fusion products on the surface of the cloud radar networking area, and can be widely used in cloud visualization monitoring and applications.

[0049] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Other features, objectives and advantages of the present disclosure will become more apparent through the following detailed description of non-limiting embodiments in conjunction with the accompanying drawings. In the accompanying drawings:

[0051] Figure 1 A flow chart of a method for reconstructing a three-dimensional cloud body by integrating satellite, ground and cloud according to an embodiment of the present disclosure is shown.

[0052] Figure 2 A schematic diagram showing a cloud radar networking area acquisition process according to an embodiment of the present disclosure.

[0053] Figure 3A structural diagram of a satellite-ground-cloud fusion three-dimensional cloud body reconstruction device according to an embodiment of the present disclosure is shown.

[0054] Figure 4 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown.

[0055] Figure 5 It is a structural diagram of a computer system suitable for implementing the data transmission method according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0056] Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. In addition, for the sake of clarity, parts not related to the description of the exemplary embodiments are omitted in the accompanying drawings.

[0057] In the present disclosure, it should be understood that terms such as "include" or "have" are intended to indicate the presence of features, numbers, steps, behaviors, components, parts, or a combination thereof disclosed in the specification, and do not exclude the possibility that one or more other features, numbers, steps, behaviors, components, parts, or a combination thereof exist or are added.

[0058] It should also be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present disclosure may be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0059] The details of the embodiments of the present disclosure are described in detail below through specific examples.

[0060] As mentioned above, satellite observation data is affected by many factors such as the Earth's atmosphere, surface, position of the sun, and the working status of onboard instruments. In addition, the cloud's infrared radiation intensity is related to factors such as cloud density, cloud top height, and cloud thickness. The cloud top height directly inverted by the satellite sometimes has large errors. At the same time, the data obtained from single-point observations of ground-based clouds have the characteristics of many "point" products, few "surface" products, and a single vertical product. These characteristics limit the effectiveness of comprehensive observations. Therefore, the existing three-dimensional cloud reconstruction methods cannot quickly and accurately reconstruct three-dimensional clouds over a large range.

[0061] In view of this, the present invention proposes a method for reconstructing a three-dimensional cloud body by integrating satellite, ground and cloud. By effectively combining the large-scale observation of geostationary meteorological satellites and the high-precision observation of ground-based cloud radars, the two are matched in time and space and data are fused. The three-dimensional reconstruction of clouds in the cloud radar networking area can be achieved quickly and accurately, thereby improving the speed and accuracy of three-dimensional cloud body reconstruction. The reconstructed three-dimensional cloud body can provide a variety of products such as cloud top height, cloud bottom height, combined reflectivity factor, combined radial velocity product and three-dimensional cloud fusion product on the surface of the cloud radar networking area, which can be widely used in cloud visualization monitoring and application.

[0062] Figure 1 A flow chart of a method for reconstructing a three-dimensional cloud body by integrating satellite, ground and cloud according to an embodiment of the present disclosure is shown. Figure 1 As shown, the method for reconstructing a three-dimensional cloud body by integrating satellite, ground and cloud includes the following steps S101-S107:

[0063] In step S101, ground-based cloud observation data of at least three cloud radars are obtained, wherein the at least three cloud radars are networked at a preset station distance;

[0064] In step S102, based on the acquired ground-based cloud observation data, the cloud top height, cloud bottom height, reflectivity factor profile and radial velocity profile of each cloud radar installation point are obtained vertically.

[0065] In step S103, multi-channel scanning imaging radiometer data and cloud detection product data of a geostationary meteorological satellite are obtained;

[0066] In step S104, the ground-based cloud observation data, the multi-channel scanning imaging radiometer data and the cloud detection product data are temporally and spatially matched to obtain satellite-ground matching data;

[0067] In step S105, based on the satellite-ground matching data, the cloud top height of the satellite in the preset area around each cloud radar installation point is inverted to obtain the cloud top height of the preset area of ​​each cloud radar installation point, and further obtain the cloud top height of the cloud radar networking area;

[0068] In step S106, the cloud base height of each cloud radar is interpolated to obtain the cloud base height of the cloud radar network area;

[0069] In step S107, the cloud base height and cloud top height of the cloud radar networking area are matched to obtain a three-dimensional cloud body boundary;

[0070] In step S108, based on the cloud radar reflectivity factor profile and the radial velocity profile, surface interpolation is performed at each vertical height layer to fill the three-dimensional cloud body to obtain a reconstructed three-dimensional cloud body, wherein the height of each vertical height layer is determined by the vertical distance resolution of the cloud radar.

[0071] In the disclosed embodiment, the cloud radar may be a millimeter wave cloud radar, and the at least three cloud radars may be arranged and networked in a polygonal manner. For example, when there are three cloud radars, a triangular layout is recommended, when there are four cloud radars, a square or rectangular layout is recommended, and when there are five cloud radars, a pentagonal layout is recommended. In addition, when the number of cloud radars is large, in addition to forming a polygon, it is also necessary to lay out in the middle area of ​​the polygon to achieve full coverage of the internal area of ​​the polygon. There is a certain station distance between the cloud radars, and the certain station distance can be up to 100 kilometers between two adjacent stations.

[0072] In the disclosed embodiment, the cloud top height, cloud bottom height, reflectivity factor profile and radial velocity profile of each cloud radar installation point in the vertical overhead space are obtained based on the acquired ground-based cloud observation data, including: obtaining the cloud radar power spectrum data in the ground-based cloud observation data; obtaining the main peak of the power spectrum according to the position, width and amplitude of the peak in the power spectrum data, and obtaining the reflectivity factor and radial velocity according to the main peak of the power spectrum; obtaining the power spectrum data on each vertical height layer, and obtaining the reflectivity factor profile and radial velocity profile in the vertical direction according to the power spectrum data on each vertical height layer; obtaining the cloud top height and cloud bottom height in the vertical direction according to the reflectivity factor profile and radial velocity profile. Wherein, the height of each vertical height layer is determined by the vertical distance resolution of the cloud radar, for example, it can be a vertical height layer every 30 meters.

[0073] In the disclosed embodiment, the geostationary meteorological satellite may be a Fengyun-4 meteorological satellite, and the multi-channel scanning imaging radiometer data includes the thermal infrared channel data that is most sensitive to the cloud top height among the multiple channels. The multi-channel scanning imaging radiometer data is the primary data observed by the meteorological satellite, which is usually represented by the brightness value of the remote sensing image pixel, records the gray value of the target object, has no unit, and its size is related to the radiation resolution of the sensor, the emissivity of the target object, the atmospheric transmittance and scattering rate, etc. In previous applications, it is often necessary to convert the channel data radiation calibration into a value with actual physical meaning, but the radiation calibration conversion will inevitably introduce uncertainty errors. In the disclosed embodiment, the cloud detection product data is the secondary data after processing the data of the meteorological satellite, which can characterize whether each pixel point observed by the satellite is a cloud point. The cloud detection product can be used to perform quality control on the three-dimensional cloud body. For example, if the satellite does not monitor the cloud, the cloud top height and cloud bottom height and the three-dimensional cloud body in the cloud radar networking area should not exist.

[0074] In the disclosed embodiment, in order to eliminate the uncertainty error introduced by the above-mentioned radiation calibration conversion, it is considered that when the geostationary meteorological satellite is observing in the cloud radar networking area, the atmosphere, surface, solar altitude angle and the working state of the on-board instrument in the networking area in a short period of time can be approximately considered to remain unchanged, and the only change is the radiation capacity of the cloud body. Therefore, when the same satellite in the networking area is observed, the change of the satellite channel data in each pixel can directly reflect the change of cloud information. Further, considering that the thermal infrared channel data is related to the infrared radiation of the target object, the magnitude of the infrared radiation energy directly reflects the height of the cloud top temperature, and the cloud top temperature determines the cloud top height. Therefore, by firstly matching the cloud top height obtained from the cloud radar observation data with the thermal infrared channel data of the meteorological satellite in time and space, obtaining the satellite-ground matching data, and then obtaining the satellite-ground cloud fusion factor based on the satellite-ground matching data, and finally realizing the satellite cloud top height inversion in the preset area around each cloud radar installation point based on the satellite-ground cloud fusion factor, the satellite cloud top height inversion in the cloud radar networking area can be effectively realized.

[0075] In the disclosed embodiment, the ground-based cloud observation data, the multi-channel scanning imaging radiometer data and the cloud detection product data are temporally and spatially matched to obtain satellite-ground matching data, including: taking M minutes before and after the satellite observation time as the ground-based cloud observation data time window; determining the cloud-free time ratio in the time window based on the cloud detection product data; when the cloud-free time ratio in the time window is less than the first preset threshold, searching for the pixel point closest to the satellite according to the location information of the cloud radar installation point for matching to obtain spatial matching data; normalizing the cloud top height and cloud bottom height in the time window, and then matching the normalized data with the spatial matching data to obtain the satellite-ground matching data, wherein M is a positive integer. When the cloud-free time ratio in the time window is greater than or equal to the first preset threshold, it is determined that the time matching has failed, and the spatial matching is no longer performed this time, and the next time window is waited.

[0076] Specifically, the spatial resolution of the thermal infrared channel of the Fengyun-4 meteorological satellite is 4km×4km, while the observation horizontal range of the millimeter-wave cloud radar at an altitude of 10km is hundreds of meters, and the meteorological satellite data is only acquired at preset observation times. Therefore, there are certain differences between the two in space and time. Before data fusion, the multi-channel scanning imaging radiometer data of the meteorological satellite and the ground-based cloud observation data of the cloud radar need to be matched in time and space. The time-space matching specifically includes: first, determining the time window of ground-based cloud observation data according to the observation time of the satellite, for example, M minutes before and after the satellite observation time can be used as the time window of ground-based cloud observation data, wherein M is a positive integer; then, determining the proportion of cloud-free time within the determined time window based on the cloud detection product data; when the proportion of cloud-free time within the time window is less than a first preset threshold, searching for the satellite and matching the corresponding pixel point according to the location information of the cloud radar installation point to obtain spatial matching data, wherein the first preset threshold can be comprehensively determined based on historical data and actual conditions, for example, it can be 30%; finally, normalizing the cloud top height and cloud bottom height respectively within the time window, and then matching the normalized data with the spatial matching data to obtain the satellite-to-ground matching data.

[0077] In the embodiment of the present disclosure, when determining the cloud radar data time window, the satellite observation time can be pushed forward and backward by N minutes respectively, and a total of M=2N+1 minutes of data can be obtained to further expand the data sample and improve the processing accuracy. In the embodiment of the present disclosure, the normalization processing can be processed by taking the average, mode, median, etc.

[0078] In the disclosed embodiment, the cloud top height inversion of the satellite in the preset area around each cloud radar installation point based on the satellite-ground matching data is implemented to obtain the cloud top height of the preset area of ​​each cloud radar installation point, including: normalizing the cloud top height in the time window to obtain the normalized cloud top height H of the matching pixel point a ; Get the thermal infrared channel data Z from the meteorological satellite multi-channel scanning imaging radiometer data of the matching pixel point a ; Based on the formula Get the satellite-ground-cloud fusion factor of the cloud radar at the observation time corresponding to the time window Based on the formula Get the cloud top height H of other pixels around the cloud radar installation point at the time of observation by the satellite ij , where i and j are the row and column numbers of the locations of other satellite pixel points; the cloud top height of the preset area of ​​each cloud radar installation point is obtained based on the cloud top height of the pixels around all cloud radar installation points during the observation by the satellite.

[0079] In the disclosed embodiment, the cloud top height of the cloud radar networking area can be further obtained by combining the cloud top heights of the preset areas of the cloud radar installation points to obtain the cloud top height of the cloud radar networking area, including: when the preset areas of the cloud radar installation points overlap, determining that the average of the cloud top heights of the preset areas of the cloud radar installation points constituting the overlap is the cloud top height of the overlapping area. Specifically, since the cloud radar networking area is composed of the preset areas of the cloud radar installation points, the cloud top height of the cloud radar networking area can be obtained by combining the cloud top heights of the preset areas of the cloud radar installation points. However, due to many factors, there may be overlaps between the preset areas of the cloud radars. At this time, the cloud top heights of the preset areas of the cloud radar installation points constituting the overlap can be averaged as the cloud top height of the overlapping area.

[0080] In the disclosed embodiment, after determining the cloud top height of the cloud radar networking area, the cloud bottom height of the vertical overhead space of each cloud radar installation point in the ground-based cloud observation data can also be interpolated to obtain the cloud bottom height of the cloud radar networking area, and then the cloud bottom height of the cloud radar networking area is matched with the cloud top height to obtain the three-dimensional cloud body boundary.

[0081] In the disclosed embodiment, when there are multiple layers of clouds in the vertical observation direction of the cloud radar, the cloud top height, cloud bottom height, reflectivity factor profile and radial velocity profile of the vertical overhead space of the cloud radar installation point can be determined based on the observation data of the topmost cloud with a thickness greater than the second preset threshold. Specifically, the sky state needs to be considered for satellite-ground matching. Generally, the matching effect is best when the zenith is a large area of ​​layered clouds. At the same time, since it is also a common situation that there are multiple layers of clouds in the vertical direction, when there are multiple layers of clouds in the vertical observation direction of the cloud radar, since the geostationary meteorological satellite can only obtain the data of the topmost layer, or the next layer of clouds when the topmost layer or several layers of clouds are relatively thin, the cloud top height, cloud bottom height, reflectivity factor profile and radial velocity profile of the vertical overhead space of the cloud radar installation point can be determined based on the observation data of the topmost cloud with a thickness greater than the second preset threshold. Among them, the second preset threshold can be set as needed, for example, 1 km.

[0082] In the embodiments of the present disclosure, Figure 2As shown, the cloud radar networking area can be determined in the following manner: first determine the cloud radar observation area that needs to be observed; then network at least three ground-based millimeter-wave cloud radars with a certain station distance in the cloud radar observation area. Due to the influence of factors such as equipment installation conditions, the networked cloud radars are arranged in an irregular shape with different distances. The best satellite-ground matching radius can be selected according to the actual station distances of adjacent cloud radars to obtain the preset area Q1 that each cloud radar can effectively cover; then use satellite remote sensing technology to perform cluster analysis on the multi-channel scanning imaging radiometer data of meteorological satellites to obtain the judgment result of whether each pixel is a cloud at each observation time, and then obtain cloud detection product data. Based on the cloud detection product data, the cloud range Q2 is judged in the cloud radar networking observation area; finally, the overlapping area Q12 of the coverage range Q1 and the cloud range Q2 is obtained to obtain the cloud radar networking area.

[0083] In the disclosed embodiment, the surface interpolation is performed at each vertical height layer based on the cloud radar reflectivity factor profile and the radial velocity profile, and the cloud base height is interpolated, which can be an interpolation performed with the satellite spatial resolution as a grid.

[0084] According to the technical solution provided by the embodiment of the present disclosure, by effectively combining the characteristics of large-scale meteorological satellite observations and high-precision ground-based cloud radar observations, the two are matched in time and space and data fused, so that the three-dimensional reconstruction of clouds in the cloud radar networking area can be achieved quickly and accurately, and the speed and accuracy of three-dimensional cloud body reconstruction can be improved; the reconstructed three-dimensional cloud body can provide a variety of products such as cloud top height, cloud bottom height and three-dimensional cloud fusion products on the surface of the cloud radar networking area, which can be widely used in cloud visualization monitoring and application. In the embodiment of the present disclosure, after obtaining the reconstructed three-dimensional cloud body, the reflectivity factor and radial velocity of the three-dimensional cloud body can also be taken as extreme values ​​to obtain the combined reflectivity factor and combined radial velocity of the cloud radar networking area, wherein the reflectivity factor and radial velocity of the three-dimensional cloud body are taken as extreme values, the reflectivity factor is taken as the maximum value, and the radial velocity is taken as the minimum value.

[0085] Figure 3 A structural diagram of a device for reconstructing a three-dimensional cloud body by fusion of satellite, ground and cloud according to an embodiment of the present disclosure is shown as follows: Figure 3 As shown, the device for reconstructing a three-dimensional cloud body by fusion of satellite, ground and cloud includes:

[0086] The first acquisition module 301 is configured to acquire ground-based cloud observation data of at least three cloud radars, and obtain the cloud top height, cloud bottom height, reflectivity factor profile and radial velocity profile of the vertical overhead space of each cloud radar installation point based on the acquired ground-based cloud observation data, wherein the at least three cloud radars are networked at a preset station spacing;

[0087] A second acquisition module 302 is configured to acquire multi-channel scanning imaging radiometer data and cloud detection products of geostationary meteorological satellites, wherein the multi-channel scanning imaging radiometer data includes thermal infrared channel data;

[0088] The time-space matching module 303 is configured to perform time-space matching on the ground-based cloud observation data, the multi-channel scanning imaging radiometer data and the cloud detection product data to obtain satellite-ground matching data;

[0089] The inversion module 304 is configured to realize the inversion of the cloud top height of the satellite in the preset area around each cloud radar installation point based on the satellite-ground matching data, obtain the cloud top height of the preset area of ​​each cloud radar installation point, and further obtain the cloud top height of the cloud radar networking area;

[0090] The determination module 305 is configured to interpolate the cloud base height of each cloud radar to obtain the cloud base height of the cloud radar networking area;

[0091] The reconstruction module 306 is configured to match the cloud base height and the cloud top height of the cloud radar networking area to obtain a three-dimensional cloud body boundary; based on the cloud radar reflectivity factor profile and the radial velocity profile, perform surface interpolation at each vertical height layer to fill the three-dimensional cloud body to obtain a reconstructed three-dimensional cloud body, wherein the height of each vertical height layer is determined by the vertical distance resolution of the cloud radar.

[0092] In the disclosed embodiment, the cloud radar may be a millimeter wave cloud radar, and the at least three cloud radars may be arranged and networked in a polygonal manner. For example, when there are three cloud radars, a triangular layout is recommended, when there are four cloud radars, a square or rectangular layout is recommended, and when there are five cloud radars, a pentagonal layout is recommended. In addition, when the number of cloud radars is large, in addition to forming a polygon, it is also necessary to lay out in the middle area of ​​the polygon to achieve full coverage of the internal area of ​​the polygon. There is a certain station distance between the cloud radars, and the certain station distance can be up to 100 kilometers between two adjacent stations.

[0093] In the disclosed embodiment, the cloud top height, cloud bottom height, reflectivity factor and radial velocity profile of each cloud radar installation point in the vertical overhead space are obtained based on the acquired ground-based cloud observation data, including: obtaining the cloud radar power spectrum data in the ground-based cloud observation data; obtaining the main peak of the power spectrum according to the position, width and amplitude of the peak in the power spectrum data, and obtaining the reflectivity factor and radial velocity according to the main peak of the power spectrum; obtaining the power spectrum data on each vertical height layer, and obtaining the reflectivity factor profile and radial velocity profile in the vertical direction according to the power spectrum data on each vertical height layer; obtaining the cloud top height and cloud bottom height in the vertical direction according to the reflectivity factor profile and radial velocity profile. Wherein, the height of each vertical height layer is determined by the vertical distance resolution of the cloud radar, for example, it can be a vertical height layer every 30 meters.

[0094] In the disclosed embodiment, the geostationary meteorological satellite may be a Fengyun-4 meteorological satellite, and the multi-channel scanning imaging radiometer data includes the thermal infrared channel data that is most sensitive to the cloud top height among the 14 channels. The multi-channel scanning imaging radiometer data is the primary data of satellite observation, which is usually represented by the brightness value of the remote sensing image pixel, records the gray value of the target object, has no unit, and its size is related to the radiation resolution of the sensor, the emissivity of the target object, the atmospheric transmittance and scattering rate, etc. In previous applications, it is often necessary to convert the channel data radiation calibration into a value with actual physical meaning, but the radiation calibration conversion will inevitably introduce uncertainty errors. In the disclosed embodiment, the cloud detection product data is the secondary data after processing the data of the meteorological satellite, which can characterize whether each pixel point observed by the satellite is a cloud point. The cloud detection product can be used to perform quality control on three-dimensional cloud bodies. For example, if the satellite does not monitor the cloud, the cloud top height and cloud bottom height and three-dimensional cloud body in the cloud radar networking area should not exist.

[0095] In the disclosed embodiment, in order to eliminate the uncertainty error introduced by the above-mentioned radiation calibration conversion, it is considered that when the geostationary meteorological satellite observes in the cloud radar networking area, the atmosphere, surface, solar altitude angle and the working state of the on-board instrument in the networking area in a short period of time can be approximately considered to remain unchanged, and the only change is the radiation capacity of the cloud body. Therefore, when the same satellite in the networking area is observed, the change of the satellite channel data in each pixel can directly reflect the change of cloud information. Further, considering that the thermal infrared channel data is related to the infrared radiation of the target object, the cloud top temperature determines the cloud top height, and the temperature directly reflects the magnitude of the infrared radiation energy. Therefore, by firstly matching the cloud top height obtained from the cloud radar observation data with the thermal infrared channel data of the meteorological satellite in time and space, obtaining the satellite-ground matching data, and then obtaining the satellite-ground cloud fusion factor based on the satellite-ground matching data, and finally realizing the satellite cloud top height inversion in the preset area around each cloud radar installation point based on the satellite-ground cloud fusion factor, the satellite cloud top height inversion in the cloud radar networking area can be effectively realized. Among them, the preset area is a circular area with the cloud radar installation point as the center and the first preset distance as the radius, and the first preset distance can be 80 kilometers.

[0096] In the disclosed embodiment, the ground-based cloud observation data, the multi-channel scanning imaging radiometer data and the cloud detection product data are temporally and spatially matched to obtain satellite-ground matching data, including: taking M minutes before and after the satellite observation time as the ground-based cloud observation data time window; determining the cloud-free time ratio in the time window based on the cloud detection product data; when the cloud-free time ratio in the time window is less than the first preset threshold, searching for the pixel point closest to the satellite according to the location information of the cloud radar installation point for matching to obtain spatial matching data; normalizing the cloud top height and cloud bottom height in the time window, and then matching the normalized data with the spatial matching data to obtain the satellite-ground matching data, wherein M is a positive integer. When the cloud-free time ratio in the time window is greater than or equal to the first preset threshold, it is determined that the time matching has failed, and the spatial matching is no longer performed this time, and the next time window is waited.

[0097] Specifically, the spatial resolution of the thermal infrared channel of the Fengyun-4 meteorological satellite is 4km×4km, while the observation horizontal range of the millimeter-wave cloud radar at an altitude of 10km is hundreds of meters, and the meteorological satellite data is only acquired at preset observation times. Therefore, there are certain differences between the two in space and time. Before data fusion, the multi-channel scanning imaging radiometer data of the meteorological satellite and the ground-based cloud observation data of the cloud radar need to be matched in time and space. The time-space matching specifically includes: first, determining the time window of ground-based cloud observation data according to the observation time of the satellite, for example, M minutes before and after the satellite observation time can be used as the time window of ground-based cloud observation data, wherein M is a positive integer; then, determining the proportion of cloud-free time within the determined time window based on the cloud detection product data; when the proportion of cloud-free time within the time window is less than a first preset threshold, searching for the satellite and matching the corresponding pixel point according to the location information of the cloud radar installation point to obtain spatial matching data, wherein the first preset threshold can be comprehensively determined based on historical data and actual conditions, for example, it can be 30%; finally, normalizing the cloud top height and cloud bottom height respectively within the time window, and then matching the normalized data with the spatial matching data to obtain the satellite-to-ground matching data.

[0098] In the embodiment of the present disclosure, when determining the cloud radar data time window, the satellite observation time can be pushed forward and backward by N minutes respectively, and a total of M=2N+1 minutes of data can be obtained to further expand the data sample and improve the processing accuracy. In the embodiment of the present disclosure, the normalization processing can be processed by taking the average, mode, median, etc.

[0099] In the disclosed embodiment, the cloud top height inversion of the satellite in the preset area around each cloud radar installation point based on the satellite-ground matching data is implemented to obtain the cloud top height of the preset area of ​​each cloud radar installation point, including: normalizing the cloud top height in the time window to obtain the normalized cloud top height H of the matching pixel point a ; Get the thermal infrared channel data Z from the meteorological satellite multi-channel scanning imaging radiometer data of the matching pixel point a ; Based on the formula Get the satellite-ground-cloud fusion factor of the cloud radar at the observation time corresponding to the time window Based on the formula The cloud top height Hij of other pixels around the cloud radar installation point of the satellite at the time of the observation is obtained, wherein i and j are the row number and column number of the positions of other pixels of the satellite; the cloud top height of the preset area of ​​each cloud radar installation point is obtained based on the cloud top height of the pixels around all cloud radar installation points of the satellite at the time of the observation.

[0100] In the disclosed embodiment, the cloud top height of the cloud radar networking area can be further obtained by combining the cloud top heights of the preset areas of the cloud radar installation points to obtain the cloud top height of the cloud radar networking area, including: when the preset areas of the cloud radar installation points overlap, determining that the average of the cloud top heights of the preset areas of the cloud radar installation points constituting the overlap is the cloud top height of the overlapping area. Specifically, since the cloud radar networking area is composed of the preset areas of the cloud radar installation points, the cloud top height of the cloud radar networking area can be obtained by combining the cloud top heights of the preset areas of the cloud radar installation points. However, due to many factors, there may be overlaps between the preset areas of the cloud radars. At this time, the cloud top heights of the preset areas of the cloud radar installation points constituting the overlap can be averaged as the cloud top height of the overlapping area.

[0101] In the disclosed embodiment, after determining the cloud top height of the cloud radar networking area, the cloud bottom height of the vertical overhead space of each cloud radar installation point in the ground-based cloud observation data can also be interpolated to obtain the cloud bottom height of the cloud radar networking area, and then the cloud bottom height of the cloud radar networking area is matched with the cloud top height to obtain the three-dimensional cloud body boundary.

[0102] In the disclosed embodiment, when there are multiple layers of clouds in the vertical observation direction of the cloud radar, the cloud top height, cloud bottom height, reflectivity factor profile and radial velocity profile of the vertical overhead space of the cloud radar installation point can be determined based on the observation data of the topmost cloud with a thickness greater than the second preset threshold. Specifically, the sky state needs to be considered for satellite-ground matching. Generally, the matching effect is best when the zenith is a layered cloud with a continuous large area. At the same time, since it is also a common situation that there are multiple layers of clouds in the vertical direction, when there are multiple layers of clouds in the vertical observation direction of the cloud radar, since the meteorological satellite can only obtain the data of the topmost layer, or the next layer of clouds when the topmost layer or several layers of clouds are relatively thin, the cloud top height, cloud bottom height, reflectivity factor profile and radial velocity profile of the vertical overhead space of the cloud radar installation point can be determined based on the observation data of the topmost cloud with a thickness greater than the second preset threshold. Among them, the second preset threshold can be set as needed, for example, 1 km.

[0103] In the disclosed embodiment, the surface interpolation is performed at each vertical height layer based on the cloud radar reflectivity factor profile and the radial velocity profile, and the cloud base height is interpolated, which can be an interpolation performed with the satellite spatial resolution as a grid.

[0104] According to the technical solution provided in the embodiments of the present disclosure, by effectively combining the large-scale observation of meteorological satellites and the high-precision observation of ground-based cloud radars, the two are matched in time and space and data fused, so that the three-dimensional reconstruction of clouds in the cloud radar networking area can be achieved quickly and accurately, thereby improving the speed and accuracy of three-dimensional cloud body reconstruction; the reconstructed three-dimensional cloud body can provide a variety of products such as cloud top height, cloud bottom height and three-dimensional cloud fusion products on the surface of the cloud radar networking area, which can be widely used in cloud visualization monitoring and applications.

[0105] In the disclosed embodiment, after obtaining the reconstructed three-dimensional cloud body, the reflectivity factor and radial velocity of the three-dimensional cloud body can also be taken as extreme values ​​to obtain the combined reflectivity factor and combined radial velocity of the cloud radar networking area, wherein the extreme values ​​of the reflectivity factor and radial velocity of the three-dimensional cloud body are taken as, the maximum value of the reflectivity factor is taken, and the minimum value of the radial velocity is taken.

[0106] The present disclosure also discloses an electronic device, Figure 4 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown. Figure 4 As shown, the electronic device 400 includes a memory 401 and a processor 402; wherein,

[0107] The memory 401 is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor 402 to implement any of the above method steps.

[0108] Figure 5 It is a structural diagram of a computer system suitable for implementing a data transmission method according to an embodiment of the present disclosure.

[0109] like Figure 5 As shown, the computer system 500 includes a processing unit 501, which can perform various processes in the above-mentioned embodiments according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage part 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the computer system 500 are also stored. The processing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0110] The following components are connected to the I / O interface 505: an input part 506 including a keyboard, a mouse, etc.; an output part 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage part 508 including a hard disk, etc.; and a communication part 509 including a network interface card such as a LAN card, a modem, etc. The communication part 509 performs communication processing via a network such as the Internet. The drive 510 is also connected to the I / O interface 505 as needed. Removable media 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., are installed on the drive 510 as needed, so that the computer program read therefrom is installed into the storage part 508 as needed. Among them, the processing unit 501 can be implemented as a processing unit such as a CPU, a GPU, a TPU, an FPGA, an NPU, etc.

[0111] In particular, according to an embodiment of the present invention, the method described above can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program tangibly contained on a readable medium, and the computer program includes a program code for executing the data transmission method. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 509, and / or installed from a removable medium 511.

[0112] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the road map or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0113] The units or modules involved in the embodiments of the present invention may be implemented by software or hardware. The units or modules described may also be arranged in a processor, and the names of these units or modules do not, in some cases, limit the units or modules themselves.

[0114] As another aspect, an embodiment of the present invention further provides a computer-readable storage medium, which may be a computer-readable storage medium included in the device described in the above embodiment; or a computer-readable storage medium that exists independently and is not assembled into the device. The computer-readable storage medium stores one or more programs, and the programs are used by one or more processors to execute the method described in the embodiment of the present invention.

[0115] The above description is only a preferred embodiment of the present invention and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present invention is not limited to the technical solutions formed by the specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with (but not limited to) the technical features with similar functions disclosed in the embodiments of the present invention.

Claims

1. A method for reconstructing a three-dimensional cloud body by integrating satellite, ground and cloud, characterized in that: include: Acquiring ground-based cloud observation data from at least three cloud radars, wherein the at least three cloud radars are networked at a preset station spacing; Based on the acquired ground-based cloud observation data, the cloud top height, cloud bottom height, reflectivity factor profile and radial velocity profile of each cloud radar installation point are obtained; Acquire multi-channel scanning imaging radiometer data and cloud detection product data from geostationary meteorological satellites; Performing temporal and spatial matching on the ground-based cloud observation data, the multi-channel scanning imaging radiometer data and the cloud detection product data to obtain satellite-ground matching data; Based on the satellite-ground matching data, the cloud top height of the satellite in the preset area around each cloud radar installation point is inverted to obtain the cloud top height of the preset area around each cloud radar installation point, and further obtain the cloud top height of the cloud radar networking area; The cloud base height of each cloud radar is interpolated to obtain the cloud base height of the cloud radar network area; Matching the cloud base height and cloud top height of the cloud radar network area to obtain a three-dimensional cloud body boundary; Based on the cloud radar reflectivity factor profile and radial velocity profile, performing surface interpolation at each vertical height layer to fill the three-dimensional cloud body to obtain a reconstructed three-dimensional cloud body, wherein the height of each vertical height layer is determined by the vertical range resolution of the cloud radar; The step of performing temporal and spatial matching of the ground-based cloud observation data, the multi-channel scanning imaging radiometer data and the cloud detection product data to obtain satellite-ground matching data includes: The M minutes before and after the satellite observation time is used as the ground-based cloud observation data time window; Determine the proportion of cloud-free time within the time window based on the cloud detection product data; When the proportion of cloud-free time in the time window is less than a first preset threshold, according to the location information of the cloud radar installation point, the pixel point closest to the satellite is searched for matching to obtain spatial matching data; The cloud top height and cloud bottom height of the cloud radar are normalized respectively within the time window, and then the normalized data are matched with the space matching data to obtain the satellite-ground matching data, wherein M is a positive integer.

2. The method according to claim 1, wherein the cloud top height, cloud bottom height, reflectivity factor profile and radial velocity profile of each cloud radar installation point are obtained based on the acquired ground-based cloud observation data, including: Acquiring cloud radar power spectrum data from the ground-based cloud observation data; Obtain a main peak of the power spectrum according to the position, width and amplitude of the peak body in the power spectrum data, and obtain a reflectivity factor and a radial velocity according to the main peak of the power spectrum; Acquire power spectrum data at each vertical height layer, and obtain a vertical reflectivity factor profile and a radial velocity profile according to the power spectrum data at each vertical height layer; The cloud top height and cloud bottom height in the vertical direction are obtained according to the reflectivity factor profile and the radial velocity profile.

3. The method according to claim 1, wherein the cloud top height inversion of the satellite in the preset area around each cloud radar installation point based on the satellite-ground matching data is realized to obtain the cloud top height of the preset area of ​​each cloud radar installation point, comprising: Normalize the cloud top height of the cloud radar within the time window to obtain the normalized cloud top height of the matching pixel point ; Get the thermal infrared channel data from the multi-channel scanning imaging radiometer data matching the pixel point ; Based on the formula Get the satellite-ground-cloud fusion factor of the cloud radar at the observation time corresponding to the time window ; Based on the formula Get the cloud top height of other pixels around the cloud radar installation point at the time of the satellite observation , where i and j are the row and column numbers of the locations of other satellite pixels; Based on the cloud top heights of the pixels around all cloud radar installation points at the time of the observation, the cloud top heights of the preset areas of the cloud radar installation points are obtained; Among them, the preset area is a circular area with the cloud radar installation point as the center and the first preset distance as the radius.

4. According to the method according to any one of claims 1 to 3, further obtaining the cloud top height of the cloud radar networking area comprises: When there is overlap between the preset areas of the cloud radar installation points, it is determined that the average of the cloud top heights of the preset areas of the cloud radar installation points constituting the overlap is the cloud top height of the overlapping area.

5. The method according to any one of claims 1 to 3, wherein: When there are multiple layers of clouds in the vertical observation direction of the cloud radar, the cloud top height, cloud bottom height, reflectivity factor profile and radial velocity profile in the vertical overhead space of the cloud radar installation point are determined based on the observation data of the topmost cloud whose thickness is greater than the second preset threshold.

6. According to the method of claim 1, the interpolation refers to interpolation performed with satellite spatial resolution as a grid.

7. The method according to claim 1, further comprising: The reflectivity factor and radial velocity of the three-dimensional cloud body are taken as extreme values ​​to obtain the combined reflectivity factor and combined radial velocity of the cloud radar networking area, wherein the reflectivity factor and radial velocity of the three-dimensional cloud body are taken as extreme values, the reflectivity factor is taken as the maximum value, and the radial velocity is taken as the minimum value.

8. A device for reconstructing a three-dimensional cloud body by fusion of satellite, ground and cloud, characterized in that: include: A first acquisition module is configured to acquire ground-based cloud observation data of at least three cloud radars, and obtain a cloud top height, a cloud bottom height, a reflectivity factor profile, and a radial velocity profile of a vertical overhead space of each cloud radar installation point based on the acquired ground-based cloud observation data, wherein the at least three cloud radars are networked at a preset station spacing; A second acquisition module is configured to acquire multi-channel scanning imaging radiometer data and cloud detection product data of geostationary meteorological satellites; a space-time matching module configured to perform space-time matching on the ground-based cloud observation data, the multi-channel scanning imaging radiometer data and the cloud detection product data to obtain satellite-ground matching data; An inversion module is configured to realize the inversion of the cloud top height of the satellite in the preset area around each cloud radar installation point based on the satellite-ground matching data, obtain the cloud top height of the preset area of ​​each cloud radar installation point, and further obtain the cloud top height of the cloud radar networking area; A determination module is configured to interpolate the cloud base height of each cloud radar to obtain the cloud base height of the cloud radar networking area; A reconstruction module is configured to match the cloud base height and cloud top height of the cloud radar networking area to obtain a three-dimensional cloud body boundary; based on the cloud radar reflectivity factor profile and radial velocity profile, perform surface interpolation at each vertical height layer to fill the three-dimensional cloud body to obtain a reconstructed three-dimensional cloud body, wherein the height of each vertical height layer is determined by the vertical distance resolution of the cloud radar; The step of performing temporal and spatial matching of the ground-based cloud observation data, the multi-channel scanning imaging radiometer data and the cloud detection product data to obtain satellite-ground matching data includes: The M minutes before and after the satellite observation time is used as the ground-based cloud observation data time window; Determine the proportion of cloud-free time within the time window based on the cloud detection product data; When the proportion of cloud-free time in the time window is less than a first preset threshold, according to the location information of the cloud radar installation point, the pixel point closest to the satellite is searched for matching to obtain spatial matching data; The cloud top height and cloud bottom height of the cloud radar are normalized respectively within the time window, and then the normalized data are matched with the space matching data to obtain the satellite-ground matching data, wherein M is a positive integer.

9. An electronic device comprising a memory and a processor; wherein: The memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method steps described in any one of claims 1-7.

10. A computer-readable storage medium having computer instructions stored thereon, wherein the computer instructions, when executed by a processor, implement the method steps described in any one of claims 1 to 7.

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