A method and device for identifying precipitation areas based on geostationary meteorological satellite observation data

Abstract

The present invention relates to a precipitation area identification method based on geostationary meteorological satellite observation data, including obtaining precipitation discrimination parameters of a study area collected by a geostationary meteorological satellite, and generating a precipitation area of ​​the study area according to the precipitation discrimination parameters. Aiming at the precipitation detection needs of geostationary satellites during the day, the present invention introduces information such as the optical thickness of clouds to reduce the influence of high-level thin clouds on the basis of the existing precipitation detection sensitive parameters used by GMSRA and SCaMPR, and uses an elimination method to gradually eliminate the influence of non-precipitation clouds to improve precipitation detection accuracy. The present invention relates to a precipitation area identification device, storage medium and equipment based on geostationary meteorological satellite observation data.

Description

Technical Field

[0001] The present invention relates to the field of information processing technology, and in particular to a precipitation area identification method and device based on geostationary meteorological satellite observation data. Background Art

[0002] Precipitation is one of the main causes of surface floods. Real-time and accurate acquisition of precipitation distribution data is of great significance for accurately predicting floods. Geostationary satellites have the advantages of high temporal resolution and high timeliness of observation, providing stable support for real-time monitoring of precipitation. The premise of using geostationary satellites to monitor precipitation is to accurately identify precipitation areas. Currently, the main method for identifying precipitation using geostationary satellite observation data is neural network algorithms. The neural network model is established by inputting cloud top reflectivity or brightness temperature data observed by geostationary satellites in precipitation areas and non-precipitation areas. This method has good recognition accuracy, but the accuracy is easily affected by training data, and the basic principle of precipitation detection using neural network methods is unclear, so it is difficult to directly apply it to other satellites. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a precipitation area identification method and device based on geostationary meteorological satellite observation data in view of the deficiencies in the prior art.

[0004] The technical solution of the present invention to solve the above technical problems is as follows:

[0005] A precipitation area identification method based on geostationary meteorological satellite observation data, the method comprising:

[0006] Obtain precipitation discrimination parameters for the study area collected by the geostationary meteorological satellite, wherein the precipitation discrimination parameters include the visible light 0.65 micron cloud top reflectivity R0.65, the solar zenith angle SZ, the cloud optical thickness value COT, the cloud particle effective radius value CER, the cloud top texture information, the cloud top temperature change slope S, the 3.9 micron cloud top brightness temperature Tb3.9, the 7.0 micron cloud top brightness temperature Tb7.0, the cloud top temperature value CTT and the cloud top change gradient value G t ;

[0007] A precipitation area of ​​the study area is generated according to the precipitation discrimination parameters.

[0008] Based on the above technical solution, the present invention can also be improved as follows.

[0009] Furthermore, generating the precipitation area of ​​the study area according to the precipitation discrimination parameter specifically includes:

[0010] When the visible light 0.65 micron cloud top reflectivity R0.65 of the pixel in the study area is greater than the reflection threshold, and the solar zenith angle SZ is less than the zenith angle threshold, the precipitation mask pixel value of the pixel is set to the first preset value;

[0011] Otherwise, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a first pre-precipitation area in the study area;

[0012] When the cloud optical thickness value COT of the pixel in the first pre-precipitation area is less than the thickness threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a second pre-precipitation area in the study area;

[0013] When the cloud particle effective radius value CER of the pixel in the second pre-precipitation area is less than the radius threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a third pre-precipitation area in the study area;

[0014] According to the cloud top temperature value CTT of the pixel in the third pre-precipitation area, the cloud top texture information is obtained, and when the cloud top texture information meets the preset condition, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a fourth pre-precipitation area in the study area;

[0015] According to the cloud top temperature value CTT of the pixel in the fourth pre-precipitation area, the cloud top temperature change slope S is obtained, and when the cloud top temperature change slope S is greater than or equal to the slope threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a fifth pre-precipitation area in the study area;

[0016] When the 3.9 micron cloud top brightness temperature Tb3.9 of the pixel in the fifth pre-precipitation area is greater than or equal to the first preset brightness temperature threshold, the precipitation mask pixel value of the pixel is set to the second preset value to obtain the sixth pre-precipitation area in the study area;

[0017] When the 7.0 micron cloud top brightness temperature Tb7.0 of the pixel in the sixth pre-precipitation area is greater than or equal to the second preset brightness temperature threshold, the precipitation mask pixel value of the pixel is set to the second preset value to obtain the seventh pre-precipitation area in the study area;

[0018] When the cloud top temperature CTT of the pixel in the seventh pre-precipitation area is greater than or equal to the preset cloud top temperature threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain an eighth pre-precipitation area in the study area;

[0019] The cloud top change gradient value G is obtained according to the cloud top temperature value CTT of the pixel in the eighth pre-precipitation area. t , when the cloud top gradient value Gt When it is greater than or equal to the gradient threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain the precipitation area in the study area.

[0020] Further, the cloud top texture information is obtained according to the cloud top temperature value CTT of the pixel in the third pre-precipitation area, and when the cloud top texture information meets the preset condition, the precipitation mask pixel value of the pixel is set to a second preset value to obtain the fourth pre-precipitation area in the study area, specifically including:

[0021] Obtain the cloud top temperature values ​​CTT of the six pixels adjacent to the pixel to obtain the average cloud top temperature value T avg ;

[0022] Obtain the minimum cloud top temperature value T among the cloud top temperature values ​​corresponding to all pixels in the pixel window of the preset size where the pixel is located min ;

[0023] According to the average cloud top temperature value T avg and the minimum cloud top temperature T min , get the cloud top change gradient value G t ;

[0024] According to the minimum cloud top temperature value T min , obtain the cloud top temperature change slope S;

[0025] The cloud top texture information is the cloud top change gradient value G t and the difference between the cloud top temperature change slope S;

[0026] When the cloud top texture information is less than a preset difference, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a fourth pre-precipitation area in the study area.

[0027] Further, obtaining the cloud top temperature change slope S according to the cloud top temperature value CTT of the pixel in the fourth pre-precipitation area specifically includes:

[0028] The minimum cloud top temperature value T min Input into the formula S = 0.568 (T min -217), and obtain the cloud top temperature change slope S.

[0029] Further, the cloud top change gradient value G is obtained according to the cloud top temperature value CTT of the pixel in the eighth pre-precipitation area. t , including:

[0030] Calculate the average cloud top temperature value T avg and the minimum cloud top temperature T minThe difference between the cloud top change gradient value G t .

[0031] The beneficial effect of the invention of the method is that a precipitation area identification method based on geostationary meteorological satellite observation data is proposed, including obtaining precipitation discrimination parameters of the research area collected by the geostationary meteorological satellite, wherein the precipitation discrimination parameters include the visible light 0.65 micron cloud top reflectivity R0.65, the solar zenith angle SZ, the cloud optical thickness value COT, the cloud particle effective radius value CER, the cloud top texture information, the cloud top temperature change slope S, the 3.9 micron cloud top brightness temperature Tb3.9, the 7.0 micron cloud top brightness temperature Tb7.0, the cloud top temperature value CTT and the cloud top change gradient value G t According to the precipitation discrimination parameters, the precipitation area of ​​the study area is generated. Aiming at the precipitation detection needs of geostationary satellites during the day, the present invention introduces information such as cloud optical thickness to reduce the influence of high-level thin clouds on the basis of the existing precipitation detection sensitive parameters used by GMSRA and SCaMPR, and uses the elimination method to gradually eliminate the influence of non-precipitation clouds to improve the precipitation detection accuracy.

[0032] Another technical solution of the present invention to solve the above technical problem is as follows:

[0033] A precipitation area identification device based on geostationary meteorological satellite observation data, the device comprising:

[0034] The acquisition module is used to obtain the precipitation discrimination parameters of the study area collected by the geostationary meteorological satellite, wherein the precipitation discrimination parameters include the visible light 0.65 micron cloud top reflectivity R0.65, the solar zenith angle SZ, the cloud optical thickness value COT, the cloud particle effective radius value CER, the cloud top texture information, the cloud top temperature change slope S, the 3.9 micron cloud top brightness temperature Tb3.9, the 7.0 micron cloud top brightness temperature Tb7.0, the cloud top temperature value CTT and the cloud top change gradient value G t ;

[0035] A determination module is used to generate a precipitation area of ​​the study area according to the precipitation determination parameter.

[0036] In addition, the present invention provides an electronic device, comprising: a memory for storing a computer program; and a processor for implementing the steps of a precipitation area identification method based on geostationary meteorological satellite observation data as described in any one of the above technical solutions when executing the computer program.

[0037] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the precipitation area identification method based on geostationary meteorological satellite observation data as described in any one of the above technical solutions are implemented.

[0038] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments of the present invention or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 A schematic diagram of a flow chart of a precipitation area identification method based on geostationary meteorological satellite observation data according to an embodiment of the present invention;

[0041] Figure 2 This is a module schematic diagram of a precipitation area identification device based on geostationary meteorological satellite observation data according to another embodiment of the present invention. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0043] like Figure 1 A precipitation area identification method based on geostationary meteorological satellite observation data according to an embodiment of the present invention comprises:

[0044] 110. Obtain precipitation discrimination parameters for the study area collected by the geostationary meteorological satellite, wherein the precipitation discrimination parameters include the visible light 0.65 micron cloud top reflectance R0.65, the solar zenith angle SZ, the cloud optical thickness value COT, the cloud particle effective radius value CER, the cloud top texture information, the cloud top temperature change slope S, the 3.9 micron cloud top brightness temperature Tb3.9, the 7.0 micron cloud top brightness temperature Tb7.0, the cloud top temperature value CTT and the cloud top change gradient value G t .

[0045] 120. Generate a precipitation area of ​​the study area according to the precipitation discrimination parameter.

[0046] Based on the above embodiment, further, step 120 specifically includes:

[0047] 121. When the visible light 0.65 micron cloud top reflectivity R0.65 of the pixel in the study area is greater than the reflection threshold and the solar zenith angle SZ is less than the zenith angle threshold, the precipitation mask pixel value of the pixel is set to the first preset value. Otherwise, the precipitation mask pixel value of the pixel is set to the second preset value to obtain the first pre-precipitation area in the study area.

[0048] It should be understood that the reflectivity R0.65 of the 0.65μm visible light band is a main parameter for precipitation identification. When R0.65≥0.39, more than 80% of precipitation areas can be identified, but at the same time many non-precipitation areas will be misjudged as precipitation areas. Since this algorithm is mainly applicable to daytime, the solar zenith angle SZ≤70° must be set. Therefore, pixels that meet R0.65≥0.39 and SZ≤70° are determined as the first pre-precipitation area, and the precipitation mask pixel value at the corresponding position is set to the first preset value 1, otherwise it is set to the second preset value 0. For misjudged non-precipitation areas, other precipitation sensitive parameters are used to exclude them one by one.

[0049] 122. When the cloud optical thickness value COT of a pixel in the first pre-precipitation area is less than a thickness threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a second pre-precipitation area in the study area.

[0050] It should be understood that the influence of thin clouds on the judgment of precipitation areas is eliminated by using the cloud optical thickness COT, and the cloud optical thickness threshold is set to 5 to eliminate the misjudgment of precipitation areas due to the presence of thin clouds.

[0051] 123. When the cloud particle effective radius value CER of the pixel in the second pre-precipitation area is less than the radius threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a third pre-precipitation area in the study area.

[0052] It should be understood that the cloud particle effective radius CER is used to eliminate the impact of non-precipitation clouds. When the cloud particle effective radius is less than 13 μm, the probability of precipitation is relatively small. Therefore, the radius threshold is set to 13 μm.

[0053] 124. According to the cloud top temperature value CTT of the pixel in the third pre-precipitation area, the cloud top texture information is obtained. When the cloud top texture information meets a preset condition, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a fourth pre-precipitation area in the study area.

[0054] 125. According to the cloud top temperature value CTT of the pixel in the fourth pre-precipitation area, the cloud top temperature change slope S is obtained. When the cloud top temperature change slope S is greater than or equal to the slope threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain the fifth pre-precipitation area in the study area.

[0055] It should be understood that the impact of non-precipitation clouds is eliminated based on the cloud top temperature change slope S. The slope threshold is set to 29.

[0056] 126. When the 3.9 micron cloud top brightness temperature Tb3.9 of the pixel in the fifth pre-precipitation area is greater than or equal to the first preset brightness temperature threshold, the precipitation mask pixel value of the pixel is set to the second preset value to obtain the sixth pre-precipitation area in the study area.

[0057] It should be understood that the influence of non-precipitating clouds is eliminated based on the 3.9 micron cloud top brightness temperature Tb3.9, and the 3.9 micron cloud top brightness temperature threshold is set to 301K.

[0058] 127. When the 7.0 micron cloud top brightness temperature Tb7.0 of the pixel in the sixth pre-precipitation area is greater than or equal to the second preset brightness temperature threshold, the precipitation mask pixel value of the pixel is set to the second preset value to obtain the seventh pre-precipitation area in the study area.

[0059] It should be understood that the 7.0-micron cloud top brightness temperature Tb7.0 is used to eliminate the impact of non-precipitating clouds, and the 7.0-micron cloud top brightness temperature threshold is set to 250K.

[0060] 128. When the cloud top temperature CTT of the pixel in the seventh pre-precipitation area is greater than or equal to a preset cloud top temperature threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain the eighth pre-precipitation area in the study area.

[0061] It should be understood that the cloud top temperature CTT is used to eliminate the influence of non-precipitating clouds. When the cloud top temperature is greater than 287K, the probability of precipitation is small, so the cloud top temperature threshold is set to 287K.

[0062] 129. Obtain the cloud top change gradient value G according to the cloud top temperature value CTT of the pixel in the eighth pre-precipitation area. t , when the cloud top gradient value G t When it is greater than or equal to the gradient threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain the precipitation area in the study area.

[0063] It should be understood that the cloud top change gradient value G t Eliminate the influence of non-precipitation clouds. Set the cloud top change gradient information value G t When the temperature is ≥68, it is a non-precipitation area.

[0064] Furthermore, step 124 specifically includes:

[0065] Obtain the cloud top temperature values ​​CTT of the six pixels adjacent to the pixel to obtain the average cloud top temperature value T avg .

[0066] Obtain the minimum cloud top temperature value T among the cloud top temperature values ​​corresponding to all pixels in the pixel window of the preset size where the pixel is located min .

[0067] According to the average cloud top temperature value T avg and the minimum cloud top temperature T min , get the cloud top change gradient value G t .

[0068] According to the minimum cloud top temperature value T min , and obtain the cloud top temperature change slope S.

[0069] The cloud top texture information is the cloud top change gradient value G t and the difference between the cloud top temperature change slope S;

[0070] When the cloud top texture information is less than a preset difference, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a fourth pre-precipitation area in the study area.

[0071] It should be understood that the six pixels around the pixel are four pixels in the horizontal direction and two pixels in the vertical direction, and the preset size is a 25×25 pixel window, wherein the preset difference value is -27.

[0072] Furthermore, step 125 specifically includes:

[0073] The minimum cloud top temperature value T min Input into the formula S = 0.568 (T min -217), and obtain the cloud top temperature change slope S.

[0074] Furthermore, step 129 specifically includes:

[0075] Calculate the average cloud top temperature value T avg and the minimum cloud top temperature T min The difference between the cloud top change gradient value G t .

[0076] A precipitation area identification method based on geostationary meteorological satellite observation data proposed in the above embodiment includes obtaining precipitation discrimination parameters of a research area collected by a geostationary meteorological satellite, wherein the precipitation discrimination parameters include a visible light 0.65 micron cloud top reflectivity R0.65, a solar zenith angle SZ, a cloud optical thickness value COT, a cloud particle effective radius value CER, cloud top texture information, a cloud top temperature change slope S, a 3.9 micron cloud top brightness temperature Tb3.9, a 7.0 micron cloud top brightness temperature Tb7.0, a cloud top temperature value CTT, and a cloud top change gradient value G t; According to the precipitation discrimination parameters, the precipitation area of ​​the study area is generated. Aiming at the precipitation detection needs of geostationary satellites during the day, the present invention reduces the influence of high-level thin clouds by introducing information such as cloud optical thickness on the basis of the existing precipitation detection sensitive parameters used by GMSRA and SCaMPR, and at the same time gradually eliminates the influence of non-precipitation clouds by using the elimination method to improve the precipitation detection accuracy.

[0077] It should be understood that accurate precipitation monitoring helps to improve the forecast accuracy of flood disasters caused by precipitation. The precipitation area monitoring algorithm based on geostationary satellite observation data during the day proposed in the above embodiment can significantly improve the recognition rate (POD) of daytime precipitation areas and reduce the false alarm rate (FAR) compared with the existing Fengyun-4 precipitation product. For a more objective comparison, the following is the process and verification data of precipitation detection using the above embodiment.

[0078] The precipitation detection was carried out using the observation data and cloud products of Japan's Himawari-8 geostationary satellite at 05:00 (UTC) on July 1, 2019, and the Fengyun-4 geostationary satellite precipitation products at the same time were used for comparison. In order to compare and analyze the difference between the two precipitation detection results, more than 2,000 ground rain gauge data distributed across the country at the same time were used as verification data, and the precipitation detection indicators such as HSS, CSI, POD and FAR of the two precipitation detection results were calculated respectively, as shown in Table 1 Comparison and verification of precipitation area detection accuracy:

[0079] Table 1

[0080]

[0081] From the comparison in the above table, it can be seen that the precipitation area detection results based on the geostationary satellite data during the day proposed in the above embodiment are better than the FY4 precipitation product in all indicators.

[0082] Figure 2 As shown, a precipitation area identification device based on geostationary meteorological satellite observation data, the device comprises:

[0083] The acquisition module is used to obtain the precipitation discrimination parameters of the study area collected by the geostationary meteorological satellite, wherein the precipitation discrimination parameters include the visible light 0.65 micron cloud top reflectivity R0.65, the solar zenith angle SZ, the cloud optical thickness value COT, the cloud particle effective radius value CER, the cloud top texture information, the cloud top temperature change slope S, the 3.9 micron cloud top brightness temperature Tb3.9, the 7.0 micron cloud top brightness temperature Tb7.0, the cloud top temperature value CTT and the cloud top change gradient value G t ;

[0084] A determination module is used to generate a precipitation area of ​​the study area according to the precipitation determination parameter.

[0085] In addition, the present invention provides an electronic device, comprising: a memory for storing a computer program; and a processor for implementing the steps of a precipitation area identification method based on geostationary meteorological satellite observation data as described in any one of the above technical solutions when executing the computer program.

[0086] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the precipitation area identification method based on geostationary meteorological satellite observation data as described in any one of the above technical solutions are implemented.

[0087] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0088] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0089] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0090] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0091] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0092] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0093] Based on such understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of each of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0094] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

[0095] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A precipitation area identification method based on geostationary meteorological satellite observation data, characterized in that: The method comprises: Obtain precipitation discrimination parameters for the study area collected by the geostationary meteorological satellite, wherein the precipitation discrimination parameters include the visible light 0.65 micron cloud top reflectivity R0.65, the solar zenith angle SZ, the cloud optical thickness value COT, the cloud particle effective radius value CER, the cloud top texture information, the cloud top temperature change slope S, the 3.9 micron cloud top brightness temperature Tb3.9, the 7.0 micron cloud top brightness temperature Tb7.0, the cloud top temperature value CTT and the cloud top change gradient value G t ; Generating a precipitation area of ​​the study area according to the precipitation discrimination parameter; Generating the precipitation area of ​​the study area according to the precipitation discrimination parameter specifically includes: When the visible light 0.65 micron cloud top reflectivity R0.65 of the pixel in the study area is greater than the reflection threshold, and the solar zenith angle SZ is less than the zenith angle threshold, the precipitation mask pixel value of the pixel is set to the first preset value; Otherwise, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a first pre-precipitation area in the study area; When the cloud optical thickness value COT of the pixel in the first pre-precipitation area is less than the thickness threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a second pre-precipitation area in the study area; When the cloud particle effective radius value CER of the pixel in the second pre-precipitation area is less than the radius threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a third pre-precipitation area in the study area; According to the cloud top temperature value CTT of the pixel in the third pre-precipitation area, the cloud top texture information is obtained, and when the cloud top texture information meets the preset condition, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a fourth pre-precipitation area in the study area; According to the cloud top temperature value CTT of the pixel in the fourth pre-precipitation area, the cloud top temperature change slope S is obtained, and when the cloud top temperature change slope S is greater than or equal to the slope threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a fifth pre-precipitation area in the study area; When the 3.9 micron cloud top brightness temperature Tb3.9 of the pixel in the fifth pre-precipitation area is greater than or equal to the first preset brightness temperature threshold, the precipitation mask pixel value of the pixel is set to the second preset value to obtain the sixth pre-precipitation area in the study area; When the 7.0 micron cloud top brightness temperature Tb7.0 of the pixel in the sixth pre-precipitation area is greater than or equal to the second preset brightness temperature threshold, the precipitation mask pixel value of the pixel is set to the second preset value to obtain the seventh pre-precipitation area in the study area; When the cloud top temperature CTT of the pixel in the seventh pre-precipitation area is greater than or equal to the preset cloud top temperature threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain an eighth pre-precipitation area in the study area; The cloud top change gradient value G is obtained according to the cloud top temperature value CTT of the pixel in the eighth pre-precipitation area. t , when the cloud top gradient value G t When it is greater than or equal to the gradient threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain the precipitation area in the study area.

2. The precipitation area identification method based on geostationary meteorological satellite observation data according to claim 1 is characterized in that: The cloud top texture information is obtained according to the cloud top temperature value CTT of the pixel in the third pre-precipitation area, and when the cloud top texture information meets the preset condition, the precipitation mask pixel value of the pixel is set to a second preset value to obtain the fourth pre-precipitation area in the study area, specifically including: Obtain the cloud top temperature values ​​CTT of the six pixels adjacent to the pixel to obtain the average cloud top temperature value T avg ; Obtain the minimum cloud top temperature value T among the cloud top temperature values ​​corresponding to all pixels in the pixel window of the preset size where the pixel is located min ; According to the average cloud top temperature value T avg and the minimum cloud top temperature T min , get the cloud top change gradient value G t ; According to the minimum cloud top temperature value T min , obtain the cloud top temperature change slope S; The cloud top texture information is the cloud top change gradient value G t and the difference between the cloud top temperature change slope S; When the cloud top texture information is less than a preset difference, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a fourth pre-precipitation area in the study area.

3. The precipitation area identification method based on geostationary meteorological satellite observation data according to claim 1 is characterized in that: The step of obtaining the cloud top temperature change slope S according to the cloud top temperature value CTT of the pixel in the fourth pre-precipitation area specifically includes: The minimum cloud top temperature value T min Input into the formula S = 0.568 (T min -217), and obtain the cloud top temperature change slope S.

4. The precipitation area identification method based on geostationary meteorological satellite observation data according to claim 2 is characterized in that: The cloud top change gradient value G is obtained according to the cloud top temperature value CTT of the pixel in the eighth pre-precipitation area. t , specifically including: Calculate the average cloud top temperature value T avg and the minimum cloud top temperature T min The difference between the cloud top change gradient value G t .

5. A precipitation area identification device based on geostationary meteorological satellite observation data, characterized in that: The device comprises: The acquisition module is used to obtain the precipitation discrimination parameters of the study area collected by the geostationary meteorological satellite, wherein the precipitation discrimination parameters include the visible light 0.65 micron cloud top reflectivity R0.65, the solar zenith angle SZ, the cloud optical thickness value COT, the cloud particle effective radius value CER, the cloud top texture information, the cloud top temperature change slope S, the 3.9 micron cloud top brightness temperature Tb3.9, the 7.0 micron cloud top brightness temperature Tb7.0, the cloud top temperature value CTT and the cloud top change gradient value G t ; A determination module, used for generating a precipitation area of ​​the study area according to the precipitation determination parameter; The determination module is specifically configured to set the precipitation mask pixel value of the pixel to a first preset value when the visible light 0.65 micron cloud top reflectance R0.65 of the pixel in the study area is greater than the reflection threshold and the solar zenith angle SZ is less than the zenith angle threshold; Otherwise, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a first pre-precipitation area in the study area; When the cloud optical thickness value COT of the pixel in the first pre-precipitation area is less than the thickness threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a second pre-precipitation area in the study area; When the cloud particle effective radius value CER of the pixel in the second pre-precipitation area is less than the radius threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a third pre-precipitation area in the study area; According to the cloud top temperature value CTT of the pixel in the third pre-precipitation area, the cloud top texture information is obtained, and when the cloud top texture information meets the preset condition, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a fourth pre-precipitation area in the study area; According to the cloud top temperature value CTT of the pixel in the fourth pre-precipitation area, the cloud top temperature change slope S is obtained, and when the cloud top temperature change slope S is greater than or equal to the slope threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a fifth pre-precipitation area in the study area; When the 3.9 micron cloud top brightness temperature Tb3.9 of the pixel in the fifth pre-precipitation area is greater than or equal to the first preset brightness temperature threshold, the precipitation mask pixel value of the pixel is set to the second preset value to obtain the sixth pre-precipitation area in the study area; When the 7.0 micron cloud top brightness temperature Tb7.0 of the pixel in the sixth pre-precipitation area is greater than or equal to the second preset brightness temperature threshold, the precipitation mask pixel value of the pixel is set to the second preset value to obtain the seventh pre-precipitation area in the study area; When the cloud top temperature CTT of the pixel in the seventh pre-precipitation area is greater than or equal to the preset cloud top temperature threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain an eighth pre-precipitation area in the study area; The cloud top change gradient value G is obtained according to the cloud top temperature value CTT of the pixel in the eighth pre-precipitation area. t , when the cloud top gradient value G t When it is greater than or equal to the gradient threshold, the precipitation mask pixel value of the pixel is set to a second preset value to obtain the precipitation area in the study area.

6. The precipitation area identification device based on geostationary meteorological satellite observation data according to claim 5, characterized in that: The determination module is specifically used to obtain the cloud top temperature values ​​CTT of the six pixels adjacent to the pixel, and obtain the average cloud top temperature value T avg ; Obtain the minimum cloud top temperature value T among the cloud top temperature values ​​corresponding to all pixels in the pixel window of the preset size where the pixel is located min ; According to the average cloud top temperature value T avg and the minimum cloud top temperature T min , get the cloud top change gradient value G t ; According to the minimum cloud top temperature value T min , obtain the cloud top temperature change slope S; The cloud top texture information is the cloud top change gradient value G t and the difference between the cloud top temperature change slope S; When the cloud top texture information is less than a preset difference, the precipitation mask pixel value of the pixel is set to a second preset value to obtain a fourth pre-precipitation area in the study area.

7. An electronic device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the precipitation area identification method based on geostationary meteorological satellite observation data as described in any one of claims 1 to 4 when executing the computer program.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the precipitation area identification method based on geostationary meteorological satellite observation data as claimed in any one of claims 1 to 4 are implemented.

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