Subtropical high pressure identification method and device based on satellite and numerical model data

Abstract

The present invention discloses a method and device for identifying subtropical high pressure based on satellite and numerical model data, wherein the method comprises: performing identification based on numerical model data to generate a first identification result; performing identification based on satellite data to generate a second identification result; based on the first identification result and the second identification result, correcting using a first preset method to generate a third identification result; processing the third identification result using a second preset method to generate a fourth identification result; extracting the fourth identification result using a third preset method to generate a high pressure identification result. The subtropical high pressure identification method based on satellite and numerical model data of the present invention improves the accuracy of the identification of the western Pacific subtropical high, and can enable numerical model products to better serve weather and meteorological services.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of meteorological technology, and in particular to a method and device for identifying subtropical high pressure based on satellite and numerical model data. Background Art

[0002] In the meteorological field, according to the meteorological definition, the 588dagpm contour line (referred to as the 588 line) on the 500hPa isobaric surface is generally used to characterize the Western Pacific Subtropical High (referred to as the Western Pacific Subtropical High), and the high pressure range it covers is the range of the Western Pacific Subtropical High. However, in actual meteorological operations, the 588 line on the weather map is not always continuous, and sometimes it is impossible to analyze the complete 588 line. In addition, due to the lack of observation data at sea, if the 588 line is used to describe the activities of the subtropical high, the Western Pacific Subtropical High will be distorted, or even create an illusion. Summary of the invention

[0003] The embodiment of the present invention provides a subtropical high pressure identification method and device based on satellite and numerical model data, which improves the accuracy of the western Pacific subtropical high identification and enables the numerical model products to better serve the weather and meteorological business.

[0004] To achieve the above objectives, in a first aspect, the present invention provides a subtropical high pressure identification method based on satellite and numerical model data, comprising:

[0005] Perform identification based on the numerical pattern data to generate a first identification result;

[0006] Perform identification based on the satellite data to generate a second identification result;

[0007] Based on the first recognition result and the second recognition result, a correction is performed using a first preset method to generate a third recognition result;

[0008] Processing the third recognition result using a second preset method to generate a fourth recognition result;

[0009] The fourth identification result is extracted using a third preset method to generate a high-voltage identification result.

[0010] In one embodiment of the present invention, the performing identification based on the numerical pattern data to generate a first identification result includes:

[0011] acquiring the numerical model data;

[0012] The numerical pattern data is identified according to a preset threshold value to generate the first identification result.

[0013] In one embodiment of the present invention, the performing identification based on satellite data to generate a second identification result includes:

[0014] Acquire the satellite data at the same time as the numerical model data;

[0015] The satellite data is segmented based on a preset segmentation algorithm to generate the second identification result.

[0016] In one embodiment of the present invention, the generating a third recognition result by performing correction based on the first recognition result and the second recognition result by using a first preset method includes:

[0017] Obtain L2 cloud top height data;

[0018] Based on the L2 cloud top height data, the first recognition result and the second recognition result are corrected using the first preset method to generate the third recognition result.

[0019] In one embodiment of the present invention, the processing the third recognition result by using the second preset method to generate the fourth recognition result includes:

[0020] The third identification result is filtered in sequence using a fixed terrain filtering method and a domain filtering method to generate the fourth identification result.

[0021] In one embodiment of the present invention, the subtropical high pressure identification method based on satellite and numerical model data further includes:

[0022] The high-voltage identification result and the fourth identification result are superimposed and displayed.

[0023] In a second aspect, the present invention provides a subtropical high pressure identification device based on satellite and numerical model data, comprising: a first generation module, a second generation module, a third generation module, a fourth generation module and a fifth generation module. The first generation module is used to perform identification based on numerical model data to generate a first identification result. The second generation module is used to perform identification based on satellite data to generate a second identification result. The third generation module is used to correct the first identification result and the second identification result using a first preset method to generate a third identification result. The fourth generation module is used to process the third identification result using a second preset method to generate a fourth identification result. The fifth generation module is used to extract the fourth identification result using a third preset method to generate a high pressure identification result.

[0024] In one embodiment of the present invention, the first generation module includes: a first acquisition unit and a first generation unit. The first acquisition unit is used to acquire the numerical pattern data. The first generation unit is used to identify the numerical pattern data according to a preset threshold value to generate the first identification result.

[0025] In a third aspect, the present invention provides an electronic device, comprising:

[0026] at least one processor; and

[0027] a memory communicatively coupled to the at least one processor;

[0028] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the subtropical high pressure identification method based on satellite and numerical model data as described above.

[0029] In a fourth aspect, the present invention provides a computer-readable storage medium, comprising a computer program and instructions, which, when executed on a computer, enables the computer to execute the subtropical high pressure identification method based on satellite and numerical model data as described above.

[0030] Compared with the prior art, the subtropical high pressure identification method and device based on satellite and numerical model data according to the present invention improves the accuracy of the western Pacific subtropical high pressure identification and enables the numerical model products to better serve the weather and meteorological business. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a flow chart of a method for identifying subtropical high pressure based on satellite and numerical model data in Embodiment 1 of the present invention;

[0032] Figure 2 is a schematic diagram of a process for generating a first identification result in Embodiment 1 of the present invention;

[0033] Figure 3 is a schematic diagram of a process for generating a second identification result in the first embodiment of the present invention;

[0034] Figure 4 is a schematic diagram of a process for generating a third identification result in the first embodiment of the present invention;

[0035] Figure 5 This is a schematic diagram of the structure of a subtropical high pressure identification device based on satellite and numerical model data in Embodiment 2 of the present invention;

[0036] Figure 6 It is a schematic diagram of the structure of an electronic device in Embodiment 3 of the present invention;

[0037] Figure 7 It is a logical flow diagram of a subtropical high pressure identification method based on satellite and numerical model data in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0038] The embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention, rather than to limit the embodiments of the present invention. It is also necessary to explain that, for ease of description, only parts related to the embodiments of the present invention are shown in the accompanying drawings, rather than all structures.

[0039] To facilitate understanding, the main implementation concepts of the embodiments of the present invention are first briefly described.

[0040] The inventor discovered the technical defects described in the previous background technology, comprehensively considered the dynamic and thermodynamic factors of the Western Pacific Subtropical High, combined satellite remote sensing observation data and quantitative numerical model products, and corrected each other, avoiding the illusion caused by the use of 588 lines alone, and improving the accuracy of the Western Pacific Subtropical High identification. In addition, by combining remote sensing observation data and quantitative numerical model products and comparing their presentation in large-scale weather systems, we can explore the laws and seek the warning role of numerical model products in weather system monitoring, so that numerical model products can better serve weather and meteorological services.

[0041] Embodiment 1

[0042] Figure 1 is a flow chart of a method for identifying subtropical high pressure based on satellite and numerical model data in Embodiment 1 of the present invention, such as Figure 1 As shown, embodiment 1 provides a subtropical high pressure identification method based on satellite and numerical model data, including:

[0043] Step S100, performing identification based on the numerical pattern data to generate a first identification result;

[0044] Among them, Figure 2 As shown, the step S100 specifically includes:

[0045] Step S101, obtaining the numerical model data;

[0046] Step S102, identifying the numerical pattern data according to a preset threshold value to generate the first identification result;

[0047] Specifically, Figure 7As shown, the numerical model data refers to the meteorological forecast data obtained using the meteorological numerical model, including but not limited to the GRAPES data of the National Meteorological Information Center and the ECMWF data of the European Center. Based on the 500hPa geopotential height field (HGT) data in the numerical model, 587.5dagpm is used as the threshold (preset threshold) to make an initial judgment on the range of the subtropical high. That is, the area with a geopotential height greater than 587.5dagpm is judged to be the Western Pacific Subtropical High area, otherwise it is a non-Western Pacific Subtropical High area, that is, the first identification result includes the first Western Pacific Subtropical High area and the first non-Western Pacific Subtropical High area, and the specific identification method is as follows:

[0048]

[0049] Where HGT(i,j) is the potential height of the grid point, f 1 (i, j) is the result of whether the grid point is a subtropical high based on model data, where 1 is the western Pacific subtropical high area and 0 is the non-western Pacific subtropical high area.

[0050] Step S200, performing identification based on satellite data to generate a second identification result;

[0051] Among them, Figure 3 As shown, the step 200 specifically includes:

[0052] Step S201, acquiring the satellite data at the same time as the numerical model data;

[0053] Step S202, segmenting the satellite data based on a preset segmentation algorithm to generate the second identification result;

[0054] Specifically, the satellite data is FY4A satellite data, based on the long-wave infrared brightness temperature data (10.8um) of the FY4A satellite at the hour of each month and every day, the monthly average is performed, and the monthly average 500hPa potential height field 588 line of the fifth generation atmospheric reanalysis data set (ERA5) of ECMWF (European Center for Medium-Range Weather Forecasts) is combined to explore the law of the two, so as to find the typical long-wave infrared brightness temperature contour corresponding to the western Pacific subtropical high every month (that is, using statistical averaging, the monthly average data of the two are superimposed together). For example, from July to October, the 588 line is consistent with the approximate range of 276K.

[0055] like Figure 7 As shown, based on the typical contour values ​​obtained above, the satellite data image is binary segmented for different months, and the segmentation formula is as follows:

[0056]

[0057] Where T is the segmentation value, TB(i,j) is the brightness temperature of the grid point, and f 2(i, j) is the identification result of whether the grid point is a subtropical high based on satellite data, where 1 is the western Pacific subtropical high area and 0 is the non-western Pacific subtropical high area; that is, the second identification result includes the second western Pacific subtropical high area and the second non-western Pacific subtropical high area.

[0058] Step S300, based on the first recognition result and the second recognition result, a correction is performed using a first preset method to generate a third recognition result;

[0059] Among them, Figure 4 As shown, the step S300 specifically includes:

[0060] Step S301, obtaining L2 cloud top height data;

[0061] Step S302, based on the L2 cloud top height data, using the first preset method to correct the first recognition result and the second recognition result to generate the third recognition result;

[0062] Specifically, obtain the FY4A L2 cloud top height (CTH) data product (which can be obtained directly from the Fengyun Data official website), such as Figure 7 As shown, based on the satellite data product, the subtropical high area with inconsistent identification results in step S100 and step S200 is corrected.

[0063] The principles of revision are as follows:

[0064] If the numerical model identifies the area as the Western Pacific Subtropical High, but the satellite data shows that it is not the Western Pacific Subtropical High, if the cloud top height in these areas is less than 4.5km or greater than 6.5km, then these areas can be identified as the Western Pacific Subtropical High. If the cloud top height in these areas is between 4.5km and 6.5km, then these areas do not meet the conditions and need to be eliminated, that is:

[0065]

[0066] Where CTH(i,j) is the cloud top height of the grid point, f 2 ′(i,j) is the corrected identification result of the western Pacific subtropical high, that is, the final identification result of the western Pacific subtropical high. For example: when the geopotential height is less than 587.5dagpm(f 1 (i,j)=0), it is not the western Pacific subtropical high area; when the potential height is greater than 587.5dagpm(f 1 (i,j)=1), the brightness temperature is less than the threshold f 2 (i,j)=0, and the cloud top height is between 4.5km-6.5km, which is not the western Pacific subtropical high area; when the geopotential height is greater than 587.5dagpm(f 1 (i,j)=1), the brightness temperature is less than the threshold f 2(i,j)=0, but the cloud top height is less than 4.5km or greater than 6.5km, it is the western Pacific subtropical high area; when the potential height is greater than 587.5dagpm(f 1 (i,j)=1), and the brightness temperature is greater than the threshold f 2 (i,j)=1, which means the western Pacific subtropical high region.

[0067] Step S400, processing the third recognition result by using a second preset method to generate a fourth recognition result;

[0068] The step S400 specifically includes: filtering the third identification result in sequence by using a fixed terrain filtering method and a domain filtering method to generate the fourth identification result.

[0069] Specifically, due to the influence of terrain and local thermal convection, terrain clouds or local convective clouds are sometimes formed in the subtropical high area. Therefore, it is necessary to perform filtering processing on the western Pacific subtropical high area identified in step 300, such as Figure 7 As shown, it is specifically divided into two methods: fixed terrain filtering and neighborhood filtering, which are performed in turn.

[0070] The fixed terrain filtering is specifically as follows: Investigate the formation of clouds at the same time and location in the same season every year under the control of the subtropical high. These clouds are terrain clouds and have no obvious relationship with the weather system, so they can be directly filtered out. Based on the ERA5 reanalysis data set, the multi-year average cloud cover (Total Cloud Cover, TCC) probability of the four seasons of spring, summer, autumn and winter from 1979 to 2020 is calculated, and the areas with an annual mean value greater than 0.7 are identified as perennial cloud areas and removed. The specific formula is as follows:

[0071]

[0072] Among them, y(i,j) is whether the point (i,j) is a perennial cloud area, 0 for no, 1 for yes, and TCC(i,j) is the average cloud cover probability of point (i,j).

[0073] Among them, neighborhood filtering is specifically: Neighborhood filtering is an image processing method based on the neighborhood around pixels, which aims to filter out some isolated cloud blocks in the subtropical high area and reduce interference. Set an M*M template, N is the total number of grid points, and the template is as follows:

[0074] 1 1 1 1 1 1 0 0 0 1 1 0 0 0 1 1 0 0 0 1 1 1 1 1 1

[0075] For the above template, the following formula is used for filtering:

[0076]

[0077] Among them, x is the binary pixel value; i is the grid value around the template, and y is the pixel value after filtering; when y=0, all pixel values ​​in the template are 0, otherwise they remain unchanged.

[0078] Step S500: extracting the fourth identification result by using a third preset method to generate a high-voltage identification result.

[0079] Step S600, the high-voltage identification result and the fourth identification result are superimposed and displayed.

[0080] Specifically, the subtropical high ridgeline is the junction of the southeast wind and the southwest wind in the subtropical high anticyclonic (clockwise) flow field, that is, the wind direction shear. It can be considered that the area near the ridgeline is the central area of ​​the subtropical high, which is the most important feature of the subtropical high and has important significance in meteorological operations. Its westward advance and eastward retreat will cause the high temperature range to expand and shrink. For the western Pacific subtropical high area identified above, the wind field u component contour line of the model zero field is superimposed. The model zero field is the variable with a forecast time of 0 in the numerical model forecast data mentioned in step 1. The u variable in the wind field variable is selected to present the subtropical high ridgeline. The u=0 contour line crossing the western Pacific subtropical high here is the subtropical high ridgeline. When superimposed with the identified subtropical high area, the subtropical high characteristics can be more clearly and intuitively displayed, providing more valuable meteorological information for forecasters.

[0081] In summary, the subtropical high pressure identification method based on satellite and numerical model data of this embodiment comprehensively considers the dynamic and thermodynamic factors of the western Pacific subtropical high, combines satellite remote sensing observation data and quantitative numerical model products, and corrects each other to avoid the illusion caused by using the 588 line alone, thereby improving the accuracy of the western Pacific subtropical high identification; and combines remote sensing observation data and quantitative numerical model products, and compares the display situation of the two on large-scale weather systems, so as to explore the laws and seek the warning role of numerical model products in weather system monitoring, so that numerical model products can better serve weather and meteorological services.

[0082] Embodiment 2

[0083] Figure 5 : is a schematic diagram of the structure of a subtropical high pressure identification device based on satellite and numerical model data in Embodiment 2 of the present invention, such as Figure 5As shown, embodiment 2 provides a subtropical high pressure identification device based on satellite and numerical model data, including: a first generation module 501, a second generation module 502, a third generation module 503, a fourth generation module 504 and a fifth generation module 505. The first generation module 501 is used to perform identification based on numerical model data and generate a first identification result. The second generation module 502 is used to perform identification based on satellite data and generate a second identification result. The third generation module 503 is used to correct the first identification result and the second identification result using a first preset method to generate a third identification result. The fourth generation module 504 is used to process the third identification result using a second preset method to generate a fourth identification result. The fifth generation module 505 is used to extract the fourth identification result using a third preset method to generate a high pressure identification result.

[0084] In this embodiment, the first generation module 501 includes: a first acquisition unit and a first generation unit. The first acquisition unit is used to acquire the numerical pattern data. The first generation unit is used to identify the numerical pattern data according to a preset threshold value and generate the first identification result.

[0085] In this embodiment, the second generation module 502 includes: a second acquisition unit and a second generation unit. The second acquisition unit is used to acquire the satellite data at the same time as the numerical model data. The second generation unit is used to segment the satellite data based on a preset segmentation algorithm to generate the second identification result.

[0086] In this embodiment, the third generation module 503 includes: a third acquisition unit and a third generation unit. The third acquisition unit is used to acquire L2 cloud top height data. The third generation unit is used to correct the first recognition result and the second recognition result based on the L2 cloud top height data using the first preset method to generate the third recognition result.

[0087] In this embodiment, the fourth generation module 504 includes a fourth generation unit, which is used to filter the third recognition result in sequence by using a fixed terrain filtering method and a domain filtering method to generate the fourth recognition result.

[0088] In this embodiment, the subtropical high pressure identification device based on satellite and numerical model data further includes an overlay display module for displaying the high pressure identification result and the fourth identification result in an overlay manner.

[0089] The various variations and specific examples of the subtropical high pressure identification method based on satellite and numerical model data provided in Example 1 are also applicable to the subtropical high pressure identification device based on satellite and numerical model data provided in this example. Through the above detailed description of a subtropical high pressure identification method based on satellite and numerical model data, those skilled in the art can clearly know the implementation method of a subtropical high pressure identification device based on satellite and numerical model data in this example. Therefore, for the sake of brevity of the specification, it will not be described in detail here.

[0090] Embodiment 3

[0091] Figure 6 is a schematic diagram of the structure of an electronic device in Embodiment 3 of the present invention, such as Figure 6 As shown, the third embodiment further provides an electronic device 600 , which may include: a processor 601 and a memory 602 .

[0092] The memory 602 is used to store programs. The memory 602 may include volatile memory, such as random-access memory (RAM), such as static random-access memory (SRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), etc. The memory may also include non-volatile memory, such as flash memory. The memory 602 is used to store computer programs (such as applications, functional modules, etc. that implement the above method), computer instructions, etc. The above computer programs, computer instructions, etc. may be partitioned and stored in one or more memories 602. And the above computer programs, computer instructions, data, etc. may be called by the processor 601.

[0093] The above-mentioned computer programs, computer instructions, etc. may be stored in partitions in one or more memories 602 . And the above-mentioned computer programs, computer instructions, etc. may be called by the processor 601 .

[0094] The processor 601 is used to execute the computer program stored in the memory 602 to implement each step of the method involved in the above embodiment.

[0095] For details, please refer to the relevant description in the previous method embodiment.

[0096] The processor 601 and the memory 602 may be independent structures or integrated structures. When the processor 601 and the memory 602 are independent structures, the memory 602 and the processor 601 may be coupled and connected via a bus 603 .

[0097] The electronic device of this embodiment can execute the technical solution in the above method, and its specific implementation process and technical principle are the same, which will not be repeated here.

[0098] Embodiment 4

[0099] Embodiment 4 also provides a computer-readable storage medium, including a computer program and instructions. When the computer program or instructions are executed on a computer, the computer executes the subtropical high pressure identification method based on satellite and numerical model data of any embodiment of the present invention.

[0100] Computer-readable storage media include: USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical disks, and other media that can store program codes.

[0101] This embodiment also provides a computer program product, which includes: a computer program, which is stored in a readable storage medium. At least one processor of an electronic device can read the computer program from the readable storage medium, and at least one processor executes the computer program so that the electronic device executes the solution provided by any of the above embodiments.

[0102] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the disclosure of the present invention can be performed in parallel, sequentially or in different orders, as long as the desired results of the technical solution disclosed in the present invention can be achieved, and this document does not limit this.

[0103] In summary, the subtropical high pressure identification method and device based on satellite and numerical model data of the present invention comprehensively consider the dynamic and thermodynamic factors of the western Pacific subtropical high, combine satellite remote sensing observation data and quantitative numerical model products, and correct each other to avoid the illusion caused by using the 588 line alone, thereby improving the accuracy of the western Pacific subtropical high identification; and by combining remote sensing observation data and quantitative numerical model products, comparing the two in terms of their display situation on large-scale weather systems, it is possible to explore the laws and seek the warning role of numerical model products in weather system monitoring, so that numerical model products can better serve weather and meteorological services.

[0104] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for identifying subtropical high pressure based on satellite and numerical model data, characterized in that: include: Perform identification based on the numerical pattern data to generate a first identification result; Perform identification based on the satellite data to generate a second identification result; Based on the first recognition result and the second recognition result, a correction is performed using a first preset method to generate a third recognition result; Processing the third recognition result using a second preset method to generate a fourth recognition result; Extracting the fourth identification result by using a third preset method to generate a high-voltage identification result; The method of generating a third recognition result by correcting the first recognition result and the second recognition result using a first preset method includes: Obtain L2 cloud top height data; Based on the L2 cloud top height data, the first recognition result and the second recognition result are corrected by using the first preset method to generate the third recognition result; The step of processing the third recognition result by using the second preset method to generate the fourth recognition result includes: The third identification result is filtered in sequence using a fixed terrain filtering method and a domain filtering method to generate the fourth identification result.

2. The subtropical high pressure identification method based on satellite and numerical model data as claimed in claim 1, characterized in that: The performing identification based on the numerical pattern data to generate a first identification result includes: acquiring the numerical model data; The numerical pattern data is identified according to a preset threshold value to generate the first identification result.

3. The subtropical high pressure identification method based on satellite and numerical model data as claimed in claim 1, characterized in that: The performing identification based on the satellite data to generate a second identification result includes: Acquire the satellite data at the same time as the numerical model data; The satellite data is segmented based on a preset segmentation algorithm to generate the second identification result.

4. The subtropical high pressure identification method based on satellite and numerical model data as claimed in claim 1, characterized in that: Also includes: The high-voltage identification result and the fourth identification result are superimposed and displayed.

5. A subtropical high pressure identification device based on satellite and numerical model data, characterized in that: include: A first generating module, used for performing identification based on the numerical pattern data to generate a first identification result; A second generating module, used for performing identification based on satellite data and generating a second identification result; A third generating module, configured to generate a third recognition result by performing corrections using a first preset method based on the first recognition result and the second recognition result; A fourth generating module, used to process the third identification result by using a second preset method to generate a fourth identification result; a fifth generating module, configured to extract the fourth identification result by using a third preset method to generate a high-voltage identification result; The third generation module includes: a third acquisition unit and a third generation unit, the third acquisition unit is used to acquire L2 cloud top height data, and the third generation unit is used to correct the first recognition result and the second recognition result based on the L2 cloud top height data by using the first preset method to generate the third recognition result; The fourth generation module includes a fourth generation unit, and the fourth generation unit is used to filter the third identification result in sequence by using a fixed terrain filtering method and a domain filtering method to generate the fourth identification result.

6. The subtropical high pressure identification device based on satellite and numerical model data as claimed in claim 5, characterized in that: The first generation module comprises: A first acquisition unit, used to acquire the numerical model data; The first generating unit is used to identify the numerical pattern data according to a preset threshold value to generate the first identification result.

7. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively coupled to the at least one processor; Wherein, the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the subtropical high pressure identification method based on satellite and numerical model data as described in any one of claims 1-4.

8. A computer-readable storage medium, characterized in that: The method comprises a computer program and instructions. When the computer program or the instructions are executed on a computer, the computer is enabled to execute the subtropical high pressure identification method based on satellite and numerical model data as described in any one of claims 1 to 4.

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