Linear convection prediction correction method based on horizontal secondary grid flux

Abstract

The invention discloses a linear convection forecast correction method based on horizontal secondary grid flux. The linear convection forecast correction method comprises the following steps: acquiring forecast data of a numerical weather forecast mode; according to the forecast data, judging an area where linear convection forecast by a numerical mode occurs; respectively calculating the turbulent flux of the horizontal secondary grid according to a first calculation formula and a second calculation formula in the linear convection generation area; multiplying the turbulent fluxes of the horizontal secondary grids obtained by the first calculation formula and the second calculation formula to obtain a product; and correcting the intensity and the speed of the linear convection according to the position relationship between a negative value region and a strong echo region of the product in the sensitive layer. According to the linear convection forecasting correction method based on the horizontal secondary grid flux, the strength and the moving speed of linear convection are directly subjected to qualitative and quantitative adjustment by combining physical basis, and the accuracy, the real-time performance and the adaptability of convection forecasting are remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical fields of atmospheric science and data processing, and particularly relates to a method for correcting linear convection forecasts based on horizontal sub-grid fluxes. Background Art

[0002] Linear convection (such as squall lines) is a convective system with a wide range, high intensity, and long duration, often accompanied by weather phenomena such as heavy precipitation, strong winds, hail, thunderstorms, and even tornadoes. The refined and accurate forecasting of linear convection is an important part of meteorological forecasting and warning technologies.

[0003] Currently, the forecasting of linear convection usually adopts the method of algorithm correction based on numerical weather prediction models. First, the numerical model numerically solves the motion and changes of the atmosphere using observational data and physical parameterization schemes to obtain weather forecasts including linear convection; then, a convection correction algorithm adjusts the output results in the numerical model according to a specific method to give the final convection forecast.

[0004] Based on the current convection forecasting process, the correction methods for convection forecasts are mainly divided into two categories:

[0005] 1. Correction based on physical improvement: This type of method improves the accuracy of convection forecasts by improving the physical process parameterization schemes (such as convection, radiation, boundary layer, etc.) in the numerical model. However, this method requires re-performing numerical forecasts, has a high computational cost, and is unstable under different weather situations, making it difficult to ensure special optimization for linear convection.

[0006] 2. Correction based on statistical methods: This type of method adjusts the convection forecast through statistical analysis of historical forecast data and observational data. For example, through the "rainfall blanking" method, it is considered that the weak precipitation area in the convection precipitation forecast may be false, and thus corrected to no precipitation. However, this type of method mainly focuses on the adjustment of the precipitation coverage area and intensity in weak convective weather, lacks in-depth understanding of the physical processes of strong convective weather such as linear convection, and cannot effectively adjust the intensity and movement speed of linear convection.

[0007] In addition, the current convection correction methods do not make special corrections for typical weather phenomena such as linear convection, do not provide adjustments for the intensity and movement speed of linear convection, and are difficult to meet the actual needs of severe convective forecasting. In summary, for linear convection, the existing convection forecasting and correction methods still have significant deficiencies in intensity and movement speed adjustments and are difficult to meet the actual needs. Summary of the Invention

[0008] The present invention aims to solve at least one of the technical problems existing in the related technologies to a certain extent.

[0009] The present invention aims to provide a method for correcting the prediction of linear convection based on horizontal sub-grid fluxes. Combining physical principles, it can directly qualitatively adjust the intensity and movement speed of linear convection without recalculating numerical weather predictions, thus providing accurate auxiliary information for linear convection prediction.

[0010] To achieve the above object, on the one hand, the present invention provides a method for correcting the prediction of linear convection based on horizontal sub-grid fluxes, including:

[0011] Obtaining the prediction data of the numerical weather prediction model;

[0012] Based on the prediction data, determining the area where linear convection occurs in the numerical model prediction;

[0013] In the area where linear convection occurs, calculating the horizontal sub-grid turbulent fluxes respectively according to the first calculation formula and the second calculation formula; among them, the first calculation formula is:

[0014] ;

[0015] Wherein, represents the sub-grid turbulent flux in the direction, takes 1 to represent the east-west direction and 2 to represent the north-south direction; represents the potential temperature; is the coordinate distance in the direction; is the partial differential operator;

[0016] ;

[0017] In the formula, is a fixed parameter set to 0.25; is the horizontal grid resolution; is the deformation rate tensor, and the calculation formula is , is the counting symbol equivalent to , and are both selected from 1 and 2;

[0018] The second calculation formula is:

[0019] ;

[0020] In the formula, represents the wind speed in the and are respectively when takes 1 and 2; is the scale adaptation coefficient, obtained from ;

[0021] Multiply the horizontal sub-grid turbulent fluxes obtained from the first and second calculation formulas to obtain a product; and correct the intensity and speed of linear convection according to the positional relationship between the negative value area and the strong echo area in the sensitive layer.

[0022] A further preferred technical solution of the present invention is that the forecast data obtained from the numerical weather prediction model is the original meteorological forecast data or the secondary meteorological forecast product made according to the original meteorological forecast data.

[0023] Preferably, the forecast data at least includes horizontal wind field data, vertical velocity data, potential temperature or temperature field data, and the distribution data of radar reflectivity factor.

[0024] Preferably, according to the vertical velocity data and the distribution of radar reflectivity factor, determine the area where linear convection occurs in the numerical model forecast;

[0025] Calculate the horizontal sub-grid turbulent flux according to the horizontal wind field data and the potential temperature or temperature field data.

[0026] Preferably, the sensitive layer is the 2000-meter height layer from the ground.

[0027] Preferably, according to the positional relationship between the negative value area and the strong echo area in the sensitive layer, correct the intensity of linear convection, specifically:

[0028] When the negative value area is inside the strong echo area, then enhance the intensity forecast of linear convection; otherwise, weaken the intensity forecast of linear convection.

[0029] Preferably, according to the positional relationship between the negative value area and the strong echo area in the sensitive layer, correct the speed of linear convection, specifically:

[0030] When the negative value area is in front of the center of the strong echo area, that is, on the moving direction side, then enhance the moving speed forecast of linear convection; otherwise, weaken the moving speed forecast of linear convection.

[0031] On the other hand, the present invention provides a non-transitory computer-readable storage medium, on which computer instructions are stored, and the computer instructions cause the computer to execute the above-mentioned method for correcting the linear convection forecast based on the horizontal sub-grid flux.

[0032] Another aspect of the present invention provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete communication with each other through the communication bus. The processor calls the logical instructions in the memory to execute the above-mentioned linear convection prediction correction method based on the horizontal sub-grid flux.

[0033] Another aspect of the present invention provides a computer program product. The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer executes the above-mentioned linear convection prediction correction method based on the horizontal sub-grid flux.

[0034] Beneficial effects: The linear convection prediction correction method based on the horizontal sub-grid flux of the present invention directly adjusts the intensity and moving speed of the linear convection by combining physical basis, significantly improving the accuracy, real-time performance, and adaptability of the convection prediction.

[0035] Compared with the existing correction methods, the present invention combines physical basis, deeply analyzes the physical process of convection by introducing the core idea of horizontal sub-grid flux, ensuring that the correction method has a solid physical foundation. The present invention does not need to recalculate the numerical prediction, directly corrects the prediction results of the existing numerical model, avoids the high computational cost of recalculating the numerical prediction, and significantly improves the computational efficiency. The present invention optimizes the prediction of linear convection specifically, performs excellently in the prediction effect of linear convection, can provide qualitative adjustment opinions for the prediction of its intensity and moving speed, and improves the prediction accuracy. Description of the Drawings

[0036] Figure 1 It is a flowchart of the linear convection prediction correction method based on the horizontal sub-grid flux of the present invention;

[0037] Figure 2 It is the actual observation map of the linear convection radar reflectivity factor and the numerical model prediction result in Embodiment 1; Figure 2 In (a), it is the actual observation of the linear convection radar reflectivity factor at 08:00 Beijing time, Figure 2 In (b), it is the actual observation of the linear convection radar reflectivity factor at 11:00 Beijing time, Figure 2 In (c), it is the numerical model prediction result at 08:00 Beijing time, Figure 2 In (d), it is the numerical model prediction result at 11:00 Beijing time;

[0038] Figure 3 It is the distribution map of the horizontal sub-grid turbulent fluxes calculated by the first calculation formula and the second calculation formula respectively in Embodiment 1, and the horizontal distribution map of the product of the two horizontal sub-grid turbulent fluxes; Figure 3In (a), it is the horizontal distribution map of the horizontal sub-grid turbulent flux calculated according to the first calculation formula. Figure 3 In (b), it is the horizontal distribution map of the horizontal sub-grid turbulent flux calculated according to the second calculation formula. Figure 3 In (c), it is the horizontal distribution map of the product of the two horizontal sub-grid turbulent fluxes calculated by the two calculation formulas. Specific implementation manner

[0039] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments, and they should not be construed as limitations on the present invention. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention. In the description of the present invention, it should be understood that the terms used are only for the purpose of description and cannot be construed as indicating or implying relative importance.

[0040] The following combines Figures 1-3 to describe the linear convection prediction correction method based on the horizontal sub-grid flux provided by the present invention.

[0041] Example 1: This example provides a linear convection prediction correction method based on the horizontal sub-grid flux.

[0042] Taking the linear convection that occurred in a certain area on July 10, 2023 as an example, a case demonstration of the correction algorithm is carried out. As Figure 2 shown, at 08:00 Beijing time on July 10, 2023, the strong echo area shows that the convection develops and aggregates into a line, located in the area shown in Figure 2 In (a). After that, it continues to move eastward, the convection intensity increases, and the range increases. At 11:00 Beijing time, the main body of the linear convection moves into the area shown in Figure 2 In (b).

[0043] The Precision Weather Analysis and Forecasting System (PWAFS) has the ability to predict the basic situation of this convection process. As Figure 2 shown in (c), in the numerical prediction results starting at 20:00 Beijing time on July 9, 2023, the linear convection at 08:00 on the 10th is basically predicted. However, in the subsequent prediction results, the convection intensity does not maintain, and the convection moving speed is too slow. As Figure 2 shown in (d), there are large errors in the prediction of this linear convection process.

[0044] For this, a linear convective prediction correction method based on horizontal sub-grid fluxes is adopted for correction. The specific steps are as follows: Figure 1 as shown below, including:

[0045] S1. Obtain the data of the PWAFS prediction system. The time of using the data is 08:00 Beijing time on July 10, 2023. The strong reflectivity echo area is marked with gray shading in the base map. The prediction data should at least include horizontal wind field data, vertical velocity data, potential temperature or temperature field data, and the distribution data of radar reflectivity factor.

[0046] S2. According to the radar reflectivity echo simulated by the model, select the Figure 3 area shown below as the range where linear convection occurs.

[0047] S3. In the area where linear convection occurs, calculate the horizontal sub-grid turbulent fluxes respectively according to the first calculation formula and the second calculation formula. Among them, the first calculation formula is:

[0048] ;

[0049] where represents the sub-grid turbulent flux in the direction. takes 1 to represent the east-west direction and 2 to represent the north-south direction; represents the potential temperature; is the direction coordinate distance; is the partial differential operator; is the turbulent diffusion coefficient, and the calculation formula is:

[0050] ;

[0051] In the formula, is a fixed parameter set to 0.25; is the horizontal grid resolution; is the deformation rate tensor, and the calculation formula is , is the counting symbol equivalent to , and are both selected from 1 and 2;

[0052] The second calculation formula is:

[0053] ;

[0054] In the formula, represents the wind speed in the direction; and are respectively when ; is the scale adaptation coefficient, obtained from ;

[0055] Since the moving direction of the linear convection in this forecast is due east, only the east-west direction is used, that is . The distribution at a height of 2 km is as shown in Figure 3 (a) and Figure 3 (b) in

[0056] S4. Multiply the horizontal sub-grid turbulent fluxes obtained from the first calculation formula and the second calculation formula to obtain a product. The distribution of this product at a height of 2 km is as shown in Figure 3 (c) in

[0057] S5. Display the above product and the radar echo obtained from numerical weather prediction simultaneously, and compare their relative position relationships. The negative value region of the product is located within the range of the strong echo region. The correction suggestion for the intensity is positive, that is, the intensity of the linear convection predicted by the numerical model should be appropriately enhanced. Quantitatively, in this example, the sensitive layer is located within the strong echo range where the product value is lower than -0.2 K 2 m 4 s -4 and the area reaches 540 km 2 , and it is recommended that the correction amount of the intensity forecast of the linear convection (recorded by the simulated radar reflectivity) be +5.0 dBZ.

[0058] Compare the position relationship between the negative value region of the product and the strong echo center, and it is found that the negative value region is located in the eastward direction of the echo. The correction suggestion for the moving speed is positive, that is, the moving speed of the linear convection predicted by the numerical model should be appropriately enhanced. Quantitatively, in this example, the distance between the negative value region of the product and the strong echo center is about 34 km, and it is recommended that the correction amount of the moving speed forecast of the linear convection be +2.0 m s -1 .

[0059] Based on the above results, the conclusion given by this correction algorithm is: the intensity forecast of the linear convection should be appropriately enhanced, and the moving speed of the linear convection should be appropriately increased. According to this conclusion, correct the forecast of the linear convection to improve the forecast accuracy.

[0060] Embodiment 2: This embodiment provides a non-transitory computer-readable storage medium, on which computer instructions are stored. These computer instructions cause the computer to execute a method for correcting the forecast of linear convection based on horizontal sub-grid fluxes. The method includes the following steps:

[0061] Obtain the forecast data of the numerical weather prediction model;

[0062] According to the forecast data, judge the area where the linear convection predicted by the numerical model occurs;

[0063] In the region where linear convection occurs, calculate the horizontal sub-grid turbulent fluxes respectively according to the first calculation formula and the second calculation formula in Embodiment 1;

[0064] Multiply the horizontal sub-grid turbulent fluxes obtained from the first calculation formula and the second calculation formula to obtain a product; and correct the intensity and velocity of the linear convection according to the positional relationship between the negative value region of the product and the strong echo region in the sensitive layer.

[0065] Embodiment 3: This embodiment provides an electronic device, which may include: a processor, a communications interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus. The processor can call the logical instructions in the memory to execute a method for correcting the prediction of linear convection based on the horizontal sub-grid fluxes. The method includes the following steps:

[0066] Obtain the forecast data of the numerical weather prediction model;

[0067] According to the forecast data, determine the region where the linear convection predicted by the numerical model occurs;

[0068] In the region where linear convection occurs, calculate the horizontal sub-grid turbulent fluxes respectively according to the first calculation formula and the second calculation formula in Embodiment 1;

[0069] Multiply the horizontal sub-grid turbulent fluxes obtained from the first calculation formula and the second calculation formula to obtain a product; and correct the intensity and velocity of the linear convection according to the positional relationship between the negative value region of the product and the strong echo region in the sensitive layer.

[0070] In addition, when the logical instructions in the above-mentioned memory are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0071] Example 4: This example provides a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute a linear convection prediction correction method based on horizontal sub-grid fluxes. The method includes the following steps:

[0072] Obtain the forecast data of the numerical weather prediction model;

[0073] According to the forecast data, determine the area where linear convection occurs in the numerical model forecast;

[0074] In the area where linear convection occurs, calculate the horizontal sub-grid turbulent fluxes respectively according to the first calculation formula and the second calculation formula in Example 1;

[0075] Multiply the horizontal sub-grid turbulent fluxes obtained from the first calculation formula and the second calculation formula to obtain a product; and correct the intensity and speed of linear convection according to the positional relationship between the negative value area and the strong echo area of the product in the sensitive layer.

[0076] The device embodiments described above are merely illustrative. 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 to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this example. Those of ordinary skill in the art can understand and implement it without creative labor.

[0077] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course also by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the prior art can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0078] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for correcting the prediction of linear convection based on horizontal sub-grid fluxes, characterized in that, Including: Obtaining forecast data of a numerical weather prediction model; Judging the area where linear convection occurs in the numerical model forecast according to the forecast data; In the area where linear convection occurs, calculating the horizontal sub-grid turbulent fluxes respectively according to the first calculation formula and the second calculation formula; wherein, the first calculation formula is: ； Among them, represents the sub-grid turbulent flux in the direction. Taking 1 represents the east-west direction, and taking 2 represents the north-south direction; represents the potential temperature; is the distance in the direction coordinate; is the partial differential operator; is the turbulent diffusion coefficient, and the calculation formula is: ； wherein, is a fixed parameter set to 0.25; is the horizontal grid resolution; is the deformation rate tensor, and the calculation formula is , is the counting symbol equivalent to , and are both selected from 1 and 2; The second calculation formula is: ； In the formula, represents the wind speed in the direction; and are respectively when taking 1 and 2 ; is the scale adaptation coefficient, obtained from Multiplying the horizontal sub-grid turbulent fluxes obtained from the first calculation formula and the second calculation formula to obtain a product; and correcting the intensity and speed of the linear convection according to the positional relationship between the negative value area and the strong echo area of the product in the sensitive layer.

2. The method for correcting linear convection prediction based on horizontal sub-grid fluxes according to claim 1, wherein, The obtained forecast data of the numerical weather prediction model is the original meteorological forecast data or a secondary meteorological forecast product made according to the original meteorological forecast data.

3. The method for correcting linear convection prediction based on horizontal sub-grid flux according to claim 2, wherein, The forecast data at least includes horizontal wind field data, vertical velocity data, potential temperature or temperature field data, and data on the distribution of radar reflectivity factors.

4. The method for correcting linear convection prediction based on horizontal sub-grid fluxes according to claim 3, characterized in that Judging the area where linear convection occurs in the numerical model forecast according to the vertical velocity data and the distribution of radar reflectivity factors; Calculating the horizontal sub-grid turbulent fluxes according to the horizontal wind field data and the potential temperature or temperature field data.

5. The method for correcting linear convection prediction based on horizontal sub-grid fluxes according to claim 1, characterized in that, The sensitive layer is the layer at a height of 2000 meters from the ground.

6. The method for correcting the linear convection prediction based on the horizontal sub-grid flux according to claim 1, wherein Correcting the intensity of the linear convection according to the positional relationship between the negative value area and the strong echo area of the product in the sensitive layer, specifically: When the negative value area is inside the strong echo area, the intensity forecast of the linear convection is enhanced; otherwise, the intensity forecast of the linear convection is weakened.

7. The method for correcting linear convection prediction based on horizontal sub-grid fluxes according to claim 1, wherein Correcting the speed of the linear convection according to the positional relationship between the negative value area and the strong echo area of the product in the sensitive layer, specifically: When the negative value area is in front of the center of the strong echo area, that is, on the moving direction side, the moving speed forecast of the linear convection is enhanced; otherwise, the moving speed forecast of the linear convection is weakened.

8. A non-transitory computer-readable storage medium, characterized in that, Stored thereon are computer instructions, and the computer instructions cause a computer to execute the method for correcting the linear convection forecast based on the horizontal sub-grid flux according to any one of claims 1-7.

9. An electronic device, characterized in that, Including: A processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete mutual communication through the communication bus, and the processor calls the logic instructions in the memory to execute the method for correcting the linear convection forecast based on the horizontal sub-grid flux according to any one of claims 1-7.

10. A computer program product, characterized in that, The computer program product includes a computer program, the computer program is stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer executes the method for correcting the linear convection forecast based on the horizontal sub-grid flux according to any one of claims 1-7.

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