A data processing method and system for weather management engineering

Abstract

The application discloses a data processing method and system for weather management engineering, and relates to the technical field of weather management engineering. The data processing method comprises the following steps: standardizing weather forecast data and establishing a weather forecast data baseline; determining an influence domain, which comprises a spatial range and a time range; determining a target function form and a weather element input type of the influence domain, wherein the target function is f(x) = T and T>0; setting a basic equation, using a time sequence to obtain an analysis solution for performance evaluation and economic evaluation. The application can solve the technical problem of insufficient weather forecast accuracy to a certain extent, improve the use value of weather forecast data, and has the advantages of universality, portability and convenience for practical application.

Description

[0001] This application is a divisional application of patent number "2024105312925", application date "2024-04-29", and name "Weather management engineering method, system, device and storage medium". TECHNICAL FIELD

[0002] The present application relates to the technical field of numerical processing of weather forecasting, more specifically, it relates to a data processing method and system of weather management engineering. BACKGROUND

[0003] Numerical weather prediction is the mainstream technical solution of current weather forecasting, and the overall technical level of numerical weather prediction determines the spatial resolution, accuracy and prediction timeliness of weather forecasting results. The technical route of numerical weather prediction includes three main technical links: atmospheric real-time monitoring, data assimilation and numerical model calculation. Atmospheric real-time monitoring includes several technical methods, such as meteorological satellite, occultation, radar, sounding balloon, unmanned aerial vehicle, ground station, etc. The monitoring accuracy, monitoring location layout and networking, and data collection and processing of these technical methods will affect the results of data assimilation and numerical model calculation, that is, the results of weather forecasting. Due to the long technical route and multiple technical links of numerical weather prediction, the improvement of weather forecasting accuracy needs to rely on the coordinated progress of the whole technical route. In reality, the physical impact and economic impact of weather on different scenarios, different industries, different spaces and different times are significantly different, and the resilience of different scenarios and different industries to weather changes is also different, which determines that their demand for weather forecasting accuracy is also different when responding to weather changes.

[0004] In the prior art, there are the following defects: significant technical improvement of a single link in the technical route of numerical weather prediction, which is difficult to significantly improve the accuracy of weather forecasting results. Moreover, the improvement of the accuracy of weather forecasting results also requires high economic investment, which determines that the accuracy of weather forecasting information that can be used is limited by both technology and economy. SUMMARY

[0005] In order to overcome the above technical defects, the present application provides a data processing method, system, device and storage medium of weather management engineering.

[0006] In order to solve the above problems, the present application is realized according to the following technical scheme: a data processing method of weather management engineering, comprising:

[0007] Standardizing weather forecasting data to establish a weather forecasting data baseline;

[0008] Determine the impact domain, the impact domain includes spatial range and time range;

[0009] determining a form of a target function and a weather element input type of the influence domain, the target function being and Tv0;

[0010] setting a basic equation, the basic equation being:

[0011]

[0012]

[0013] using a time, to obtain an analysis solution

[0014] performing performance evaluation and economic evaluation.

[0015] In one embodiment, the basic form of the weather forecast data baseline is a two-dimensional array, expressed as where i is the category of the weather element, including wind speed, wind direction, atmospheric pressure, air temperature, rainfall, solar radiation, lightning, x, y, z are longitude, latitude and height respectively, and t is time.

[0016] In one embodiment, the influence domain is represented by , where is a continuous interval, or a non-continuous interval.

[0017] In one embodiment, the target function is obtained by regression analysis, correlation analysis, artificial intelligence algorithm, and is continuously iterated and optimized.

[0018] In one embodiment, the analysis solution is obtained by using a time, to obtain an analysis solution including:

[0019] establishing a transformation relationship between and , denoted as

[0020] According to , sequentially transform to obtain analysis solutions at subsequent times

[0021] Substitute the analysis solutions into the target function T in turn to obtain the predicted values of the target function T at subsequent times.

[0022] In one embodiment, the performance evaluation includes:

[0023] When or When the weather management engineering data processing method is applied to the situation of the weather management engineering data processing method, the timeliness of the weather management engineering data processing method is determined as 0-n times, and the prediction accuracy greater than n times will no longer meet the demand or the weather management engineering data processing method analysis is no longer effective.

[0024] In one embodiment, the economic evaluation includes:

[0025] The input cost is calculated;

[0026] The input cost includes weather forecast data acquisition cost, related data collection, calculation program development, management system development, labor cost;

[0027] The economic benefit is calculated by using the prediction accuracy evaluation data;

[0028] The cost-benefit analysis is performed to determine whether to use the weather management engineering data processing method to implement weather management on the management object.

[0029] The application also provides a weather management engineering data processing system, which comprises:

[0030] A baseline module is configured to standardize weather forecast data and establish a weather forecast data baseline;

[0031] An influence domain module is configured to determine an influence domain, which includes a spatial range and a time range;

[0032] A target function module is configured to determine a target function form and a weather element input type of the influence domain, wherein the target function is And T>0;

[0033] A basic equation module is configured to set a basic equation, which is:

[0034]

[0035]

[0036]

[0037] An analysis module is configured to use Times to obtain an analysis solution

[0038] An evaluation module is configured to perform performance evaluation and economic evaluation.

[0039] The application also provides an electronic device, which comprises:

[0040] At least one processor;And a memory connected with the at least one processor in communication;Wherein the memory stores the computer program that can be executed by the at least one processor, the computer program is executed by the at least one processor, to enable the at least one processor to execute the data processing method of weather management engineering.

[0041] The application further provides a computer readable storage medium, characterized by storing a computer program, the computer program is used to make the processor execute to realize the data processing method of weather management engineering.

[0042] Compared with the prior art, the beneficial effects of the application are:

[0043] The data processing method of weather management engineering comprises standardizing weather forecast data and establishing a weather forecast data baseline;Determine the influence domain, the influence domain includes spatial range and time range;Determine the target function form and the weather element input type of the influence domain, wherein the target function is And T>0;Set the basic equation, the basic equation is Using Time, the analytical solution is obtained Performance evaluation and economic evaluation are carried out.The above method solves the technical problem of insufficient weather forecast accuracy to a certain extent, improves the use value of weather forecast data, and has universality and portability, which is convenient for practical application. BRIEF DESCRIPTION OF DRAWINGS

[0044] The specific embodiments of the application will be further described in detail below with reference to the accompanying drawings, in which:

[0045] Figure 1 It is the flow chart of the data processing method of weather management engineering of the embodiment of the application;

[0046] Figure 2 It is the structural schematic diagram of the data processing system of weather management engineering of the embodiment of the application;

[0047] Figure 3 It is the structural schematic diagram of the electronic equipment of the embodiment of the application. DETAILED DESCRIPTION

[0048] In reality, the degree of physical and economic impact of weather on different scenarios, different industries, different spaces, and different times varies significantly. Different scenarios and different industries have different resilience to weather changes, which determines their different needs for weather forecast accuracy when responding to weather changes. How to meet the actual needs of different scenarios and different industries in responding to weather changes and ultimately obtain efficient weather change response results under the existing available weather forecast data technology level is a very important technical problem. The technical method for solving this technical problem can be defined as a data processing method of weather management engineering.

[0049] In order to enable personnel in the technical field to better understand the present application scheme, the technical solutions in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the present application.

[0050] The preferred embodiments of the present application will be described below in combination with the drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application.

[0051] As shown in the drawings, the present application provides a data processing method of weather management engineering, comprising: Figure 1

[0052] Step 101: Standardize the weather forecast data and establish a weather forecast data baseline.

[0053] Specifically, the basic form of the weather forecast data baseline is a two-dimensional array, and the expression is where i is the category of weather elements, including wind speed, wind direction, atmospheric pressure, air temperature, rainfall, solar radiation, lightning, etc., x, y, and z are longitude, latitude, and height, respectively, and t is time. When t is equal to the current time, the weather information is real-time information, when t is greater than the current time, the weather information is forecast information. When t is less than the current time, the weather information is historical information. Real-time weather information and historical weather information can be stored forecast information, or real-time weather information and historical weather information processed according to actual monitoring using various algorithms. Generally, real-time weather information and historical weather information processed according to actual monitoring can be understood as information closest to the actual weather situation known at the technical level. In particular, in the weather forecast data baseline, there are some arrays composed of actual monitored weather information. These weather information can be considered as real weather information under the condition of ignoring equipment monitoring error. ​

[0054] Step 102: Determine the impact domain, which includes spatial range and time range.

[0055] Specifically, the impact domain adopts to represent respectively, longitude, latitude, height, time within the impact domain. Among them, are continuous intervals, or non-continuous intervals. Their general expressions are as follows:

[0056] The purpose of determining the impact domain is to filter the data needed to be used from the weather forecast data baseline, and to prepare for the next step.

[0057] Step 103: Determine the form of the objective function and the input type of the weather elements in the impact domain, wherein the objective function is and T>0.

[0058] Specifically, in the objective function, i is the type of weather elements that affect the objective function, c is the matrix of all control variables of the objective function except weather elements, k represents control variables, for example, if there are n control variables, then k=1, 2, 3…n. The specific form of the objective function T can be obtained by using weather history data and control variable history data, using regression analysis, correlation analysis, artificial intelligence algorithm and other tools, and can be optimized by continuous iteration. It should be noted that the objective function is the core of the data processing method of weather management engineering, which can be the power generation of wind turbines, the water level of reservoirs, or the safety threshold of unmanned aerial vehicle flight environment, as well as transportation cost function, logistics cost function, warehousing cost function, tourist attraction passenger flow, take-out order quantity and other various activities related to weather changes.

[0059] Step 104: Set the basic equation, which is

[0060]

[0061]

[0062] Specifically, in the basic equation, ψ is the function to be minimized, s.t is the meaning of constraint condition, which is the abbreviation of English (subject to), M is the constraint condition of weather real-time monitoring, and δ is the demand accuracy constraint condition. is the forecast data within the impact domain derived from the numerical weather model, is the analysis data for weather management that needs to be solved, i.e. analysis solution. is the actual observation data of weather elements of m observation sites within the impact domain, For the spatial operator function, the function is to convert the element closest to the observation site position into the element with the same position as the observation site. The accuracy of the objective function is δ, where T is the measured value of the objective function, the predicted value calculated by the analysis solution, and ε is the required accuracy, the inverse matrix of the background error covariance matrix used by the numerical weather prediction data baseline source. Here, Both are in vector form.

[0063] More specifically, the solution of the basic equation of weather management engineering needs to meet two conditions: one is to obtain the weather monitoring data in the influence domain, that is, Here, is the current time or historical time, that is, 0 represents the current time; the second is to obtain the weather forecast data in the influence domain at the corresponding time and where the constraint condition means that the total amount of the analysis solution must satisfy the condition that the total amount of the obtained analysis solution is equal to the total amount of the observation value. At the same time, the analysis solution also needs to meet the requirement of the required accuracy, that is, Under the above two constraint conditions, the analysis solution is solved based on the minimum distance deviation from the original weather forecast data.

[0064] Step 105: using the time, the analysis solution

[0065] Specifically, the transformation relationship between and is established using correlation analysis, regression analysis, artificial intelligence algorithm, etc., and is denoted as the function Then, according to the function , the is sequentially transformed to obtain the analysis solution at the subsequent time Then the analysis solution is sequentially substituted into the objective function T to obtain the predicted value of the objective function T at the subsequent time, denoted as

[0066] Step 106: performance evaluation and economic evaluation.

[0067] Specifically, the data processing method of weather management engineering is evaluated in performance and economy by using historical data to determine its economic effectiveness and continuously iterate and upgrade. Through historical data, the time effectiveness of the accuracy of the forecast results of the objective function can be evaluated and analyzed by the method in Table 1. For example, using historical rainfall forecast grid data, the accuracy of the forecast results of the objective function of the reservoir water level management is determined, and the time effectiveness is determined. Among them The meaning is that the weather forecast data is directly substituted into the objective function T to obtain the predicted value, is the predicted value obtained by using the analytical solution of the weather management engineering equation. and respectively represent the direct prediction accuracy and the prediction accuracy after analysis of the objective function.

[0068]

[0069] Table 1 Time effectiveness of the forecast results of the objective function using the analytical solution

[0070] The judgment basis for performance evaluation is that when or occurs, it is determined that the time effectiveness of the data processing method of weather management engineering is 0-n times, and the prediction accuracy greater than n times will no longer meet the demand or the analysis of the data processing method of weather management engineering will no longer be effective.

[0071] By using performance evaluation, it can be determined that the value of the objective function obtained by reanalyzing the weather forecast data using the data processing method of weather management engineering has a time effectiveness accuracy for how long. In actual application, the management effectiveness can be selected according to the actual accuracy demand of the management target and the method is continuously optimized and upgraded. At the same time, similar methods can be used for economic evaluation. First, the cost of using the data processing method of weather management engineering is calculated, including the cost of obtaining weather forecast data, collecting related data, developing calculation programs, developing management systems, and labor costs. Second, the economic benefits are calculated by using the prediction accuracy evaluation data in Table 1. Finally, the cost-benefit analysis is done to determine whether to use the data processing method of weather management engineering to implement weather management on the management object.

[0072] Therefore, the application can solve the technical problem of insufficient weather forecast accuracy to a certain extent without changing the existing weather forecast technical level and forecast accuracy, by modeling the management target of the management object, setting the demand accuracy of the management target, and using the thinking of system engineering and control theory to meet the demand accuracy of the management target for weather management through mathematical optimization, thereby improving the use value of weather forecast data. The application has universality and portability. For different scenes and different management objects, only a few elements such as the objective function and the influence domain need to be adjusted to realize scene conversion, and then the historical data is continuously optimized and iterated for engineering practice, which is convenient for practical application.

[0073] As shown in Figure 2 The application also provides a data processing system for weather management engineering, which comprises:

[0074] A baseline module 201 is configured to standardize weather forecast data and establish a weather forecast data baseline.

[0075] An influence domain module 202 is configured to determine an influence domain, which comprises a spatial range and a time range.

[0076] An objective function module 203 is configured to determine the form of an objective function and the input type of weather elements in the influence domain, wherein the objective function is and T>0.

[0077] A basic equation module 204 is configured to set a basic equation, which is

[0078]

[0079]

[0080]

[0081] An analysis module 205 is configured to obtain an analysis solution by using time, and the analysis solution is

[0082] An evaluation module 206 is configured to perform performance evaluation and economic evaluation.

[0083] Figure 3A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0084] like Figure 3 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0085] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0086] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above.

[0087] In some embodiments, an information push method can be implemented as a computer program tangibly embodied in a computer readable storage medium, e.g., storage unit 18. In some embodiments, parts or all of the computer program can be loaded and / or installed onto electronic device 10 via, e.g., ROM 12 and / or communication unit 19. When the computer program is loaded onto RAM 13 and executed by processor 11, one or more steps of the above-described method can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform an information push method by other means, e.g., with the aid of firmware.

[0088] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, specially designed application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0089] Computer programs implementing methods of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program, when executed, implements the functions / acts specified in the flowcharts and / or block diagrams. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as part of a standalone software package, or entirely on a remote machine or server.

[0090] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0091] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0092] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0093] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. Servers can be cloud servers, also known as cloud computing servers or cloud hosts, which are a host product in the cloud computing service system to solve the defects of great management difficulty and weak business scalability in traditional physical hosts and VPS services.

[0094] The embodiment of the present application also provides a computer program product, which comprises a computer program, and the computer program realizes the method when being executed by a processor.

[0095] The computer program product in the implementation process can be written in one or more programming languages or combinations thereof to execute the computer program code for performing the operation of the present application, and the programming language includes object-oriented programming language such as Java, Smalltalk, C++, and also includes conventional procedural programming language such as 'C' language or similar programming language. The program code can be executed completely on the user computer, partially on the user computer, as an independent software package, partially on the user computer and partially on a remote computer, or completely on a remote computer or server. In the case involving a remote computer, the remote computer can be connected to the user computer through any kind of network including local area network (LAN) or wide area network (WAN), or can be connected to an external computer (for example, connected through the Internet by using an Internet service provider).

[0096] It should be understood that the steps shown in the above forms can be reordered, added or deleted. For example, the steps described in the present application can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions of the present application can be achieved, and the present application is not limited herein.

[0097] The above specific embodiments do not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent replacement and improvement within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A data processing method of weather management engineering, characterized by, The application relates to a weather management engineering system and method. The weather forecast data is standardized to establish a weather forecast data baseline; The basic form of the weather forecast data baseline is a two-dimensional array, and the expression is Wherein i is the category of the weather element, including wind speed, wind direction, atmospheric pressure, air temperature, rainfall, solar radiation, lightning, x, y, z are longitude, latitude and height respectively, and t is time; wherein, when t is equal to the current time, the weather information is real-time information; when t is greater than the current time, the weather information is forecast information; when t is less than the current time, the weather information is historical information; An influence domain is determined, which includes a spatial range and a time range; determining a form of an objective function and a weather element input type of the influence domain, the objective function being and T > 0; Setting up the basic equation, which is: In the basic equation, ψ is the function to be minimized, s.t is the constraint condition, M is the constraint condition of weather real-time monitoring, δ is the demand accuracy constraint condition; δ is the accuracy of the objective function, where T is the measured value of the objective function, is the forecast value calculated by the analysis solution, and ε is the demand accuracy, is the inverse matrix of the background error covariance matrix used by the numerical weather model which is the baseline source of weather forecast data; are all in vector form; Utilizing The time, the analysis solution is obtained Performance evaluation and economic evaluation are carried out; The method comprises the steps of: The time sequence is obtained by analysis The method comprises the steps of: establishing a transformation relationship with , denoted as According to The analysis solution of the subsequent time is obtained by sequentially transforming ​ Analysis solutions are substituted into a target function T in sequence to obtain predicted values of the target function T at subsequent different times; The performance evaluation includes: when the situation of or occurs, the timeliness of the data processing method of weather management engineering is determined as 0-n times, and the prediction accuracy greater than n times no longer meets the demand or the data processing method of weather management engineering analysis is no longer effective; The economic evaluation includes: Costs are calculated; The costs include weather forecast data acquisition costs, related data collection, calculation program development, management system development and labor costs; Economic benefits are calculated by using prediction accuracy evaluation data; Cost-benefit analysis is carried out to determine whether the weather management engineering data processing method is used to implement weather management on a management object.

2. The data processing method of weather management engineering according to claim 1, characterized in that, The influence domain adopts is represented by is a continuous interval, or a discontinuous interval.

3. The data processing method of weather management engineering according to claim 2, characterized in that, The target function is obtained by regression analysis, correlation analysis and artificial intelligence algorithms, and is continuously iterated and optimized.

4. A data processing system for weather management engineering, characterized by The system includes: The benchmark line module is used for standardizing weather forecast data and establishing a weather forecast data benchmark line; a basic form of the weather forecast data benchmark line is a two-dimensional array, and an expression is Wherein i is a category of weather elements, including wind speed, wind direction, atmospheric pressure, air temperature, rainfall, solar radiation, and lightning, x, y, and z are longitude, latitude, and height respectively, and t is time; wherein when t is equal to a current time, the weather information is real-time information; when t is greater than the current time, the weather information is forecast information; and when t is less than the current time, the weather information is historical information. An influence domain module for determining an influence domain, which includes a spatial range and a time range; a target function module, configured to determine a target function form and a weather element input type of the influence domain, wherein the target function is and T >

0. A basic equation module for setting a basic equation, which is: In the basic equation, ψ is the function to be minimized, s.t is the constraint condition, M is the constraint condition of weather real-time monitoring, δ is the demand accuracy constraint condition; δ is the accuracy of the objective function, where T is the measured value of the objective function, is the prediction value calculated by the analysis solution, and ε is the demand accuracy, is the inverse matrix of the background error covariance matrix used by the numerical weather model which is the baseline source of weather forecast data; are all in vector form; an analysis module for utilizing a time instance, resulting in an analytical solution An evaluation module for carrying out performance evaluation and economic evaluation; The method comprises the steps of: The time sequence is obtained by analysis The method comprises the steps of: establishing a transformation relationship with , denoted as According to The analysis solution of the subsequent time is obtained by sequentially transforming ​ Analysis solutions are substituted into a target function T in sequence to obtain predicted values of the target function T at subsequent different times; The performance evaluation includes: when the situation of or occurs, the timeliness of the data processing method of weather management engineering is determined as 0-n times, and the prediction accuracy greater than n times no longer meets the demand or the data processing method of weather management engineering analysis is no longer effective; The economic evaluation includes: Costs are calculated; The costs include weather forecast data acquisition costs, related data collection, calculation program development, management system development and labor costs; Economic benefits are calculated by using prediction accuracy evaluation data; Cost-benefit analysis is carried out to determine whether the weather management engineering data processing method is used to implement weather management on a management object.

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