Data processing method and system for weather management engineering

Abstract

The invention discloses a data processing method and system for weather management engineering, and the method comprises the steps: carrying out the standardized processing of weather forecast data, and building a weather forecast data reference line; determining an influence domain, wherein the influence domain comprises a space range and a time range; the form of an objective function and the weather element input type of the influence domain are determined, the objective function is # imgabs0 #, and T is larger than 0; and setting a basic equation, and obtaining an analytical solution # imgabs2 # by using the time of # imgabs1 # to carry out efficiency evaluation and economic evaluation. According to the method, the technical problem of insufficient weather forecast accuracy can be solved to a certain extent, the use value of weather forecast data is improved, and the method has the advantages of universality, portability and convenience in practical application.

Description

[0001] This application is a divisional application of patent number "2024105312925", application date "2024-04-29", and name "A weather management engineering method, system, equipment and storage medium". Technical Field

[0002] The present invention relates to the technical field of weather forecast numerical processing, and more specifically, to a data processing method and system for weather management engineering. Background Art

[0003] Numerical weather model is the mainstream technical solution for current weather forecasting. The overall technical level of numerical weather model determines the spatial resolution, accuracy and timeliness of weather forecast results. The technical route of numerical weather model 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 satellites, occultation, radar, sounding balloons, drones, ground stations, etc. The monitoring accuracy, monitoring location layout and networking, as well as data aggregation and processing of these technical methods will affect the data assimilation and numerical model calculation results, that is, the weather forecast results. Due to the long technical route and many technical links of numerical weather model, the improvement of weather forecast accuracy needs to rely on the coordinated progress of the whole technical route. In reality, the degree of physical and economic impact of weather on different scenarios, different industries, different spaces and different times is significantly different. Different scenarios and different industries have different resilience to weather changes, which determines that when responding to weather changes, they have different requirements for the accuracy of weather forecasts.

[0004] The existing technology has the following defects: significant technical improvements in a single link in the technical route of numerical weather models are unlikely to have a significant impact on the accuracy of weather forecast results. Moreover, improving the accuracy of weather forecast results requires a relatively high economic investment, which determines that the accuracy of weather forecast information that can be used has both technical and economic limitations. Summary of the invention

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

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

[0007] Standardize weather forecast data and establish a weather forecast data baseline;

[0008] Determine an impact domain, wherein the impact domain includes a spatial range and a temporal range;

[0009] Determine the objective function form and the weather element input type of the impact domain, the objective function is And Tv0;

[0010] Set the basic equation, which is:

[0011]

[0012]

[0013] use The analytical solution is obtained

[0014] Conduct performance evaluation and economic evaluation.

[0015] In one embodiment, 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, temperature, rainfall, solar radiation, and lightning; x, y, and z are latitude and longitude and altitude, respectively; and t is time.

[0016] In one embodiment, the impact domain adopts It indicates that, It can be a continuous interval or a non-continuous interval.

[0017] In one embodiment, the objective function is obtained through regression analysis, correlation analysis, and artificial intelligence algorithm, and is optimized through continuous iteration.

[0018] In one embodiment, the use , analytical solution include:

[0019] Establish and The transformation relationship is denoted as

[0020] according to right Perform transformations in sequence to obtain analytical solutions at different times

[0021] Substitute the analytical solutions into the objective function T in turn to obtain the predicted values ​​of the objective function T at different subsequent times.

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

[0023] When it appears or In this case, the timeliness of the data processing method of weather management engineering is determined to be 0-n times. The forecast accuracy greater than n times will no longer meet the needs or the analysis of the data processing method of weather management engineering will no longer be valid.

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

[0025] Calculate the cost of investment;

[0026] The cost of the investment includes the cost of obtaining weather forecast data, relevant data collection, computing program development, management system development, and labor costs;

[0027] Calculate economic benefits using forecast accuracy assessment data;

[0028] Conduct a cost-benefit analysis to decide whether to use the data processing methods of weather management engineering to implement weather management on the management object.

[0029] The present invention also provides a data processing system for weather management engineering, the system comprising:

[0030] The baseline module is used to standardize the weather forecast data and establish a weather forecast data baseline;

[0031] An impact domain module, used to determine an impact domain, wherein the impact domain includes a spatial range and a temporal range;

[0032] The objective function module is used to determine the objective function form and the weather element input type of the impact domain, wherein the objective function is And T>0;

[0033] The basic equation module is used to set the basic equation, which is:

[0034]

[0035]

[0036]

[0037] Analysis module for exploiting The analytical solution is obtained

[0038] Evaluation module, used for performance evaluation and economic evaluation.

[0039] The present invention further provides an electronic device, comprising:

[0040] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the data processing method of weather management engineering.

[0041] The present invention also provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, and the computer program is used to implement the data processing method of weather management engineering when executed by a processor.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] The data processing method of weather management engineering includes standardizing weather forecast data and establishing a weather forecast data baseline; determining the impact domain, which includes spatial range and time range; determining the objective function form and the weather element input type of the impact domain, where the objective function is And T>0; set the basic equation, the basic equation is use , analytical solution Through the above method, the technical problem of insufficient accuracy of weather forecast is solved to a certain extent, and the use value of weather forecast data is improved. In addition, the present invention has universality and portability, and is convenient for practical application. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The specific embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings, wherein:

[0045] Figure 1 is a flow chart of a data processing method for weather management engineering according to an embodiment of the present invention;

[0046] Figure 2 is a schematic diagram of the structure of a data processing system for weather management engineering according to an embodiment of the present invention;

[0047] Figure 3 It is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In reality, the degree of physical and economic impact of weather on different scenarios, industries, spaces, and times varies significantly. Different scenarios and industries have different resilience to weather changes, which determines that they have different requirements for the accuracy of weather forecasts when responding to weather changes. How to achieve efficient weather change response results based on the actual needs of different scenarios and industries and the technical level of available weather forecast data is a very important technical issue, and the technical method to solve this technical problem can be defined as a data processing method for weather management engineering.

[0049] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

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

[0051] like Figure 1 As shown, the present invention provides a data processing method for weather management engineering, comprising:

[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, expressed as Where i is the category of weather elements, including wind speed, wind direction, atmospheric pressure, temperature, rainfall, solar radiation, lightning, etc., x, y, z are latitude and longitude and altitude respectively, and t is time. When t is equal to the current time, the weather information is real-time information, and 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 they can be processed by various algorithms based on actual monitoring. In general, real-time weather information and historical weather information processed based on actual monitoring data can be understood as the information closest to the actual weather conditions known at the technical level. In particular, in the weather forecast data baseline, there are some arrays that are composed of weather information actually monitored. These weather information can be considered as real weather information under the condition of ignoring equipment monitoring errors.

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

[0055] Specifically, the impact domain adopts express, are respectively the longitude, latitude, altitude and time in the affected area. is a continuous interval or a discontinuous interval. Their general expressions are as follows:

[0056] The purpose of determining the impact domain is to filter the data that needs to be used from the weather forecast data baseline in preparation for the next step.

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

[0058] Specifically, in the objective function, i is the type of weather factor that affects the objective function, c is the matrix of all control variables of the objective function except weather factors, and k represents the control variable. 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 historical weather data and historical data of control variables, using tools such as regression analysis, correlation analysis, and artificial intelligence algorithms, and can be optimized through continuous iteration. It should be noted that the objective function is the core of the data processing method of weather management engineering. It may be the power generation of a wind turbine, the water level of a reservoir, or the safety threshold of a drone flight environment, as well as the management objectives of various activities related to weather changes, such as transportation cost function, logistics cost function, warehousing cost function, passenger flow of tourist attractions, and takeaway order volume.

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

[0060]

[0061]

[0062] Specifically, in the basic equation, ψ is the function to be minimized, st is the meaning of constraint condition, which is the abbreviation of the English word (subject to), M is the constraint condition for real-time weather monitoring, and δ is the required accuracy constraint condition. is the forecast data in the impact domain from the numerical weather model, The analytical data for weather management that needs to be solved is called analytical solution. is the actual observation data of weather elements affecting m observation stations in the domain, is a spatial operator function, which is used to convert The element closest to the observation site is converted into the element at the same position as the observation site. δ is the accuracy of the objective function, where T is the measured value of the objective function. is the predicted value calculated using the analytical solution, ε is the required accuracy, is the inverse matrix of the background error covariance matrix used by the numerical weather model from which the weather forecast data baseline is derived. All are in vector form.

[0063] More specifically, the solution of the basic equations of weather management engineering needs to meet two conditions: first, to obtain the real-time weather monitoring data within the influence domain, that is, Here is the current time or historical time, that is 0:00 represents the current time; second, obtain the weather forecast data for the corresponding time in the affected domain and The constraints The meaning of is that the total amount of the analytical solution is conserved, that is, the obtained analytical solution must satisfy the condition that the total amount is equal to the total amount of the observed value. At the same time, the analytical solution also needs to meet the required accuracy requirements, that is, Under the above two constraints, the analytical solution is obtained based on the minimum distance deviation from the original weather forecast data.

[0064] Step 105: Exploitation The analytical solution is obtained

[0065] Specifically, correlation analysis, regression analysis, artificial intelligence algorithms, etc. are used to establish and The transformation relationship is expressed as function Then according to the function right Perform transformations in sequence to obtain analytical solutions at different times Then, the analytical solution is substituted into the objective function T in turn to obtain the predicted values ​​of the objective function T at different subsequent times, which are recorded as

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

[0067] Specifically, historical data is used to evaluate the performance and economics of the data processing methods of weather management engineering, determine their economic effectiveness and continuously iterate and upgrade. Through historical data, the timeliness of the accuracy of the forecast results of the objective function calculated by the analysis solution can be evaluated using the method in Table 1. For example, using the grid data of historical rainfall forecasts, the reservoir water level is analyzed to determine the accuracy of the forecast results of the weather management engineering objective function required for reservoir water level management, and how long it is valid. The meaning is that the weather forecast data is directly Substitute the objective function T to get the predicted value, It is the forecast value obtained by using the analytical solution of the weather management engineering equation. and They represent the direct prediction accuracy of the objective function and the prediction accuracy after analysis respectively.

[0068]

[0069] Table 1 Timeliness of the forecast results using the analytical solution as the objective function

[0070] The basis for judging the effectiveness evaluation is that or When it occurs, the timeliness of the data processing method of weather management engineering is determined to be 0-n times. The forecast accuracy greater than n times will no longer meet the needs or the analysis of the data processing method of weather management engineering will no longer be valid.

[0071] By using performance evaluation, we can determine how long the time-efficiency accuracy of the objective function value obtained by reanalyzing the weather forecast data using the data processing method of weather management engineering is. In practical applications, we can select management effectiveness and continuously optimize and upgrade methods based on the actual accuracy requirements of the management objectives. At the same time, similar methods can be used for economic evaluation. First, calculate the cost of using the data processing method of weather management engineering, including the cost of obtaining weather forecast data, relevant data collection, calculation program development, management system development, and labor costs. Secondly, use the forecast accuracy evaluation data in Table 1 to calculate the economic benefits. Finally, do a cost-benefit analysis to decide whether to use the data processing method of weather management engineering to implement weather management on the management object.

[0072] Therefore, the present invention can, without changing the existing weather forecasting technology level and forecasting accuracy, model the management target for the management object, set the required accuracy of the management target, and then use the thinking of system engineering and control theory to meet the required accuracy of weather management by mathematical optimization. To a certain extent, it solves the technical problem of insufficient weather forecast accuracy and improves the use value of weather forecast data. The present invention is universal and portable. For different scenarios and different management objects, only a few elements such as the objective function and the influence domain need to be adjusted to achieve scenario conversion, and then the historical data can be used for continuous optimization and iteration to carry out engineering practice, which is convenient for practical application.

[0073] like Figure 2 As shown, the present invention also provides a data processing system for weather management engineering, the data processing system for weather management engineering comprising:

[0074] The baseline module 201 is used to perform standardization processing on the weather forecast data and establish a weather forecast data baseline.

[0075] The impact domain module 202 is used to determine the impact domain, where the impact domain includes a spatial range and a temporal range.

[0076] The objective function module 203 is used to determine the objective function form and the weather element input type of the impact domain, wherein the objective function is And T>0.

[0077] The basic equation module 204 is used to set the basic equation, which is:

[0078]

[0079]

[0080]

[0081] Analysis module 205, used to utilize The analytical solution is obtained

[0082] Evaluation module 206 is used to perform performance evaluation and economic evaluation.

[0083] Figure 3A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment 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 processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

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

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

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

[0087] In some embodiments, an information push method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform an information push method in any other appropriate manner (e.g., by means of firmware).

[0088] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0089] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0090] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0091] To provide interaction with a user, the systems and techniques described herein may 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 trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0092] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may 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] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0094] An embodiment of the present invention further provides a computer program product, which includes a computer program, and the computer program is implemented when executed by a processor.

[0095] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0096] 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 present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0097] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A data processing method for weather management engineering, characterized in that: include: Standardize weather forecast data and establish a weather forecast data baseline; 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, temperature, rainfall, solar radiation, lightning, x, y, z are latitude and longitude and altitude 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; Determine an impact domain, wherein the impact domain includes a spatial range and a temporal range; Determine the objective function form and the weather element input type of the impact domain, the objective function is And T>0; Set the basic equation, which is: In the basic equation, ψ is the function to be minimized, st is the constraint, M is the constraint for real-time weather monitoring, δ is the required accuracy constraint; δ is the accuracy of the objective function, where T is the measured value of the objective function, is the predicted value calculated using the analytical solution, ε is the required accuracy, The inverse matrix of the background error covariance matrix used by the numerical weather model that is the source of the weather forecast data baseline; All are in vector form; use , analytical solution Conduct performance evaluation and economic evaluation; Among them, the use , analytical solution include: Establish and The transformation relationship is denoted as according to right Perform transformations in sequence to obtain analytical solutions at different times Substitute the analytical solution into the objective function T in turn to obtain the predicted value of the objective function T at different subsequent times; The effectiveness evaluation includes: or In the case of a situation where the timeliness of the data processing method of weather management engineering is determined to be 0-n times, the forecast 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 valid; The economic evaluation includes: Calculate the cost of investment; The cost of the investment includes the cost of obtaining weather forecast data, relevant data collection, computing program development, management system development, and labor costs; Calculate economic benefits using forecast accuracy assessment data; Conduct a cost-benefit analysis to decide whether to use the data processing methods of weather management engineering to implement weather management on the management object.

2. The data processing method for weather management engineering according to claim 1, characterized in that: The impact domain adopts It indicates that, It can be a continuous interval or a non-continuous interval.

3. The data processing method for weather management engineering according to claim 2, characterized in that: The objective function is obtained through regression analysis, correlation analysis, and artificial intelligence algorithm, and is optimized through continuous iteration.

4. A data processing system for weather management engineering, characterized in that: The system comprises: The baseline module is used to standardize the weather forecast data and establish a weather forecast data baseline; 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, temperature, rainfall, solar radiation, lightning, x, y, z are latitude and longitude and altitude 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; An impact domain module, used to determine an impact domain, wherein the impact domain includes a spatial range and a temporal range; The objective function module is used to determine the objective function form and the weather element input type of the impact domain, wherein the objective function is And T>0; The basic equation module is used to set the basic equation, which is: In the basic equation, ψ is the function to be minimized, st is the constraint, M is the constraint for real-time weather monitoring, δ is the required accuracy constraint; δ is the accuracy of the objective function, where T is the measured value of the objective function, is the predicted value calculated using the analytical solution, ε is the required accuracy, The inverse matrix of the background error covariance matrix used by the numerical weather model that is the source of the weather forecast data baseline; All are in vector form; Analysis module for exploiting The analytical solution is obtained Evaluation module, used for performance evaluation and economic evaluation; Among them, the use , analytical solution include: Establish and The transformation relationship is denoted as according to right Perform transformations in sequence to obtain analytical solutions at different times Substitute the analytical solution into the objective function T in turn to obtain the predicted value of the objective function T at different subsequent times; The effectiveness evaluation includes: or In the case of a situation where the timeliness of the data processing method of weather management engineering is determined to be 0-n times, the forecast 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 valid; The economic evaluation includes: Calculate the cost of investment; The cost of the investment includes the cost of obtaining weather forecast data, relevant data collection, computing program development, management system development, and labor costs; Calculate economic benefits using forecast accuracy assessment data; Conduct a cost-benefit analysis to decide whether to use the data processing methods of weather management engineering to implement weather management on the management object.

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