A method and apparatus for temperature correction of ECMWF model

Abstract

The application provides a temperature correction method and device of ECMWF mode, and relates to the technical field of meteorological data processing, and comprises the following steps: obtaining temperature data of a to-be-corrected meteorological station from a reporting starting time to a current time; performing interpolation processing on low-time-resolution 2-meter predicted temperature data; using a preset hyperparameter set and high-time-resolution 2-meter measured temperature data, revising high-time-resolution 2-meter predicted temperature data to obtain corrected 2-meter predicted temperature data; repeating the above steps for a preset number of times to obtain corrected 2-meter predicted temperature data in a target time period; based on the corrected 2-meter predicted temperature data in the target time period and measured temperature data in the target time period, determining optimal preset hyperparameters of the to-be-corrected meteorological station; and using the optimal preset hyperparameters to correct subsequent high-time-resolution 2-meter predicted temperature data, thereby solving the technical problem of low accuracy of ECMWF mode temperature prediction data.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of meteorological data processing, and in particular to a temperature correction method and device of an ECMWF model. BACKGROUND

[0002] With the rapid development of science and technology, people's requirements for weather forecast are getting higher and higher, and high-precision high-temporal and spatial resolution forecasts are needed to meet the needs of production and life. The ECMWF model of Europe is a global leading numerical model, and most provincial and municipal meteorological stations refer to its forecast results. In order to provide more accurate and higher resolution forecast results and reduce the proportion of subjective forecast, many researchers try various methods to improve the forecast accuracy. It is crucial to improve the accuracy of the model itself, but it is also more difficult to improve the accuracy of the model itself due to the large amount of computing resources required by the model.

[0003] No effective solution has been proposed for the above problems. SUMMARY

[0004] Therefore, the purpose of the present application is to provide a temperature correction method and device of an ECMWF model to alleviate the technical problem of low accuracy of temperature forecast data of the ECMWF model.

[0005] In a first aspect, the present application provides a temperature correction method of an ECMWF model, comprising: a step of obtaining temperature data of a to-be-corrected weather station from a reporting time to a current time, wherein the temperature data includes low-temporal-resolution 2-meter forecast temperature data and high-temporal-resolution 2-meter measured temperature data; a first revision step of performing interpolation processing on the low-temporal-resolution 2-meter forecast temperature data to obtain high-temporal-resolution 2-meter forecast temperature data, and using a preset hyperparameter set and the high-temporal-resolution 2-meter measured temperature data to revise the high-temporal-resolution 2-meter forecast temperature data to obtain corrected 2-meter forecast temperature data; a step of repeatedly executing the obtaining step and the first revision step for a preset number of times to obtain corrected 2-meter forecast temperature data in a target time period; a step of determining an optimal preset hyperparameter corresponding to the to-be-corrected weather station based on the corrected 2-meter forecast temperature data in the target time period and high-temporal-resolution 2-meter measured temperature data in the target time period; and a second revision step of using the optimal preset hyperparameter to correct high-temporal-resolution 2-meter forecast temperature data of the to-be-corrected weather station after the target time period.

[0006] Further, the high-time-resolution 2-meter forecast temperature data is revised by using the preset hyperparameter set and the high-time-resolution 2-meter measured temperature data to obtain revised 2-meter forecast temperature data, including: determining the decreasing average error of the current time corresponding to each preset hyperparameter by using the preset hyperparameter set, the high-time-resolution 2-meter measured temperature data and the high-time-resolution 2-meter forecast temperature data; and respectively revising the high-time-resolution 2-meter forecast temperature data by using the decreasing average error of the current time corresponding to each preset hyperparameter to obtain the revised 2-meter forecast temperature data.

[0007] Further, the calculation formula of the decreasing average error of the current time is , wherein, is the decreasing average error of the current time, is the preset hyperparameter, is the decreasing average error of the previous day of the current time, is the high-time-resolution 2-meter forecast temperature data of the current time. Further, the optimal preset hyperparameter corresponding to the to-be-revised weather station is determined based on the revised 2-meter forecast temperature data in the target time period and the high-time-resolution 2-meter measured temperature data in the target time period, including: calculating the mean square error or the root mean square error corresponding to each preset hyperparameter based on the revised 2-meter forecast temperature data in the target time period and the high-time-resolution 2-meter measured temperature data in the target time period; and determining the preset hyperparameter corresponding to the most decreased mean square error or root mean square error in the target time period as the optimal preset hyperparameter.

[0008] Further, the optimal preset hyperparameter corresponding to the to-be-revised weather station is determined based on the revised 2-meter forecast temperature data in the target time period and the high-time-resolution 2-meter measured temperature data in the target time period, including: calculating the mean square error or the root mean square error corresponding to each preset hyperparameter based on the revised 2-meter forecast temperature data in the target time period and the high-time-resolution 2-meter measured temperature data in the target time period; and determining the preset hyperparameter corresponding to the most decreased mean square error or root mean square error in the target time period as the optimal preset hyperparameter.

[0009] ​​Secondly, embodiments of the present invention also provide a temperature correction device for the ECMWF model, comprising: an acquisition unit for acquiring temperature data from the weather station to be corrected from the start time to the current time, wherein the temperature data includes: low temporal resolution 2-meter forecast temperature data and high temporal resolution 2-meter measured temperature data; and a first revision unit for interpolating the low temporal resolution 2-meter forecast temperature data to obtain high temporal resolution 2-meter forecast temperature data, and revising the high temporal resolution 2-meter forecast temperature data using a preset hyperparameter set and the high temporal resolution 2-meter measured temperature data. The process involves: a revision unit to obtain corrected 2-meter forecast temperature data; an execution unit to repeatedly execute the acquisition unit and the first revision unit a preset number of times to obtain corrected 2-meter forecast temperature data within a target time period; a determination unit to determine the optimal preset hyperparameters corresponding to the weather station to be corrected based on the corrected 2-meter forecast temperature data within the target time period and the high temporal resolution 2-meter measured temperature data within the target time period; and a second revision unit to correct the high temporal resolution 2-meter forecast temperature data of the weather station to be corrected after the target time period using the optimal preset hyperparameters.

[0010] Further, the first revision unit is configured to: determine the decreasing average error of the current time corresponding to each preset hyperparameter using the preset hyperparameter set, the high temporal resolution 2-meter measured temperature data, and the high temporal resolution 2-meter predicted temperature data; and correct the high temporal resolution 2-meter predicted temperature data using the decreasing average error of the current time corresponding to each preset hyperparameter to obtain the corrected 2-meter predicted temperature data.

[0011] Furthermore, the formula for calculating the decreasing average error at the current moment is as follows: ,in, The current time Decreasing average error To preset hyperparameters, The current time The decreasing average error of the previous day, The current time High temporal resolution 2-meter forecast temperature data from the previous day.

[0012] Furthermore, the determining unit is also used to: calculate the mean square error or root mean square error corresponding to each preset hyperparameter based on the corrected 2-meter forecast temperature data within the target time period and the high temporal resolution 2-meter measured temperature data within the target time period; and determine the preset hyperparameter corresponding to the one whose mean square error or root mean square error decreases the most within the target time period as the optimal preset hyperparameter.

[0013] In a third aspect, an electronic device is provided, which includes a memory configured to store a program supporting a processor to execute the method of the first aspect, and the processor configured to execute the program stored in the memory.

[0014] In a fourth aspect, a computer readable storage medium is provided, which stores a computer program.

[0015] In the embodiment of the present application, by the obtaining step, the temperature data of the to-be-corrected meteorological station from the reporting time to the current time is obtained, wherein the temperature data includes low-time-resolution 2-meter forecast temperature data and high-time-resolution 2-meter measured temperature data; the first revising step is to interpolate the low-time-resolution 2-meter forecast temperature data to obtain high-time-resolution 2-meter forecast temperature data, and revise the high-time-resolution 2-meter forecast temperature data by using a preset hyperparameter set and the high-time-resolution 2-meter measured temperature data to obtain corrected 2-meter forecast temperature data; the executing step is to repeatedly execute the obtaining step and the first revising step for a preset number of times to obtain corrected 2-meter forecast temperature data in a target time period; the determining step is to determine the optimal preset hyperparameter corresponding to the to-be-corrected meteorological station based on the corrected 2-meter forecast temperature data in the target time period and the high-time-resolution 2-meter measured temperature data in the target time period; and the second revising step is to revise the high-time-resolution 2-meter forecast temperature data of the to-be-corrected meteorological station after the target time period by using the optimal preset hyperparameter, so as to achieve the purpose of correcting the forecast temperature data of the ECMWF mode by using the adaptive Kalman filter, and further solve the technical problem of low accuracy of the temperature forecast data of the ECMWF mode, thereby achieving the technical effect of improving the accuracy of the temperature forecast data of the ECMWF mode.

[0016] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art upon examination of the following or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

[0017] In order to make the above objectives, characteristics and advantages of the present application more apparent, the following preferred embodiments are specifically described with reference to the attached drawings, and the detailed description is as follows. BRIEF DESCRIPTION OF DRAWINGS

[0018] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 A flowchart of a temperature correction method for ECMWF mode provided in an embodiment of the present invention;

[0020] Figure 2 A schematic diagram of a temperature correction device for ECMWF mode provided in an embodiment of the present invention;

[0021] Figure 3 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Example 1:

[0024] According to an embodiment of the present invention, an embodiment of a temperature correction method for ECMWF mode is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0025] Figure 1 This is a flowchart of a temperature correction method for ECMWF mode according to an embodiment of the present invention, as follows: Figure 1 As shown, the method includes the following steps:

[0026] Step S102: Obtain the temperature data of the weather station to be corrected from the start time to the current time. The temperature data includes: high time resolution 2-meter forecast temperature data, low time resolution 2-meter forecast temperature data and high time resolution 2-meter measured temperature data.

[0027] It should be noted that the period from the start time of the above report to the current time is generally 72 hours.

[0028] Step S104, the first revision step, interpolates the low temporal resolution 2-meter forecast temperature data to obtain high temporal resolution 2-meter forecast temperature data, and uses a preset hyperparameter set and the high temporal resolution 2-meter measured temperature data to revise the high temporal resolution 2-meter forecast temperature data to obtain the corrected 2-meter forecast temperature data.

[0029] It should be noted that the value range of each preset hyperparameter in the above preset hyperparameter set is 0 to 1. Since multiple preset hyperparameters are needed to revise the high temporal resolution 2-meter forecast temperature data, the amount of computation is large. Therefore, multi-threading or multi-processing can be used. Each preset hyperparameter w corresponds to a program that occupies one thread or process, and each thread or process simultaneously revises the high temporal resolution 2-meter forecast temperature data.

[0030] Step S106: Execute the step of determining the current time after a preset time period as the current time, and repeat the acquisition step and the first revision step a preset number of times to obtain the corrected 2-meter forecast temperature data within the target time period.

[0031] It should be noted that the preset duration is generally 24 hours, the preset number of times is 30, that is, the target time period is 30 days.

[0032] Step S108, Determine the optimal preset hyperparameters corresponding to the weather station to be corrected, based on the corrected 2-meter forecast temperature data within the target time period and the high temporal resolution 2-meter measured temperature data within the target time period.

[0033] Step S110, the second revision step, uses the optimal preset hyperparameters to correct the high temporal resolution 2-meter forecast temperature data of the weather station to be corrected after the target time period.

[0034] It should be noted that, generally, the optimal preset hyperparameters are used to correct the high temporal resolution 2-meter forecast temperature data of the weather station to be corrected within 30 days after the target time period. Then, the correction results of these 30 days are used to evaluate and redetermine the optimal preset hyperparameters. The 2-meter temperature of the following 30 days is corrected using this optimal preset hyperparameters, and so on.

[0035] In this embodiment of the invention, the acquisition step involves acquiring temperature data from the time of reporting to the current time of the weather station to be corrected. The temperature data includes: low temporal resolution 2-meter forecast temperature data and high temporal resolution 2-meter measured temperature data. The first revision step involves interpolating the low temporal resolution 2-meter forecast temperature data to obtain high temporal resolution 2-meter forecast temperature data, and revising the high temporal resolution 2-meter forecast temperature data using a preset hyperparameter set and the high temporal resolution 2-meter measured temperature data to obtain corrected 2-meter forecast temperature data. The execution step involves repeating the acquisition step and the first revision step a preset number of times to obtain the correction within the target time period. The process involves: 1) determining the optimal preset hyperparameters corresponding to the weather station to be corrected, based on the corrected 2-meter forecast temperature data within the target time period and the high temporal resolution 2-meter measured temperature data within the target time period; 2) using the optimal preset hyperparameters to correct the high temporal resolution 2-meter forecast temperature data of the weather station to be corrected after the target time period. This achieves the goal of correcting the forecast temperature data of the ECMWF model using adaptive Kalman filtering, thereby solving the technical problem of low accuracy in temperature forecast data of the ECMWF model and improving the technical effect of improving the accuracy of temperature forecast data of the ECMWF model.

[0036] In this embodiment of the invention, step S104 includes the following steps:

[0037] Using the preset hyperparameters and the high temporal resolution 2-meter predicted temperature data, the decreasing average error at the current moment corresponding to multiple values ​​of the preset hyperparameters is determined;

[0038] The high temporal resolution 2-meter forecast temperature data is corrected by using the decreasing average error corresponding to multiple preset hyperparameter values ​​at the current time, and the corrected 2-meter forecast temperature data is obtained.

[0039] In this embodiment of the invention, firstly, each preset hyperparameter and the high-resolution 2-meter forecast temperature data are substituted into the formula for calculating the decreasing average error at the current time to obtain the decreasing average error at the current time corresponding to multiple values ​​of the preset hyperparameters.

[0040] The formula for calculating the decreasing average error at the current time is: ,in, The current time Decreasing average error To preset hyperparameters, The current time The decreasing average error of the previous day, The current time High temporal resolution 2-meter forecast temperature data from the previous day.

[0041] Next, the decreasing average error corresponding to the current time of the preset hyperparameter is subtracted from the high-resolution 2-meter forecast temperature data to obtain multiple corrected 2-meter forecast temperature data. The number of corrected 2-meter forecast temperature data is the same as the number of preset hyperparameters.

[0042] In this embodiment of the invention, step S108 includes the following steps:

[0043] Based on the corrected 2-meter predicted temperature data within the target time period and the high temporal resolution 2-meter measured temperature data within the target time period, the mean square error or root mean square error corresponding to each preset hyperparameter is calculated.

[0044] The preset hyperparameter that corresponds to the maximum decrease in mean square error or root mean square error within the target time period is determined as the optimal preset hyperparameter.

[0045] In this embodiment of the invention, after obtaining the 30-day corrected 2-meter forecast temperature data corresponding to each preset hyperparameter, the mean square error or root mean square error between the 30-day corrected 2-meter forecast temperature data corresponding to each preset hyperparameter and the 30-day high temporal resolution 2-meter measured temperature data is calculated. The preset hyperparameter that reduces the mean square error or root mean square error the most over 30 days is determined as the optimal preset hyperparameter thereafter.

[0046] Finally, the high temporal resolution 2-meter forecast temperature data were corrected using the optimal preset hyperparameters.

[0047] In this embodiment of the invention, adaptive Kalman filtering is used to correct the forecast temperature data, resulting in a significant positive correction for 2m temperature. By correcting the numerical model through this objective method, forecast errors are reduced, providing a reference for forecasters and better serving people's production and life, thus meeting the current societal need for forecast accuracy.

[0048] Example 2:

[0049] This invention also provides a temperature correction device for ECMWF mode, which is used to execute the temperature correction method for ECMWF mode provided in the above-described embodiments of this invention. The following is a detailed description of the temperature correction device for ECMWF mode provided in this invention.

[0050] like Figure 2 As shown, Figure 2 This is a schematic diagram of the temperature correction device for the ECMWF mode described above. The temperature correction device for the ECMWF mode includes:

[0051] The acquisition unit 10 acquires the temperature data of the weather station to be corrected from the time of reporting to the current time. The temperature data includes: low temporal resolution 2-meter forecast temperature data and high temporal resolution 2-meter measured temperature data.

[0052] The first revision unit 20 interpolates the low temporal resolution 2-meter forecast temperature data to obtain high temporal resolution 2-meter forecast temperature data, and then uses a preset hyperparameter set and the high temporal resolution 2-meter measured temperature data to revise the high temporal resolution 2-meter forecast temperature data to obtain corrected 2-meter forecast temperature data.

[0053] The execution unit 30 determines the current time after a preset time period as the current time. The acquisition unit and the first revision unit repeatedly execute the preset number of times to obtain the corrected 2-meter forecast temperature data within the target time period.

[0054] The determining unit 40 determines the optimal preset hyperparameters corresponding to the weather station to be corrected based on the corrected 2-meter forecast temperature data within the target time period and the high temporal resolution 2-meter measured temperature data within the target time period.

[0055] The second revision unit 50 uses the optimal preset hyperparameters to correct the high temporal resolution 2-meter forecast temperature data of the weather station to be corrected after the target time period.

[0056] In this embodiment of the invention, temperature data from the weather station to be corrected, from the initial reporting time to the current time, is acquired. This temperature data includes: low temporal resolution 2-meter forecast temperature data and high temporal resolution 2-meter measured temperature data. The low temporal resolution 2-meter forecast temperature data is interpolated to obtain high temporal resolution 2-meter forecast temperature data. Using a preset hyperparameter set and the high temporal resolution 2-meter measured temperature data, the high temporal resolution 2-meter forecast temperature data is revised to obtain corrected 2-meter forecast temperature data. The current time is determined after a preset time interval. The acquisition unit and the first revision unit are executed repeatedly a preset number of times. The corrected 2-meter forecast temperature data for the target time period is obtained. Based on the corrected 2-meter forecast temperature data for the target time period and the high temporal resolution 2-meter measured temperature data for the target time period, the optimal preset hyperparameters corresponding to the weather station to be corrected are determined. Using the optimal preset hyperparameters, the high temporal resolution 2-meter forecast temperature data of the weather station to be corrected after the target time period is corrected. This achieves the purpose of correcting the forecast temperature data of the ECMWF model using adaptive Kalman filtering, thereby solving the technical problem of low accuracy of temperature forecast data in the ECMWF model and thus realizing the technical effect of improving the accuracy of temperature forecast data in the ECMWF model.

[0057] Example 3:

[0058] This invention also provides an electronic device, including a memory and a processor. The memory is used to store a program that supports the processor in executing the method described in Embodiment 1 above, and the processor is configured to execute the program stored in the memory.

[0059] See Figure 3 This invention also provides an electronic device 100, including: a processor 60, a memory 61, a bus 62 and a communication interface 63, wherein the processor 60, the communication interface 63 and the memory 61 are connected through the bus 62; the processor 60 is used to execute executable modules, such as computer programs, stored in the memory 61.

[0060] The memory 61 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 63 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc.

[0061] Bus 62 can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0062] The memory 61 is used to store programs. After receiving an execution instruction, the processor 60 executes the program. The method executed by the device for defining the flow process disclosed in any of the foregoing embodiments of the present invention can be applied to the processor 60 or implemented by the processor 60.

[0063] Processor 60 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 60 or by instructions in software form. Processor 60 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 61. Processor 60 reads the information in memory 61 and, in conjunction with its hardware, completes the steps of the above method.

[0064] Example 4:

[0065] This invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the method described in Embodiment 1 above.

[0066] Furthermore, in the description of the embodiments of the present invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention based on the specific circumstances.

[0067] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0068] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the shown or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0069] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0070] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0071] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A temperature correction method for ECMWF mode, characterized in that, include: The acquisition step involves acquiring temperature data from the weather station to be corrected from the time of reporting to the current time. The temperature data includes: low temporal resolution 2-meter forecast temperature data and high temporal resolution 2-meter measured temperature data. The first revision step involves interpolating the low temporal resolution 2-meter forecast temperature data to obtain high temporal resolution 2-meter forecast temperature data, and then revising the high temporal resolution 2-meter forecast temperature data using a preset hyperparameter set and the high temporal resolution 2-meter measured temperature data to obtain corrected 2-meter forecast temperature data. The execution steps are as follows: the time after a preset time period is determined as the current time; the acquisition step and the first revision step are repeated a preset number of times to obtain the corrected 2-meter forecast temperature data within the target time period. The determination process involves identifying the optimal preset hyperparameters for the weather station to be corrected based on the corrected 2-meter forecast temperature data within the target time period and the high temporal resolution 2-meter measured temperature data within the target time period. The second revision step involves using the optimal preset hyperparameters to correct the high temporal resolution 2-meter forecast temperature data of the weather station to be corrected after the target time period. Using a preset hyperparameter set and the high temporal resolution 2-meter measured temperature data, the high temporal resolution 2-meter predicted temperature data is revised to obtain corrected 2-meter predicted temperature data, including: Using the preset hyperparameter set, the high temporal resolution 2-meter measured temperature data, and the high temporal resolution 2-meter predicted temperature data, the decreasing average error at the current moment corresponding to each preset hyperparameter is determined; By using the decreasing average error corresponding to each preset hyperparameter at the current time, the high temporal resolution 2-meter forecast temperature data is corrected to obtain the corrected 2-meter forecast temperature data.

2. The method according to claim 1, characterized in that, The formula for calculating the decreasing average error at the current moment is: ,in, The current time Decreasing average error To preset hyperparameters, The current time The decreasing average error of the previous day, The current time High temporal resolution 2-meter forecast temperature data from the previous day.

3. The method according to claim 1, characterized in that, Based on the corrected 2-meter forecast temperature data and the high temporal resolution 2-meter measured temperature data within the target time period, the optimal preset hyperparameters corresponding to the weather station to be corrected are determined, including: Based on the corrected 2-meter predicted temperature data within the target time period and the high temporal resolution 2-meter measured temperature data within the target time period, the mean square error or root mean square error corresponding to each preset hyperparameter is calculated. The preset hyperparameter that corresponds to the maximum decrease in mean square error or root mean square error within the target time period is determined as the optimal preset hyperparameter.

4. A temperature correction device for ECMWF mode, characterized in that, include: The acquisition unit acquires temperature data from the weather station to be corrected from the time of reporting to the current time. The temperature data includes: low temporal resolution 2-meter forecast temperature data and high temporal resolution 2-meter measured temperature data. The first revision unit interpolates the low temporal resolution 2-meter forecast temperature data to obtain high temporal resolution 2-meter forecast temperature data, and then uses a preset hyperparameter set and the high temporal resolution 2-meter measured temperature data to revise the high temporal resolution 2-meter forecast temperature data to obtain the corrected 2-meter forecast temperature data. The execution unit determines the current time after a preset time period as the current time. The acquisition unit and the first revision unit repeatedly execute the preset number of times to obtain the corrected 2-meter forecast temperature data within the target time period. The determining unit determines the optimal preset hyperparameters corresponding to the weather station to be corrected based on the corrected 2-meter forecast temperature data within the target time period and the high temporal resolution 2-meter measured temperature data within the target time period. The second revision unit uses the optimal preset hyperparameters to correct the high temporal resolution 2-meter forecast temperature data of the weather station to be corrected after the target time period. The first revision unit is used for: Using the preset hyperparameter set, the high temporal resolution 2-meter measured temperature data, and the high temporal resolution 2-meter predicted temperature data, the decreasing average error at the current moment corresponding to each preset hyperparameter is determined; By using the decreasing average error corresponding to each preset hyperparameter at the current time, the high temporal resolution 2-meter forecast temperature data is corrected to obtain the corrected 2-meter forecast temperature data.

5. The apparatus according to claim 4, characterized in that, The formula for calculating the decreasing average error at the current moment is: ,in, The current time Decreasing average error To preset hyperparameters, The current time The decreasing average error of the previous day, The current time High temporal resolution 2-meter forecast temperature data from the previous day.

6. The apparatus according to claim 4, characterized in that, The determining unit is further configured to: Based on the corrected 2-meter predicted temperature data within the target time period and the high temporal resolution 2-meter measured temperature data within the target time period, the mean square error or root mean square error corresponding to each preset hyperparameter is calculated. The preset hyperparameter that corresponds to the maximum decrease in mean square error or root mean square error within the target time period is determined as the optimal preset hyperparameter.

7. An electronic device, characterized in that, The system includes a memory and a processor, the memory being used to store a program that enables the processor to execute the method of any one of claims 1 to 3, and the processor being configured to execute the program stored in the memory.

8. A computer-readable storage medium storing a computer program thereon, characterized in that, When a computer program is run by a processor, it performs the steps of the method described in any one of claims 1 to 3.

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