Precipitation forecasting method and device based on meteorological parameters, computer equipment, medium and product
By conducting sensitivity tests and adjustments to meteorological parameters, the optimal forecast scheme was generated, which solved the problem of insufficient accuracy in freezing rain forecasts under complex terrain and achieved higher forecast accuracy.
Patent Information
- Application Number
- CN202511104170.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-07
- Publication Date
- 2025-11-14
AI Technical Summary
Existing technologies are ill-suited to adapting to the dynamic changes in key factors contributing to freezing rain formation in complex terrain, leading to reduced accuracy in freezing rain forecasts.
By conducting sensitivity tests on various meteorological parameters, obtaining sensitivity coefficients, determining target meteorological parameters, adjusting initial parameter values, generating multiple updated forecast schemes, and calculating forecast scores to obtain the optimal forecast scheme for freezing rain forecasting.
It improves the accuracy of freezing rain forecasts, adapts to meteorological changes at different altitudes, and reduces false alarms and missed reports.
Smart Images
Figure CN120949360A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of precipitation forecasting technology, and in particular to a precipitation forecasting method, apparatus, computer equipment, medium, and product based on meteorological parameters. Background Technology
[0002] As a high-impact weather event, accurate forecasting of freezing rain is crucial for disaster prevention and mitigation. Forecast score is an important indicator for measuring the accuracy of freezing rain forecasts, and the selection of meteorological parameters and their threshold ranges in the forecast model has a significant impact on the forecast score.
[0003] Since the contribution of different meteorological factors to freezing rain formation is not constant, especially under complex terrain conditions, the formation mechanism of freezing rain often changes with increasing altitude, and the sensitivity of some key parameters decreases with increasing altitude; conversely, the sensitivity of other parameters increases significantly. Therefore, forecasting methods using single or fixed threshold combinations are difficult to adapt to the dynamic changes of key factors in freezing rain formation at different altitudes, leading to reduced accuracy in freezing rain forecasts for complex terrain areas. Summary of the Invention
[0004] Therefore, it is necessary to provide a precipitation forecasting method, device, computer equipment, medium, and product based on meteorological parameters that can improve the accuracy of freezing rain forecasting, addressing the aforementioned technical problems.
[0005] Firstly, this application provides a precipitation forecasting method based on meteorological parameters, including:
[0006] Sensitivity tests were conducted on each meteorological parameter to obtain the sensitivity coefficient of each meteorological parameter to the forecast score. Based on the sensitivity coefficient, the target meteorological parameter was determined from all meteorological parameters.
[0007] Obtain the initial parameter values corresponding to each target meteorological parameter in the initial forecast scheme, and repeatedly adjust the initial parameter values according to the sensitivity coefficient to obtain multiple updated forecast schemes;
[0008] Calculate the forecast score for each updated forecast scheme, obtain the target forecast scheme based on the forecast score, and use the target forecast scheme to forecast freezing rain.
[0009] In one embodiment, the sensitivity coefficients include the sensitivity coefficients of each meteorological parameter at different altitudes; the step of determining the target meteorological parameter from all meteorological parameters based on the sensitivity coefficients includes:
[0010] For each meteorological parameter, the sensitivity change trend of the meteorological parameter is obtained based on the sensitivity coefficient of the meteorological parameter at different altitudes;
[0011] The meteorological parameters corresponding to the sensitivity change trend that meets the preset conditions are used as the target meteorological parameters.
[0012] In one embodiment, the step of repeatedly adjusting the initial parameter values based on the sensitivity coefficient to obtain multiple updated forecast schemes includes:
[0013] According to the preset reduction range, the initial parameter values are gradually adjusted to obtain multiple candidate parameter values corresponding to each target meteorological parameter;
[0014] By arranging and combining all candidate parameters and initial parameter values, multiple updated forecast schemes are obtained.
[0015] In one embodiment, the step of calculating the forecast score for each updated forecast scheme includes:
[0016] For each updated forecast scheme, obtain the forecast results for freezing rain forecast using the updated forecast scheme; the forecast results include the number of correct forecasts, the number of false alarms, and the number of missed forecasts;
[0017] The forecast score is obtained for each updated forecast scheme based on the forecast results; the forecast score is used to characterize the forecast performance of the updated forecast scheme.
[0018] In one embodiment, the step of obtaining a target forecast scheme based on the forecast score includes:
[0019] Obtain multiple altitude regions;
[0020] For each altitude region, the candidate forecast scheme with the highest forecast score for that altitude region is selected as the target forecast scheme for that altitude region.
[0021] In one embodiment, the step of forecasting freezing rain using a target forecasting scheme includes:
[0022] Obtain the regional elevation of the precipitation area and determine the target elevation area that matches the regional elevation;
[0023] Freezing rain forecasts are performed on precipitation areas using target forecasting schemes corresponding to target elevation regions.
[0024] Secondly, this application also provides a precipitation forecasting device based on meteorological parameters, comprising:
[0025] The sensitivity testing module is used to conduct sensitivity tests on each meteorological parameter, obtain the sensitivity coefficient of each meteorological parameter to the forecast score, and determine the target meteorological parameter from all meteorological parameters based on the sensitivity coefficient.
[0026] The parameter adjustment module is used to obtain the initial parameter values corresponding to each target meteorological parameter in the initial forecast scheme, and repeatedly adjust the initial parameter values according to the sensitivity coefficient to obtain multiple updated forecast schemes.
[0027] The freezing rain forecast module is used to calculate the forecast score of each updated forecast scheme, obtain the target forecast scheme based on the forecast score, and perform freezing rain forecasting based on the target forecast scheme.
[0028] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method steps of any one of the first aspects.
[0029] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method steps of any one of the first aspects.
[0030] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the method steps of any one of the first aspects.
[0031] The aforementioned precipitation forecasting methods, devices, computer equipment, media, and products based on meteorological parameters obtain sensitivity coefficients for each meteorological parameter to the forecast score by conducting sensitivity tests on each meteorological parameter. Based on these sensitivity coefficients, target meteorological parameters are determined from all meteorological parameters, and initial parameter values corresponding to each target meteorological parameter in the initial forecast scheme are obtained. The initial parameter values are repeatedly adjusted based on the sensitivity coefficients to obtain multiple updated forecast schemes. The forecast score of each updated forecast scheme is calculated, and the target forecast scheme is obtained based on the forecast score. Freezing rain forecasts are then performed using the target forecast schemes. This approach can accurately obtain key meteorological parameters and, consequently, accurately obtain the optimal values of the target meteorological parameters, thereby improving the accuracy of precipitation forecasts. Attached Figure Description
[0032] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0033] Figure 1 This is an application environment diagram of a precipitation forecasting method based on meteorological parameters in one embodiment;
[0034] Figure 2 This is a flowchart illustrating a precipitation forecasting method based on meteorological parameters in one embodiment.
[0035] Figure 3 This is a flowchart illustrating a precipitation forecasting method based on meteorological parameters in another embodiment;
[0036] Figure 4 This is a structural block diagram of a precipitation forecasting device based on meteorological parameters in one embodiment;
[0037] Figure 5 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation
[0038] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.
[0039] The precipitation forecasting method based on meteorological parameters provided in this application can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or placed on a cloud or other network server. Terminal 102 is used to perform sensitivity tests on each meteorological parameter, obtain the sensitivity coefficient of each meteorological parameter to the forecast score, determine the target meteorological parameter from all meteorological parameters based on the sensitivity coefficient, obtain the initial parameter values corresponding to each target meteorological parameter in the initial forecast scheme, repeatedly adjust the initial parameter values according to the sensitivity coefficient to obtain multiple updated forecast schemes, calculate the forecast score of each updated forecast scheme, obtain the target forecast scheme based on the forecast score, and perform freezing rain forecasting using the target forecast scheme. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. IoT devices can be smart speakers, smart TVs, smart air conditioners, smart vehicle devices, projection devices, etc. Portable wearable devices can be smartwatches, smart bracelets, head-mounted devices, etc. Headset devices can be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. Server 104 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.
[0040] In one exemplary embodiment, such as Figure 2 As shown, a precipitation forecasting method based on meteorological parameters is provided, and this method is applied to... Figure 1Taking terminal 102 as an example, the explanation includes the following steps 202 to 206. Wherein:
[0041] S202: Conduct sensitivity tests on each meteorological parameter to obtain the sensitivity coefficient of each meteorological parameter to the forecast score, and determine the target meteorological parameter from all meteorological parameters based on the sensitivity coefficient.
[0042] Optionally, sensitivity testing involves perturbing all meteorological parameters involved in freezing rain forecasting, artificially adjusting the value of a particular parameter, and observing its impact on the final forecast score. The sensitivity coefficient quantifies this impact numerically. Based on the sensitivity coefficient, the parameter with the most significant impact on the forecast score is selected as the target meteorological parameter, i.e., the most critical input variable in freezing rain forecasting.
[0043] S204: Obtain the initial parameter values corresponding to each target meteorological parameter in the initial forecast scheme, and repeatedly adjust the initial parameter values according to the sensitivity coefficient to obtain multiple updated forecast schemes.
[0044] Optionally, the initial parameter values refer to the original set values of each target meteorological parameter extracted and selected from the initial forecast scheme, such as setting the initial temperature threshold to -2℃ and the initial humidity threshold to 80%. Based on the sensitivity coefficient, the initial values of the target meteorological parameters are adjusted multiple times, and a new updated forecast scheme is generated after each adjustment. Through multiple iterations, a series of updated forecast schemes with different parameter combinations are formed, covering the possible value range of key parameters.
[0045] S206: Calculate the forecast score for each updated forecast scheme, obtain the target forecast scheme based on the forecast score, and make freezing rain forecasts using the target forecast scheme.
[0046] Optionally, each updated forecast scheme can be simulated or backtested using historical data to calculate its forecast score, such as the accuracy, false alarm rate, and missed alarm rate of freezing rain forecasts. The scores of all updated schemes are compared, and the scheme with the highest score (i.e., the best forecast performance) is selected as the target forecast scheme. Finally, the target scheme is used to conduct actual freezing rain forecasts, and the forecast results are output.
[0047] In the above-mentioned precipitation forecasting method based on meteorological parameters, sensitivity tests are conducted on each meteorological parameter to obtain the sensitivity coefficient of each meteorological parameter to the forecast score. Based on the sensitivity coefficient, the target meteorological parameter is determined from all meteorological parameters, and the initial parameter values corresponding to each target meteorological parameter in the initial forecast scheme are obtained. The initial parameter values are repeatedly adjusted according to the sensitivity coefficient to obtain multiple updated forecast schemes. The forecast score of each updated forecast scheme is calculated, and the target forecast scheme is obtained based on the forecast score. Freezing rain forecasting is performed through the target forecast scheme, which can accurately obtain key meteorological parameters and thus accurately obtain the optimal value of the target meteorological parameter, thereby improving the accuracy of precipitation forecasting.
[0048] In an exemplary embodiment, the sensitivity coefficient includes the sensitivity coefficient of each meteorological parameter at different altitudes; the step of determining the target meteorological parameter from all meteorological parameters based on the sensitivity coefficient includes: for each meteorological parameter, obtaining the sensitivity change trend corresponding to the meteorological parameter based on the sensitivity coefficient of the meteorological parameter at different altitudes; and taking the meteorological parameter corresponding to the sensitivity change trend that meets the preset conditions as the target meteorological parameter.
[0049] Optionally, for each meteorological parameter, its overall impact on the forecast score is calculated, and the sensitivity coefficient of that parameter at each altitude is obtained. The sensitivity coefficients of each meteorological parameter at different altitudes are integrated to obtain the trend of the sensitivity of that meteorological parameter with altitude. Meteorological parameters whose trends meet preset conditions are selected as target meteorological parameters. For example, if the sensitivity coefficient of a meteorological parameter increases with increasing altitude, it indicates that its impact on the forecast results is weakening, and therefore, that meteorological parameter does not need to be given special consideration.
[0050] In this embodiment, by taking each meteorological parameter and obtaining the sensitivity change trend of the meteorological parameter at different altitudes based on the sensitivity coefficient of the meteorological parameter, the meteorological parameter corresponding to the sensitivity change trend that meets the preset conditions is taken as the target meteorological parameter. This can ensure that the selected target parameters are suitable for different altitudes and improve the accuracy of meteorological parameter selection.
[0051] In an exemplary embodiment, the step of repeatedly adjusting the initial parameter values according to the sensitivity coefficient to obtain multiple updated forecast schemes includes: gradually adjusting each initial parameter value according to a preset reduction range to obtain multiple candidate parameter values corresponding to each target meteorological parameter; and arranging and combining all candidate parameters and initial parameter values to obtain multiple updated forecast schemes.
[0052] Optionally, for each determined target meteorological parameter, its initial parameter value is gradually adjusted according to a preset reduction margin (such as a fixed proportion of 5%, 10%, etc., adjusting the initial value each time), resulting in a series of candidate values for the parameter. All candidate parameter values of the target meteorological parameter are then combined with the unadjusted initial parameter values in a full permutation, and each combination corresponds to an updated forecast scheme.
[0053] In this embodiment, by gradually adjusting the initial parameter values according to a preset reduction range, multiple candidate parameter values corresponding to each target meteorological parameter are obtained. By arranging and combining all candidate parameters and initial parameter values, multiple updated forecast schemes are obtained, which can accurately obtain the optimal forecast scheme, thereby improving the accuracy of precipitation forecast.
[0054] In an exemplary embodiment, the step of calculating the forecast score for each updated forecast scheme includes: for each updated forecast scheme, obtaining the forecast result of freezing rain forecast using the updated forecast scheme; the forecast result includes the number of correct forecasts, the number of false alarms, and the number of missed forecasts; obtaining the forecast score for each updated forecast scheme based on the forecast result; the forecast score is used to characterize the forecast performance of the updated forecast scheme.
[0055] Optionally, for each updated forecast scheme, the scheme is used to simulate and forecast historical or real-time freezing rain events, and the forecast results are recorded. These forecast results include the number of correct forecasts (e.g., the scheme forecasts freezing rain, and it actually occurs; or it forecasts no freezing rain, and it does not occur), the number of false alarms (e.g., the scheme forecasts freezing rain, but it does not occur), and the number of missed forecasts (e.g., the scheme forecasts no freezing rain, but it occurs). Based on these three types of data, a forecast score for each scheme is calculated using a preset scoring formula. The scoring formula can be the hit rate (TS score): number of correct forecasts / (number of correct forecasts + number of false alarms + number of missed forecasts), emphasizing the accuracy of forecasts for events with freezing rain. The forecast score directly reflects the forecast effectiveness of the scheme; a higher score indicates a higher accuracy rate, fewer false alarms and missed forecasts, and a stronger ability to forecast freezing rain.
[0056] In this embodiment, by obtaining the forecast results of freezing rain forecast using the updated forecast scheme for each updated forecast scheme, and obtaining the forecast score of each updated forecast scheme based on the forecast results, the optimal forecast scheme can be accurately obtained, thereby improving the accuracy of precipitation forecast.
[0057] In an exemplary embodiment, the step of obtaining a target forecast scheme based on the forecast score includes: obtaining multiple altitude regions; and for each altitude region, selecting the candidate forecast scheme with the highest forecast score corresponding to the altitude region as the target forecast scheme corresponding to the altitude region.
[0058] The forecast area is divided into multiple sub-regions based on altitude (such as low-altitude, mid-altitude, and high-altitude regions). For each sub-region, the candidate forecast scheme with the highest forecast score is selected from all updated forecast schemes and designated as the target forecast scheme specific to that altitude region.
[0059] In this embodiment, by acquiring multiple altitude regions, the candidate forecast scheme with the highest forecast score for each altitude region is selected as the target forecast scheme for that altitude region. This can accurately match the meteorological patterns at different altitudes, reduce false alarms or missed forecasts caused by terrain, and thus improve the accuracy of precipitation forecasts.
[0060] In an exemplary embodiment, the step of forecasting freezing rain using a target forecasting scheme includes: obtaining the regional elevation of the precipitation area, determining a target elevation area that matches the regional elevation, and forecasting freezing rain in the precipitation area using the target forecasting scheme corresponding to the target elevation area.
[0061] Optionally, when freezing rain forecasting is required for a region where precipitation may occur, the actual elevation information of the region is first obtained. This actual elevation is then compared with multiple target elevation regions to find the corresponding target elevation region. Freezing rain forecasting is then performed using the target forecasting scheme corresponding to the target elevation region.
[0062] In this embodiment, by obtaining the regional elevation of the precipitation area, a target elevation area matching the regional elevation is determined, and freezing rain forecasts are performed on the precipitation area using the target forecast scheme corresponding to the target elevation area, which can improve the accuracy of precipitation forecasts.
[0063] In one exemplary embodiment, such as Figure 3 As shown, a precipitation forecasting method based on meteorological parameters is provided, which includes the following steps:
[0064] Sensitivity tests were conducted on each meteorological parameter to obtain its sensitivity coefficient to the forecast score. For each meteorological parameter, the sensitivity change trend was obtained based on its sensitivity coefficient at different altitudes. The meteorological parameter whose sensitivity change trend meets preset conditions was selected as the target meteorological parameter. The sensitivity coefficient includes the sensitivity coefficient of each meteorological parameter at different altitudes.
[0065] The initial parameter values corresponding to each target meteorological parameter in the initial forecast scheme are obtained. The initial parameter values are gradually adjusted according to the preset reduction range to obtain multiple candidate parameter values corresponding to each target meteorological parameter. All candidate parameters and initial parameter values are arranged and combined to obtain multiple updated forecast schemes.
[0066] For each updated forecast scheme, the forecast results for freezing rain forecasts using the updated forecast scheme are obtained; the forecast results include the number of correct forecasts, the number of false alarms, and the number of missed forecasts; the forecast score for each updated forecast scheme is obtained based on the forecast results; the forecast score is used to characterize the forecast performance of the updated forecast scheme.
[0067] Multiple altitude regions are obtained; for each altitude region, the candidate forecast scheme with the highest forecast score is selected as the target forecast scheme for that altitude region.
[0068] Obtain the regional elevation of the precipitation area and determine the target elevation area that matches the regional elevation; use the target forecasting scheme corresponding to the target elevation area to forecast freezing rain in the precipitation area.
[0069] In this embodiment, sensitivity tests are conducted on each meteorological parameter to obtain the sensitivity coefficient of each meteorological parameter to the forecast score. Based on the sensitivity coefficient, the target meteorological parameter is determined from all meteorological parameters, and the initial parameter values corresponding to each target meteorological parameter in the initial forecast scheme are obtained. The initial parameter values are repeatedly adjusted according to the sensitivity coefficient to obtain multiple updated forecast schemes. The forecast score of each updated forecast scheme is calculated, and the target forecast scheme is obtained based on the forecast score. Freezing rain forecasting is performed using the target forecast scheme, which can accurately obtain key meteorological parameters and thus accurately obtain the optimal value of the target meteorological parameter, thereby improving the accuracy of precipitation forecasting.
[0070] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.
[0071] Based on the same inventive concept, this application also provides a meteorological parameter-based precipitation forecasting device for implementing the above-mentioned meteorological parameter-based precipitation forecasting method. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more meteorological parameter-based precipitation forecasting device embodiments provided below can be found in the limitations of the meteorological parameter-based precipitation forecasting method described above, and will not be repeated here.
[0072] In one exemplary embodiment, such as Figure 4 As shown, a precipitation forecasting device based on meteorological parameters is provided, including: a sensitivity testing module 10, a parameter adjustment module 20, and a freezing rain forecasting module 30, wherein:
[0073] Sensitivity testing module 10 is used to conduct sensitivity tests on each meteorological parameter, obtain the sensitivity coefficient of each meteorological parameter to the forecast score, and determine the target meteorological parameter from all meteorological parameters based on the sensitivity coefficient.
[0074] The parameter adjustment module 20 is used to obtain the initial parameter values corresponding to each target meteorological parameter in the initial forecast scheme, and repeatedly adjust the initial parameter values according to the sensitivity coefficient to obtain multiple updated forecast schemes.
[0075] The freezing rain forecast module 30 is used to calculate the forecast score of each updated forecast scheme, obtain the target forecast scheme based on the forecast score, and perform freezing rain forecasting based on the target forecast scheme.
[0076] In an exemplary embodiment, the sensitivity coefficient includes the sensitivity coefficient of each meteorological parameter at different altitudes; the sensitivity test module 10 is also used to obtain the sensitivity change trend of each meteorological parameter based on the sensitivity coefficient of the meteorological parameter at different altitudes; and to take the meteorological parameter corresponding to the sensitivity change trend that meets the preset conditions as the target meteorological parameter.
[0077] In an exemplary embodiment, the parameter adjustment module 20 is further configured to gradually adjust each initial parameter value according to a preset reduction range to obtain multiple candidate parameter values corresponding to each target meteorological parameter; and to arrange and combine all candidate parameters and initial parameter values to obtain multiple updated forecast schemes.
[0078] In an exemplary embodiment, the freezing rain forecast module 30 is further configured to obtain the forecast results of freezing rain forecasting using the updated forecast scheme for each updated forecast scheme; the forecast results include the number of correct forecasts, the number of false forecasts, and the number of missed forecasts; obtain the forecast score of each updated forecast scheme based on the forecast results; the forecast score is used to characterize the forecast effect of the updated forecast scheme.
[0079] In an exemplary embodiment, the freezing rain forecast module 30 is further configured to acquire multiple elevation regions; for each elevation region, the candidate forecast scheme with the highest forecast score corresponding to the elevation region is selected as the target forecast scheme corresponding to the elevation region.
[0080] In an exemplary embodiment, the freezing rain forecast module 30 is further configured to obtain the regional elevation of the precipitation area, determine the target elevation area that matches the regional elevation, and perform freezing rain forecasting on the precipitation area through the target forecasting scheme corresponding to the target elevation area.
[0081] The modules in the aforementioned precipitation forecasting device based on meteorological parameters can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.
[0082] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 5 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a precipitation forecasting method based on meteorological parameters. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.
[0083] Those skilled in the art will understand that Figure 5The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.
[0084] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps: performing sensitivity tests on each meteorological parameter to obtain the sensitivity coefficient of each meteorological parameter to the forecast score; determining the target meteorological parameter from all meteorological parameters based on the sensitivity coefficient; obtaining the initial parameter value corresponding to each target meteorological parameter in the initial forecast scheme; repeatedly adjusting the initial parameter value based on the sensitivity coefficient to obtain multiple updated forecast schemes; calculating the forecast score of each updated forecast scheme; obtaining the target forecast scheme based on the forecast score; and performing freezing rain forecasting using the target forecast scheme.
[0085] In one embodiment, the sensitivity coefficient includes the sensitivity coefficients of each meteorological parameter at different altitudes; the process of determining the target meteorological parameter from all meteorological parameters based on the sensitivity coefficients when the processor executes the computer program includes: for each meteorological parameter, obtaining the sensitivity change trend corresponding to the meteorological parameter based on the sensitivity coefficients of the meteorological parameter at different altitudes; and taking the meteorological parameter corresponding to the sensitivity change trend that meets the preset conditions as the target meteorological parameter.
[0086] In one embodiment, the processor executing a computer program involves repeatedly adjusting the initial parameter values according to the sensitivity coefficient to obtain multiple updated forecast schemes, including: gradually adjusting each initial parameter value according to a preset reduction range to obtain multiple candidate parameter values corresponding to each target meteorological parameter; and arranging and combining all candidate parameters and initial parameter values to obtain multiple updated forecast schemes.
[0087] In one embodiment, the processor executing the computer program involves calculating the forecast score for each updated forecast scheme, including: for each updated forecast scheme, obtaining the forecast result of freezing rain forecast using the updated forecast scheme; the forecast result includes the number of correct forecasts, the number of false alarms, and the number of missed forecasts; obtaining the forecast score for each updated forecast scheme based on the forecast result; the forecast score is used to characterize the forecast performance of the updated forecast scheme.
[0088] In one embodiment, the process of obtaining a target forecast scheme based on a forecast score when the processor executes a computer program includes: obtaining multiple altitude regions; and for each altitude region, selecting the candidate forecast scheme with the highest forecast score corresponding to the altitude region as the target forecast scheme corresponding to the altitude region.
[0089] In one embodiment, the freezing rain forecasting via a target forecasting scheme when the processor executes a computer program includes: obtaining the regional elevation of the precipitation area, determining a target elevation area that matches the regional elevation, and forecasting freezing rain for the precipitation area using the target forecasting scheme corresponding to the target elevation area.
[0090] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, it performs the following steps: performing sensitivity tests on each meteorological parameter to obtain the sensitivity coefficient of each meteorological parameter to the forecast score; determining the target meteorological parameter from all meteorological parameters based on the sensitivity coefficient; obtaining the initial parameter value corresponding to each target meteorological parameter in the initial forecast scheme; repeatedly adjusting the initial parameter value based on the sensitivity coefficient to obtain multiple updated forecast schemes; calculating the forecast score of each updated forecast scheme; obtaining the target forecast scheme based on the forecast score; and performing freezing rain forecasting through the target forecast scheme.
[0091] In one embodiment, the sensitivity coefficient includes the sensitivity coefficients of each meteorological parameter at different altitudes; when the computer program is executed by the processor, the process of determining the target meteorological parameter from all meteorological parameters based on the sensitivity coefficients includes: for each meteorological parameter, obtaining the sensitivity change trend corresponding to the meteorological parameter based on the sensitivity coefficients of the meteorological parameter at different altitudes; and taking the meteorological parameter corresponding to the sensitivity change trend that meets the preset conditions as the target meteorological parameter.
[0092] In one embodiment, when the computer program is executed by the processor, the process of repeatedly adjusting the initial parameter values according to the sensitivity coefficient to obtain multiple updated forecast schemes includes: gradually adjusting each initial parameter value according to a preset reduction range to obtain multiple candidate parameter values corresponding to each target meteorological parameter; and arranging and combining all candidate parameters and initial parameter values to obtain multiple updated forecast schemes.
[0093] In one embodiment, when the computer program is executed by the processor, the calculation of forecast scores for each updated forecast scheme includes: for each updated forecast scheme, obtaining the forecast result of freezing rain forecast using the updated forecast scheme; the forecast result includes the number of correct forecasts, the number of false alarms, and the number of missed forecasts; obtaining the forecast score for each updated forecast scheme based on the forecast result; the forecast score is used to characterize the forecast performance of the updated forecast scheme.
[0094] In one embodiment, the process of obtaining a target forecast scheme based on a forecast score when the computer program is executed by a processor includes: obtaining multiple altitude regions; and for each altitude region, selecting the candidate forecast scheme with the highest forecast score corresponding to the altitude region as the target forecast scheme corresponding to the altitude region.
[0095] In one embodiment, the freezing rain forecasting method involving a target forecasting scheme when the computer program is executed by a processor includes: obtaining the regional elevation of the precipitation area, determining a target elevation area that matches the regional elevation, and forecasting freezing rain for the precipitation area using the target forecasting scheme corresponding to the target elevation area.
[0096] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps: performing sensitivity tests on each meteorological parameter to obtain a sensitivity coefficient for each meteorological parameter to a forecast score; determining a target meteorological parameter from all meteorological parameters based on the sensitivity coefficient; obtaining initial parameter values corresponding to each target meteorological parameter in an initial forecast scheme; repeatedly adjusting the initial parameter values based on the sensitivity coefficient to obtain multiple updated forecast schemes; calculating the forecast score for each updated forecast scheme; obtaining a target forecast scheme based on the forecast score; and performing freezing rain forecasting using the target forecast scheme.
[0097] In one embodiment, the sensitivity coefficient includes the sensitivity coefficients of each meteorological parameter at different altitudes; when the computer program is executed by the processor, the process of determining the target meteorological parameter from all meteorological parameters based on the sensitivity coefficients includes: for each meteorological parameter, obtaining the sensitivity change trend corresponding to the meteorological parameter based on the sensitivity coefficients of the meteorological parameter at different altitudes; and taking the meteorological parameter corresponding to the sensitivity change trend that meets the preset conditions as the target meteorological parameter.
[0098] In one embodiment, when the computer program is executed by the processor, the process of repeatedly adjusting the initial parameter values according to the sensitivity coefficient to obtain multiple updated forecast schemes includes: gradually adjusting each initial parameter value according to a preset reduction range to obtain multiple candidate parameter values corresponding to each target meteorological parameter; and arranging and combining all candidate parameters and initial parameter values to obtain multiple updated forecast schemes.
[0099] In one embodiment, when the computer program is executed by the processor, the calculation of forecast scores for each updated forecast scheme includes: for each updated forecast scheme, obtaining the forecast result of freezing rain forecast using the updated forecast scheme; the forecast result includes the number of correct forecasts, the number of false alarms, and the number of missed forecasts; obtaining the forecast score for each updated forecast scheme based on the forecast result; the forecast score is used to characterize the forecast performance of the updated forecast scheme.
[0100] In one embodiment, the process of obtaining a target forecast scheme based on a forecast score when the computer program is executed by a processor includes: obtaining multiple altitude regions; and for each altitude region, selecting the candidate forecast scheme with the highest forecast score corresponding to the altitude region as the target forecast scheme corresponding to the altitude region.
[0101] In one embodiment, the freezing rain forecasting method involving a target forecasting scheme when the computer program is executed by a processor includes: obtaining the regional elevation of the precipitation area, determining a target elevation area that matches the regional elevation, and forecasting freezing rain for the precipitation area using the target forecasting scheme corresponding to the target elevation area.
[0102] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.
[0103] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.
[0104] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.
Claims
1. A precipitation forecasting method based on meteorological parameters, characterized in that, The method includes: Sensitivity tests were conducted on each meteorological parameter to obtain the sensitivity coefficient of each meteorological parameter to the forecast score. Based on the sensitivity coefficient, the target meteorological parameter was determined from all meteorological parameters. Obtain the initial parameter values corresponding to each target meteorological parameter in the initial forecast scheme, and repeatedly adjust the initial parameter values according to the sensitivity coefficient to obtain multiple updated forecast schemes; Forecast scores are calculated for each of the updated forecast schemes. A target forecast scheme is obtained based on the forecast scores, and freezing rain forecasts are performed using the target forecast scheme.
2. The method according to claim 1, characterized in that, The sensitivity coefficients include the sensitivity coefficients of each meteorological parameter at different altitudes; determining the target meteorological parameter from all meteorological parameters based on the sensitivity coefficients includes: For each meteorological parameter, the sensitivity change trend of the meteorological parameter is obtained based on the sensitivity coefficient of the meteorological parameter at different altitudes. The meteorological parameters corresponding to the sensitivity change trend that meets the preset conditions are used as the target meteorological parameters.
3. The method according to claim 1, characterized in that, The process of repeatedly adjusting the initial parameter value based on the sensitivity coefficient to obtain multiple updated forecast schemes includes: According to the preset reduction range, the initial parameter values are gradually adjusted to obtain multiple candidate parameter values corresponding to each target meteorological parameter; By arranging and combining all candidate parameters and initial parameter values, multiple updated forecast schemes are obtained.
4. The method according to claim 1, characterized in that, The calculation of the forecast score for each of the updated forecast schemes includes: For each updated forecast scheme, obtain the forecast results for freezing rain forecast using the updated forecast scheme; the forecast results include the number of correct forecasts, the number of false alarms, and the number of missed forecasts; The forecast score of each of the updated forecast schemes is obtained based on the forecast results; the forecast score is used to characterize the forecast performance of the updated forecast scheme.
5. The method according to claim 1, characterized in that, The step of obtaining the target forecast scheme based on the forecast score includes: Obtain multiple altitude regions; For each altitude region, the candidate forecasting scheme with the highest forecasting score for that altitude region is selected as the target forecasting scheme for that altitude region.
6. The method according to claim 5, characterized in that, The freezing rain forecasting using the target forecasting scheme includes: Obtain the regional elevation of the precipitation area and determine the target elevation area that matches the regional elevation. Freezing rain forecasts are performed on the precipitation area using the target forecasting scheme corresponding to the target altitude region.
7. A precipitation forecasting device based on meteorological parameters, characterized in that, The device includes: The sensitivity testing module is used to perform sensitivity tests on each meteorological parameter, obtain the sensitivity coefficient of each meteorological parameter to the forecast score, and determine the target meteorological parameter from all meteorological parameters based on the sensitivity coefficient. The parameter adjustment module is used to obtain the initial parameter values corresponding to each target meteorological parameter in the initial forecast scheme, and repeatedly adjust the initial parameter values according to the sensitivity coefficient to obtain multiple updated forecast schemes. The freezing rain forecast module is used to calculate the forecast score of each of the updated forecast schemes, obtain the target forecast scheme based on the forecast score, and perform freezing rain forecasting through the target forecast scheme.
8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.
10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.