Short and temporary rainfall early warning method and system based on Beidou signal water vapor inversion

Abstract

The invention discloses a short and temporary rainfall early warning method and system based on Beidou signal water vapor inversion, and the method comprises the steps: obtaining and analyzing Beidou signal data of a target region, and obtaining zenith total delay data of the target region; acquiring and analyzing ground meteorological data of the target area, and determining zenith dry delay data of the target area; determining atmospheric precipitable water amount data of the target area based on the zenith total delay data and the dry delay data; determining data characteristics of the atmospheric precipitable water amount data, and evaluating the rainfall intensity of the target area based on the data characteristics to obtain a rainfall intensity evaluation value; and determining a rainfall level based on the rainfall intensity evaluation value, and determining a rainfall early warning scheme of the target area based on the rainfall level. According to the invention, the positioning service capability of the Beidou system is successfully expanded to the field of meteorological disaster prevention and reduction, and precursor signals of rapid accumulation, convergence and the like of water vapor before rainfall can be captured, so that a potential heavy rainfall area can be extracted and identified, and the effective prediction period of short-term and imminent forecasting is obviously prolonged.

Description

TECHNICAL FIELD

[0001] The present application relates to the meteorological monitoring technical field, in particular to a short-approaching rainfall early warning method and system based on Beidou signal water vapor inversion. BACKGROUND

[0002] Short-approaching rainfall, especially the sudden and local severe convective weather, is a major challenge in the traditional meteorological forecasting field. Its life history is short and develops rapidly, which brings great threat to city operation, transportation, agricultural production and people's life and property safety.

[0003] However, the traditional short-approaching forecast mainly relies on the extrapolation of weather radar and satellite cloud images, which is essentially a "tracking" of the rainfall phenomenon that has occurred. The prediction period is limited, it is difficult to capture the early stage of the rainstorm system, and the response to sudden rainfall events is slow, and the early warning has serious lag. SUMMARY

[0004] In order to solve the above technical problems, the present application provides a short-approaching rainfall early warning method and system based on Beidou signal water vapor inversion, comprising:

[0005] Obtain the Beidou signal data of the target area, and analyze the Beidou signal data to obtain the zenith total delay data of the target area;

[0006] Obtain the ground meteorological data of the target area, and analyze the ground meteorological data to determine the zenith dry delay data of the target area;

[0007] Analyze and calculate the zenith total delay data and the dry delay data of the target area to obtain the atmospheric precipitable water data of the target area;

[0008] Analyze the atmospheric precipitable water data, determine the data characteristics, and evaluate the rainfall intensity of the target area based on the data characteristics to obtain the rainfall intensity evaluation value of the target area;

[0009] Determine the rainfall grade of the target area based on the rainfall intensity evaluation value, and determine the rainfall early warning scheme of the target area based on the rainfall grade.

[0010] Further, the Beidou signal data of the target area is obtained, and the Beidou signal data of the target area is analyzed to obtain the zenith total delay data of the target area, comprising:

[0011] Obtain the Beidou signal data of the target area, and determine the actual propagation time value of each Beidou satellite signal received by the target area in each time node from the Beidou signal data of the target area;

[0012] determining a theoretical propagation time value of each Beidou satellite signal received by the target region at each time node, and calculating a difference between the actual propagation time value and the theoretical propagation time value;

[0013] comprehensively calculating the differences based on a pre-designed calculation model to obtain a zenith total delay value of the target region at each time node;

[0014] collecting the zenith total delay values of the target region at each time node in time sequence to obtain the zenith total delay data of the target region.

[0015] Further, the ground meteorological data of the target region is acquired and analyzed to determine the zenith wet delay data of the target region, including:

[0016] The ground meteorological data of the target region is acquired, and the ground pressure value, geographical latitude value and ellipsoidal height value of the target region at each time node are determined from the ground meteorological data of the target region;

[0017] The zenith wet delay value of the target region at each time node is calculated based on the ground pressure value, geographical latitude value and ellipsoidal height value;

[0018] The zenith wet delay values of the target region at each time node are collected in time sequence to obtain the zenith wet delay data of the target region.

[0019] Further, the calculation formula of the zenith wet delay value is:

[0020] ,

[0021] Wherein, ZHD is the zenith wet delay value of the target region, P0 is the ground pressure value of the target region, is the geographical latitude value of the target region, and H is the ellipsoidal height value of the target region.

[0022] Further, the zenith total delay data and the wet delay data of the target region are analyzed and calculated to obtain the atmospheric precipitable water data of the target region, including:

[0023] The zenith total delay data and the wet delay data of the target region are aligned according to the time nodes, and the difference between the zenith total delay value and the zenith wet delay value of the target region at each time node is calculated in time sequence to obtain the zenith wet delay value of the target region at each time node;

[0024] A preset conversion coefficient of the target region is determined, and the zenith wet delay value of the target region at each time node is multiplied by the preset conversion coefficient to obtain the atmospheric precipitable water value of the target region at each time node;

[0025] The atmospheric precipitable water value of the target region at each time node is collected in time sequence to obtain atmospheric precipitable water data of the target region.

[0026] Further, the atmospheric precipitable water data is analyzed to determine data characteristics, and the rainfall intensity of the target region is evaluated based on the data characteristics to obtain a rainfall intensity evaluation value of the target region, including:

[0027] A data change curve graph of the time progress is constructed based on the atmospheric precipitable water data, and peak points and valley points in the data change curve graph are determined;

[0028] The data change curve graph is divided into a plurality of curve segments based on the peak points and the valley points, and an upward curve segment from a valley point to a peak point is determined from the curve segments;

[0029] The slope value and the change amplitude value of the upward curve segment are calculated, and the maximum value of the upward curve segment is determined;

[0030] The slope value of the upward curve segment is normalized to obtain a change coefficient of the upward curve segment, and a reference change amplitude value and a reference maximum value are determined;

[0031] The difference between the change amplitude value and the reference change amplitude value and the maximum value and the reference maximum value of the upward curve segment is calculated respectively, and the calculated difference is evaluated to obtain a change amplitude difference evaluation value and a maximum difference evaluation value of the upward curve segment;

[0032] The rainfall intensity evaluation value of the target region is calculated based on the change coefficient, the change amplitude difference evaluation value, and the maximum difference evaluation value of the upward curve segment.

[0033] Further, the calculation formula of the rainfall intensity evaluation value of the target region is:

[0034] ,

[0035] Wherein, D is the rainfall intensity evaluation value of the target region, k is the change coefficient of the upward curve segment, a is the first preset weight, X is the change amplitude difference evaluation value of the upward curve segment, b is the second preset weight, and Y is the maximum difference evaluation value of the upward curve segment.

[0036] Further, the rainfall intensity evaluation value is determined based on the rainfall intensity evaluation value to determine the rainfall grade of the target region, including:

[0037] A preset rainfall grade-rainfall intensity evaluation value interval correspondence is preset, and the preset rainfall grade-rainfall intensity evaluation value interval correspondence is associated with a corresponding preset rainfall grade for each rainfall intensity evaluation value interval.

[0038] The rainfall intensity evaluation value of the target area is obtained, and a preset rainfall grade corresponding to the rainfall intensity evaluation value interval is determined as the rainfall grade of the target area based on a mapping relationship in a preset rainfall grade-rainfall intensity evaluation value interval correspondence relationship within which the rainfall intensity evaluation value interval to which the rainfall intensity evaluation value belongs.

[0039] Further, the rainfall warning scheme of the target area is determined based on the rainfall grade, and includes:

[0040] If the rainfall grade of the target area is less than the first preset grade, the rainfall warning scheme of the target area is to issue a blue attention level warning prompt;

[0041] If the rainfall grade of the target area is greater than the first preset grade and less than the second preset grade, the rainfall warning scheme of the target area is to issue a yellow warning level warning prompt;

[0042] If the rainfall grade of the target area is greater than the second preset grade and less than the third preset grade, the rainfall warning scheme of the target area is to issue an orange warning level warning prompt;

[0043] If the rainfall grade of the target area is greater than or equal to the fourth preset grade, the rainfall warning scheme of the target area is to issue a red emergency level warning prompt.

[0044] The application also provides a short-term rainfall warning system based on Beidou signal water vapor inversion, which includes:

[0045] The first acquisition module is used to acquire the Beidou signal data of the target area, and perform data analysis on the Beidou signal data to obtain the zenith total delay data of the target area;

[0046] The second acquisition module is used to acquire the ground meteorological data of the target area, and analyze the ground meteorological data to determine the zenith dry delay data of the target area;

[0047] The calculation module is used to analyze and calculate the zenith total delay data and the dry delay data of the target area to obtain the atmospheric precipitable water data of the target area;

[0048] The evaluation module is used to analyze the atmospheric precipitable water data, determine the data characteristics, and evaluate the rainfall intensity of the target area based on the data characteristics to obtain the rainfall intensity evaluation value of the target area;

[0049] The warning module is used to determine the rainfall grade of the target area based on the rainfall intensity evaluation value, and determine the rainfall warning scheme of the target area based on the rainfall grade.

[0050] Compared with the prior art, the short-term rainfall warning method and system based on Beidou signal water vapor inversion has the beneficial effects that:

[0051] The application obtains zenith total delay by analyzing Beidou signals, and accurately deducts dry delay combined with ground meteorological data, finally inverts atmospheric precipitable water, converts satellite navigation signals into millimeter-level precision atmospheric water vapor content data, realizes real-time, continuous and quantitative monitoring of water vapor distribution of a target area, and overcomes the limitation of low spatial and temporal resolution of traditional sounding observation;

[0052] The application captures key water vapor signs before rainfall by analyzing the spatial and temporal variation characteristics of atmospheric precipitable water, and the "cause and effect" prediction idea significantly prolongs the effective prediction period of short-term prediction compared with the traditional method of relying on radar echo extrapolation, and gains valuable time for disaster prevention and risk avoidance.

[0053] The application establishes a quantitative evaluation model from water vapor data to rainfall intensity based on the statistical relationship between water vapor characteristics and rainfall intensity, converts continuous water vapor observation data into discrete rainfall grade judgment, eliminates the uncertainty of subjective experience judgment, and improves the standardization and reproducibility of the prediction conclusion.

[0054] The application directly maps technical observation indicators into a graded early warning scheme, ensures that monitoring and prediction results can be efficiently converted into actual actions for disaster prevention and mitigation, and forms a complete business closed loop of monitoring-prediction-early warning-response.

[0055] The application can timely trigger high-level warnings by capturing explosive growth of water vapor, effectively makes up for the defects of traditional prediction methods in sudden rainstorm prediction, and significantly improves the defense level of urban waterlogging, mountain torrents and other derivative disasters. BRIEF DESCRIPTION OF DRAWINGS

[0056] Figure 1 is a flow structure schematic diagram of a short-term rainfall early warning method based on water vapor inversion of Beidou signals in the embodiment of the application.

[0057] Figure 2 is a composition schematic diagram of a short-term rainfall early warning system based on water vapor inversion of Beidou signals in the embodiment of the application. DETAILED DESCRIPTION

[0058] The specific embodiments of the application will be further described in detail below in combination with the drawings and examples. The following examples are used to illustrate the application, but not to limit the scope of the application.

[0059] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the platform 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 this application.

[0060] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0061] like Figure 1 As shown in the embodiments of this application, a short-term precipitation warning method based on BeiDou signal water vapor inversion is provided, including: S100: acquiring BeiDou signal data of the target area and parsing the BeiDou signal data to obtain the total zenith delay data of the target area; S200: acquiring surface meteorological data of the target area and analyzing the surface meteorological data to determine the zenith dry delay data of the target area; S300: analyzing and calculating the total zenith delay data and dry delay data of the target area to obtain atmospheric precipitable water data of the target area; S400: analyzing the atmospheric precipitable water data, determining data characteristics, and evaluating the precipitation intensity of the target area based on the data characteristics to obtain the precipitation intensity assessment value of the target area; S500: determining the precipitation level of the target area based on the precipitation intensity assessment value, and determining the precipitation warning scheme of the target area based on the precipitation level.

[0062] Further, the application obtains zenith total delay by analyzing Beidou signals, and accurately deducts dry delay combined with ground meteorological data, finally inverts atmospheric precipitable water, converts satellite navigation signals into millimeter-level atmospheric water vapor content data, realizes real-time, continuous and quantitative monitoring of water vapor distribution of the target area, and overcomes the limitation of low spatial and temporal resolution of traditional sounding observation; the application analyzes the spatial and temporal variation characteristics of atmospheric precipitable water, captures the key water vapor signs before rainfall, and the "cause and effect" prediction idea significantly prolongs the effective prediction period of short-term prediction compared with the traditional method of relying on radar echo extrapolation, which saves valuable time for disaster prevention and risk avoidance; the application establishes a quantitative evaluation model from water vapor data to rainfall intensity based on the statistical relationship between water vapor characteristics and rainfall intensity, converts continuous water vapor observation data into discrete rainfall grade judgment, eliminates the uncertainty of subjective experience judgment, and improves the standardization and reproducibility of the prediction conclusion; the application directly maps technical observation indicators into a hierarchical warning scheme, ensures that the monitoring and prediction results can be efficiently converted into practical actions for disaster prevention and mitigation, and forms a complete business closed loop of monitoring-prediction-warning-response; the application can trigger high-level warning in time by capturing the explosive growth of water vapor, effectively makes up for the defects of traditional prediction methods in sudden rainstorm prediction, and significantly improves the defense level of urban waterlogging, mountain torrents and other derivative disasters.

[0063] In the embodiment of the application, a short-term rainfall warning method based on Beidou signal water vapor inversion is provided, the Beidou signal data of a target area is obtained, and the Beidou signal data is analyzed to obtain zenith total delay data of the target area, including: obtaining the Beidou signal data of the target area, and determining the actual propagation time value of each Beidou satellite signal received by the target area at each time node from the Beidou signal data of the target area; determining the theoretical propagation time value of each Beidou satellite signal received by the target area at each time node, and calculating the difference between the actual propagation time value and the theoretical propagation time value; based on a pre-designed calculation model, the calculated difference values are comprehensively calculated to obtain the zenith total delay value of the target area at each time node; the zenith total delay values of the target area at each time node are collected in time sequence to obtain the zenith total delay data of the target area.

[0064] Specifically, the satellite signals observed by the target area Beidou receiver are continuously received, and the actual propagation time of the signals from each Beidou satellite to the ground receiver is accurately determined; based on the accurate satellite orbit ephemeris, the known coordinates of the receiver and the complete physical correction model, the theoretical propagation time of the signals in the vacuum environment is calculated, and the measured and theoretical time difference of each satellite signal is calculated one by one, and the comprehensive delay effect of the troposphere and ionosphere on the signals is accurately quantified; these path delay data from different directions and different elevation angles are input into a precise parameter estimation model for comprehensive solution, which can effectively separate various error sources and finally calculate the complex slant path delay into a standardized total delay amount pointing to the zenith direction, thereby outputting the zenith total delay sequence varying with time. This step successfully converts the error sources in the navigation satellite signals into valuable observation information, achieving high-precision, all-weather and near-real-time remote sensing monitoring of the atmospheric state; the generated zenith total delay data time sequence not only has a measurement accuracy of millimeters, but also achieves a high time resolution of minutes, which can clearly capture the rapid and subtle changes in the atmospheric state; this technology lays an irreplaceable data foundation for the inversion of core meteorological elements and provides a crucial prerequisite for subsequent accurate separation of water vapor signals and reliable short-term rainfall warning.

[0065] In the embodiments of the present application, a short-term rainfall warning method based on Beidou signal water vapor inversion is provided, which comprises: acquiring ground meteorological data of a target area, and analyzing the ground meteorological data to determine zenith dry delay data of the target area, comprising: acquiring ground meteorological data of a target area, and determining ground pressure values, geographical latitude values and ellipsoidal height values of the target area in each time node from the ground meteorological data of the target area; calculating based on the ground pressure values, geographical latitude values and ellipsoidal height values to obtain the zenith dry delay values of the target area in each time node; collecting the zenith dry delay values of the target area in each time node in time sequence to obtain the zenith dry delay data of the target area.

[0066] Specifically, the time series data provided by the target area ground meteorological observation station is acquired, and the ground pressure value, geographical latitude value and ellipsoidal height value at each time node are accurately extracted therefrom; based on these key parameters, the signal delay caused by the dry air component in the atmosphere is estimated, and the global gravity field change is precisely corrected using the geographical latitude and ellipsoidal height value to eliminate the subtle influence of different geographical positions and altitudes; a corresponding and quantitative zenith dry delay value is generated for each time node, and finally these delay values arranged in time series are integrated to form a complete and continuous zenith dry delay dataset. This step successfully converts the easily obtained ground meteorological parameters into a high-precision estimation of the stable component in the tropospheric delay; the calculation result has a remarkable precision of millimeter level, which provides an essential reference for effectively separating the changing water vapor signal from the total delay; the dry air is relatively stable in space-time distribution, which makes the calculation result based on the model extremely reliable and avoids the jumps and noises that may occur in direct observation; by generating this high-precision and high-stability dry delay data, the key factor, atmospheric precipitable water, which determines the occurrence of rainfall, is accurately inverted, which clears the main obstacle and lays an indispensable quantitative foundation.

[0067] In the embodiments of the present application, a short-term rainfall warning method based on Beidou signal water vapor inversion is provided, and the calculation formula of the zenith dry delay value is:

[0068] ,

[0069] Wherein, ZHD is the zenith dry delay value of the target area, P0 is the ground pressure value of the target area, is the geographical latitude value of the target area, and H is the ellipsoidal height value of the target area.

[0070] In the embodiments of the present application, a short-term rainfall warning method based on Beidou signal water vapor inversion is provided, and the zenith total delay data and dry delay data of the target area are analyzed and calculated to obtain the atmospheric precipitable water data of the target area, including: aligning the zenith total delay data and dry delay data of the target area according to the time nodes, and calculating the difference between the zenith total delay value and the zenith dry delay value of the target area at each time node in time sequence to obtain the zenith wet delay value of the target area at each time node; determining a preset conversion coefficient of the target area, and multiplying the zenith wet delay value of the target area at each time node by the preset conversion coefficient to obtain the atmospheric precipitable water value of the target area at each time node; and collecting the atmospheric precipitable water values of the target area at each time node in time sequence to obtain the atmospheric precipitable water data of the target area.

[0071] Specifically, the zenith total delay value and the zenith wet delay value at the same time node are accurately aligned and the difference is calculated, and the zenith wet delay value caused purely by the water vapor component in the atmosphere is successfully separated through the rigorous physical relationship of total delay-wet delay; the conversion coefficient determined in advance based on local climate characteristics and atmospheric profile data is used to multiply the wet delay value at each time node by the conversion coefficient, thereby realizing the accurate conversion from signal delay to the more meteorologically meaningful physical quantity, atmospheric precipitable water; the instantaneous PWV values are integrated in time sequence to construct an atmospheric precipitable water data set that fully reflects the continuous change of the total water vapor content in the target area. This step effectively removes the interference of stable gas components by accurately separating dry and wet delays, so that the weak signal of the active meteorological element of water vapor can be highlighted. The atmospheric precipitable water data generated ultimately not only provides millimeter-level precision water vapor total amount information, but also has a minute-level high time resolution, which can clearly capture the fine change process of rapid accumulation and convergence of water vapor; the abstract satellite signal delay is converted into a direct and intuitive water vapor parameter that can be directly used for meteorological analysis, providing the most direct and reliable decision basis for subsequent rainfall mechanism analysis, strong weather identification and short-impending forecast and warning, and laying a solid data foundation.

[0072] In the embodiments of the present application, a short-impending rainfall warning method based on Beidou signal water vapor inversion is provided, which analyzes the atmospheric precipitable water data, determines the data characteristics, and evaluates the rainfall intensity of the target area based on the data characteristics to obtain the rainfall intensity evaluation value of the target area, including: constructing a time schedule data change curve graph based on the atmospheric precipitable water data, and determining the peak point and valley point in the data change curve graph; based on the peak point and the valley point, the data change curve graph is divided into a plurality of curve segments, and an ascending curve segment from the valley point to the peak point is determined from the curve segments; the slope value and the change amplitude value of the ascending curve segment are calculated, and the maximum value of the ascending curve segment is determined; the slope value of the ascending curve segment is normalized to obtain the change coefficient of the ascending curve segment, and the reference change amplitude value and the reference maximum value are respectively determined; the difference between the change amplitude value and the reference change amplitude value and the maximum value and the reference maximum value of the ascending curve segment is calculated, and the calculated difference is evaluated to obtain the change amplitude difference evaluation value and the maximum difference evaluation value of the ascending curve segment; based on the change coefficient, the change amplitude difference evaluation value and the maximum difference evaluation value of the ascending curve segment, the rainfall intensity evaluation value of the target area is calculated.

[0073] Specifically, a curve graph of the atmospheric precipitable water content changing over time is constructed, the peak and valley points in the fluctuation thereof are accurately identified, and the rising curve segment from the valley to the peak is extracted as the key analysis object, which intuitively reflects the rapid accumulation process of water vapor; the slope (reflecting the accumulation rate) and the change amplitude (reflecting the total accumulation amount) of the rising segment are calculated synchronously, and the peak level is recorded; in order to eliminate the background differences of regions and seasons, the slope is normalized to obtain a universal change coefficient, and the change amplitude and the peak value are compared with the local historical reference value to calculate the change amplitude difference evaluation value and the peak difference evaluation value, respectively; the three-dimensional indexes of the change coefficient, the amplitude difference and the peak difference are integrated and calculated through a calculation model to output a comprehensive rainfall intensity evaluation value. This step realizes the multi-feature fusion judgment from water vapor data to rainfall intensity, effectively avoids the misjudgment of a single index through the triple constraints of rate, total amount and extreme value; this step has strong self-adaptability, and through normalization processing and comparison with the local reference value, the evaluation model can adapt to the climate background characteristics of different regions and different seasons; this step establishes a quantitative evaluation scale, converts the continuous and abstract water vapor change curve into a specific and operable intensity evaluation value, provides a scientific basis for accurate division of the warning level, and significantly improves the objectivity and accuracy level of short- and long-range rainfall forecast.

[0074] In the embodiments of the present application, a short- and long-range rainfall warning method based on Beidou signal water vapor inversion is provided, and the calculation formula of the rainfall intensity evaluation value of the target area is:

[0075] ,

[0076] wherein D is the rainfall intensity evaluation value of the target area, k is the change coefficient of the rising curve segment, a is the first preset weight, X is the change amplitude difference evaluation value of the rising curve segment, b is the second preset weight, and Y is the maximum difference evaluation value of the rising curve segment.

[0077] In the embodiments of the present application, a short- and long-range rainfall warning method based on Beidou signal water vapor inversion is provided, and the rainfall grade of the target area is determined based on the rainfall intensity evaluation value, which comprises: presetting a preset rainfall grade-rainfall intensity evaluation value interval correspondence relationship, and each rainfall intensity evaluation value interval is associated with a corresponding preset rainfall grade; obtaining the rainfall intensity evaluation value of the target area, and selecting the preset rainfall grade corresponding to the rainfall intensity evaluation value interval as the rainfall grade of the target area based on the mapping relationship of the rainfall intensity evaluation value interval in the preset rainfall grade-rainfall intensity evaluation value interval correspondence relationship.

[0078] Specifically, different rainfall intensity evaluation value intervals are scientifically divided in advance according to historical meteorological data and disaster impact analysis, and corresponding rainfall grades are set for each interval to form a set of solid classification rules. After the real-time rainfall intensity evaluation value of the target area is calculated, it is compared with the preset interval threshold value, and the specific interval to which the value belongs is automatically matched and locked through logical judgment, and then the associated final rainfall grade is directly called and determined. This step ensures the high objectivity and consistency of the warning level determination, completely eliminates the randomness of human subjective judgment, so that the same meteorological conditions will trigger the same level of warning at any time and in any place. This step realizes instantaneous response and can complete grade determination at the moment of evaluation value calculation, which saves valuable time for subsequent warning information release; a highly structured decision product that can be directly understood and applied by the emergency response system is output, thereby driving the automatic operation of the entire warning process and significantly improving the efficiency and reliability of short- and short-range rainfall warning business.

[0079] In the embodiments of the present application, a short- and short-range rainfall warning method based on Beidou signal water vapor inversion is provided. The rainfall warning scheme of the target area is determined based on the rainfall grade, including: if the rainfall grade of the target area is less than the first preset grade, the rainfall warning scheme of the target area is to issue a blue attention level warning prompt; if the rainfall grade of the target area is greater than the first preset grade and less than the second preset grade, the rainfall warning scheme of the target area is to issue a yellow warning level warning prompt; if the rainfall grade of the target area is greater than the second preset grade and less than the third preset grade, the rainfall warning scheme of the target area is to issue an orange warning level warning prompt; if the rainfall grade of the target area is greater than or equal to the fourth preset grade, the rainfall warning scheme of the target area is to issue a red emergency level warning prompt.

[0080] Specifically, the automatic generation of early warning instructions is realized by setting clear level thresholds; according to the rainfall level calculated in the early stage, it is logically compared with the four preset key thresholds (first to fourth preset levels), when the level is lower than the first threshold, the blue attention level warning is started; when the level is between the first and second thresholds, the yellow warning level warning is started; when the level is further improved between the second and third thresholds, it is upgraded to the orange warning level; once the level reaches or exceeds the highest threshold, the highest level of red emergency level warning is triggered. This step completely eliminates the fuzzy zone in the early warning process through the quantitative level threshold, ensures that each level of warning corresponds to a specific atmospheric condition and disaster risk level; this step forms a standardized instruction output, which instantly converts complex monitoring data flow into clear and explicit color-coded warning signals; this highly structured warning product enables government departments, emergency agencies and the public to quickly understand the risk level without secondary interpretation, and strictly follow the preset plan to start the matching response action, from the simple reminder of the blue level to the comprehensive emergency response of the red level, thereby building a complete disaster prevention closed loop from accurate risk identification to efficient social linkage, greatly improving the timeliness and orderliness of extreme weather response.

[0081] As Figure 2 shown, in the embodiment of the present application, a short-term rainfall early warning system based on Beidou signal water vapor inversion is provided, comprising: a first acquisition module for acquiring Beidou signal data of a target area, and performing data analysis on the Beidou signal data to obtain zenith total delay data of the target area; a second acquisition module for acquiring ground meteorological data of the target area, and analyzing the ground meteorological data to determine the zenith dry delay data of the target area; a calculation module for analyzing and calculating the zenith total delay data and the dry delay data of the target area to obtain atmospheric precipitable water data of the target area; an evaluation module for analyzing the atmospheric precipitable water data, determining the data characteristics, and evaluating the rainfall intensity of the target area based on the data characteristics to obtain a rainfall intensity evaluation value of the target area; a warning module for determining the rainfall level of the target area based on the rainfall intensity evaluation value, and determining the rainfall warning scheme of the target area based on the rainfall level.

[0082] In summary, the embodiment of the present application provides a short-impending rainfall early warning method and system based on Beidou signal water vapor inversion, which comprises: obtaining and analyzing Beidou signal data of a target area to obtain zenith total delay data of the target area; obtaining and analyzing ground meteorological data of the target area to determine zenith dry delay data of the target area; determining atmospheric precipitable water data of the target area based on the zenith total delay data and the dry delay data; determining data characteristics of the atmospheric precipitable water data, and evaluating rainfall intensity of the target area based on the data characteristics to obtain a rainfall intensity evaluation value; determining a rainfall grade based on the rainfall intensity evaluation value, and determining a rainfall early warning scheme of the target area based on the rainfall grade. The positioning service capability of the Beidou system is successfully expanded to the meteorological disaster prevention and mitigation field, and the rapid accumulation, convergence and other precursor signals of water vapor before rainfall can be captured to extract and identify potential heavy rainfall areas, thereby significantly prolonging the effective prediction period of short-impending prediction.

[0083] Finally, it should be noted that: obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application also intends to include these modifications and variations.

[0084] The above is only one embodiment of the present application, but cannot limit the scope of the present application, and any structural changes made according to the present application should be considered to fall within the scope of the present application.

[0085] The term "comprising" or any other similar word is intended to cover non-exclusive inclusion, so that the process, platform, article or device / platform including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or includes elements inherent to the process, platform, article or device / platform.

[0086] So far, the technical solutions of the present application have been described in combination with the further embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to closely related technical features without departing from the principles of the present application, and the technical solutions after the changes or replacements will fall within the protection scope of the present application.

[0087] The above is only a preferred embodiment of the present application, and is not intended to limit the protection scope of the present application.

Claims

1. A short-term precipitation warning method based on water vapor inversion from BeiDou signals, characterized in that, include: Acquire BeiDou signal data for the target area and perform data parsing on the BeiDou signal data to obtain the total zenith delay data for the target area; Acquire surface meteorological data for the target area and analyze the surface meteorological data to determine the zenith dry delay data for the target area; The total zenith delay data and dry delay data of the target area are analyzed and calculated to obtain the atmospheric precipitable water data of the target area; Analyze atmospheric precipitable water data, determine data characteristics, and assess rainfall intensity in the target area based on data characteristics to obtain rainfall intensity assessment values ​​for the target area; The rainfall level of the target area is determined based on the rainfall intensity assessment value, and the rainfall warning plan for the target area is determined based on the rainfall level.

2. The short-term precipitation early warning method based on BeiDou signal water vapor inversion according to claim 1, characterized in that, The process of acquiring BeiDou signal data for the target area and parsing the BeiDou signal data to obtain the total zenith delay data for the target area includes: Acquire BeiDou signal data for the target area, and determine the actual propagation time of each BeiDou satellite signal received in the target area at each time point from the BeiDou signal data for the target area; Determine the theoretical propagation time value of each Beidou satellite signal received in the target area at each time point, and calculate the difference between the actual propagation time value and the theoretical propagation time value; Based on the preset calculation model, these differences are comprehensively calculated to obtain the total zenith delay value of the target region at each time point. The total zenith delay values ​​of the target area at each time point are collected in chronological order to obtain the total zenith delay data of the target area.

3. The short-term precipitation early warning method based on BeiDou signal water vapor inversion according to claim 2, characterized in that, The acquisition and analysis of surface meteorological data for the target area to determine the zenith dry delay data for the target area includes: Acquire surface meteorological data of the target area, and determine the surface air pressure, geographic latitude, and ellipsoidal altitude of the target area at each time point from the surface meteorological data of the target area; The zenith dry delay value of the target area at each time point is obtained by calculating the ground air pressure value, geographic latitude value and ellipsoidal height value. The zenith dry delay values ​​of the target area at each time point are collected in chronological order to obtain the zenith dry delay data of the target area.

4. The short-term precipitation early warning method based on BeiDou signal water vapor inversion according to claim 3, characterized in that, The formula for calculating the zenith dry delay value is as follows: ， Where ZHD is the zenith dry delay value of the target area, and P0 is the surface air pressure value of the target area. H represents the geographical latitude of the target area, and H represents the ellipsoidal height of the target area.

5. The short-term precipitation early warning method based on BeiDou signal water vapor inversion according to claim 3, characterized in that, The analysis and calculation of the total zenith delay data and dry delay data of the target area yields atmospheric precipitable water data for the target area, including: The total zenith delay data and dry delay data of the target area are aligned according to time nodes, and the difference between the total zenith delay value and the dry zenith delay value of the target area at each time node is calculated in chronological order to obtain the wet zenith delay value of the target area at each time node. Determine the preset conversion coefficient for the target area, and multiply the zenith wet delay value of the target area at each time node with the preset conversion coefficient to obtain the atmospheric precipitable water value of the target area at each time node; The atmospheric precipitable water values ​​of the target area at each time point are collected in chronological order to obtain the atmospheric precipitable water data of the target area.

6. The short-term precipitation early warning method based on BeiDou signal water vapor inversion according to claim 5, characterized in that, The process of analyzing atmospheric precipitable water data, determining data characteristics, and assessing rainfall intensity in the target area based on these characteristics to obtain a rainfall intensity assessment value for the target area includes: Construct a time-series data change curve based on atmospheric precipitable water data, and determine the peak and trough points in the data change curve. Based on the peak and valley points, the data change curve is divided into multiple curve segments, and the rising curve segment from the valley point to the peak point is determined from the curve segments. Calculate the slope and magnitude of change of the rising curve segment, and determine the maximum value of the rising curve segment; The slope value of the rising curve segment is normalized to obtain the variation coefficient of the rising curve segment, and the baseline variation range value and the baseline maximum value are determined respectively. Calculate the difference between the change amplitude value of the rising curve segment and the baseline change amplitude value, as well as the difference between the maximum value and the baseline maximum value. Evaluate the calculated differences to obtain the evaluation value of the change amplitude difference and the evaluation value of the maximum difference of the rising curve segment. The rainfall intensity assessment value for the target area is obtained by calculating the variation coefficient, variation range difference assessment value, and maximum difference assessment value of the rising curve segment.

7. A short-term precipitation warning method based on BeiDou signal water vapor inversion according to claim 6, characterized in that, The formula for calculating the rainfall intensity assessment value of the target area is as follows: ， Where D is the rainfall intensity assessment value of the target area, k is the variation coefficient of the rising curve segment, a is the first preset weight, X is the variation difference assessment value of the rising curve segment, b is the second preset weight, and Y is the maximum difference assessment value of the rising curve segment.

8. A short-term precipitation early warning method based on BeiDou signal water vapor inversion according to claim 6, characterized in that, The determination of the rainfall level of the target area based on the rainfall intensity assessment value includes: A preset mapping relationship between rainfall level and rainfall intensity assessment value range is established. For each rainfall intensity assessment value range, a corresponding preset rainfall level is associated with it. Obtain the rainfall intensity assessment value of the target area, and based on the mapping relationship between the rainfall intensity assessment value interval to which the rainfall intensity assessment value belongs and the preset rainfall level-rainfall intensity assessment value interval correspondence, select the preset rainfall level corresponding to the rainfall intensity assessment value interval as the rainfall level of the target area.

9. A short-term precipitation warning method based on BeiDou signal water vapor inversion according to claim 8, characterized in that, The rainfall early warning scheme based on rainfall level to determine the target area includes: If the rainfall level in the target area is lower than the first preset level, the rainfall warning plan for the target area will be to issue a blue alert level warning. If the rainfall level in the target area is greater than the first preset level but less than the second preset level, the rainfall warning plan for the target area will be to issue a yellow alert level warning. If the rainfall level in the target area is greater than the second preset level but less than the third preset level, the rainfall warning plan for the target area will be to issue an orange warning level alert. If the rainfall level in the target area is greater than or equal to the fourth preset level, the rainfall warning plan for the target area will be to issue a red emergency warning.

10. A short-term precipitation early warning system based on water vapor inversion from BeiDou signals, characterized in that, include: The first acquisition module is used to acquire BeiDou signal data of the target area and perform data parsing on the BeiDou signal data to obtain the total zenith delay data of the target area. The second acquisition module is used to acquire surface meteorological data of the target area, analyze the surface meteorological data, and determine the zenith dry delay data of the target area. The calculation module is used to analyze and calculate the total zenith delay data and dry delay data of the target area to obtain the atmospheric precipitable water data of the target area. The assessment module is used to analyze atmospheric precipitable water data, determine data characteristics, and assess the rainfall intensity of the target area based on the data characteristics to obtain the rainfall intensity assessment value of the target area. The early warning module is used to determine the rainfall level of the target area based on the rainfall intensity assessment value, and to determine the rainfall early warning plan for the target area based on the rainfall level.

Images