Tornado early warning system and method based on vortex density and critical phase transition height

Abstract

This invention discloses a tornado early warning system and method based on vortex density and critical phase transition height, including a data acquisition module, a data preprocessing module, a vortex post-phase transition parameter calculation module, a vortex ground contact determination module, a tornado formation probability quantification module, and a graded early warning module. This invention uses vortex density change as the core driving variable, coupling post-phase transition density and critical phase transition height, breaking through the limitations of traditional methods relying on macroscopic empirical parameters. It defines the critical conditions for tornado formation from a physical perspective, achieving refined quantification of tornado formation probability and significantly improving early warning accuracy and timeliness. Simultaneously, the system parameter configuration can be flexibly adjusted according to the meteorological conditions of the observation area, equipment accuracy, tornado occurrence frequency, and disaster prevention capabilities, thus flexibly adapting to different scenarios. Furthermore, all parameters can be acquired through existing meteorological equipment without additional hardware, and core calculations can be performed using conventional tools, making it easy to embed into existing early warning systems and highly scalable.

Description

Technical Field

[0001] This invention relates to the field of meteorological disaster monitoring and prediction technology, specifically to a tornado early warning system and method based on vortex density and critical phase transition height. Background Technology

[0002] Tornadoes are small-scale, strongly rotating extreme convective weather systems with instantaneous winds reaching level 12 or higher. They are characterized by their suddenness, destructive power, small impact range, and high catastrophic potential, easily causing serious casualties, building damage, and ecological destruction. They are a key focus and challenge in meteorological disaster prevention and mitigation work.

[0003] Existing tornado monitoring and forecasting technologies mainly rely on macroscopic meteorological parameters of mesocyclones, such as vertical wind shear intensity, ambient water vapor content, and mesocyclone rotation speed. They assess tornado potential by statistically analyzing the correlation between these macroscopic parameters and tornado occurrence. However, these methods have the following drawbacks: 1. They cannot explain the sudden transformation of tornadoes: some mesocyclones that meet the macroscopic warning parameters fail to develop into tornadoes, while others that do not reach the macroscopic threshold rapidly transform into tornadoes, leading to high rates of missed and false alarms. 2. They lack quantitative analysis of core driving variables: they do not consider vortex density changes as the core driving variable for tornado formation, ignoring the crucial regulatory role of the sudden density increase caused by water vapor condensation / sublimation phase transition on vortex radius and angular velocity, and failing to define the critical conditions for tornado formation from a physical perspective. 3. They have poor scenario adaptability: existing methods often use fixed statistical models, failing to consider differences in meteorological conditions and observation equipment accuracy across different regions, and cannot adjust parameter acquisition methods and analysis models according to actual scenarios. Summary of the Invention

[0004] The purpose of this invention is to provide a tornado early warning system and method based on vortex density and critical phase transition height, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a tornado early warning system based on vortex density and critical phase transition height, comprising a data acquisition module, a data preprocessing module, a vortex phase transition parameter calculation module, a vortex ground contact determination module, a tornado formation probability quantification module, a graded early warning module, a data storage module, and a system parameter configuration module. The data storage module establishes data connections with the data acquisition module, the data preprocessing module, the vortex phase transition parameter calculation module, the vortex ground contact determination module, the tornado formation probability quantification module, the graded early warning module, and the system parameter configuration module, respectively.

[0006] The data preprocessing module includes a data cleaning unit and a data transformation unit. The data cleaning unit is used to remove outliers from the original data, and the data transformation unit is used to standardize and normalize the original data.

[0007] The vortex phase transition parameter calculation module includes a latent heat determination unit, a latent heat conversion efficiency inversion calculation unit, a critical shear rate calculation unit, and a maximum density calculation unit after phase transition. The latent heat determination unit identifies the water vapor phase transition type within the vortex core based on dual-polarization radar echo characteristics, and determines the latent heat accordingly. The latent heat conversion efficiency inversion calculation unit is used to invert the latent heat conversion efficiency. The critical shear rate calculation unit is used to calculate the critical shear rate of the vortex phase transition. The maximum density calculation unit after phase transition is used to calculate the maximum density threshold after the vortex phase transition. If the latent heat determination unit identifies the phase transition type as water vapor condensing into liquid water droplets, then the latent heat is taken as the value. If the phase transition type is identified as water vapor condensing into solid snow crystals, then the latent heat is taken as... The critical shear rate calculation unit uses the following formula: in This is the critical shear velocity for vortex phase transition. The critical radius for vortex phase transition. It is the critical angular velocity; The formula used to calculate the maximum density after phase transition is as follows: in The maximum density threshold after the vortex phase transition. This is the critical phase transition density.

[0008] The latent heat conversion efficiency inversion calculation unit includes a historical case data retrieval subunit, a single-case angular velocity increase calculation subunit, a single-case conversion efficiency inversion subunit, and an outlier removal and statistical averaging subunit. The historical case data retrieval subunit retrieves a dataset of historical tornadoes of the corresponding region and phase change type from the historical database. The single-case angular velocity increase calculation subunit calculates the maximum angular velocity increase for a single case. The single-case conversion efficiency inversion subunit inverts the latent heat conversion efficiency of a single case. The outlier removal and statistical averaging subunit removes outliers according to preset criteria and calculates the average value as the final latent heat conversion efficiency. The single-case angular velocity increase calculation subunit uses the following formula: in For the first The maximum increase in vortex angular velocity in each case For the first The measured maximum angular velocity after phase transition in this case study. For the first Critical angular velocity of vortex phase transition in one case; The formula used for the single-case conversion efficiency inversion sub-unit is as follows: in For the first The latent heat conversion efficiency of each case For the first Critical radius of vortex phase transition in one case. The latent heat of the vortex phase transition; Outlier removal and statistical averaging sub-units were performed using the double standard deviation criterion on the inverted values. Latent heat conversion efficiency Outlier removal is performed by calculating all... arithmetic mean and standard deviation The formula is as follows: Then determine the normal value range: Then, outliers outside the range are removed, and the number of remaining valid cases is recorded as follows. The effective latent heat conversion efficiency set is Finally, after removing outliers The effective latent heat conversion efficiency is calculated using the arithmetic mean method, and the statistical average is used as the representative value of the latent heat conversion efficiency during the evolution of cyclonic tornadoes. The formula is as follows: in This represents the statistical average of latent heat conversion efficiency. The number of valid tornado cases, For the first The latent heat conversion efficiency of one effective case.

[0009] The vortex-to-ground contact determination module includes an atmospheric buoyancy critical density acquisition unit, a density breakthrough ratio calculation unit, and a determination result output unit. The atmospheric buoyancy critical density acquisition unit calculates the atmospheric buoyancy critical density by combining regional altitude, temperature, humidity, and air pressure parameters. The density breakthrough ratio calculation unit calculates the density breakthrough ratio. The determination result output unit outputs the determination result based on the density breakthrough ratio. The calculation formula is as follows: in This represents the maximum density after the phase transition. The critical density for atmospheric buoyancy; the judgment rule for the output unit of the judgment result is: if If the vortex can overcome atmospheric buoyancy and fall from high altitude to the ground, it possesses the physical conditions to form a tornado upon impact. If the vortex is supported by atmospheric buoyancy and cannot fall, there is no risk of tornado formation (the risk of tornado formation is extremely low).

[0010] The tiered early warning module includes an early warning level mapping unit, an intelligent early warning content generation unit, and a multi-channel early warning release unit. The early warning level mapping unit is used to map the real-time generated probability to the corresponding early warning level based on the probability threshold configured according to the scenario. It also adjusts the early warning level according to the scenario by combining regional population density and disaster prevention and mitigation capabilities. The intelligent early warning content generation unit is used to extract the core elements of the early warning, including the probability of tornado formation, the affected area, the time of impact, the early warning timeliness, and the wind force level forecast. It generates differentiated early warning text content for different user types. At the same time, it generates targeted disaster prevention and avoidance guidance suggestions by combining the early warning level and the characteristics of the affected area. The multi-channel early warning release unit is used to connect with public channels, meteorological departments, and emergency departments to release early warning information simultaneously.

[0011] The system parameter configuration module includes a scene type management unit, a calculation parameter configuration unit, a hierarchical and fitting model configuration unit, and a warning level threshold configuration unit. The scene type management unit is used to preset geographical scenes, accuracy scenes, tornado frequency scenes, and disaster prevention capability scenes. The calculation parameter configuration unit is used to configure the specific latent heat standard value and latent heat conversion efficiency inversion rules corresponding to different phase change types. The hierarchical and fitting model configuration unit is used to configure the hierarchical rules and probability statistics function fitting models. The warning level threshold configuration unit is used to configure the warning level system, the tornado generation probability threshold corresponding to each warning level, and the warning release timeliness and update frequency corresponding to different warning levels.

[0012] The tornado early warning method based on vortex density and critical phase transition height includes the following steps: Step 1, obtaining vortex critical phase transition parameters; Step 2, calculating vortex parameters after phase transition; Step 3, determining vortex impact and descent; Step 4, quantifying tornado generation probability; and Step 5, issuing graded early warnings. In step one above, the data acquisition module obtains the core parameters of the critical phase transition moment of the vortex, including the critical phase transition density. Critical phase transition radius Critical phase transition angular velocity Atmospheric critical buoyancy density Critical phase transition height ; In step two above, the parameter calculation module after the vortex phase transition determines the type of vortex phase transition and calculates the latent heat conversion efficiency. Critical shear rate of phase transition Maximum density after phase transition ; In step three above, the vortex-to-ground determination module calculates the atmospheric buoyancy critical density and density breakthrough ratio to determine whether a tornado will be generated. If so, it proceeds to step four; otherwise, it returns to step one for continuous monitoring. In step four above, the critical height of the vortex phase transition will be monitored in real time. Input the tornado generation probability quantization module, and the tornado generation probability quantization module outputs the real-time tornado generation probability; In step five above, the graded early warning module classifies the early warning level and issues early warning information based on the real-time tornado generation probability obtained in step four.

[0013] In step one, the critical phase transition radius Determined by the radial range of the echo from the dual-polarization radar, and ,in The overall characteristic radius of the vortex, and the critical phase transition density. The critical phase transition angular velocity was obtained through radar differential reflectivity inversion. Critical phase transition height obtained through Doppler radar inversion. Altitude is obtained through radar echo inversion.

[0014] In step four, the tornado generation probability quantification module calculates the real-time generation probability using a constructed piecewise statistical function. The construction steps of the piecewise statistical function are as follows: 4.1 Data Preparation: Collect data including , The historical vortex-tornado cases that generate binary classification results for tornadoes are used to uniformly calculate the scores of all cases. value; 4.2 Layered processing: Determine minimum value Maximum value Divided into equal intervals Layers, arranging cases by They are categorized into their corresponding levels, and then further subdivided within each level. Equidistant layers were obtained Given several intervals, find the median of each interval. As this interval The representative value; 4.3 Interval Probability Calculation: [The text abruptly ends here, likely due to an incomplete sentence The ratio of the number of tornado occurrences within a given interval to the total number of occurrences is used as the initial probability for that interval. ,right Apply range constraints: hour, Take 0.05, hour, Take 1; 4.4 Function Fitting: A negative correlation monotonic model was used as the fitting model, with... For independent variable, As the dependent variable, the following were obtained through fitting: The probability statistics function of tornado generation corresponding to each level , ... By integrating the fitting formulas of each layer, a piecewise statistical function is formed: The range of all statistical functions is constrained to be... .

[0015] Compared with existing technologies, the advantages of this invention are as follows: This invention uses vortex density change as the core driving variable, coupling the density after phase transition with the critical phase transition height, breaking through the limitations of traditional reliance on macroscopic empirical parameters, defining the critical conditions for tornado formation from a physical essence, realizing the refined quantification of tornado formation probability, and significantly improving the accuracy and timeliness of early warning; at the same time, the system parameter configuration can be flexibly adjusted according to the meteorological conditions of the observation area, equipment accuracy, tornado occurrence frequency, and disaster prevention capabilities, thereby flexibly adapting to different scenarios; and all parameters can be obtained through existing meteorological equipment without the need for additional hardware, the core calculation can be achieved through conventional tools, it is easy to embed into existing early warning business systems, and has strong scalability. Attached Figure Description

[0016] Figure 1 This is a system structure block diagram of the present invention; Figure 2 This is a block diagram of the vortex phase transition parameter calculation module of the present invention; Figure 3 This is a structural block diagram of the vortex ground contact determination module of the present invention; Figure 4 This is a structural block diagram of the graded early warning module of the present invention; Figure 5 This is a block diagram of the system parameter configuration module of the present invention; Figure 6 This is a flowchart of the method of the present invention.

[0017] In the diagram: 1. Data acquisition module; 2. Data preprocessing module; 21. Data cleaning unit; 22. Data conversion unit; 3. Parameter calculation module after vortex phase transition; 31. Latent heat determination unit; 32. Latent heat conversion efficiency inversion calculation unit; 321. Historical case data retrieval subunit; 322. Single case angular velocity increase calculation subunit; 323. Single case conversion efficiency inversion subunit; 324. Outlier removal and statistical averaging subunit; 33. Critical shear rate calculation unit; 34. Maximum density calculation unit after phase transition; 4. Vortex 41. Tornado Ground Contact Determination Module; 42. Atmospheric Buoyancy Critical Density Acquisition Unit; 43. Density Breakthrough Ratio Calculation Unit; 44. Determination Result Output Unit; 5. Tornado Generation Probability Quantification Module; 6. Graded Early Warning Module; 61. Early Warning Level Mapping Unit; 62. Early Warning Content Intelligent Generation Unit; 63. Multi-channel Early Warning Release Unit; 7. Data Storage Module; 8. System Parameter Configuration Module; 81. Scene Type Management Unit; 82. Calculation Parameter Configuration Unit; 83. Layered and Fitting Model Configuration Unit; 84. Early Warning Level Threshold Configuration Unit. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see the appendix Figure 1 -Appendix Figure 5This invention provides an embodiment of a tornado early warning system based on vortex density and critical phase transition height, comprising a data acquisition module 1, a data preprocessing module 2, a vortex phase transition parameter calculation module 3, a vortex ground contact determination module 4, a tornado formation probability quantification module 5, a graded early warning module 6, a data storage module 7, and a system parameter configuration module 8. The data storage module 7 establishes data connections with the data acquisition module 1, data preprocessing module 2, vortex phase transition parameter calculation module 3, vortex ground contact determination module 4, tornado formation probability quantification module 5, graded early warning module 6, and system parameter configuration module 8, respectively. The data acquisition module 1 acquires the data required for early warning, such as core parameters at the critical phase transition moment of the vortex and historical vortex-tornado cases. The data preprocessing module 2 preprocesses the raw data. The vortex phase transition parameter calculation module 3 calculates the parameters after the vortex phase transition. The vortex ground contact determination module 4 determines whether a tornado will form. The tornado formation probability quantification module 5 calculates the tornado formation probability. The graded early warning module 6 is used for... A graded early warning system is implemented based on the probability of tornado formation. Data storage module 7 stores data, and system parameter configuration module 8 configures system parameters. Data preprocessing module 2 includes a data cleaning unit 21 and a data conversion unit 22. The data cleaning unit 21 removes outliers from the original data, and the data conversion unit 22 standardizes and normalizes the original data. The vortex phase transition parameter calculation module 3 includes a latent heat determination unit 31, a latent heat conversion efficiency inversion calculation unit 32, a critical shear rate calculation unit 33, and a maximum density calculation unit 34. The latent heat determination unit 31 identifies the water vapor phase transition type within the vortex core based on dual-polarization radar echo characteristics, and determines the latent heat accordingly. The latent heat conversion efficiency inversion calculation unit 32 inverts the latent heat conversion efficiency. The critical shear rate calculation unit 33 calculates the critical shear rate of the vortex phase transition, and the maximum density calculation unit 34 calculates the maximum density threshold after the vortex phase transition. If the latent heat determination unit 31 identifies the phase transition type as water vapor condensing into liquid water droplets, then the latent heat is taken as the value. If the phase transition type is identified as water vapor condensing into solid snow crystals, then the latent heat is taken as... The critical shear rate calculation unit 33 uses the following formula: in This is the critical shear velocity for vortex phase transition. The critical radius for vortex phase transition. It is the critical angular velocity; The formula used in the maximum density calculation unit 34 after phase transition is as follows: in The maximum density threshold after the vortex phase transition. This is the critical phase transition density; The latent heat conversion efficiency inversion calculation unit 32 includes a historical case data retrieval subunit 321, a single case angular velocity increase calculation subunit 322, a single case conversion efficiency inversion subunit 323, and an outlier removal and statistical averaging subunit 324. The historical case data retrieval subunit 321 retrieves a dataset of historical tornadoes of the corresponding region and phase change type from the historical database. The single case angular velocity increase calculation subunit 322 calculates the maximum angular velocity increase for a single case. The single case conversion efficiency inversion subunit 323 inverts the latent heat conversion efficiency of a single case. The outlier removal and statistical averaging subunit 324 removes outliers according to preset criteria and calculates the average value as the final latent heat conversion efficiency. The formula used in the single case angular velocity increase calculation subunit 322 is as follows: in For the first The maximum increase in vortex angular velocity in each case For the first The measured maximum angular velocity after phase transition in this case study. For the first Critical angular velocity of vortex phase transition in one case; The formula used in the single-case conversion efficiency inversion sub-unit 323 is as follows: in For the first The latent heat conversion efficiency of each case For the first Critical radius of vortex phase transition in one case. The latent heat of the vortex phase transition ratio; outlier removal and statistical averaging sub-unit 324 are performed using the double standard deviation criterion for the inverted values. Latent heat conversion efficiency Outlier removal is performed by calculating all... Arithmetic mean and standard deviation The formula is as follows: Then determine the normal value range: Then, outliers outside the range are removed, and the number of remaining valid cases is recorded as follows. The effective latent heat conversion efficiency set is Finally, after removing outliers The effective latent heat conversion efficiency is calculated using the arithmetic mean method, and the statistical average is used as the representative value of the latent heat conversion efficiency during the evolution of cyclonic tornadoes. The formula is as follows: in This represents the statistical average of latent heat conversion efficiency. The number of valid tornado cases, For the first The latent heat conversion efficiency of a valid case; the vortex ground contact determination module 4 includes an atmospheric buoyancy critical density acquisition unit 41, a density breakthrough ratio calculation unit 42, and a determination result output unit 43. The atmospheric buoyancy critical density acquisition unit 41 is used to calculate the atmospheric buoyancy critical density by combining regional altitude, temperature, humidity, and air pressure parameters. The density breakthrough ratio calculation unit 42 is used to calculate the density breakthrough ratio. The determination result output unit 43 outputs the determination result based on the density breakthrough ratio. The formula for calculating the density breakthrough ratio is as follows: in This represents the maximum density after the phase transition. The critical density for atmospheric buoyancy; the judgment rule for the judgment result output unit 43 is: if If the vortex can overcome atmospheric buoyancy and fall from high altitude to the ground, it possesses the physical conditions to form a tornado upon impact. If the vortex is supported by atmospheric buoyancy and cannot fall, there is no risk of tornado formation. The graded early warning module 6 includes an early warning level mapping unit 61, an intelligent early warning content generation unit 62, and a multi-channel early warning release unit 63. The early warning level mapping unit 61 is used to map the real-time generated probability to the corresponding early warning level based on the probability threshold configured according to the scenario, and to adjust the early warning level according to the scenario based on the regional population density and disaster prevention and mitigation capabilities. The intelligent early warning content generation unit 62 is used to extract the core elements of the early warning, including the probability of tornado formation, the affected area, the time of impact, the early warning timeliness, and the wind force level prediction, and to generate differentiated early warning text content for different user types. At the same time, it generates targeted disaster prevention and avoidance guidance suggestions based on the early warning level and the characteristics of the affected area. The multi-channel early warning release unit 63 is used for The system connects with public channels, meteorological departments, and emergency response departments to simultaneously release early warning information. The system parameter configuration module 8 includes a scene type management unit 81, a calculation parameter configuration unit 82, a hierarchical and fitting model configuration unit 83, and an early warning level threshold configuration unit 84. The scene type management unit 81 is used to preset geographical scenes, accuracy scenes, tornado frequency scenes, and disaster prevention capability scenes. The calculation parameter configuration unit 82 is used to configure the specific latent heat standard value and latent heat conversion efficiency inversion rules corresponding to different phase change types. The hierarchical and fitting model configuration unit 83 is used to configure the hierarchical rules and probability statistics function fitting models. The early warning level threshold configuration unit 84 is used to configure the early warning level system, the tornado generation probability threshold corresponding to each early warning level, and the early warning release timeliness and update frequency corresponding to different early warning levels.

[0020] Please see the appendix Figure 6The present invention provides an embodiment of a tornado early warning method based on vortex density and critical phase transition height, comprising: step one, obtaining vortex critical phase transition parameters; step two, calculating vortex parameters after phase transition; step three, determining vortex impact and descent; step four, quantifying tornado formation probability; and step five, issuing graded early warnings. In step one above, the data acquisition module 1 acquires the core parameters at the critical phase transition moment of the vortex, including the critical phase transition density. Critical phase transition radius Critical phase transition angular velocity Atmospheric critical buoyancy density Critical phase transition height Among them, the critical phase transition radius Determined by the radial range of the echo from the dual-polarization radar, and ,in The overall characteristic radius of the vortex, and the critical phase transition density. The critical phase transition angular velocity was obtained through radar differential reflectivity inversion. Critical phase transition height obtained through Doppler radar inversion. Obtained by radar echo altitude inversion; In step two above, the parameter calculation module 3 after the vortex phase transition determines the type of vortex phase transition and calculates the latent heat conversion efficiency. Critical shear rate of phase transition Maximum density after phase transition ; In step three above, the vortex-to-ground determination module 4 calculates the atmospheric buoyancy critical density and density breakthrough ratio to determine whether a tornado will be generated. If so, step four is executed; otherwise, step one is returned for continuous monitoring. In step four above, the critical height of the vortex phase transition will be monitored in real time. Input the tornado generation probability quantization module 5, and the tornado generation probability quantization module 5 outputs the real-time tornado generation probability; wherein, the tornado generation probability quantization module 5 calculates the real-time generation probability through a constructed piecewise statistical function, and the construction steps of the piecewise statistical function are as follows: 4.1 Data Preparation: Collect data including , The historical vortex-tornado cases that generate binary classification results for tornadoes are used to uniformly calculate the scores of all cases. value; 4.2 Layered processing: Determine minimum value Maximum value Divided into equal intervals Layers, arranging cases by They are categorized into their corresponding levels, and then further subdivided within each level. Equidistant layers were obtained Given several intervals, find the median of each interval. As this interval The representative value; 4.3 Interval Probability Calculation: [The text abruptly ends here, likely due to an incomplete sentence The ratio of the number of tornado occurrences within a given interval to the total number of occurrences is used as the initial probability for that interval. ,right Apply range constraints: At that time, take 0.05. When, take 1; 4.4 Function Fitting: A negative correlation monotonic model was used as the fitting model, with... For independent variable, As the dependent variable, the following were obtained through fitting: The probability statistics function of tornado generation corresponding to each level , ... By integrating the fitting formulas of each layer, a piecewise statistical function is formed: The range of all statistical functions is constrained to be... ; In step five above, the graded early warning module 6 classifies the early warning level and issues early warning information based on the real-time tornado generation probability obtained in step four.

[0021] Based on the above, the advantages of this invention are as follows: When using this invention, the data acquisition module 1 first acquires the core parameters at the critical phase transition moment of the vortex, and the system parameter configuration module 8 completes the scenario adaptation settings in advance. The scenario type management unit 81 presets scenarios such as geography and equipment accuracy, the calculation parameter configuration unit 82 configures the phase transition and latent heat related calculation parameters, the stratification and fitting model configuration unit 83 sets the stratification and function fitting rules, and the warning level threshold configuration unit 84 defines the warning probability threshold. Subsequently, the vortex phase transition post-parameter calculation module 3 performs core calculations. The specific latent heat determination unit 31 identifies the phase transition type and matches the specific latent heat. The latent heat conversion efficiency inversion calculation unit 32 acquires historical cases through the historical case data retrieval subunit 321. The latent heat conversion efficiency inversion is completed by the single case angular velocity increase calculation subunit 322, the single case conversion efficiency inversion subunit 323, and the outlier removal and statistical averaging subunit 324. Then, the critical shear velocity calculation unit 33 and the maximum density calculation unit 34 after the phase transition calculate the critical shear velocity and the maximum density after the phase transition in sequence. Next, the vortex ground contact determination module 4 obtains the atmospheric buoyancy critical density through the atmospheric buoyancy critical density acquisition unit 41, the density breakthrough ratio calculation unit 42 calculates the density breakthrough ratio, and the determination result output unit 43 determines whether the vortex has the conditions for ground contact based on the density breakthrough ratio. The data of vortices that meet the conditions are sent to the tornado generation probability quantification module 5. The tornado generation probability quantification module 5 outputs the real-time tornado generation probability. Then, the graded early warning module 6 matches the real-time tornado generation probability to the early warning level through the early warning level mapping unit 61. The early warning content intelligent generation unit 62 generates differentiated early warning text, and the multi-channel early warning release unit 63 completes the multi-terminal release of early warning information. All data, including raw data, calculation results, and early warning records, are uniformly stored by the data storage module 7, providing complete data support for subsequent latent heat conversion efficiency inversion and model optimization. The data preprocessing module 2 is used to preprocess the acquired raw data. The data cleaning unit 21 completes the processing of outliers and missing values, and the data conversion unit 22 achieves unitarization and format standardization.

[0022] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A tornado early warning system based on vortex density and critical phase transition height, comprising a data acquisition module (1), a data preprocessing module (2), a vortex phase transition parameter calculation module (3), a vortex touchdown determination module (4), a tornado generation probability quantification module (5), a graded early warning module (6), a data storage module (7) and a system parameter configuration module (8), characterized in that: The data storage module (7) establishes data connections with the data acquisition module (1), the data preprocessing module (2), the vortex phase transition parameter calculation module (3), the vortex ground contact determination module (4), the tornado generation probability quantification module (5), the graded early warning module (6), and the system parameter configuration module (8), respectively.

2. The tornado early warning system based on vortex density and critical phase transition height according to claim 1, characterized in that: The data preprocessing module (2) includes a data cleaning unit (21) and a data conversion unit (22). The data cleaning unit (21) is used to remove outliers from the original data, and the data conversion unit (22) is used to standardize and normalize the original data.

3. The tornado early warning system based on vortex density and critical phase transition height according to claim 1, characterized in that: The vortex phase transition parameter calculation module (3) includes a latent heat determination unit (31), a latent heat conversion efficiency inversion calculation unit (32), a critical shear rate calculation unit (33), and a maximum density calculation unit (34) after phase transition. The latent heat determination unit (31) identifies the water vapor phase transition type in the vortex core based on the dual-polarization radar echo characteristics, and determines the latent heat accordingly. The latent heat conversion efficiency inversion calculation unit (32) is used to invert the latent heat conversion efficiency. The critical shear rate calculation unit (33) is used to calculate the critical shear rate of the vortex phase transition. The maximum density calculation unit (34) after phase transition is used to calculate the maximum density threshold after the vortex phase transition. If the latent heat determination unit (31) identifies the phase transition type as water vapor condensing into liquid water droplets, then it takes the latent heat. If the phase transition type is identified as water vapor condensing into solid snow crystals, then the latent heat is taken as... The critical shear rate calculation unit (33) uses the following formula: in This is the critical shear velocity for vortex phase transition. The critical radius for vortex phase transition. It is the critical angular velocity; The formula used for calculating the maximum density after phase transition (34) is as follows: Among them The maximum density threshold after vortex phase transition This is the critical phase transition density.

4. The tornado early warning system based on vortex density and critical phase transition height according to claim 3, characterized in that: The latent heat conversion efficiency inversion calculation unit (32) includes a historical case data retrieval subunit (321), a single case angular velocity increase calculation subunit (322), a single case conversion efficiency inversion subunit (323), and an outlier removal and statistical averaging subunit (324). The historical case data retrieval subunit (321) is used to retrieve the historical case dataset of tornadoes that have reached the ground in the corresponding region and phase change type from the historical database. The single case angular velocity increase calculation subunit (322) is used to calculate the maximum increase in angular velocity of a single case. The single case conversion efficiency inversion subunit (323) is used to invert the latent heat conversion efficiency of a single case. The outlier removal and statistical averaging subunit (324) is used to remove outliers according to preset criteria and calculate the average value as the final latent heat conversion efficiency. The formula used by the single case angular velocity increase calculation subunit (322) is as follows: in For the first The maximum increase in vortex angular velocity in each case For the first The measured maximum angular velocity after phase transition in this case study. For the first Critical angular velocity of vortex phase transition in one case; The formula used for the single-case conversion efficiency inversion subunit (323) is as follows: in The latent heat conversion efficiency of the first case is... Let be the critical radius of the vortex phase transition in the th case. The latent heat of the vortex phase transition; Outlier removal and statistical averaging sub-units (324) were processed using the double standard deviation criterion for the inverted values. Latent heat conversion efficiency Outlier removal is performed by calculating all... arithmetic mean and standard deviation The formula is as follows: Then determine the normal value range: Then, outliers outside the range are removed, and the number of remaining valid cases is recorded as follows. The effective latent heat conversion efficiency set is Finally, after removing outliers The effective latent heat conversion efficiency is calculated using the arithmetic mean method, and the statistical average is used as the representative value of the latent heat conversion efficiency during the evolution of cyclonic tornadoes. The formula is as follows: in This represents the statistical average of latent heat conversion efficiency. The number of valid tornado cases, For the first The latent heat conversion efficiency of one effective case.

5. The tornado early warning system based on vortex density and critical phase transition height according to claim 1, characterized in that: The vortex-to-ground contact determination module (4) includes an atmospheric buoyancy critical density acquisition unit (41), a density breakthrough ratio calculation unit (42), and a determination result output unit (43). The atmospheric buoyancy critical density acquisition unit (41) is used to calculate the atmospheric buoyancy critical density by combining regional altitude, temperature, humidity, and air pressure parameters. The density breakthrough ratio calculation unit (42) is used to calculate the density breakthrough ratio. The determination result output unit (43) outputs the determination result based on the density breakthrough ratio. The formula for calculating the density breakthrough ratio is as follows: in This represents the maximum density after the phase transition. The critical density for atmospheric buoyancy; the judgment rule of the judgment result output unit (43) is: if If the vortex can overcome atmospheric buoyancy and fall from high altitude to the ground, it possesses the physical conditions to form a tornado upon impact. If the vortex is supported by atmospheric buoyancy and cannot fall, there is no risk of tornado formation.

6. The tornado early warning system based on vortex density and critical phase transition height according to claim 1, characterized in that: The graded early warning module (6) includes an early warning level mapping unit (61), an early warning content intelligent generation unit (62), and a multi-channel early warning release unit (63). The early warning level mapping unit (61) is used to map the real-time generated probability to the corresponding early warning level according to the probability threshold configured according to the scenario, and to adjust the early warning level according to the scenario in combination with the regional population density and disaster prevention and mitigation capabilities. The early warning content intelligent generation unit (62) is used to extract the core elements of the early warning, including the probability of tornado formation, the affected area, the time of impact, the early warning timeliness, and the wind force level prediction. It generates differentiated early warning text content for different user types, and generates targeted disaster prevention and mitigation guidance suggestions in combination with the early warning level and the characteristics of the affected area. The multi-channel early warning release unit (63) is used to connect with public channels, meteorological departments and emergency departments to release early warning information simultaneously.

7. The tornado early warning system based on vortex density and critical phase transition height according to claim 1, characterized in that: The system parameter configuration module (8) includes a scene type management unit (81), a calculation parameter configuration unit (82), a hierarchical and fitting model configuration unit (83), and a warning level threshold configuration unit (84). The scene type management unit (81) is used to preset geographical scenes, accuracy scenes, tornado frequency scenes, and disaster prevention capability scenes. The calculation parameter configuration unit (82) is used to configure the specific latent heat standard value and latent heat conversion efficiency inversion rules corresponding to different phase change types. The hierarchical and fitting model configuration unit (83) is used to configure the hierarchical rules and probability statistics function fitting model. The warning level threshold configuration unit (84) is used to configure the warning level system, the tornado generation probability threshold corresponding to each warning level, and the warning release time and update frequency corresponding to different warning levels.

8. A tornado early warning method based on vortex density and critical phase transition height, comprising: Step 1, obtaining vortex critical phase transition parameters; Step 2, calculating parameters after vortex phase transition; Step 3, determining vortex impact and descent; Step 4, quantifying tornado formation probability; Step 5, issuing graded early warnings; characterized in that: In step one above, the data acquisition module (1) acquires the core parameters of the critical phase transition moment of the vortex, including the critical phase transition density. Critical phase transition radius Critical phase transition angular velocity Atmospheric critical buoyancy density Critical phase transition height ; In step two above, the parameter calculation module (3) after the vortex phase transition determines the type of vortex phase transition and calculates the latent heat conversion efficiency. Critical shear rate of phase transition Maximum density after phase transition ; In step three above, the vortex touchdown determination module (4) calculates the atmospheric buoyancy critical density and density breakthrough ratio to determine whether a tornado will be generated. If so, step four is executed; otherwise, step one is returned for continuous monitoring. In step four above, the critical height of the vortex phase transition monitored in real time is input into the tornado generation probability quantification module (5), and the tornado generation probability quantification module (5) outputs the real-time tornado generation probability. In step five above, the graded early warning module (6) divides the early warning level according to the real-time tornado generation probability obtained in step four and issues early warning information.

9. The tornado early warning method based on vortex density and critical phase transition height according to claim 8, characterized in that: In step one, the critical phase transition radius Determined by the radial range of the echo from the dual-polarization radar, and ,in The overall characteristic radius of the vortex, and the critical phase transition density. The critical phase transition angular velocity was obtained through radar differential reflectivity inversion. Critical phase transition height obtained through Doppler radar inversion. Altitude is obtained through radar echo inversion.

10. The tornado early warning method based on vortex density and critical phase transition height according to claim 8, characterized in that: In step four, the tornado generation probability quantification module (5) calculates the real-time generation probability through a constructed piecewise statistical function. The construction steps of the piecewise statistical function are as follows: 4.1 Data Preparation: Collect data including , The historical vortex-tornado cases that generate binary classification results for tornadoes are used to uniformly calculate the scores of all cases. value; 4.2 Layered processing: Determine minimum value Maximum value Divided into equal intervals Layers, including case studies According to the corresponding level, further subdivisions are made within each level. Equidistant layers were obtained Given several intervals, find the median of each interval. As this interval The representative value; 4.3 Interval Probability Calculation: [The text abruptly ends here, likely due to an incomplete sentence The ratio of the number of tornado occurrences within a given interval to the total number of occurrences is used as the initial probability for that interval. To avoid the influence of extreme values ​​caused by observation errors on the fitting results, Apply range constraints: hour, Take 0.05, hour, Take 1; 4.4 Function Fitting: A negative correlation monotonic model was used as the fitting model, with... For independent variable, As the dependent variable, the following were obtained through fitting: The probability statistics function of tornado generation corresponding to each level , ... By integrating the fitting formulas of each layer, a piecewise statistical function is formed: The range of all statistical functions is constrained to be... .

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