A tornado micro-pressure change data monitoring system and method

Abstract

The present invention discloses a tornado micro-pressure change data monitoring system and method, which relates to the technical field of micro-pressure data processing. The system includes: a regional radar activation information determination module, an optimal sampling frequency analysis module, a regional tornado micro-pressure comprehensive information determination module, a regional secondary monitoring execution module, and a regional micro-pressure early warning module. By analyzing the data collected by the micro-pressure gauge, the present invention scientifically judges the radar activation requirements, avoids resource waste, optimizes the sampling frequency of the micro-pressure gauge according to the environmental and micro-pressure observation conditions, and ensures the effectiveness of data collection. Through in-depth analysis of multi-source data, it accurately judges the micro-pressure state and provides a numerical basis for subsequent decision-making. Conducts targeted secondary monitoring when necessary to further verify the meteorological conditions. It can also issue early warning information in a timely manner, enabling relevant personnel to take preventive and response measures in advance and reducing the possible losses caused by tornadoes.

Description

Technical Field

[0001] The present invention relates to the technical field of micro-pressure data processing, and specifically to a tornado micro-pressure change data monitoring system and method. Background Art

[0002] As a highly destructive weather phenomenon, a tornado can instantaneously release huge amounts of energy, causing devastating damage to buildings and infrastructure in a short period of time and having an immeasurable impact on people's production and life. When traditional meteorological observation methods are used for this highly local and sudden weather phenomenon of tornadoes, although they can measure the radial velocity of precipitation particles to obtain airflow movement information, in terms of micro-pressure monitoring, their ability to detect micro-pressure changes not related to precipitation is limited, and it is difficult to ensure measurement accuracy. Therefore, it is necessary to construct a tornado micro-pressure change data monitoring system that uses a micro-pressure gauge in conjunction with a radar, which helps to improve tornado warning capabilities and reduce disaster losses.

[0003] The prior art, such as the invention patent with the publication number CN104778517B, is a micro-meteorological disaster warning method and system based on micro-meteorological and satellite remote sensing data. It applies satellite remote sensing technology to the monitoring of micro-meteorological disasters in the power grid, realizing the combined application of macro-meteorology and micro-meteorology. The micro-meteorological data in the ground observation database and the micro-meteorological data in the satellite remote sensing observation database are transmitted to the warning platform server through the GSM network. Through the analysis program, the measured data is deeply mined to sort out statistical information such as the maximum value, minimum value, and average value in any historical time period, and the specific information of each monitoring point is intuitively described for users in the form of graphs and curves. According to the disaster classification standard, the influence range of the disaster weather is judged, and the power grid facilities affected by the disaster weather are accurately located.

[0004] The prior art, such as the invention patent with the publication number CN109241161B, is a meteorological data management method, including: formulating the spatio-temporal resolution standard of multi-source meteorological data, and establishing a multi-dimensional grid weather data set with unified standards; establishing data processing and data conversion standards based on the spatio-temporal resolution standard of the multi-dimensional grid weather data set, and performing grid conversion on multi-source meteorological data; using Cassandra technology to establish a distributed decentralized database, aggregating the grid-converted multi-source meteorological data and dividing it into multiple nodes, and at the same time unifying all nodes to form a cluster to uniformly manage the meteorological data.

[0005] As can be seen from the above solution, in the monitoring of meteorological disaster data such as tornadoes, there are certain limitations in efficient collaborative monitoring and rational utilization of resources. Currently, there is a tendency to use monitoring equipment independently or conduct simple data correlation, often only making simple comparisons between micro-pressure data and a small number of environmental parameters. However, in actual complex meteorological monitoring scenarios, the micro-pressure monitoring of tornadoes requires comprehensive consideration of the combined effects and dynamic changes of multiple factors in all aspects and at multiple levels. The relatively independent and extensive monitoring mode is difficult to achieve an ideal level in terms of resource conservation, monitoring depth, and warning accuracy, which may lead to problems such as waste of monitoring resources, inaccurate judgment of the micro-pressure characteristics of tornadoes, and the inability of the system to flexibly respond to meteorological changes. Summary of the Invention

[0006] In view of the deficiencies of the prior art, the present invention provides a monitoring system and method for tornado micro-pressure change data, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is realized through the following technical solutions: In the first aspect of the present invention, a monitoring system for tornado micro-pressure change data is provided, including:

[0008] An area radar activation information determination module, which is used to collect area tornado micro-pressure observation data through a micro-pressure gauge, analyze the abnormal indicators of tornado micro-pressure observation, and thereby judge the area radar activation information, where the area radar activation information includes required radar activation and non-required radar activation.

[0009] An optimal sampling frequency analysis module, which is used to synchronously collect area environmental parameters when the area radar activation information is judged to be non-required radar activation, and combine the abnormal indicators of tornado micro-pressure observation to obtain the optimal sampling frequency of the micro-pressure gauge, and perform area micro-pressure monitoring at the optimal sampling frequency of the micro-pressure gauge.

[0010] An area tornado micro-pressure comprehensive information determination module, which is used to synchronously activate area radar monitoring when the area radar activation information is judged to be required radar activation, thereby obtaining area tornado micro-pressure comprehensive data, analyzing and obtaining area tornado micro-pressure abnormal correction indicators, and judging area tornado micro-pressure comprehensive information, where the area tornado micro-pressure comprehensive information includes normal micro-pressure, abnormal micro-pressure, and micro-pressure warning.

[0011] An area secondary monitoring execution module, which is used to adjust the acquisition parameters of the micro-pressure gauge and the radar respectively when the area tornado micro-pressure comprehensive information is judged to be abnormal micro-pressure, and analyze the secondary verification monitoring execution cycle in combination with the area tornado micro-pressure abnormal correction indicators, and thereby execute area secondary verification monitoring.

[0012] An area micro-pressure warning module, which is used to generate a warning message and issue a warning to a preset management terminal when the area tornado micro-pressure comprehensive information is micro-pressure warning.

[0013] In the second aspect of the present invention, a method for monitoring tornado micro-pressure change data is provided, including the following steps:

[0014] S1. Obtain regional micro-pressure observation data through a micro-pressure gauge, analyze the abnormal indicators of micro-pressure observation, and thereby judge the regional radar activation information. The regional radar activation information includes the need for radar activation and the non-need for radar activation. When the regional radar activation information is judged as the non-need for radar activation, execute S2. When the regional radar activation information is judged as the need for radar activation, execute S3;

[0015] S2. Synchronously collect regional environmental parameters, combine with the abnormal indicators of micro-pressure observation, obtain the optimal sampling frequency of the micro-pressure gauge, and perform regional micro-pressure monitoring at the optimal sampling frequency of the micro-pressure gauge;

[0016] S3. Synchronously activate regional radar monitoring, thereby obtain comprehensive regional micro-pressure data, analyze and obtain comprehensive abnormal characteristic indicators of regional micro-pressure, and judge the comprehensive regional micro-pressure information. The comprehensive regional micro-pressure information includes normal micro-pressure, abnormal micro-pressure, and micro-pressure warning. When the comprehensive regional micro-pressure information is abnormal micro-pressure, execute S4. When the comprehensive regional micro-pressure information is micro-pressure warning, execute S5;

[0017] S4. Adjust the acquisition parameters of the micro-pressure gauge and the radar respectively, and analyze the execution period of secondary verification monitoring in combination with the comprehensive abnormal characteristic indicators of regional micro-pressure, thereby perform regional secondary verification monitoring;

[0018] S5. Generate a warning message and issue a warning to a preset management terminal.

[0019] Compared with the prior art, the embodiments of the present invention have at least the following beneficial effects:

[0020] (1) By providing a tornado micro-pressure change data monitoring system and method, the present invention can achieve efficient and accurate monitoring of tornado micro-pressure, effectively improve the meteorological disaster warning ability, scientifically judge the radar activation demand by analyzing the data collected by the micro-pressure gauge, avoid resource waste, and the optimal sampling frequency analysis module can optimize the sampling frequency of the micro-pressure gauge according to the environmental and micro-pressure observation conditions to ensure the effectiveness of data acquisition. Deeply analyze multi-source data, accurately judge the micro-pressure state, and provide a numerical basis for subsequent decision-making. Conduct targeted secondary monitoring when necessary to further verify the meteorological conditions. It can also timely issue warning information, enabling relevant personnel to take preventive and response measures in advance and reducing the losses that may be brought by tornadoes.

[0021] (2) By judging the regional radar activation information, the present invention accurately determines whether the regional radar is activated, avoiding the blind activation of the radar, effectively reducing energy consumption and equipment loss, and realizing the rational allocation of monitoring resources. When the abnormal index of tornado micro-pressure observation is less than the verification index, it is determined that the radar does not need to be activated, and only the micro-pressure gauge is relied on for continuous monitoring, maintaining the conventional monitoring efficiency and saving resources. When the abnormal index is greater than or equal to the verification index, the radar is activated in a timely manner, giving full play to its detection ability for a wide range of meteorological targets such as precipitation particles and airflow movement, improving the accuracy of judging the activity characteristics, intensity and development trend of tornadoes, laying a solid data foundation for subsequent more accurate early warning decisions, and enhancing the effectiveness and reliability of the monitoring system.

[0022] (3) By judging the regional micro-pressure comprehensive information, when it is determined that the micro-pressure is normal, unnecessary resource investment and misjudgment interference are avoided. If the micro-pressure is abnormal, it helps to further accurately master the details of micro-pressure changes and the characteristics of meteorological targets, eliminate potential interference factors, and improve the accuracy of judging the potential threat of tornadoes. Once it is judged as a micro-pressure early warning, the system immediately generates and issues an early warning message, enabling relevant personnel to know in time that a tornado is coming or occurring, so as to quickly take response measures, minimizing the losses caused by tornadoes to the greatest extent, and reflecting the high efficiency and reliability of the monitoring system in dealing with tornado disasters.

[0023] Of course, it is not necessary for any product implementing the present invention to achieve all the above advantages simultaneously. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of the system module of the present invention.

[0025] Figure 2 It is a schematic diagram of the method flow of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0027] Please refer to Figure 1 As shown, the embodiments of the present invention provide a monitoring system for tornado micro-pressure change data, including:

[0028] The regional radar activation information determination module is used to collect regional tornado micro-pressure observation data through a micro-pressure gauge, analyze the abnormal indicators of tornado micro-pressure observation, and thereby determine the regional radar activation information, where the regional radar activation information includes the need to activate the radar and the non-need to activate the radar.

[0029] In this embodiment, the process of analyzing the abnormal indicators of tornado micro-pressure observation is as follows:

[0030] During a preset monitoring period, collect regional tornado micro-pressure observation data, where the regional tornado micro-pressure observation data includes the average micro-pressure value, the extreme difference in micro-pressure change, the micro-pressure change rate, the extreme difference in gravity wave amplitude change, and the extreme difference in gravity wave period length change.

[0031] It should be noted that if the average micro-pressure value shows a large deviation, such as being significantly higher or lower than the normal range, it may indicate an abnormality in the atmospheric environment, such as possible large-scale weather system changes or local strong air flow disturbances, etc.

[0032] It should be explained that the extreme difference in micro-pressure change refers to the difference between the maximum micro-pressure value and the minimum micro-pressure value during a preset monitoring period.

[0033] The extreme difference in gravity wave amplitude change refers to the difference between the maximum value and the minimum value of the recorded gravity wave amplitude during a preset monitoring period.

[0034] The extreme difference in gravity wave period length change refers to the difference between the maximum value and the minimum value of the obtained gravity wave period length during a preset monitoring period.

[0035] It should also be noted that the regional tornado micro-pressure observation data is collected by the micro-pressure gauge in real time at the second level. It should be noted that the extreme difference in gravity wave amplitude change and the extreme difference in gravity wave period length change are obtained through a five-minute sliding Fourier analysis of the data collected by the micro-pressure gauge.

[0036] It should be noted that the five-minute sliding Fourier analysis refers to, during the monitoring process, each time selecting the micro-pressure data with a continuous duration of five minutes as an analysis window and performing Fourier transform calculation on it. Through Fourier transform, the micro-pressure data sequence in the time domain is decomposed into the superposition of sine waves and cosine waves with different frequency components, so as to obtain the spectral information of the micro-pressure data within these five minutes. The spectrum contains the amplitude and phase information of various frequency components in the micro-pressure signal, and then the relevant characteristics of wave components such as gravity waves can be analyzed. After completing the analysis of this five-minute data, the time window slides forward by a certain time interval (such as one minute), and then new continuous five-minute micro-pressure data is selected for the same Fourier transform calculation. Repeating this process continuously, as time goes by, a series of spectra varying with time can be obtained, and these spectra jointly construct the three-dimensional dynamic spectrum of "period - amplitude - time" of gravity waves. This analysis method can dynamically capture the changes of characteristics such as the period and amplitude of gravity waves over time, which helps to more comprehensively and deeply understand the dynamic characteristics of gravity waves in the atmosphere and their relationship with tornado activities, providing important data basis for accurately monitoring and studying the micro-pressure changes of tornadoes.

[0037] Based on the analysis and processing of the regional tornado micro-pressure observation data, the tornado micro-pressure observation anomaly index is obtained, and the regional tornado micro-pressure observation index is used to characterize the abnormal degree of the tornado micro-pressure observation data collected by the micro-pressure gauge.

[0038] In a specific embodiment, the process of obtaining the tornado micro-pressure observation anomaly index is as follows:

[0039] Extract the reference micro-pressure observation data stored in the database. The reference micro-pressure observation data includes the ideal average micro-pressure value, the reference micro-pressure change extreme difference, the reference micro-pressure change rate, the reference gravity wave amplitude change extreme difference, and the reference gravity wave period length change extreme difference.

[0040] Based on the regional tornado micro-pressure observation data and the reference micro-pressure observation data, through comprehensive analysis and processing, the tornado micro-pressure observation anomaly index is obtained.

[0041] Among them, the specific method for obtaining the tornado micro-pressure observation anomaly index is as follows:

[0042] , where, is the tornado micro-pressure observation anomaly index, is the average micro-pressure value, is the micro-pressure change extreme difference, is the micro-pressure change rate, is the reference gravity wave amplitude change extreme difference, is the reference gravity wave period length change extreme difference, is the ideal average micro-pressure value, is the reference micro-pressure change extreme difference, is the reference micro-pressure change rate, is the extreme value difference of the change in the reference gravity wave amplitude, is the extreme value difference of the change in the reference gravity wave period length, is the weight of the average micro-pressure value, is the weight of the extreme value difference of the micro-pressure change, is the weight of the micro-pressure change rate, is the weight of the extreme value difference of the change in the gravity wave amplitude, is the weight of the extreme value difference of the change in the gravity wave period length, is the natural constant.

[0043] It should be noted that the weight of the average micro-pressure value, the weight of the extreme value difference of the micro-pressure change, the weight of the micro-pressure change rate, the weight of the extreme value difference of the change in the gravity wave amplitude, and the weight of the extreme value difference of the change in the gravity wave period length are pre-set values directly extracted from the database. The specific extraction method is to construct a special data table in the database, and correspond these weights to specific identifiers or indexes respectively. For example, different fields can be set according to the weight type, and each field stores the corresponding weight. When a certain weight needs to be extracted, an accurate query is performed in the database according to its corresponding identifier (such as the weight name or number) to obtain the required weight.

[0044] It also should be noted that the tornado micro-pressure observation anomaly index obtained by comprehensively analyzing and processing the regional tornado micro-pressure observation data takes into account the mutual influence between these parameters. For example, if the average micro-pressure value changes rapidly in a short period of time, then the micro-pressure change rate must be large. The change in the average micro-pressure value will affect the density structure and stability of the atmosphere, and thus affect the generation and propagation of gravity waves. When the average micro-pressure value shows abnormal fluctuations, it may stimulate or inhibit gravity wave activities, resulting in changes in the extreme value difference of the gravity wave amplitude change. Larger fluctuations in the average micro-pressure value may cause the gravity wave period to become unstable, increasing the extreme value difference of the gravity wave period length change. A larger extreme value difference of the micro-pressure change means that the air pressure changes violently, which is usually accompanied by a higher micro-pressure change rate. When the extreme value difference of the micro-pressure change is large, it indicates that the air pressure disturbance in the atmosphere is strong. This strong air pressure disturbance can serve as an excitation source for gravity waves, enhancing gravity wave activities, resulting in an increase in the extreme value difference of the gravity wave amplitude change. When the extreme value difference of the micro-pressure change is large, the propagation speed and propagation characteristics of the gravity wave will change, leading to instability of the gravity wave period length, and further increasing the extreme value difference of the gravity wave period length change. A rapid micro-pressure change rate means that the degree and frequency of air pressure change are high. This strong air pressure change will strongly stimulate the gravity waves in the atmosphere, prompting the gravity wave amplitude to change rapidly, thus increasing the extreme value difference of the gravity wave amplitude change. When the extreme value difference of the gravity wave amplitude change increases, it means that the gravity wave energy changes violently, which may affect the propagation characteristics of the gravity wave, and further lead to changes in the extreme value difference of the gravity wave period length change.

[0045] In a specific embodiment, by analyzing the abnormal indicators of tornado micro-pressure observations, the abnormal degree of the tornado micro-pressure observation data collected by the micro-pressure gauge can be reflected. On the one hand, efficient resource conservation is achieved. When the indicator shows that the overall fluctuation range of the micro-pressure observation data is small and within a relatively stable range, it means that the current atmospheric environment state is stable and the abnormal degree of the micro-pressure data is low. At this time, it is determined that there is no need to turn on the radar, avoiding the unnecessary startup of the radar equipment, thus saving a large amount of energy consumption and unnecessary loss of the equipment, enabling the monitoring resources to be reasonably allocated and ensuring that the resources are concentrated for the critical monitoring moments that really need them. On the other hand, accurate judgment greatly improves the monitoring efficiency and accuracy. When the indicator indicates that the micro-pressure shows abnormal changes, predicting an increase in the abnormal degree of the micro-pressure data, the radar is turned on in a timely manner, giving full play to its detection advantages for a wide range of meteorological targets such as precipitation particles and air flow movement, obtaining more key information and combining it with the micro-pressure gauge data, enabling a more comprehensive and in-depth analysis of the activity characteristics, intensity and development trend of the tornado, providing sufficient and accurate data support for subsequent early warning decisions, and effectively enhancing the ability of the entire monitoring system to respond to tornado disasters.

[0046] In this embodiment, to judge the regional radar turn-on information, the specific analysis process is as follows:

[0047] Extract the preset abnormal verification indicators for tornado micro-pressure observations in the database.

[0048] If the abnormal indicator of tornado micro-pressure observation is less than the abnormal verification indicator of tornado micro-pressure observation, then record the regional radar turn-on information as no radar turn-on required.

[0049] If the abnormal indicator of tornado micro-pressure observation is less than the abnormal verification indicator of tornado micro-pressure observation, it means that during the current monitoring period, the overall fluctuation range of the regional tornado micro-pressure observation data collected by the micro-pressure gauge is small and within a relatively stable range. The atmospheric environment state in this area is relatively stable at this time, and there is no possible abnormal trend in the micro-pressure data. Based on this situation, only relying on the micro-pressure gauge to continuously monitor in the current state can meet the basic needs, and there is no need to turn on the radar for additional monitoring, thus avoiding the energy consumption and equipment loss caused by the unnecessary startup of the radar equipment, and realizing the reasonable allocation and conservation of monitoring resources.

[0050] If the abnormal indicator of tornado micro-pressure observation is greater than or equal to the abnormal verification indicator of tornado micro-pressure observation, then record the regional radar turn-on information as radar turn-on required.

[0051] If the tornado micro-pressure observation anomaly index is greater than or equal to the tornado micro-pressure observation anomaly verification index, it indicates that the atmospheric environment in this area is very likely to be in an unstable state, and the observed micro-pressure data shows an abnormal trend. At this time, relying solely on the micro-pressure gauge can no longer comprehensively and accurately grasp the meteorological conditions. It is urgent to turn on the radar monitoring and utilize the radar's detection capabilities for more extensive meteorological targets such as precipitation particles and air flow movement to obtain more key information, which is combined with the micro-pressure gauge data to more deeply and comprehensively analyze and judge the activity characteristics, intensity, and development trend of tornadoes, providing more sufficient numerical basis for subsequent early warning decisions.

[0052] By judging the regional radar turn-on information, accurately determining whether the regional radar is turned on or not, it avoids the blind start of the radar, effectively reduces energy consumption and equipment loss, and realizes the rational allocation of monitoring resources. When the tornado micro-pressure observation anomaly index is less than the verification index, it is determined that there is no need to turn on the radar, and only rely on the micro-pressure gauge for continuous monitoring, maintaining the conventional monitoring efficiency and saving resources. When the anomaly index is greater than or equal to the verification index, the radar is turned on in a timely manner, giving full play to its detection capabilities for extensive meteorological targets such as precipitation particles and air flow movement, improving the accuracy of judging the activity characteristics, intensity, and development trend of tornadoes, laying a solid data foundation for more accurate subsequent early warning decisions, and enhancing the effectiveness and reliability of the monitoring system.

[0053] The optimal sampling frequency analysis module is used to synchronously collect regional environmental parameters when the regional radar turn-on information is judged as not requiring the radar to be turned on, and combine them with the tornado micro-pressure observation anomaly index to obtain the optimal sampling frequency of the micro-pressure gauge, and perform regional micro-pressure monitoring at the optimal sampling frequency of the micro-pressure gauge.

[0054] In this embodiment, the process of obtaining the optimal sampling frequency of the micro-pressure gauge is as follows:

[0055] During the preset monitoring period, synchronously collect regional environmental parameters, and the regional environmental parameters include average temperature, average humidity, maximum wind speed, cumulative precipitation, and average atmospheric pressure.

[0056] It should be noted that the regional environmental parameters are collected through an environmental collection device, and the environmental collection device includes a temperature sensor, a humidity sensor, a wind speed sensor, a rain gauge, and a barometer.

[0057] According to the regional environmental parameters and the tornado micro-pressure observation anomaly index, analyze and process to obtain the micro-pressure gauge sampling indication factor, and the micro-pressure gauge sampling indication factor is used to characterize the influence degree of the current regional environment on the working state of the micro-pressure gauge.

[0058] In a specific embodiment, the specific process of obtaining the micro-pressure gauge sampling indication factor is as follows:

[0059] Extract the environmental parameters of the ideal area, including the ideal average temperature, ideal average humidity, maximum reference wind speed, ideal cumulative precipitation, and ideal average atmospheric pressure.

[0060] Based on the regional environmental parameters, ideal regional environmental parameters, and tornado micro-pressure observation anomaly indicators, analyze and process to obtain the sampling indication factor of the micro-pressure gauge.

[0061] The specific method for obtaining the sampling indication factor of the micro-pressure gauge is as follows:

[0062] , where is the sampling indication factor of the micro-pressure gauge, is the tornado micro-pressure observation anomaly indicator, is the average temperature, is the average humidity, is the maximum wind speed, is the cumulative precipitation, is the average atmospheric pressure, is the ideal average temperature, is the ideal average humidity, is the maximum reference wind speed, is the ideal cumulative precipitation, is the ideal average atmospheric pressure, and e is the natural constant.

[0063] It should be noted that analyzing and processing to obtain the sampling indication factor of the micro-pressure gauge based on the regional environmental parameters and tornado micro-pressure observation anomaly indicators takes into account their mutual influence. For example, when the temperature rises, air can hold more water vapor. Under other unchanged conditions, the average humidity may increase. In a region with a higher temperature, the air rises, and the surrounding cold air replenishes to form an air current, affecting the maximum wind speed. When the temperature rises, the molecular motion of the gas intensifies, and the pressure has an increasing trend. When the water vapor content (humidity) in the air reaches the saturation state and there are enough condensation nuclei, the water vapor will condense into water droplets or ice crystals, forming precipitation and affecting the cumulative precipitation. When the humidity increases, the air quality per unit volume decreases. According to the ideal gas state equation, at a constant temperature, the air pressure will decrease accordingly. A strong horizontal wind speed can transport water vapor and precipitation particles to different regions, changing the spatial distribution of precipitation. At the same time, the wind speed affects the falling speed and trajectory of precipitation particles. When the wind speed is large, the precipitation particles will be subjected to a greater horizontal force during the falling process, which may cause the precipitation particles to break or evaporate, affecting the cumulative precipitation. When the air pressure decreases, the saturated water vapor pressure decreases, and the relative humidity may increase. The change in air pressure will cause adiabatic expansion or compression of the air, thus affecting the temperature. According to the adiabatic process equation, when the air pressure decreases, the air will adiabatically expand and do external work, and the temperature will decrease.

[0064] In a specific embodiment, by analyzing the sampling indication factors of the micro - pressure gauge, the working state of the micro - pressure gauge corresponding to the current environment of the area can be comprehensively characterized. The sampling frequency of the micro - pressure gauge can be dynamically adjusted according to different environmental conditions and the micro - pressure changes of tornadoes. When the environment is stable and the micro - pressure changes are small, over - sampling is avoided to prevent resource waste. When the environment is unstable and the micro - pressure data is abnormal, a sufficiently high sampling frequency is ensured to capture key micro - pressure change details. This not only optimizes the resource utilization efficiency of the micro - pressure gauge but also improves the accuracy and effectiveness of micro - pressure data collection, providing an accurate numerical basis for subsequent in - depth analysis of the micro - pressure change characteristics of tornadoes and accurate judgment of the tornado activity trend, and effectively enhancing the monitoring and early warning ability of the entire monitoring system for tornado disasters.

[0065] Extract the preset threshold of the sampling indication factors of the micro - pressure gauge from the database.

[0066] Perform a difference - processing on the sampling indication factors of the micro - pressure gauge and the threshold of the sampling indication factors of the micro - pressure gauge to obtain the sampling deviation factor of the micro - pressure gauge.

[0067] It should be noted that the difference - processing refers to subtracting the threshold of the sampling indication factors of the micro - pressure gauge from the sampling indication factors of the micro - pressure gauge, and the result of the difference - processing can be greater than zero, less than zero, or equal to zero.

[0068] Extract the sampling frequency adjustment values corresponding to each sampling deviation factor interval stored in the database, and map and extract the sampling frequency adjustment value corresponding to the interval where the sampling deviation factor of the micro - pressure gauge is located, denoted as the sampling frequency adjustment value of the micro - pressure gauge.

[0069] The larger the sampling deviation factor of the micro - pressure gauge, the greater the impact of the environment on the micro - pressure gauge. A larger sampling deviation factor of the micro - pressure gauge indicates strong environmental interference, and the mapped and extracted sampling frequency adjustment value is also larger. Increasing the sampling frequency can capture fine micro - pressure changes and improve the accuracy of monitoring. Conversely, the smaller the sampling deviation factor of the micro - pressure gauge, the smaller the mapped and extracted sampling frequency adjustment value. By mapping and extracting the sampling frequency adjustment value through the sampling deviation factor of the micro - pressure gauge, resource waste and data redundancy can be avoided, the equipment efficiency and data processing efficiency can be optimized, and accurate and efficient monitoring, reasonable resource utilization, and stable system operation can be ensured.

[0070] Obtain the current sampling frequency of the micro - pressure gauge, and calculate the optimal sampling frequency of the micro - pressure gauge according to the sampling frequency adjustment value of the micro - pressure gauge.

[0071] It should be noted that if the optimal sampling frequency of the micro - pressure gauge calculated according to the sampling frequency adjustment value of the micro - pressure gauge exceeds the preset rated maximum sampling frequency of the micro - pressure gauge, then the preset rated maximum sampling frequency of the micro - pressure gauge is recorded as the optimal sampling frequency of the micro - pressure gauge.

[0072] The regional tornado micro-pressure comprehensive information determination module is used to synchronously turn on the regional radar monitoring when the regional radar activation information is judged to be the required radar activation, thereby obtaining the regional tornado micro-pressure comprehensive data, analyzing to obtain the regional tornado micro-pressure anomaly correction index, and judging the regional tornado micro-pressure comprehensive information, where the regional tornado micro-pressure comprehensive information includes normal micro-pressure, abnormal micro-pressure, and micro-pressure warning.

[0073] In this embodiment, the process of obtaining the regional tornado micro-pressure comprehensive data is as follows:

[0074] During the monitoring period, micro-pressure data is collected through a micro-pressure gauge and, through five-minute sliding Fourier analysis, a three-dimensional dynamic spectrum of "period - amplitude - time" of gravity waves is obtained, thereby obtaining micro-pressure change data, where the micro-pressure change data includes the change amount of the gravity wave long-period amplitude, the change amount of the gravity wave short-period amplitude, and the maximum period length of the gravity wave. The maximum micro-pressure monitored by the micro-pressure gauge is synchronously obtained, and the micro-pressure change data and the maximum micro-pressure are jointly used as the micro-pressure gauge monitoring parameters.

[0075] The radar monitoring parameters are obtained through radar monitoring, including the maximum echo intensity, average echo intensity, average radial velocity, and maximum reflectivity factor value of the region.

[0076] It should be understood that the way to obtain the maximum echo intensity is as follows: The radar emits electromagnetic waves. When the electromagnetic waves encounter precipitation particles (such as raindrops, hailstones, etc.), dust, water vapor, and other substances inside the tornado, they will be reflected. The radar receives the reflected signal and measures its intensity, and records the echo intensity in decibels.

[0077] The way to obtain the average radial velocity is as follows: The radar calculates the radial velocity of the target (such as tornado-related substances) relative to the radar by measuring the frequency change (Doppler effect) between the emitted and reflected electromagnetic waves, records the radial velocity values within the monitoring range, and performs mean processing to obtain the average radial velocity.

[0078] The specific way to obtain the maximum reflectivity factor value is as follows: The meteorological radar emits electromagnetic wave pulses with specific frequencies and wavelengths (such as C-band or S-band) to the monitoring area. When these electromagnetic waves encounter precipitation particles, dust, water vapor, and other target objects, they are reflected and scattered. The reflected signal is received by the radar antenna and processed through amplification, filtering, etc. Then, the radar system measures its intensity, and based on parameters such as the transmitted power, antenna gain, wavelength, and the distance between the target object and the radar, calculates the reflectivity factor, which is expressed in decibels. During the process of scanning the monitoring area at multiple elevation angles and azimuth angles, the reflectivity factor values are continuously calculated and recorded, so as to extract the maximum reflectivity factor value.

[0079] It should be understood that the reflectivity factor can be directly calculated by the built-in analysis module of the radar system.

[0080] Combine the microbarometer monitoring parameters and the radar monitoring parameters as the regional tornado microbarometric comprehensive data.

[0081] In this embodiment, the regional tornado microbarometric anomaly correction index is analyzed, and the specific analysis process is as follows:

[0082] Extract the reference microbarometric comprehensive data stored in the database. The reference microbarometric data includes the change amount of the reference gravity wave long-period amplitude, the change amount of the reference gravity wave short-period amplitude, the reference gravity wave maximum period length, the reference maximum microbarometric pressure, the reference maximum echo intensity of the region, the reference average echo intensity of the region, the reference average radial velocity of the region, and the reference maximum reflectivity factor value of the region.

[0083] Based on the regional tornado microbarometric comprehensive data and the reference microbarometric comprehensive data, analyze and process to obtain the regional tornado microbarometric comprehensive anomaly characteristic value.

[0084] The regional tornado microbarometric comprehensive anomaly characteristic value is used to characterize the anomaly degree of the tornado microbarometric data during the comprehensive monitoring of the microbarometer and the radar.

[0085] It should be noted that an increase in the change amount of the gravity wave long-period amplitude indicates a change in the atmospheric wave characteristics, a disturbance in the propagation of gravity waves, leading to an imbalance in the spatial and temporal distribution of air pressure, resulting in abnormal fluctuations in the microbarometric data and deviation from the stable state. An increase in the change amount of the short-period amplitude means that small-scale meteorological fluctuations intensify, there are more high-frequency changes in the microbarometric data, and the maximum microbarometric pressure value increases, indicating abnormal local air pressure extremes, forming a strong air pressure gradient with the surrounding area, destroying the air pressure uniformity, and directly causing significant anomalies in the microbarometric data.

[0086] An increase in the maximum echo intensity indicates an increase in scatterers such as precipitation particles and dust in the monitoring area, enhanced radar wave reflection. The aggregation of such substances affects the atmospheric electromagnetic characteristics and energy distribution, changes the airflow movement, causes sudden changes in air pressure, and leads to intensified fluctuations in the microbarometric data and an increase in the anomaly degree. An increase in the average echo intensity means that the precipitation or scatterers are widely distributed and have a high density, gradually changing the atmospheric optical and electromagnetic characteristics, interfering with the air pressure field uniformity, resulting in the microbarometric pressure deviating from the normal state and an increase in the anomaly degree. Large fluctuations in the average radial velocity reflect disordered airflow movement. Strong shear and vortices interfere with the stability of the air pressure field, and the microbarometric pressure changes rapidly with the abnormal movement of the airflow, resulting in abnormal fluctuations in the data and an increase in the anomaly degree. When the maximum reflectivity factor value increases, it means that the number of precipitation particles in the region increases sharply, the size becomes larger, or the phase change is complex, resulting in an increase in the scattering and reflection ability of radar waves. The accumulation of a large number of precipitation particles changes the pattern of atmospheric water vapor distribution and heat exchange, triggering violent airflow movement and sudden changes in air pressure. For example, during the rapid condensation and growth of raindrops or the formation of hail, the release of latent heat intensifies convection, causing the air pressure field to become unbalanced, and the microbarometric data fluctuates significantly and instantaneously, deviating from the mean value, and the anomaly degree increases.

[0087] In a specific embodiment, the specific method for obtaining the comprehensive anomaly characteristic value of the regional tornado micro-pressure is as follows:

[0088] ,

[0089] ,

[0090] ,

[0091] wherein, is the comprehensive anomaly characteristic value of the regional tornado micro-pressure, is the characterization factor of the micro-pressure gauge monitoring parameter, is the characterization factor of the radar monitoring parameter, is the change amount of the gravity wavelength period amplitude, is the change amount of the gravity wave short period amplitude, is the maximum period length of the gravity wave, is the maximum micro-pressure, is the maximum echo intensity, is the average echo intensity, is the average radial velocity, is the maximum reflectivity factor value, is the reference gravity wavelength period amplitude change amount, is the reference gravity wave short period amplitude change amount, is the reference maximum period length of the gravity wave, is the reference maximum micro-pressure, is the reference maximum echo intensity, is the reference average echo intensity, is the reference average radial velocity, is the reference maximum reflectivity factor value, and e is the natural constant.

[0092] It should be understood that the softplus function is a built-in function in Python, .

[0093] It should be noted that the regional tornado micropressure comprehensive anomaly characteristic values ​​obtained by analyzing and processing the regional tornado micropressure comprehensive data take into account the mutual influence between these parameters. For example, when the maximum echo intensity increases abnormally, it often means that there is strong convective activity or a large number of heavy precipitation particles gathering locally, which may increase the average echo intensity. A larger maximum echo intensity is often accompanied by a strong updraft or horizontal airflow shear, and these airflow movements will affect the average radial velocity. The higher the maximum echo intensity, the stronger the scattering of radar waves by the target, which usually corresponds to larger size and higher concentration of precipitation particles or other strong scatterers, and these situations will also lead to an increase in the maximum reflectivity factor value. When the average echo intensity increases, it may mean that the precipitation area is expanded or the concentration of precipitation particles increases, which will affect the airflow movement and thus change the average radial velocity. When the average echo intensity is high, it means that there are more precipitation particles or scatterers in the area, which increases the possibility of a high reflectivity factor value. Changes in the long-period amplitude variation may affect the overall stability of the atmosphere, and then affect the excitation and propagation characteristics of short-period gravity waves, resulting in changes in the short-period amplitude variation. The intensified changes in the amplitude of gravity waves may cause the vertical movement of the atmosphere to increase, resulting in the redistribution of air pressure and affecting the maximum micropressure.

[0094] In a specific embodiment, by analyzing the comprehensive abnormal characteristic value of regional tornado micropressure, the comprehensive change characteristics of micropressure and related meteorological elements caused by tornado activities can be accurately grasped, and the errors and interferences that may be caused by single data can be effectively filtered out, thereby improving the accuracy of the judgment of tornado micropressure status. It helps to more accurately identify the intensity and development stage of tornado activities, and can provide a solid and reliable data basis for subsequent decision-making (such as whether to start secondary monitoring, issue warnings, etc.), which greatly improves the scientificity, effectiveness and timeliness of the entire monitoring system in responding to tornado disasters, and effectively protects the safety of people's lives and property and the stable operation of society.

[0095] The historical usage parameters of the micromanometer and the radar are obtained synchronously to analyze the correction coefficients collected by regional equipment.

[0096] The historical usage parameters of the micromanometer include the cumulative usage time of the micromanometer and the average daily sampling times.

[0097] Radar usage parameters include the radar's cumulative working time and the total number of pulse transmissions.

[0098] In a specific embodiment, the specific process of obtaining the regional equipment acquisition correction coefficient is as follows:

[0099] According to the historical use parameters of the micromanometer and the radar, the equipment comprehensive use status characteristic value is obtained through analysis and processing, and the equipment comprehensive use status characteristic value is used to characterize the historical use status of the micromanometer and the radar.

[0100] The characteristic value of the comprehensive usage status of the device is obtained as follows:

[0101] ,

[0102] wherein, is the characteristic value of the comprehensive usage status of the device, is the cumulative usage duration of the micro - manometer, is the average daily sampling times of the micro - manometer, is the cumulative working duration of the radar, is the total number of pulse emissions of the radar, is the deviation factor corresponding to the unit cumulative usage duration of the micro - manometer, is the deviation factor corresponding to a single sampling of the micro - manometer, is the deviation factor corresponding to the unit cumulative working duration of the radar, is the deviation factor corresponding to a single pulse emission of the radar, is the natural constant.

[0103] It should be understood that the swith function is a built - in function in Python, .

[0104] It should be noted that the deviation factor corresponding to the unit cumulative usage duration of the micro - manometer, the deviation factor corresponding to a single sampling of the micro - manometer, the deviation factor corresponding to the unit cumulative working duration of the radar, and the deviation factor corresponding to a single pulse emission of the radar are all preset in the database. When in use, they can be directly extracted from the database. The specific extraction method is to construct a mapping set, that is, different cumulative usage duration ranges of the micro - manometer, single - sampling situations, cumulative working duration ranges of the radar, and single - pulse emission situations are used as the keys of the mapping set, and the corresponding deviation factors are used as the values of the mapping set. For example, for the cumulative usage duration of the micro - manometer, different duration intervals can be set, and each interval corresponds to a specific deviation factor for the unit cumulative usage duration. For a single sampling of the micro - manometer, different deviation factors corresponding to different categories of sampling are set according to factors such as its sampling mode and accuracy. Intervals are divided according to different characteristics of the cumulative working duration and single - pulse emission and corresponding deviation factors are set. In actual extraction, according to the current cumulative usage duration of the micro - manometer, single - sampling situation, and the cumulative working duration and single - pulse emission status of the radar, the corresponding keys are searched in the mapping set, so as to extract the corresponding deviation factors for use in the calculation of relevant parameters such as the correction coefficient for the acquisition of regional devices, ensuring that the entire monitoring system can accurately consider the impact of the device usage history on data monitoring and analysis, and improving the reliability and accuracy of the monitoring results.

[0105] It should also be noted that by analyzing and processing the historical usage parameters of the microbarometer and the usage parameters of the radar to obtain the characteristic values of the comprehensive usage status of the equipment, it is considered that the mutual influence between them is small. For example, the longer the cumulative usage duration of the microbarometer, the more likely it is that components such as its internal sensors may age and their performance may decline, which may affect the accuracy of its measurement and further affect the reliability of the data obtained from the daily average sampling times. For example, after long-term use, the zero drift of the microbarometer may increase, resulting in systematic errors in the daily average sampling data. At the same time, if the daily average sampling times of the microbarometer are too high, it will accelerate the wear of its key components, shorten the cumulative usage duration, and the increased data volume generated by frequent sampling may exert a certain pressure on the radar data processing that works in coordination with it. In terms of the radar, the increase in the cumulative working duration will cause the performance of components such as the radar transmitter and receiver to decay, affecting the stability of pulse emission and the sensitivity of the received signal. The more the total number of pulse emissions, the faster the radar equipment ages, and the changes in key indicators such as its transmit power and frequency stability affect the detection ability of meteorological targets and indirectly affect the data correlation accuracy of the microbarometer in comprehensive monitoring.

[0106] In a specific embodiment, by analyzing the characteristic values of the comprehensive usage status of the equipment, it is possible to comprehensively evaluate the operating conditions of the microbarometer and the radar equipment, and timely understand the aging degree, performance decay situation, and potential problems that may exist in the equipment. When determining the acquisition correction coefficient of the regional equipment, it is possible to make reasonable adjustments based on the characteristic values of the comprehensive usage status of the equipment, so that the monitoring data can more accurately reflect the actual meteorological situation, improve the accuracy of the entire monitoring system for tornado microbarometric monitoring, and provide strong data support for more effectively warning of tornado disasters.

[0107] Extract the acquisition correction coefficients corresponding to each usage status characteristic value interval stored in the database, and map and extract the acquisition correction coefficient corresponding to the interval where the characteristic value of the comprehensive usage status of the equipment is located, which is recorded as the regional tornado microbarometric anomaly correction index.

[0108] It should be noted that factors such as the cumulative usage duration and daily average sampling times of the microbarometer, as well as the cumulative working duration and total number of pulse emissions of the radar, will all affect the performance of the equipment and further affect the accuracy of the monitoring data. By extracting the regional tornado microbarometric anomaly correction index based on the characteristic values of the comprehensive usage status of the equipment, it is possible to fully consider the influence of the equipment status on the monitoring data, reasonably correct the tornado microbarometric anomaly index, ensure that the final monitoring result is closer to the actual situation, and improve the reliability and accuracy of the entire monitoring system.

[0109] Based on the regional tornado microbarometric comprehensive anomaly characteristic value and the regional equipment acquisition correction coefficient, analyze and process to obtain the regional tornado microbarometric anomaly correction index, and the regional tornado microbarometric anomaly correction index is used to characterize the degree of tornado microbarometric anomaly determination after comprehensive monitoring and correction of the regional microbarometer and the radar.

[0110] In a specific embodiment, the method for obtaining the regional tornado micro-pressure anomaly correction index is as follows:

[0111] , where is the regional tornado micro-pressure anomaly correction index, is the comprehensive anomaly characteristic value of the regional tornado micro-pressure, is the correction coefficient for regional equipment acquisition.

[0112] It should be understood that the softsign function is a built-in function in Python, .

[0113] In a specific embodiment, by analyzing the regional tornado micro-pressure anomaly correction index, the abnormal degree of the tornado micro-pressure can be judged more accurately, and misjudgments caused by factors such as equipment aging and environmental interference can be effectively excluded. When the index shows a low abnormal degree, the system can reasonably maintain routine monitoring to avoid waste of resources caused by overreaction; while when the index indicates a serious abnormality, an alarm can be triggered in time to reduce the possible losses caused by tornadoes, and at the same time provide more accurate data support for meteorological research.

[0114] In this embodiment, the process of judging the comprehensive information of the regional tornado micro-pressure is as follows:

[0115] Extract the first micro-pressure verification index and the second micro-pressure verification index preset in the database.

[0116] If the regional tornado micro-pressure anomaly correction index is less than or equal to the first micro-pressure verification index, the comprehensive information of the regional tornado micro-pressure is recorded as normal micro-pressure.

[0117] If the regional tornado micro-pressure anomaly correction index is less than or equal to the first micro-pressure verification index, it indicates that the micro-pressure condition in the current area is within the normal fluctuation range and is not significantly affected by tornado activities or other abnormal meteorological factors. The atmospheric environment is relatively stable, and the relationship between various meteorological parameters conforms to the characteristics under normal weather conditions. The possibility of severe weather changes such as tornadoes occurring in the short term is relatively low, and the system can continue to maintain the routine monitoring state without taking further special countermeasures.

[0118] If the regional tornado micro-pressure anomaly correction index is greater than the first micro-pressure verification index and less than or equal to the second micro-pressure verification index, the comprehensive information of the regional tornado micro-pressure is recorded as abnormal micro-pressure.

[0119] If the regional tornado micro-pressure anomaly correction index is greater than the first micro-pressure verification index and less than or equal to the second micro-pressure verification index, it indicates that although the micro-pressure condition in the current region has shown a certain degree of anomaly, this degree of anomaly is not sufficient to conclusively determine that a tornado is about to occur or has occurred. There may be some potential meteorological change trends or interference factors that need to be further verified. At this time, secondary monitoring of this region is required to more precisely capture the details of micro-pressure changes and the characteristics of meteorological targets, further clarify the true state of the atmospheric environment, eliminate the possibility of misjudgment, and provide more reliable data support for accurately judging whether there is a tornado threat in the follow-up.

[0120] If the regional tornado micro-pressure anomaly correction index is greater than the second micro-pressure verification index, the regional tornado micro-pressure comprehensive information is recorded as a micro-pressure warning.

[0121] If the regional tornado micro-pressure anomaly correction index is greater than the second micro-pressure verification index, it indicates that the atmospheric environment in this region is in a highly unstable state, and the degree of anomaly of the monitored micro-pressure data is relatively high. At this time, the abnormal relationship between various meteorological parameters and the significant change of micro-pressure have clearly shown the severity of the abnormal meteorological conditions. The system must immediately generate a warning message and issue a warning to the preset management terminal so that relevant personnel can take effective preventive and response measures in a timely manner.

[0122] By judging the regional micro-pressure comprehensive information, when it is determined that the micro-pressure is normal, unnecessary resource investment and misjudgment interference are avoided. If the micro-pressure is abnormal, it helps to further precisely master the details of micro-pressure changes and the characteristics of meteorological targets, eliminate potential interference factors, and improve the accuracy of judging the potential threat of tornadoes. Once it is judged as a micro-pressure warning, the system immediately generates and issues a warning message, enabling relevant personnel to be aware in a timely manner that a tornado is approaching or occurring, so as to quickly take response measures and minimize the losses caused by the tornado to the greatest extent, reflecting the efficiency and reliability of the monitoring system in dealing with tornado disasters.

[0123] The regional secondary monitoring execution module is used to, when the regional tornado micro-pressure comprehensive information is determined to be micro-pressure abnormal, respectively adjust the acquisition parameters of the micro-pressure gauge and the radar, and analyze the secondary verification monitoring execution cycle in combination with the regional tornado micro-pressure anomaly correction index, thereby performing regional secondary verification monitoring.

[0124] In this embodiment, the regional secondary verification monitoring is performed as follows:

[0125] Perform a difference processing on the regional tornado micro-pressure anomaly correction index and the first micro-pressure verification index to obtain the regional tornado micro-pressure comprehensive anomaly deviation factor.

[0126] Extract the secondary verification monitoring periods corresponding to each comprehensive anomaly deviation factor interval stored in the database, and map to extract the secondary verification monitoring period corresponding to the interval where the regional tornado micro-pressure comprehensive anomaly deviation factor is located, denoted as the secondary verification monitoring execution period.

[0127] Extract the preset rated maximum sampling frequency of the micro-pressure gauge and the preset rated maximum resolution of the radar. Accordingly, adjust the micro-pressure gauge at the preset rated maximum sampling frequency and adjust the radar at the preset rated maximum resolution. Meanwhile, conduct regional secondary verification monitoring according to the secondary verification monitoring execution period.

[0128] In a specific embodiment, after the secondary monitoring is completed, re-analyze to obtain the regional tornado micro-pressure anomaly correction index, denoted as the regional tornado micro-pressure secondary monitoring eigenvalue, and perform a difference processing on the regional tornado micro-pressure secondary monitoring eigenvalue and the regional tornado micro-pressure anomaly correction index to obtain the regional tornado micro-pressure secondary monitoring deviation factor.

[0129] It should be noted that the difference processing refers to subtracting the regional tornado micro-pressure anomaly correction index from the regional tornado micro-pressure secondary monitoring eigenvalue, and the result of the difference processing can be greater than zero, less than zero, or equal to zero.

[0130] When the regional tornado micro-pressure secondary monitoring deviation factor is greater than zero, directly generate a warning prompt.

[0131] When the regional tornado micro-pressure secondary monitoring deviation factor is less than zero, extract the adjustment parameters corresponding to each secondary monitoring deviation factor interval stored in the database, and map to extract the adjustment parameters corresponding to the interval where the regional tornado micro-pressure secondary monitoring deviation factor is located, denoted as the regional tornado micro-pressure monitoring device adjustment parameters, and adjust the regional tornado micro-pressure monitoring device with the regional tornado micro-pressure monitoring device adjustment parameters.

[0132] It should be noted that the regional tornado micro-pressure monitoring device adjustment parameters include the micro-pressure gauge sampling frequency adjustment value and the radar resolution adjustment value.

[0133] It should also be noted that if the extracted regional tornado micro-pressure monitoring device adjustment parameters exceed the preset rated minimum adjustment ability of the device, then perform monitoring and operation with the preset rated minimum parameters of the device.

[0134] If the regional tornado micro-pressure monitoring device adjustment parameters are equal to zero, continue to control the micro-pressure gauge to perform monitoring and operation at the preset rated maximum sampling frequency and the radar at the preset rated maximum resolution.

[0135] The regional micro-pressure warning module is used to generate a warning message and issue a warning to a preset management terminal when the regional tornado micro-pressure comprehensive information is a micro-pressure warning.

[0136] In a specific embodiment, the warning information may be "Attention! Monitoring data shows that within the scope of [specific area name], there are strong signs of instability in the current atmospheric environment, and a tornado is very likely to be forming or approaching."

[0137] Please refer to Figure 2 As shown, the embodiment of the present invention provides a method for monitoring tornado micro-pressure change data, including the following steps:

[0138] S1. Obtain regional micro-pressure observation data through a micro-pressure gauge, analyze the abnormal indicators of micro-pressure observation, and thereby judge the regional radar activation information. The regional radar activation information includes the need to activate the radar and the non-need to activate the radar. When the regional radar activation information is judged as the non-need to activate the radar, execute S2. When the regional radar activation information is judged as the need to activate the radar, execute S3.

[0139] S2. Synchronously collect regional environmental parameters, combine with the abnormal indicators of micro-pressure observation, obtain the optimal sampling frequency of the micro-pressure gauge, and perform regional micro-pressure monitoring at the optimal sampling frequency of the micro-pressure gauge.

[0140] It should be noted that in a specific embodiment, after the regional radar activation information is judged as the non-need to activate the radar, the system continuously performs regional micro-pressure monitoring at the analyzed optimal sampling frequency of the micro-pressure gauge, obtains regional micro-pressure observation data, and analyzes the abnormal indicators of micro-pressure observation. During the continuous monitoring process, if within a specific monitoring period, the abnormal indicators of micro-pressure observation exceed the preset threshold of the tornado micro-pressure observation abnormal verification indicators, this situation indicates that the complexity of the meteorological environment has suddenly increased and potential risks have emerged. The system immediately activates the radar device and fully opens the in-depth observation mode to accurately capture the subtle changes of meteorological elements. On the contrary, if the abnormal indicators of micro-pressure observation always remain within the preset threshold range, fully proving that the current meteorological environment situation is stable and there is no significant abnormal fluctuation, the system then continues to perform regional micro-pressure monitoring steadily at the optimal sampling frequency of the micro-pressure gauge and continuously accumulates data.

[0141] S3. Synchronously activate regional radar monitoring, thereby obtaining regional micro-pressure comprehensive data, analyzing and obtaining regional micro-pressure comprehensive abnormal characteristic indicators, and judging regional micro-pressure comprehensive information. The regional micro-pressure comprehensive information includes normal micro-pressure, abnormal micro-pressure, and micro-pressure warning. When the regional micro-pressure comprehensive information is abnormal micro-pressure, execute S4. When the regional micro-pressure comprehensive information is micro-pressure warning, execute S5.

[0142] S4. Adjust the acquisition parameters of the micro-pressure gauge and the radar respectively, and analyze the execution period of the secondary verification monitoring in combination with the regional micro-pressure comprehensive abnormal characteristic indicators, thereby performing regional secondary verification monitoring.

[0143] S5. Generate warning information and issue a warning to a preset management terminal.

[0144] The present invention provides a tornado micro-pressure change data monitoring system and method, which can achieve efficient and accurate monitoring of the micro-pressure of tornadoes, effectively improve the meteorological disaster warning ability, scientifically judge the radar activation requirement by analyzing the data collected by the micro-pressure gauge, avoid resource waste, and the optimal sampling frequency analysis module can optimize the sampling frequency of the micro-pressure gauge according to the environmental and micro-pressure observation conditions to ensure the effectiveness of data collection. Through comprehensive in-depth analysis of multi-source data, accurately judge the micro-pressure state and provide a numerical basis for subsequent decision-making. Conduct targeted secondary monitoring when necessary to further verify the meteorological conditions. It can also issue warning information in a timely manner, enabling relevant personnel to take preventive and response measures in advance and reducing the possible losses caused by tornadoes.

[0145] It should be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device.

[0146] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification to better explain the principle and practical application of the present invention, so that those skilled in the relevant technical field can understand and utilize the present invention well. As long as it does not deviate from the structure of the present invention or exceed the scope defined by the present invention, it should fall within the protection scope of the present invention.

Claims

1. A tornado micro-pressure change data monitoring system, characterized in that: Including: A regional radar activation information determination module, which is used to collect regional tornado micro-pressure observation data through a micro-manometer, analyze the abnormal indicators of tornado micro-pressure observations, and thereby judge the regional radar activation information. The regional radar activation information includes the need to activate the radar and the non-need to activate the radar; An optimal sampling frequency analysis module, which is used to synchronously collect regional environmental parameters when the regional radar activation information is judged as not requiring radar activation, and combine the abnormal indicators of tornado micro-pressure observations to obtain the optimal sampling frequency of the micro-manometer, and perform regional micro-pressure monitoring at the optimal sampling frequency of the micro-manometer; A regional tornado micro-pressure comprehensive information determination module, which is used to synchronously activate regional radar monitoring when the regional radar activation information is judged as requiring radar activation, thereby obtaining regional tornado micro-pressure comprehensive data, analyzing and obtaining regional tornado micro-pressure abnormal correction indicators, and judging regional tornado micro-pressure comprehensive information. The regional tornado micro-pressure comprehensive information includes normal micro-pressure, abnormal micro-pressure, and micro-pressure warning; Obtaining the regional tornado micro-pressure comprehensive abnormal characteristic value through analysis and processing of the regional tornado micro-pressure comprehensive data; The regional tornado micro-pressure comprehensive abnormal characteristic value is used to characterize the abnormal degree of the tornado micro-pressure data during the comprehensive monitoring of the micro-manometer and the radar; Synchronously obtaining the historical usage parameters of the micro-manometer and the usage parameters of the radar, and thereby analyzing the regional equipment acquisition correction coefficient; Based on the regional tornado micro-pressure comprehensive abnormal characteristic value and the regional equipment acquisition correction coefficient, analyzing and processing to obtain the regional tornado micro-pressure abnormal correction indicator. The regional tornado micro-pressure abnormal correction indicator is used to characterize the abnormal determination degree of the tornado micro-pressure after correction in the comprehensive monitoring of the regional micro-manometer and the radar; A regional secondary monitoring execution module, which is used to adjust the acquisition parameters of the micro-manometer and the radar respectively when the regional tornado micro-pressure comprehensive information is judged as abnormal micro-pressure, and analyze the secondary verification monitoring execution period in combination with the regional tornado micro-pressure abnormal correction indicator, thereby performing regional secondary verification monitoring; A regional micro-pressure warning module, which is used to generate a warning message and issue a warning to a preset management terminal when the regional tornado micro-pressure comprehensive information is a micro-pressure warning.

2. The tornado micro-pressure change data monitoring system according to claim 1, characterized in that: The specific process of analyzing the abnormal indicators of tornado micro-pressure observations is as follows: During a preset monitoring period, collect regional tornado micro-pressure observation data. The regional tornado micro-pressure observation data includes the average micro-pressure value, the extreme difference in micro-pressure change, the micro-pressure change rate, the extreme difference in gravity wave amplitude change, and the extreme difference in gravity wave period length change; Obtaining the tornado micro-pressure observation abnormal indicator through analysis and processing of the regional tornado micro-pressure observation data. The regional tornado micro-pressure observation indicator is used to characterize the abnormal degree of the tornado micro-pressure observation data collected by the micro-manometer.

3. The tornado micro-pressure change data monitoring system according to claim 2, characterized in that: The specific analysis process of judging the regional radar activation information is as follows: Extract the preset tornado micro-pressure observation abnormal verification indicator in the database; If the tornado micro-pressure observation abnormal indicator is less than the tornado micro-pressure observation abnormal verification indicator, record the regional radar activation information as not requiring radar activation; If the tornado micro-pressure observation abnormal indicator is greater than or equal to the tornado micro-pressure observation abnormal verification indicator, record the regional radar activation information as requiring radar activation.

4. The tornado micro-pressure change data monitoring system according to claim 3, characterized in that: The process of obtaining the optimal sampling frequency of the micro - pressure gauge is as follows: During a preset monitoring period, regional environmental parameters are synchronously collected. The regional environmental parameters include average temperature, average humidity, maximum wind speed, cumulative precipitation, and average atmospheric pressure; Based on the regional environmental parameters and the tornado micro - pressure observation anomaly index, a micro - pressure gauge sampling indication factor is analyzed and processed. The micro - pressure gauge sampling indication factor is used to characterize the influence degree of the current regional environment on the working state of the micro - pressure gauge; Extract the preset micro - pressure gauge sampling indication factor threshold in the database; Perform a difference process on the micro - pressure gauge sampling indication factor and the micro - pressure gauge sampling indication factor threshold to obtain a micro - pressure gauge sampling deviation factor; Extract the sampling frequency adjustment values corresponding to each sampling deviation factor interval stored in the database, and map and extract the sampling frequency adjustment value corresponding to the interval where the micro - pressure gauge sampling deviation factor is located, denoted as the micro - pressure gauge sampling frequency adjustment value; Obtain the current acquisition frequency of the micro - pressure gauge, and calculate the optimal sampling frequency of the micro - pressure gauge according to the micro - pressure gauge sampling frequency adjustment value.

5. The tornado micro-pressure change data monitoring system according to claim 1, characterized in that: The process of obtaining the comprehensive micro - pressure data of regional tornadoes is as follows: During the monitoring period, micro - pressure data is collected by the micro - pressure gauge, and through a five - minute sliding Fourier analysis, a three - dimensional dynamic spectrum of "period - amplitude - time" of gravity waves is obtained, from which micro - pressure change data is obtained. The micro - pressure change data includes the change amount of gravity wave long - period amplitude, the change amount of gravity wave short - period amplitude, and the maximum period length of gravity waves. Synchronously obtain the maximum micro - pressure monitored by the micro - pressure gauge, and jointly use the micro - pressure change data and the maximum micro - pressure as the micro - pressure gauge monitoring parameters; Obtain radar monitoring parameters through radar monitoring, including the maximum echo intensity, average echo intensity, average radial velocity, and maximum reflectivity factor value of the region; Jointly use the micro - pressure gauge monitoring parameters and the radar monitoring parameters as the comprehensive micro - pressure data of regional tornadoes.

6. The tornado micro-pressure change data monitoring system according to claim 5, characterized in that: The process of judging the comprehensive micro - pressure information of regional tornadoes is as follows: Extract the preset first micro - pressure verification index and second micro - pressure verification index in the database; If the regional tornado micro - pressure anomaly correction index is less than or equal to the first micro - pressure verification index, record the comprehensive micro - pressure information of the region as micro - pressure normal; If the regional tornado micro - pressure anomaly correction index is greater than the first micro - pressure verification index and less than or equal to the second micro - pressure verification index, record the comprehensive micro - pressure information of the region as micro - pressure abnormal; If the regional tornado micro - pressure anomaly correction index is greater than the second micro - pressure verification index, record the comprehensive micro - pressure information of the region as micro - pressure warning.

7. The tornado micro-pressure change data monitoring system according to claim 6, characterized in that: The process of performing regional secondary verification monitoring is as follows: Perform a difference process on the regional tornado micro - pressure anomaly correction index and the first micro - pressure verification index to obtain a comprehensive anomaly deviation factor of regional tornado micro - pressure; Extract the secondary verification monitoring periods corresponding to each comprehensive anomaly deviation factor interval stored in the database, and map and extract the secondary verification monitoring period corresponding to the interval where the comprehensive anomaly deviation factor of regional tornado micro - pressure is located, denoted as the secondary verification monitoring execution period; Extract the preset rated maximum sampling frequency of the microbarometer and the preset rated maximum resolution of the radar. Accordingly, adjust the microbarometer at the preset rated maximum sampling frequency and adjust the radar at the preset rated maximum resolution. At the same time, perform regional secondary verification monitoring according to the secondary verification monitoring execution cycle.

8. The tornado micro-pressure change data monitoring system according to claim 5, characterized in that: The specific acquisition method of the regional tornado microbarometer abnormal correction index is as follows: ， Among them, is the regional tornado micro-pressure anomaly correction index, is the regional tornado micro-pressure comprehensive anomaly characteristic value, is the regional equipment acquisition correction coefficient.

9. A method applied to the tornado micro-pressure change data monitoring system according to any one of claims 1-8, characterized in that: It includes the following steps: S1. Obtain regional microbarometer observation data through the microbarometer, analyze the microbarometer observation abnormal index, and thereby judge the regional radar activation information. The regional radar activation information includes required radar activation and no need for radar activation. When the regional radar activation information is judged as no need for radar activation, execute S2. When the regional radar activation information is judged as required radar activation, execute S3; S2. Synchronously collect regional environmental parameters, combine with the microbarometer observation abnormal index, obtain the optimal sampling frequency of the microbarometer, and perform regional microbarometer monitoring at the optimal sampling frequency of the microbarometer; S3. Synchronously activate regional radar monitoring, thereby obtain regional microbarometer comprehensive data, analyze and obtain the regional microbarometer comprehensive abnormal characteristic index, and judge the regional microbarometer comprehensive information. The regional microbarometer comprehensive information includes normal microbarometer, abnormal microbarometer, and microbarometer warning. When the regional microbarometer comprehensive information is abnormal microbarometer, execute S4. When the regional microbarometer comprehensive information is microbarometer warning, execute S5; S4. Adjust the acquisition parameters of the microbarometer and the radar respectively, and analyze the secondary verification monitoring execution cycle in combination with the regional microbarometer comprehensive abnormal characteristic index, thereby perform regional secondary verification monitoring; S5. Generate a warning message and issue a warning to the preset management terminal.

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