Meteorological monitoring emergency early warning data acquisition method and portable acquisition device

Abstract

The invention relates to the technical field of meteorological information acquisition, and particularly discloses a meteorological monitoring emergency early warning data acquisition method and a portable acquisition device.The method comprises the steps that a plurality of acquisition devices are arranged in a target area to acquire air pressure in the target area; when the weather in the target area meets the early warning condition, determining a monitoring area in the target area; determining risk equipment needing to be verified from the acquisition equipment in the monitoring area; performing intra-area verification, historical data verification and out-area verification on the risk equipment; evaluating the acquisition accuracy of the risk equipment according to the verification result; through a multi-verification mechanism, dynamic monitoring area adjustment, portable equipment application and multi-dimensional meteorological data acquisition of the meteorological acquisition equipment in combination with an air pressure rule, the possibility of abnormity of the meteorological acquisition equipment can be analyzed more accurately, errors in a data acquisition process are effectively reduced, and the accuracy of data acquisition is improved. Therefore, more accurate and timely decision support is provided for an early warning system.

Description

Technical Field

[0001] The present invention relates to the technical field of meteorological information collection, and in particular to a method for collecting meteorological monitoring emergency warning data and a portable collection device. Background Art

[0002] In the meteorological monitoring and early warning system, accurate and timely data collection is a crucial link in responding to extreme weather events. Traditional meteorological monitoring methods usually rely on widely distributed meteorological stations or satellite equipment to collect and analyze meteorological data for early warning.

[0003] For example, a meteorological data collection and transmission system is disclosed in the prior art, including a temperature sensor and a processor connected to the temperature sensor, and also including a Beidou short message module, and a humidity sensor, an air pressure sensor, a fan, a display, a memory, and a light intensity sensor all connected to the processor; wherein the display is located on the surface of the shell, and the temperature sensor, the humidity sensor, the air pressure sensor, the fan, the memory, and the light intensity sensor are all located inside the shell, and a breathable plate is provided on the shell at the corresponding position of the humidity sensor, the air pressure sensor, and the fan; a Fresnel lens is provided on the shell at the corresponding position of the light intensity sensor; a data transmission interface connected to the processor is provided on the shell; and the Beidou short message module is connected to the data transmission interface via a data line. Aiming at the technical problem that the meteorological data collection equipment has a single communication means, it adopts the Beidou short message module, and after collecting the meteorological data, it stores it and can communicate quickly.

[0004] However, the above-mentioned meteorological data collection system has some shortcomings. When faced with rapid changes in meteorological events, it is unable to capture data anomalies in a timely and effective manner, which can easily lead to delayed or inaccurate warnings. In addition, the collection equipment is easily damaged or malfunctions in extreme weather, further exacerbating the problem of data reliability. Summary of the invention

[0005] The purpose of the present invention is to provide a method and a portable collection device for collecting meteorological monitoring emergency warning data, so as to solve the problem that the prior art lacks effective detection and analysis of the collection equipment itself, resulting in the inability to capture data anomalies in a timely and effective manner when facing rapid changes in meteorological events, which easily leads to delayed or inaccurate warnings.

[0006] To this end, on the one hand, the present invention provides a method for collecting meteorological monitoring emergency warning data, comprising:

[0007] Deploy a number of collection devices in the target area to collect meteorological data in the target area;

[0008] When the meteorological data in the target area meets the warning conditions, determining the monitoring area in the target area;

[0009] Determine the risk equipment that needs to be verified from the collection equipment in the monitoring area;

[0010] For the risky equipment, regional verification, historical data verification and out-of-region verification are performed respectively;

[0011] Evaluate the collection accuracy of risk equipment based on the verification results;

[0012] The verification in the region is to compare the collected air pressure of the collection device closest to the risk device in the monitoring region with the collected air pressure of the risk device to verify whether the risk device has abnormal characteristics of adjacent data;

[0013] The historical data verification is to compare the historical data of the air pressure in the monitoring area with the collected air pressure of the risk equipment to verify whether the risk equipment has abnormal historical data characteristics;

[0014] The out-of-area verification is to compare the collected air pressure of the collection equipment outside the monitoring area with the collected air pressure of the risk equipment to verify whether there are abnormal trend data characteristics of the risk equipment;

[0015] The target area is an area where a low pressure trough exists.

[0016] As a preferred technical solution for the method of collecting meteorological monitoring emergency warning data, the determination of the monitoring area includes:

[0017] Acquiring air pressure distribution in the target area;

[0018] The enclosed area where the air pressure is lower than the preset value is determined as the monitoring area.

[0019] As a preferred technical solution for the method of collecting meteorological monitoring emergency warning data, the determination of risk equipment includes:

[0020] Collecting the number of historical failures of the collection equipment within the monitoring area;

[0021] The collection equipment with the highest number of historical failures and the collection equipment with abnormal changes in air pressure are identified as risky equipment.

[0022] As a preferred technical solution for the method of collecting meteorological monitoring emergency warning data, the verification within the region specifically includes:

[0023] Acquire a verification device whose distance from the risk device is less than a preset distance;

[0024] Screen out verification equipment with terrain obstacles or wind barriers between it and risk equipment;

[0025] Perform correlation analysis on the verification devices and risk devices that have not been screened out, and determine the first correlation coefficient between the collected air pressure of each verification device and the risk device;

[0026] If the first correlation coefficient of any verification device that has not been screened out is less than the preset coefficient, it is determined that there are abnormal features of adjacent data.

[0027] As a preferred technical solution for the method of collecting meteorological monitoring emergency warning data, the historical data verification specifically includes:

[0028] Extract historical data of air pressure corresponding to the location of risk equipment from the database;

[0029] Through the meteorological event matching algorithm, the verification time period in the historical data that matches the current meteorological event is identified;

[0030] The air pressure data of the verification time period is compared with the collected air pressure during the same period of time before the risk device to determine the second correlation coefficient, and the collected air pressure of the risk device is compared with the air pressure endpoint value in the historical data. If the second correlation coefficient is greater than the preset coefficient, or the maximum or minimum value in the collected air pressure exceeds the air pressure endpoint value, it is determined that abnormal characteristics of the historical data exist.

[0031] As a preferred technical solution for the method of collecting meteorological monitoring emergency warning data, the out-of-region verification specifically includes:

[0032] From the collection devices outside the monitoring area in the target area, trend-related devices are delineated at different positions of the risk devices, and the collection air pressures of each trend-related device and the risk equipment are compared respectively. If the collection air pressure of any trend-related device is less than or equal to the collection air pressure of the risk device at the same moment, it is determined that abnormal trend data features exist.

[0033] As the preferred technical solution for the collection method of meteorological monitoring emergency warning data, the collection accuracy of risk equipment under current meteorological conditions is evaluated according to the verification results, including:

[0034] Obtain the total number of occurrences of abnormal features of adjacent data, abnormal features of historical data, and abnormal features of trend data;

[0035] The total number of occurrences was used as the collection accuracy to evaluate the collection accuracy.

[0036] As a preferred technical solution for the method of collecting meteorological monitoring emergency warning data, the range of the monitoring area is periodically changed according to the air pressure in the target area.

[0037] On the other hand, the present invention provides a portable device for collecting meteorological monitoring emergency warning data, which uses the meteorological monitoring emergency warning data collection method described in the above scheme, including:

[0038] Bracket,

[0039] A collection device body, mounted on the bracket, for collecting meteorological data, wherein the meteorological data includes air pressure;

[0040] As an optimal technical solution for a portable collection device for meteorological monitoring emergency warning data, the meteorological data also includes wind direction, wind speed, temperature and humidity.

[0041] The beneficial effects of the present invention are:

[0042] The present invention provides a method for collecting meteorological monitoring emergency warning data, which realizes the monitoring of meteorological collection equipment according to the radiation trend of air pressure detection, and realizes the abnormal analysis of collection equipment that may be affected by weather under extreme weather conditions by combining multiple verification mechanisms, historical data and comprehensive comparison of equipment outside the region, so as to facilitate the evaluation of the accuracy of air pressure collected by the collection equipment and effectively avoid the false alarm of erroneous data. Through multiple verification mechanisms, dynamic monitoring area adjustment, portable device application and multi-dimensional meteorological data collection, the accuracy and reliability of meteorological data are significantly improved, and the adaptability and flexibility of the emergency warning system in dealing with extreme weather are enhanced. It is possible to more accurately analyze the possibility of abnormalities in meteorological collection equipment, effectively reduce errors in the data collection process, and thus provide more accurate and timely decision support for the warning system.

[0043] Furthermore, the present invention takes into account the characteristic of the radiative increase of air pressure from the inside to the outside in the extreme meteorological environment of the low-pressure trough. The low-pressure trough phenomenon occurs in strong weather systems such as typhoons and hurricanes. A significant low-pressure area will be formed in the central area. The air pressure is lowest in the center. As the distance from the typhoon center increases, the air pressure will gradually increase, forming a radial pressure gradient that expands outward. By utilizing the radial pressure gradient change of the air pressure, it is used as the basis for monitoring and collecting equipment. If the air pressure parameters collected by the equipment are abnormal, the possibility of abnormalities in the other parameters is higher. By utilizing the characteristics of the radial change of air pressure, effective detection of the meteorological collection equipment itself is achieved, and the analysis of the effectiveness of the other parameters can be considered while monitoring the air pressure parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 Flow chart of a method for collecting meteorological monitoring emergency warning data in an embodiment of the present invention;

[0045] Figure 2 A flowchart of the intra-region verification in an embodiment of the present invention;

[0046] Figure 3 A flowchart of historical data verification in an embodiment of the present invention;

[0047] Figure 4Schematic diagram of the structure of a convenient collection device for meteorological monitoring emergency warning data in an embodiment of the present invention.

[0048] In the figure: 1. Collection equipment body; 2. Bracket. DETAILED DESCRIPTION

[0049] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] In the description of the present invention, it should be noted that the orientations or positional relationships indicated by the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", etc. are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. Among them, the terms "first position" and "second position" are two different positions, and the first feature "above", "above" and "above" the second feature include the first feature being directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. The first feature "below", "below" and "below" the second feature include the first feature being directly below and obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature.

[0051] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0052] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0053] like Figure 1As shown, the present invention provides a method for collecting meteorological monitoring emergency warning data, comprising:

[0054] Step S1, deploying a number of collection devices in the target area to collect meteorological data in the target area;

[0055] Step S2, when the meteorological data in the target area meets the warning conditions, determine the monitoring area in the target area;

[0056] Step S3, determining risk equipment that needs to be verified from the collection equipment in the monitoring area;

[0057] Step S4, performing in-region verification, historical data verification and out-of-region verification on risky equipment respectively;

[0058] Step S5, evaluating the collection accuracy of the risky equipment according to the verification result;

[0059] Among them, the verification within the area is to compare the collected air pressure of the collection device closest to the risk device in the monitoring area with the collected air pressure of the risk device to verify whether there is abnormal feature of adjacent data of the risk device;

[0060] Historical data verification is to compare the historical data of air pressure in the monitoring area with the collected air pressure of the risk equipment to verify whether there are abnormal characteristics in the historical data of the risk equipment;

[0061] The out-of-area verification is to compare the collected air pressure of the collection equipment outside the monitoring area with the collected air pressure of the risk equipment to verify whether there are abnormal trend data characteristics of the risk equipment;

[0062] The target area is the area where there is a low pressure trough.

[0063] In the above embodiment, through multiple verification mechanisms, combined with comprehensive comparison of regional, historical data and equipment outside the region, abnormal analysis of collection equipment that may be affected by weather is realized under extreme weather conditions, which is convenient for evaluating the accuracy of air pressure collected by collection equipment and effectively avoiding false reports of erroneous data. Through multiple verification mechanisms, dynamic monitoring area adjustment, portable device application and multi-dimensional meteorological data collection, the accuracy and reliability of meteorological data are significantly improved, and the adaptability and flexibility of the emergency warning system in dealing with extreme weather are enhanced. It is possible to more accurately analyze the possibility of abnormalities in meteorological collection equipment, effectively reduce errors in the data collection process, and thus provide more accurate and timely decision support for the warning system. Further, this embodiment also takes into account the characteristics of the radial increase in air pressure from the inside to the outside in the extreme meteorological environment of the low-pressure trough. The low-pressure trough phenomenon occurs in strong weather systems such as typhoons and hurricanes. A significant low-pressure area will be formed in the central area. The air pressure is the lowest in the center. As the distance from the typhoon center increases, the air pressure will gradually increase, forming a radial pressure gradient that expands outward. By utilizing the radial pressure gradient change of air pressure, it is used as the basis for monitoring the collection equipment. If the air pressure parameters collected by the equipment are abnormal, the possibility of abnormalities in other parameters is higher. By utilizing the characteristics of the radiative change of air pressure, effective detection of the meteorological collection equipment itself is achieved. While monitoring the air pressure parameters, the effectiveness of other parameters can also be analyzed.

[0064] Specifically, the determination of monitoring areas includes:

[0065] Step S001, obtaining the air pressure distribution in the target area;

[0066] Step S002, determine the closed area with air pressure lower than the preset value as the monitoring area. In detail, the preset value can be determined in combination with the warning level and the area of ​​the target area. In implementation, considering that the preset value is used to divide the monitoring area, the preset value should not be too large, which will lead to an excessively large monitoring area, thereby increasing computing power and affecting the verification process. It should not be too small, which will lead to an excessively small monitoring area, resulting in a small sampling amount for risk equipment and poor integrity.

[0067] Specifically, the determination of risky equipment includes:

[0068] Step S011, collecting the historical number of failures of the collection equipment in the monitoring area; in detail, the historical number of failures is the number of failures of the collection equipment after it was put into service.

[0069] Step S012, the collection equipment with the highest number of historical failures and the collection equipment with abnormal changes in air pressure (i.e., the change range of the collected air pressure per unit time does not conform to the performance parameters of the collection equipment, or the change range is abnormal, with sudden rises and falls that do not conform to meteorological laws) are all determined as risk equipment. The tolerance range of the fluctuation degree of the collected air pressure can be determined based on the equipment's reference Figure 2 As shown, regional verification specifically includes:

[0070] Step S021, obtaining a verification device whose distance from the risk device is less than a preset distance; the preset distance needs to be small enough to ensure that the verification device and the risk device are under approximately the same meteorological conditions, and optionally, the preset distance is 500m.

[0071] Step S022, screening out verification equipment that has terrain obstacles or wind barriers between it and the risk equipment;

[0072] Step S023, performing correlation analysis on the verification devices and risk devices that have not been screened out, and determining the first correlation coefficient between the collected air pressure of each verification device and the risk device;

[0073] Step S024: If the first correlation coefficient of any unscreened verification device is less than the preset coefficient, it is determined that there is an abnormal feature of adjacent data. If the first correlation coefficients of all unscreened verification devices are greater than the preset coefficient, it is determined that there is no abnormal feature of adjacent data. In detail, the correlation analysis is performed using the Pearson correlation coefficient in statistics. The calculation formula for the first correlation coefficient is as follows:

[0074]

[0075] Among them, r is the first correlation coefficient, Xi and Yi are the air pressures of the two sets of air pressure data to be compared at the i-th moment, and is the respective average air pressure. The subsequent calculation of the second correlation coefficient is also performed by the above formula. Optionally, the preset coefficient is 0.8.

[0076] For example, the coordinates of a risk device A are (latitude: 30.1234°, longitude: 120.5678°). Through the calculation of the Haversin formula, devices B, C, and D within 500 meters of position A are identified as potential verification devices. Device B is located on the back of a tall building, device C is located behind the hill, and device D is located in an open area with no wind barriers between it and position A. Through terrain analysis, the system found that there were terrain obstacles between devices B and C and A, so B and C were screened out and only device D was retained as a verification device. Device D and risk device A collected air pressure data once a minute in the past hour. Through the Pearson correlation coefficient calculation, the correlation coefficient between the two devices was 0.7. Less than the preset coefficient of 0.8. The system determines that device A has abnormal adjacent data characteristics. Through the specific implementation steps of verification in the above area, data anomalies caused by equipment failure or external environmental factors can be effectively identified and eliminated to ensure the accuracy and reliability of meteorological monitoring data. This not only improves the overall performance of the meteorological warning system, but also reduces the possibility of false alarms and missed alarms, providing more solid data support for emergency response.

[0077] See also Figure 3 As shown in the figure, historical data verification specifically includes:

[0078] Step S031, extracting historical data of air pressure corresponding to the location of the risk device from the database; the historical data of air pressure should be long enough to reflect the statistical characteristics of the air pressure at the location.

[0079] Step S032, identifying the verification time period in the historical data that matches the current meteorological event through a meteorological event matching algorithm;

[0080] Step S033, comparing the air pressure data of the verification time period with the collected air pressure in front of the risk device during the same period of time to determine a second correlation coefficient;

[0081] Step S034, comparing the collected air pressure of the risk equipment with the air pressure endpoint value in the historical data;

[0082] Step S035, if the second correlation coefficient is greater than the preset coefficient, or the maximum or minimum value in the collected air pressure exceeds the air pressure endpoint value, it is determined that an abnormal feature of the historical data exists. The air pressure endpoint value is the maximum and minimum value of the air pressure in the historical data. Exemplarily, in the historical data, the maximum value of the air pressure is 1020 hPa, and the minimum value is 990 hPa. In the current meteorological event, the maximum value of the collected air pressure of the risk equipment is 1025 hPa, and the minimum value is 980 hPa. Since the maximum value exceeds the air pressure endpoint value in the historical data, it is determined that an abnormal feature of the historical data exists.

[0083] In detail, the meteorological event matching algorithm uses the characteristics of meteorological events as matching conditions and calculates similarity to identify the time period in historical meteorological events that is closest to the current event as the verification time period.

[0084] Specifically, out-of-region verification includes:

[0085] From the collection devices outside the monitoring area in the target area, trend-related devices are delineated at different positions of the risk devices, and the collection pressures of each trend-related device and the risk device are compared. If the collection pressure of any trend-related device is less than or equal to the collection pressure of the risk device at the same time, it is determined that the abnormal characteristics of the trend data exist. In detail, the collection pressure of the collection devices outside the area should be greater than the collection pressure of the risk device under normal circumstances. If the collection pressure of any trend-related device is less than or equal to the collection pressure of the risk device at the same time, it does not conform to the natural law of the low-pressure trough, indicating that the collection parameters of the risk device may be abnormal.

[0086] Specifically, the data collection accuracy of risk equipment under current meteorological conditions is evaluated based on the verification results, including:

[0087] Obtain the total number of occurrences of abnormal features of adjacent data, abnormal features of historical data, and abnormal features of trend data;

[0088] The total number of occurrences was used as the collection accuracy to evaluate the collection accuracy.

[0089] It can be understood that this method is used to evaluate the accuracy of risk equipment collection and detect abnormal phenomena, and to provide data support for meteorological collection related work, so as to facilitate the determination of whether the risk equipment is faulty and the accuracy of its collection parameters in combination with actual scenarios. Due to unstable factors in the collection process, abnormal characteristics of adjacent data, abnormal characteristics of historical data, and abnormal characteristics of trend data cannot directly prove that the risk equipment is faulty.

[0090] Specifically, the extent of the monitoring area is periodically changed according to the air pressure within the target area.

[0091] See also Figure 4 As shown, the present invention provides a portable device for collecting meteorological monitoring emergency warning data, and a method for collecting meteorological monitoring emergency warning data using the above scheme includes:

[0092] Bracket 2,

[0093] The collection device body 1 is installed on a bracket and is used to collect meteorological data, wherein the meteorological data includes air pressure, wind direction, wind speed, temperature and humidity. The convenient collection device is more suitable for networking deployment in the target area due to its small size and portability. It can be combined with fixed collection stations, monitoring drones, meteorological collection vehicles, etc. to conveniently and effectively implement the above detection method, thereby improving the convenience of detection.

[0094] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the embodiments here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A method for collecting meteorological monitoring emergency warning data, characterized in that: include: Deploy a number of collection devices in the target area to collect meteorological data in the target area; When the weather in the target area meets the warning conditions, a monitoring area in the target area is determined; Determine the risk equipment that needs to be verified from the collection equipment in the monitoring area; For the risky equipment, regional verification, historical data verification and out-of-region verification are performed respectively; Evaluate the collection accuracy of risk equipment based on the verification results; The verification in the region is to compare the collected air pressure of the collection device closest to the risk device in the monitoring region with the collected air pressure of the risk device to verify whether the risk device has abnormal characteristics of adjacent data; The historical data verification is to compare the historical data of the air pressure in the monitoring area with the collected air pressure of the risk equipment to verify whether the risk equipment has abnormal historical data characteristics; The out-of-area verification is to compare the collected air pressure of the collection equipment outside the monitoring area with the collected air pressure of the risk equipment to verify whether there are abnormal trend data characteristics of the risk equipment; The target area is an area where a low-pressure trough exists, and the meteorological data includes air pressure, wind direction, wind speed, temperature and humidity.

2. The method for collecting meteorological monitoring emergency warning data according to claim 1, characterized in that: Determination of the monitoring area includes: Acquiring air pressure distribution in the target area; The enclosed area where the air pressure is lower than the preset value is determined as the monitoring area.

3. The method for collecting meteorological monitoring emergency warning data according to claim 2 is characterized in that: The determination of risky equipment includes: Collecting the number of historical failures of the collection equipment within the monitoring area; The collection equipment with the highest number of historical failures and the collection equipment with abnormal changes in air pressure are identified as risky equipment.

4. The method for collecting meteorological monitoring emergency warning data according to claim 3 is characterized in that: The verification within the region specifically includes: Acquire a verification device whose distance from the risk device is less than a preset distance; Screen out verification equipment with terrain obstacles or wind barriers between it and risk equipment; Perform correlation analysis on the verification devices and risk devices that have not been screened out, and determine the first correlation coefficient between the collected air pressure of each verification device and the risk device; If the first correlation coefficient of any verification device that has not been screened out is less than the preset coefficient, it is determined that there are abnormal features of adjacent data.

5. The method for collecting meteorological monitoring emergency warning data according to claim 4 is characterized in that: The historical data verification specifically includes: Extract historical data of air pressure corresponding to the location of risk equipment from the database; Through the meteorological event matching algorithm, the verification time period in the historical data that matches the current meteorological event is identified; The air pressure data of the verification time period is compared with the collected air pressure during the same period of time before the risk device to determine the second correlation coefficient, and the collected air pressure of the risk device is compared with the air pressure endpoint value in the historical data. If the second correlation coefficient is greater than the preset coefficient, or the maximum or minimum value in the collected air pressure exceeds the air pressure endpoint value, it is determined that abnormal characteristics of the historical data exist.

6. The method for collecting meteorological monitoring emergency warning data according to claim 5 is characterized in that: The out-of-region verification specifically includes: From the collection devices outside the monitoring area in the target area, trend-related devices are delineated at different positions of the risk devices, and the collection air pressures of each trend-related device and the risk equipment are compared respectively. If the collection air pressure of any trend-related device is less than or equal to the collection air pressure of the risk device at the same moment, it is determined that abnormal trend data features exist.

7. The method for collecting meteorological monitoring emergency warning data according to claim 6, characterized in that: The verification results are used to evaluate the accuracy of data collection of risk equipment under current meteorological conditions, including: Obtain the total number of occurrences of abnormal features of adjacent data, abnormal features of historical data, and abnormal features of trend data; The total number of occurrences was used as the collection accuracy to evaluate the collection accuracy.

8. The method for collecting meteorological monitoring emergency warning data according to claim 7, characterized in that: The range of the monitoring area is periodically corrected according to the air pressure in the target area.

9. A portable collection device for meteorological monitoring emergency warning data, characterized in that: The method for collecting meteorological monitoring emergency warning data as a collection device applied to any one of claims 1 to 8 comprises: Bracket, The collection device body is installed on the bracket and is used for collecting meteorological data, wherein the meteorological data includes air pressure.

10. The method for collecting meteorological monitoring emergency warning data according to claim 1, characterized in that: The meteorological data also includes wind direction, wind speed, temperature and humidity.

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