A thunderstorm gale monitoring, identification and classification warning method and system

Abstract

The invention discloses a thunderstorm and gale monitoring, identification and graded early warning method and system, belonging to the technical field of meteorological forecasting. The early warning method collects weather conditions and disaster information of thunderstorm and gale successively, pre-processes the meteorological element data of each layer at high and low altitude and on the ground, environmental physical quantity element data and radar data, reads radar data and performs grid data pre-processing, counts and extracts low-layer radial velocity thresholds corresponding to ground gale of different levels, identifies CR and VIL large value areas in real time, and realizes thunderstorm and gale monitoring, identification and graded early warning. The method realizes the inquiry and review of disaster information, weather conditions and statistical characteristics of thunderstorm and gale historical data and real-time weather conditions of thunderstorm and gale at any time, and realizes automatic identification of thunderstorm and gale, realizes monitoring, identification and graded early warning of thunderstorm and gale, and has important reference value for early decision-making in industries sensitive to thunderstorm and gale.

Description

Technical Field

[0001] The present invention belongs to the technical field of weather forecasting, and in particular relates to a thunderstorm gale monitoring, identification, and graded early warning method and system. Background Art

[0002] Among the disastrous weather caused by convective storms, thunderstorms are one of the most serious severe convective weather in China due to their high frequency, short duration, and strong disaster-causing characteristics. At present, scholars at home and abroad mainly use potential forecasts and intelligent identification of thunderstorms based on radar and other detection technologies and objective extrapolation and nowcasting. Based on a large amount of historical thunderstorm data, the statistical relationship or empirical threshold of thermodynamic physical parameters is obtained by calculating sounding data, and the forecast results of sounding data and / or numerical models are used. The key physical quantity parameter sensitivity analysis, proximity concept weight analysis, multivariate linear regression analysis, and batching method, index method, void elimination method, overlapping method and other methods are used to develop objective forecasting methods for thunderstorm potential, and certain application effects have been achieved in business. In recent years, scholars at home and abroad have established automatic thunderstorm identification algorithms by statistically analyzing thunderstorm environmental parameter indicators, radar characteristic indicators, and adding lightning, satellite and other data, and using fuzzy logic algorithms, decision trees, support vector machines and other machine learning methods, and gradually carried out the near-warning business application of automatic identification of thunderstorms. However, due to the relatively few cases of thunderstorms available for study, the vertical observation accuracy is still not fine enough, the extraction of favorable environmental parameters for thunderstorms is not accurate enough, and the mechanism research on the internal flow field structure configuration of convective storms, the phase transformation of storm precipitation particles, and the superposition effect of downdrafts and multi-scale interactions in storms is not sufficient. Therefore, the monitoring and identification of severe convective forecasts, especially thunderstorms, and the short-term forecast and warning capabilities are still limited.

[0003] Whether it is potential forecast, numerical model, artificial intelligence strong wind identification based on radar and other detection technologies, or short-term extrapolation forecast, they all rely on the support of observation data. In addition to the original basic data, secondary processing data based on various types of forecasts are also particularly important, such as various environmental physical quantity parameter indicators for potential forecast, radar characteristic indicators for intelligent identification technology, and radar graphic data with classification labels. In addition, there are currently few studies on thunderstorm gale classification warning methods in various types of thunderstorm gale forecasts. However, due to different levels of disasters of different intensities, the defense response measures to be taken are also different. Therefore, it is very necessary to propose a thunderstorm gale database-based and thunderstorm gale monitoring and identification classification warning method and system, so as to provide an effective data basis for the development of various types of forecast and warning methods, and provide refined guidance for weather forecasters. Summary of the invention

[0004] In view of this, the present invention provides a thunderstorm gale monitoring, identification and graded early warning method and system.

[0005] The present invention adopts the following technical solution:

[0006] A thunderstorm gale monitoring, identification and classification early warning method, the early warning method comprises the following steps:

[0007] S1 collects information, including the weather conditions and disaster information of thunderstorms and gale, and obtains the meteorological element data of each layer at high and low altitudes and on the ground, environmental physical quantity element data and radar data corresponding to thunderstorms and gale;

[0008] S2 data preprocessing, preprocessing the meteorological element data of each layer at high and low altitude and on the ground, the environmental physical quantity element data and the radar data, the preprocessing includes: summarizing the disaster information, analyzing the actual weather conditions and statistically analyzing the actual characteristics, and entering the results of the preprocessing into the thunderstorm and gale historical database and the thunderstorm and gale real-time database, the thunderstorm and gale historical database includes the disaster information, the actual weather conditions and statistical characteristics;

[0009] S3 thunderstorm and gale identification, reading radar data in the thunderstorm and gale historical database to obtain CR, V and VIL grid data and preprocessing the grid data to obtain preprocessed radar grid data, identifying the preprocessed radar grid data, marking the corresponding time and spatial positions of the maximum wind stations of level 8, level 9 and ≥10 on the ground in the thunderstorm and gale historical database to the preprocessed radar grid data, drawing and saving the gale identification picture, forming a data set of thunderstorm and gale radar image products of different levels with identification, wherein CR is the combined reflectivity factor, V is the low-level horizontal radial velocity, and VIL is the vertical cumulative liquid water content;

[0010] S4 threshold extraction, radial velocity threshold extraction for thunderstorm gale classification warning, based on the latitude and longitude information of the maximum wind stations of level 8, level 9 and ≥10 on the ground, spatial matching is performed with the low-level radial velocity grid points of the pre-processed radar grid data described in S3, and the low-level radial velocity threshold indicators corresponding to level 8, level 9 and ≥10 ground gale are counted and extracted;

[0011] S5 monitoring and early warning, real-time monitoring, identification and graded early warning of thunderstorms and gales. Real-time identification of CR and VIL high value areas is carried out according to the identification method described in S3. When the actual low-level radial velocity in any identified area of ​​CR or VIL reaches the low-level radial velocity threshold index described in S4, it is automatically identified and an alarm is issued, and different levels of thunderstorm and gale identification and early warning products are output to realize real-time monitoring, identification and graded early warning of thunderstorms and gales.

[0012] Further, S1 comprises the steps of:

[0013] S1.1 Use historical extreme wind data to preliminarily select wind stations of level 8 or above, remove obviously erroneous data, and then sort them by time to obtain preliminary selected strong wind weather data;

[0014] S1.2 Screening the historical data of thunderstorms and gales and forming the historical database information of thunderstorms and gales, using the radar fast playback technology to play back the corresponding Doppler weather radar base data according to the preliminary selected gale weather data to obtain radar image products, checking the radar image products one by one against the preliminary selected gale weather data, eliminating the gale weather caused by non-convection, obtaining the historical thunderstorm gale samples caused by pure convection, and forming the historical database information of thunderstorms and gales based on the collected disaster information, high and low altitude layers and ground meteorological element data, environmental physical quantity element data and radar data;

[0015] S1.3 forms real-time database information of thunderstorms and strong winds, and adopts a batch processing program. When thunderstorms and strong winds occur, the meteorological element data, environmental physical quantity element data and radar data of each layer at high and low altitudes and on the ground described in S1.2 are automatically captured from the resource pool. After the thunderstorms and strong winds occur, the disaster information is obtained from the direct disaster reporting system to form real-time database information of thunderstorms and strong winds.

[0016] Furthermore, the non-convection mentioned in S1.2 includes: typhoons, cyclones and other systematic strong winds.

[0017] Furthermore, the meteorological element data of each layer at high and low altitude and on the ground in S2 include temperature, air pressure, humidity and wind field information. The wind field information includes wind field information of each layer at high and low altitude and ground wind field information. The wind field information of each layer at high and low altitude includes wind direction and wind speed. The ground wind field information includes average wind speed, average wind direction, maximum wind speed, maximum wind direction and its occurrence time; the environmental physical quantity element data include convective effective potential, sinking convective effective potential, K index, SI index, wind speed vertical shear, 850-500hPa temperature difference, lifting condensation height, 0℃ layer height, -10℃ layer height, -20℃ layer height, dry layer intensity; the radar data include radar base data, horizontal and combined reflectivity factors, horizontal radial velocity, mesocyclone and storm parameters based on monomers. The storm parameters include echo top height, echo centroid height and vertical accumulated liquid water content.

[0018] Further, S2 comprises the steps of:

[0019] S2.1 Record the start and end time, occurrence range, disaster level, disaster description and supporting materials of historical data of thunderstorm and gale, and enter the disaster information part;

[0020] S2.2 Based on the start time of the above-mentioned historical data of thunderstorms and gale, draw and analyze the weather situation maps of each layer at high and low altitudes and on the ground during the corresponding period, and give the weather classification;

[0021] S2.3 respectively inputting the weather situation maps of each layer at high and low altitude and on the ground, the meteorological elements of each layer at high and low altitude and on the ground, the environmental physical quantity elements and the radar echo into the weather real-time part of the thunderstorm and gale historical database and the weather real-time part of the thunderstorm and gale real-time database;

[0022] S2.4 uses the strong winds from ground automatic stations as real-time data, and divides thunderstorms into three levels: maximum wind level 8, maximum wind level 9, and wind level 10 and above. It also counts the weather situation characteristics, favorable environmental physical quantity element threshold indicators, radar echoes, and storm parameter characteristics when thunderstorms occur, and enters them into the system in the statistical feature part of the thunderstorm historical database.

[0023] Furthermore, the lower layer of S3 has elevation angles of 0.5° and 1.5°, and the elevation angles are scanning elevation angles in vertical detection of the radar.

[0024] Furthermore, S3 comprises the steps of:

[0025] S3.1 The grid data preprocessing includes: using a two-dimensional discrete convolution method to convert CR ≥ 40dBZ and VIL ≥ 30kg / m 2 The grid point areas that are prone to thunderstorm gale are marked with distinguishing marks respectively; the radial velocity is quality controlled and defuzzified by using the two-step velocity defuzzification method, and the grid point data of radial velocity gale areas with V ≥ 17 or ≤ -17m / s are marked with distinguishing marks;

[0026] S3.2 Based on the latitude and longitude information of the site where the maximum wind is observed on the ground, the maximum wind sites of level 8, level 9 and ≥10 on the ground are marked with marks in the pre-processed radar grid data with a time difference of [-18min, 6min] from the time when the maximum wind occurs on the ground, and a strong wind identification picture is drawn and saved to form a data set of thunderstorm strong wind radar image products of different levels with identification.

[0027] Further, S4 comprises the steps of:

[0028] S4.1 uses a two-step velocity deambiguation method to perform quality control on the radial velocity at 0.5° elevation and 1.5° elevation, and obtains the radar radial velocity grid point data after quality control;

[0029] S4.2 spatially match the longitude and latitude information of the maximum wind station on the ground to the radar radial velocity grid point to obtain the matching grid point, take the maximum absolute value of the radial velocity within a radius of 5 grid points with the matching grid point as the center, set the matching grid point to be within 50km of the radar, take the maximum of the two layers of 0.5° and 1.5° elevation radial velocity, and take the maximum value of the 0.5° elevation radial velocity within the range of 50-100km from the matching grid point to the radar;

[0030] S4.3 Based on S4.2, the low-level radial velocity thresholds corresponding to ground gales of level 8, level 9 and ≥ level 10 are counted and extracted.

[0031] Further, S5 comprises the steps of:

[0032] S5.1 performs a two-step velocity defuzzification method on the real-time low-level radial velocity to obtain radar low-level radial velocity grid point data after quality control;

[0033] S5.2 Based on the radar low-layer radial velocity grid point data described in S5.1, set the radial velocity at 0.5° and 1.5° elevation angles within 50 km from the radar to take the maximum value of the two layers, take the radial velocity at 0.5° elevation angle within 50-100 km, and obtain the radial velocity values ​​of all grid points within 0-100 km;

[0034] S5.3 Identify the CR and VIL high value areas in real time according to the identification method described in S3;

[0035] S5.4 When the radial velocity in any marked area of ​​CR or VIL reaches the gale thresholds of different levels, it will automatically identify and alarm, output different levels of thunderstorm gale identification warning products, and realize thunderstorm gale monitoring, identification and graded warning.

[0036] A thunderstorm gale monitoring, identification and classification warning system, the warning system adopts the above-mentioned warning method, and the warning system comprises:

[0037] The information collection module is used to collect the weather conditions and disaster information of thunderstorms and gale, and obtain the meteorological element data of each layer at high and low altitudes and on the ground, the environmental physical quantity element data and radar data corresponding to the thunderstorms and gale;

[0038] A preprocessing module is used to preprocess the meteorological element data of each layer at high and low altitude and on the ground, the environmental physical quantity element data and the radar data, wherein the preprocessing includes: summarizing the disaster information, analyzing the actual weather conditions and statistically analyzing the actual characteristics, and entering the results of the preprocessing into a thunderstorm and gale historical database and a thunderstorm and gale real-time database, wherein the thunderstorm and gale historical database includes the disaster information, the actual weather conditions and statistical characteristics;

[0039] An identification module is used for thunderstorm and gale identification, which reads radar data in the thunderstorm and gale historical database to obtain CR, V and VIL grid data and performs grid data preprocessing to obtain preprocessed radar grid data, identifies the preprocessed radar grid data, marks the corresponding time and spatial positions of the maximum wind stations of level 8, level 9 and ≥10 on the ground in the thunderstorm and gale historical database to the preprocessed radar grid data, draws and saves gale identification pictures, and forms thunderstorm and gale radar image product data sets of different levels with identification, wherein CR is a combined reflectivity factor, V is a low-level horizontal radial velocity, and VIL is a vertically accumulated liquid water content;

[0040] The threshold extraction module is used for extracting the radial velocity threshold of thunderstorm gale classification warning. Based on the latitude and longitude information of the maximum wind stations of level 8, level 9 and ≥10 on the ground, the module spatially matches the low-level radial velocity grid points of the preprocessed radar grid data described in S3, and counts and extracts the low-level radial velocity threshold indicators corresponding to level 8, level 9 and ≥10 ground gale.

[0041] The monitoring and early warning module is used for real-time monitoring, identification and graded early warning of thunderstorms and gale. It identifies the CR and VIL large value areas in real time according to the identification method described in S3. When the actual low-level radial velocity in any identified area of ​​CR or VIL reaches the low-level radial velocity threshold index described in S4, it automatically identifies and issues an alarm, and outputs different levels of thunderstorm and gale identification and early warning products, thereby realizing real-time monitoring, identification and graded early warning of thunderstorms and gale.

[0042] Beneficial effects:

[0043] The present invention establishes a thunderstorm and gale database, which includes an information collection module, a preprocessing module, an identification module, a thunderstorm and gale graded warning radial velocity threshold extraction module and a monitoring and early warning module, which realizes the query and review of disaster information, weather conditions and statistical characteristics of historical data of thunderstorm and gale, and real-time weather conditions of thunderstorm and gale, facilitates similar data query and comparative analysis in business forecasts, and is conducive to the condensation, use and verification of threshold indicators of environmental physical quantity elements; the present invention also realizes automatic identification of thunderstorm and gale, reduces the burden of manual identification of forecasters, and the identification module provides different levels of thunderstorm and gale radar product data sets with identification, providing identification data sets for thunderstorm and gale artificial intelligence applications. The present invention realizes the monitoring, identification and graded early warning of thunderstorm and gale, provides reference information for forecasters to issue early warnings, and has important reference value for early decision-making in industries sensitive to thunderstorm and gale. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. The drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0045] Figure 1 The present invention is a schematic flow chart of a thunderstorm gale monitoring, identification and graded early warning method. DETAILED DESCRIPTION

[0046] In order to better understand the technical solution of the present invention, the embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0047] It should be clear that 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.

[0048] Example 1

[0049] A thunderstorm and gale monitoring and identification graded warning method, such as Figure 1 As shown, the steps of the early warning method are:

[0050] S1 collects information, including the weather conditions and disaster information of thunderstorms and gale, and obtains the meteorological element data of each layer at high and low altitudes and on the ground, environmental physical quantity element data and radar data corresponding to thunderstorms and gale;

[0051] S2 data preprocessing, preprocessing the meteorological element data of each layer at high and low altitude and on the ground, the environmental physical quantity element data and the radar data, the preprocessing includes: summarizing the disaster information, analyzing the actual weather conditions and statistically analyzing the actual characteristics, and entering the results of the preprocessing into the thunderstorm and gale historical database and the thunderstorm and gale real-time database, the thunderstorm and gale historical database includes the disaster information, the actual weather conditions and statistical characteristics;

[0052] S3 thunderstorm and gale identification, reading radar data in the thunderstorm and gale historical database to obtain CR, V and VIL grid data and preprocessing the grid data to obtain preprocessed radar grid data, identifying the preprocessed radar grid data, marking the corresponding time and spatial positions of the maximum wind stations of level 8, level 9 and ≥10 on the ground in the thunderstorm and gale historical database to the preprocessed radar grid data, drawing and saving the gale identification picture, forming a data set of thunderstorm and gale radar image products of different levels with identification, wherein CR is the combined reflectivity factor, V is the low-level horizontal radial velocity, and VIL is the vertical cumulative liquid water content;

[0053] S4 threshold extraction, radial velocity threshold extraction for thunderstorm gale classification warning, based on the latitude and longitude information of the maximum wind stations of level 8, level 9 and ≥10 on the ground, spatial matching is performed with the low-level radial velocity grid points of the pre-processed radar grid data described in S3, and the low-level radial velocity threshold indicators corresponding to level 8, level 9 and ≥10 ground gale are counted and extracted;

[0054] S5 monitoring and early warning, real-time monitoring, identification and graded early warning of thunderstorms and gales. Real-time identification of CR and VIL high value areas is carried out according to the identification method described in S3. When the actual low-level radial velocity in any identified area of ​​CR or VIL reaches the low-level radial velocity threshold index described in S4, it is automatically identified and an alarm is issued, and different levels of thunderstorm and gale identification and early warning products are output to realize real-time monitoring, identification and graded early warning of thunderstorms and gales.

[0055] Further, S1 comprises the steps of:

[0056] S1.1 Use historical extreme wind data to preliminarily select wind stations of level 8 or above, remove obviously erroneous data, and then sort them by time to obtain preliminary selected strong wind weather data;

[0057] S1.2 Screening the historical data of thunderstorms and gales and forming the historical database information of thunderstorms and gales, using the radar fast playback technology to play back the corresponding Doppler weather radar base data according to the preliminary selected gale weather data to obtain radar image products, checking the radar image products one by one against the preliminary selected gale weather data, eliminating the gale weather caused by non-convection, obtaining the historical thunderstorm gale samples caused by pure convection, and forming the historical database information of thunderstorms and gales based on the collected disaster information, high and low altitude layers and ground meteorological element data, environmental physical quantity element data and radar data;

[0058] S1.3 forms real-time database information of thunderstorms and strong winds, and adopts a batch processing program. When thunderstorms and strong winds occur, the meteorological element data, environmental physical quantity element data and radar data of each layer at high and low altitudes and on the ground described in S1.2 are automatically captured from the resource pool. After the thunderstorms and strong winds occur, the disaster information is obtained from the direct disaster reporting system to form real-time database information of thunderstorms and strong winds.

[0059] Furthermore, the non-convection mentioned in S1.2 includes: typhoons, cyclones and other systematic strong winds.

[0060] Furthermore, the meteorological element data of each layer at high and low altitude and on the ground in S2 include temperature, air pressure, humidity and wind field information. The wind field information includes wind field information of each layer at high and low altitude and ground wind field information. The wind field information of each layer at high and low altitude includes wind direction and wind speed. The ground wind field information includes average wind speed, average wind direction, maximum wind speed, maximum wind direction and its occurrence time; the environmental physical quantity element data include convective effective potential, sinking convective effective potential, K index, SI index, wind speed vertical shear, 850-500hPa temperature difference, lifting condensation height, 0℃ layer height, -10℃ layer height, -20℃ layer height, dry layer intensity; the radar data include radar base data, horizontal and combined reflectivity factors, horizontal radial velocity, mesocyclone and storm parameters based on monomers. The storm parameters include echo top height, echo centroid height and vertical accumulated liquid water content.

[0061] Further, S2 comprises the steps of:

[0062] S2.1 Record the start and end time, occurrence range, disaster level, disaster description and supporting materials of historical data of thunderstorm and gale, and enter the disaster information part;

[0063] S2.2 Based on the start time of the above-mentioned historical data of thunderstorms and gale, draw and analyze the weather situation maps of each layer at high and low altitudes and on the ground during the corresponding period, and give the weather classification;

[0064] S2.3 respectively inputting the weather situation maps of each layer at high and low altitude and on the ground, the meteorological elements of each layer at high and low altitude and on the ground, the environmental physical quantity elements and the radar echo into the weather real-time part of the thunderstorm and gale historical database and the weather real-time part of the thunderstorm and gale real-time database;

[0065] S2.4 uses the strong winds from ground automatic stations as real-time data, and divides thunderstorms into three levels: maximum wind level 8, maximum wind level 9, and wind level 10 and above. It also counts the weather situation characteristics, favorable environmental physical quantity element threshold indicators, radar echoes, and storm parameter characteristics when thunderstorms occur, and enters them into the system in the statistical feature part of the thunderstorm historical database.

[0066] Furthermore, the lower layer of S3 has elevation angles of 0.5° and 1.5°, and the elevation angles are scanning elevation angles in vertical detection of the radar.

[0067] Furthermore, S3 comprises the steps of:

[0068] S3.1 The grid data preprocessing includes: using a two-dimensional discrete convolution method to convert CR ≥ 40dBZ and VIL ≥ 30kg / m 2The grid point areas that are prone to thunderstorm gale are marked with distinguishing marks respectively; the radial velocity is quality controlled and defuzzified by using the two-step velocity defuzzification method, and the grid point data of radial velocity gale areas with V ≥ 17 or ≤ -17m / s are marked with distinguishing marks;

[0069] S3.2 Based on the latitude and longitude information of the site where the maximum wind is observed on the ground, the maximum wind sites of level 8, level 9 and ≥10 on the ground are marked with marks in the pre-processed radar grid data with a time difference of [-18min, 6min] from the time when the maximum wind occurs on the ground, and a strong wind identification picture is drawn and saved to form a data set of thunderstorm strong wind radar image products of different levels with identification.

[0070] Further, S4 comprises the steps of:

[0071] S4.1 uses a two-step velocity deambiguation method to perform quality control on the radial velocity at 0.5° elevation and 1.5° elevation, and obtains the radar radial velocity grid point data after quality control;

[0072] S4.2 spatially match the longitude and latitude information of the maximum wind station on the ground to the radar radial velocity grid point to obtain the matching grid point, take the maximum absolute value of the radial velocity within a radius of 5 grid points with the matching grid point as the center, set the matching grid point to be within 50km of the radar, take the maximum of the two layers of 0.5° and 1.5° elevation radial velocity, and take the maximum value of the 0.5° elevation radial velocity within the range of 50-100km from the matching grid point to the radar;

[0073] S4.3 Based on S4.2, the low-level radial velocity thresholds corresponding to ground gales of level 8, level 9 and ≥10 are counted and extracted.

[0074] Further, S5 comprises the steps of:

[0075] S5.1 performs a two-step velocity defuzzification method on the real-time low-level radial velocity to obtain radar low-level radial velocity grid point data after quality control;

[0076] S5.2 Based on the radar low-layer radial velocity grid point data described in S5.1, set the radial velocity at 0.5° and 1.5° elevation angles within 50 km from the radar to take the maximum value of the two layers, take the radial velocity at 0.5° elevation angle within 50-100 km, and obtain the radial velocity values ​​of all grid points within 0-100 km;

[0077] S5.3 Identify the CR and VIL high value areas in real time according to the identification method described in S3;

[0078] S5.4 When the radial velocity in any marked area of ​​CR or VIL reaches the gale thresholds of different levels, it will automatically identify and alarm, output different levels of thunderstorm gale identification warning products, and realize thunderstorm gale monitoring, identification and graded warning.

[0079] A thunderstorm gale monitoring, identification and classification warning system, the warning system adopts the above-mentioned warning method, and the warning system comprises:

[0080] The information collection module is used to collect the weather conditions and disaster information of thunderstorms and gale, and obtain the meteorological element data of each layer at high and low altitudes and on the ground, the environmental physical quantity element data and radar data corresponding to the thunderstorms and gale;

[0081] A preprocessing module is used to preprocess the meteorological element data of each layer at high and low altitude and on the ground, the environmental physical quantity element data and the radar data, wherein the preprocessing includes: summarizing the disaster information, analyzing the actual weather conditions and statistically analyzing the actual characteristics, and entering the results of the preprocessing into a thunderstorm and gale historical database and a thunderstorm and gale real-time database, wherein the thunderstorm and gale historical database includes the disaster information, the actual weather conditions and statistical characteristics;

[0082] An identification module is used for thunderstorm and gale identification, which reads radar data in the thunderstorm and gale historical database to obtain CR, V and VIL grid data and performs grid data preprocessing to obtain preprocessed radar grid data, identifies the preprocessed radar grid data, marks the corresponding time and spatial positions of the maximum wind stations of level 8, level 9 and ≥10 on the ground in the thunderstorm and gale historical database to the preprocessed radar grid data, draws and saves gale identification pictures, and forms thunderstorm and gale radar image product data sets of different levels with identification, wherein CR is a combined reflectivity factor, V is a low-level horizontal radial velocity, and VIL is a vertically accumulated liquid water content;

[0083] The threshold extraction module is used for extracting the radial velocity threshold of thunderstorm gale classification warning. Based on the latitude and longitude information of the maximum wind stations of level 8, level 9 and ≥10 on the ground, the module spatially matches the low-level radial velocity grid points of the preprocessed radar grid data described in S3, and counts and extracts the low-level radial velocity threshold indicators corresponding to level 8, level 9 and ≥10 ground gale.

[0084] The monitoring and early warning module is used for real-time monitoring, identification and graded early warning of thunderstorms and gale. It identifies the CR and VIL large value areas in real time according to the identification method described in S3. When the actual low-level radial velocity in any identified area of ​​CR or VIL reaches the low-level radial velocity threshold index described in S4, it automatically identifies and issues an alarm, and outputs different levels of thunderstorm and gale identification and early warning products, thereby realizing real-time monitoring, identification and graded early warning of thunderstorms and gale.

[0085] Example 2

[0086] like Figure 1 As shown, a schematic diagram of a thunderstorm gale monitoring, identification and graded warning method process includes:

[0087] Step 1: Collect the weather conditions and disaster information of thunderstorms and gale, and obtain the high and low altitude layers and ground meteorological element data, environmental physical quantity element data and radar data corresponding to the thunderstorms and gale;

[0088] Step 1 specifically includes:

[0089] 1.1 Use historical extreme wind data to preliminarily screen out wind stations with level 8 (≥17.2m / s) and above, and perform quality control on the data, remove obviously erroneous data, and then sort by time to obtain preliminary selected strong wind weather cases;

[0090] 1.2 Screening historical cases of thunderstorms and gale winds and forming historical database information of thunderstorms and gale winds. Based on the preliminary selected gale weather cases, the radar fast playback technology is used to play back the corresponding Doppler weather radar base data to obtain radar image products. The radar image products are checked one by one against the preliminary selected gale weather cases, and the gale weather caused by non-convection is eliminated, so as to obtain historical case samples of thunderstorms and gale winds caused by pure convection, and form the historical case database information of thunderstorms and gale winds. The non-convection includes typhoons, cyclones and other systematic gale winds;

[0091] 1.3 Form real-time database information of thunderstorms and strong winds, and use batch processing procedures. When thunderstorms and strong winds occur, the meteorological element data of each layer at high and low altitudes, ground meteorological element data, environmental physical quantity element data and radar data are automatically captured from the resource pool. After thunderstorms and strong winds occur, disaster information is obtained from the disaster direct reporting system to form real-time database information of thunderstorms and strong winds.

[0092] The beneficial effect of adopting the specific scheme of step 1 above is that after screening and elimination, non-thunderstorm gale winds mixed in thunderstorm gale winds are removed, ensuring that only correct and valuable pure thunderstorm gale events are left, providing an accurate data basis for subsequent feature summary. At the same time, the thunderstorm gale database is updated in real time, and a complete database system containing historical and real-time thunderstorm gale winds is established.

[0093] Step 2, pre-processing the meteorological element data of each layer at high and low altitude and on the ground, the environmental physical quantity element data and the radar data, summarizing the disaster information, analyzing the actual weather conditions and statistically analyzing the actual characteristics, and entering the summary and analysis statistical results into the thunderstorm and gale historical database and the thunderstorm and gale real-time database, the thunderstorm and gale historical database includes the disaster information, the actual weather conditions and statistical characteristics, and the thunderstorm and gale real-time database includes the actual weather conditions;

[0094] Step 2 The specific steps are as follows:

[0095] 2.1 Record the start and end time of the thunderstorm, the scope of occurrence, the disaster level, the description of the disaster and supporting materials, etc., and enter the disaster information;

[0096] 2.2 The meteorological element data of each layer at high and low altitudes and on the ground when the thunderstorm gale occurs include temperature, air pressure, humidity and wind, among which the wind field information of each layer at high and low altitudes includes wind direction and wind speed, and the ground wind field information includes average wind speed, average wind direction, maximum wind speed, maximum wind direction and its occurrence time; draw and analyze the weather situation field maps of each layer at high and low altitudes and on the ground, and give the weather classification; the environmental physical quantity elements include convective effective potential energy, sinking convective effective potential energy, K index, SI index, wind speed vertical shear, 850-500hPa temperature difference, lifting condensation height, 0℃ layer height, -10℃ layer height, -20℃ layer height, dry layer strength; radar data include radar base data, horizontal and combined reflectivity factors, horizontal radial velocity, mesocyclone and storm parameters based on monomers, among which storm parameters include echo top height, echo centroid height and vertical cumulative liquid water content;

[0097] 2.3 Based on the start time of the above-mentioned thunderstorm and gale historical cases, draw and analyze the weather situation maps of each layer at high and low altitudes and on the ground during the corresponding period, and give the weather classification;

[0098] 2.4 The weather conditions of each layer at high and low altitudes and on the ground, the meteorological elements of each layer at high and low altitudes and on the ground, the environmental physical quantity elements and the radar echo are respectively recorded in the weather real-time part of the thunderstorm and gale historical database and the weather real-time part of the thunderstorm and gale real-time database;

[0099] 2.5 Use the ground automatic station strong wind as the real-time data, and divide the thunderstorm strong wind into three levels according to the maximum wind level 8, maximum wind level 9 and level 10 and above. The weather situation characteristics, favorable environmental physical quantity element threshold indicators, radar echoes and storm parameter characteristics when the thunderstorm strong wind occurs are counted respectively, and the statistical characteristics part of the thunderstorm strong wind historical database is entered into the system.

[0100] The thunderstorm and gale real-time database can check the current weather conditions in real time, including the weather situation of each layer at high and low altitudes and the ground, the meteorological elements of each layer at high and low altitudes and the ground, the environmental physical quantity elements and radar echoes. The data are the same as the real-time weather meteorological data in the thunderstorm and gale historical database.

[0101] The beneficial effect of the specific step of step 2 is that the disaster information of historical cases of thunderstorms and gale, weather conditions including high and low altitude and ground weather conditions, high and low altitude and ground meteorological elements, radar images, etc., as well as statistical characteristics based on multiple cases and real-time case weather information are systematically entered, which can facilitate similar case query statistics and analysis forecasts in business forecasts, is conducive to the condensation, use and verification of threshold indicators of environmental physical quantity elements, and at the same time provide data support for scientific research on thunderstorms and gale.

[0102] Step 3, thunderstorm and strong wind identification, read radar base data to obtain grid data including CR, low-level (0.5 and 1.5° elevation angles) V and VIL and preprocess them, mark the corresponding time and spatial positions of the maximum wind stations of level 8, level 9 and ≥10 on the ground into the preprocessed radar grid data, draw and save the strong wind identification picture, and form a data set of thunderstorm and strong wind radar image products of different levels with identification, where CR is the combined reflectivity factor, V is the low-level horizontal radial velocity, and VIL is the vertical accumulated liquid water content.

[0103] The radar product grid data preprocessing in step 3 specifically includes:

[0104] 3.1 Use the two-dimensional discrete convolution method to convert CR ≥ 40dBZ and VIL ≥ 30kg / m 2 The grid point areas that are prone to thunderstorm gale are marked with distinguishing marks respectively; the radial velocity is quality controlled and defuzzified by using the two-step velocity defuzzification method, and the grid point data of radial velocity gale areas with V ≥ 17 or ≤ -17m / s are marked with distinguishing marks;

[0105] 3.2 According to the latitude and longitude information of the ground-observed extreme wind sites, the extreme wind sites of level 8, level 9 and ≥10 on the ground are marked with marks in the pre-processed radar grid data with a time difference of [-18min, 6min] from the occurrence time of the ground extreme wind, and the strong wind identification picture is drawn and saved to form a data set of thunderstorm strong wind radar image products of different levels with identification.

[0106] According to the research on the characteristic quantities of thunderstorm and gale radar, it is generally believed that it is more reasonable for radar products to be ahead of the occurrence time of ground gale within 3 individual scans (18 minutes) or behind the occurrence time of ground gale within 1 individual scan (6 minutes). According to the latitude and longitude information of the site where the maximum wind is observed on the ground, the maximum wind sites of level 8, level 9 and ≥10 on the ground are marked with different colors in the aforementioned pre-processed radar grid data with a difference of [-18 minutes, 6 minutes] from the occurrence time of the maximum wind on the ground. The gale identification picture is drawn and saved to form a data set of thunderstorm and gale radar products of different levels with identification.

[0107] The beneficial effect of the specific step 3 is that the areas where thunderstorms and strong winds may occur are marked. The overlapping areas of the CR, VIL, and V marked areas and the ground strong wind station marks are the areas with the highest probability of thunderstorms and strong winds. The automatic marking of thunderstorms and strong winds is realized, which improves work efficiency compared to manual marking and reduces the workload of forecasters.

[0108] Step 4: spatially match the low-level radial velocity grid data based on the latitude and longitude information of the ground 8, 9 and ≥ 10 maximum wind speed stations, and count and extract the low-level radial velocity thresholds corresponding to different levels of ground strong winds;

[0109] Step 4 The method for extracting radial velocity thresholds corresponding to different levels of ground gale is as follows:

[0110] 4.1 A two-step velocity deblurring method is used to perform quality control and deblurring of radial velocities at 0.5° elevation and 1.5° elevation.

[0111] 4.2 According to the spatial matching of the latitude and longitude information of the maximum wind station on the ground to the radar radial velocity grid point, take the maximum absolute value of the radial velocity within the radius of 5 grid points with the matched grid point as the center. Here, it is necessary to set the matching grid point to be within 50km of the radar, take the maximum of the two layers of 0.5° and 1.5° elevation radial velocity, and take the maximum value of 0.5° elevation radial velocity within 50-100km of the matching grid point from the radar;

[0112]

[0113] 4.3 Based on 4.2, the radial velocity thresholds corresponding to the surface gale of level 8, level 9 and level 10 or higher are calculated, and the regional forecast results are as follows:

[0114]

[0115]

[0116] The beneficial effect of the specific step of step 4 is to defuzzify the radial velocity to obtain a reliable radial velocity value, obtain the maximum absolute value of the low-level radial velocity within the effective distance, and extract the low-level radial velocity thresholds corresponding to thunderstorms of levels 8, 9 and ≥10, thereby providing a reliable basis for real-time graded warnings of thunderstorms.

[0117] Step 5: Identify the CR and VIL high value areas in real time according to the identification method of step 3. When the real-time low-level radial velocity in any identified area of ​​CR or VIL reaches different levels of gale thresholds, automatically identify and alarm, and output different levels of thunderstorm gale identification warning products to realize thunderstorm gale monitoring, identification and graded warning.

[0118] Step 5 specifically includes:

[0119] 5.1 Two-step deblurring of real-time low-level radial velocities;

[0120] 5.2 Within 50km from the radar, the radial velocity at 0.5° and 1.5° elevation angles takes the maximum value of the two layers, and within 50-100km, the radial velocity at 0.5° elevation angle is taken to obtain the radial velocity values ​​of all grid points within 0-100km;

[0121] 5.3 Identify the CR and VIL large value areas in real time according to the identification method in step 3;

[0122] 5.4 When the radial velocity in any marked area of ​​CR or VIL reaches the gale threshold of different levels, it will automatically identify and alarm, output different levels of thunderstorm gale identification warning products, and realize thunderstorm gale monitoring, identification and graded warning.

[0123] The beneficial effect of the specific step of step 5 is that the radial velocity is defuzzified to obtain a reliable radial velocity value, and the maximum radial velocity value of the low layer within the effective distance is obtained. After adding the limitation within any identification area of ​​CR or VIL, the automatic identification and alarm identification of thunderstorms and gales within the influence range of severe convective thunderstorms can be ensured, and the automatic monitoring, identification and graded warning of thunderstorms and gales can be realized.

[0124] The embodiments of the present invention are described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A thunderstorm and gale monitoring, identification and graded early warning method, characterized in that: The steps of the early warning method are: S1) Collect information, collect the weather conditions and disaster information of thunderstorms and gale, obtain the high and low altitude layers and ground meteorological element data, environmental physical quantity element data and radar data corresponding to thunderstorms and gale; S2) data preprocessing, preprocessing the meteorological element data of each layer at high and low altitude and on the ground, the environmental physical quantity element data and the radar data, the preprocessing comprising: summarizing the disaster information, analyzing the weather conditions and statistically analyzing the characteristics of the actual conditions, and entering the results of the preprocessing into a thunderstorm and gale historical database and a thunderstorm and gale real-time database, the thunderstorm and gale historical database comprising the disaster information, the weather conditions and statistical characteristics; S3) thunderstorm and gale identification, reading radar data in the thunderstorm and gale historical database to obtain CR, V and VIL grid data and preprocessing the grid data to obtain preprocessed radar grid data, identifying the preprocessed radar grid data, marking the corresponding time and spatial positions of the maximum wind stations of level 8, level 9 and level ≥10 on the ground in the thunderstorm and gale historical database to the preprocessed radar grid data, drawing and saving a gale identification picture, forming a thunderstorm and gale radar image product data set of different levels with identification, wherein CR is a combined reflectivity factor, V is a low-level horizontal radial velocity, and VIL is a vertical cumulative liquid water content; S4) Threshold extraction, radial velocity threshold extraction for thunderstorm gale classification warning, based on the latitude and longitude information of the maximum wind stations of level 8, level 9 and ≥10 on the ground, spatial matching is performed with the low-level radial velocity grid points of the pre-processed radar grid data described in S3, and statistics and extraction of low-level radial velocity threshold indicators corresponding to level 8, level 9 and ≥10 ground gale; S5) Monitoring and early warning: real-time monitoring, identification and graded early warning of thunderstorms and gale. The CR and VIL high value areas are identified in real time according to the identification method described in S3. When the actual low-level radial velocity in any identified area of ​​CR or VIL reaches the low-level radial velocity threshold index described in S4, it is automatically identified and an alarm is issued. Different levels of thunderstorm and gale identification and early warning products are output to realize real-time monitoring, identification and graded early warning of thunderstorms and gale.

2. According to claim 1, a thunderstorm gale monitoring, identification and classification warning method is characterized in that: S1 includes the steps: S1.1) Use historical extreme wind data to preliminarily select wind stations of level 8 or above, remove obviously erroneous data, and then sort them by time to obtain preliminary selected wind weather data; S1.2) screening the historical data of thunderstorms and gales and forming a historical database of thunderstorms and gales; based on the preliminary selected gale weather data, using the radar fast playback technology to play back the corresponding Doppler weather radar base data to obtain radar image products; checking the radar image products one by one against the preliminary selected gale weather data; eliminating the gale weather caused by non-convection, obtaining historical thunderstorm gale samples caused by pure convection; and forming a historical database of thunderstorms and gales based on the collected disaster information, high and low altitude layers and ground meteorological element data, environmental physical quantity element data and radar data; S1.3) Form a real-time database of thunderstorm and gale information, and use a batch processing program. When thunderstorm and gale weather occurs, the high and low altitude layers and ground meteorological element data, environmental physical quantity element data and radar data described in S1.2 are automatically captured from the resource pool. After the thunderstorm and gale weather occurs, the disaster information is obtained from the disaster direct reporting system to form a real-time database of thunderstorm and gale information.

3. A thunderstorm gale monitoring, identification and classification warning method according to claim 2, characterized in that: S1.2 The non-convection mentioned in the regulations includes typhoons, cyclones and other systematic strong winds.

4. A thunderstorm gale monitoring, identification and classification early warning method according to claim 2, characterized in that: S2 The meteorological element data of each layer at high and low altitude and on the ground include temperature, air pressure, humidity and wind field information. The wind field information includes wind field information of each layer at high and low altitude and ground wind field information. The wind field information of each layer at high and low altitude includes wind direction and wind speed. The ground wind field information includes average wind speed, average wind direction, maximum wind speed, maximum wind direction and its occurrence time; the environmental physical quantity element data include convective effective potential, sinking convective effective potential, K index, SI index, wind speed vertical shear, 850-500hPa temperature difference, lifting condensation height, 0℃ layer height, -10℃ layer height, -20℃ layer height, dry layer intensity; the radar data include radar base data, horizontal and combined reflectivity factors, horizontal radial velocity, mesocyclone and storm parameters based on monomers. The storm parameters include echo top height, echo centroid height and vertical accumulated liquid water content.

5. A thunderstorm gale monitoring, identification and graded early warning method according to claim 4, characterized in that: S2 includes the steps: S2.1) Record the start and end time, occurrence range, disaster level, disaster description and supporting materials of historical data of thunderstorm and gale, and enter the disaster information part; S2.2) Based on the start time of the above-mentioned historical data of thunderstorms and gale, draw and analyze the weather situation maps of each layer at high and low altitudes and on the ground during the corresponding period, and give the weather classification; S2.3) recording the weather situation maps of each layer at high and low altitude and on the ground, meteorological elements of each layer at high and low altitude and on the ground, environmental physical quantity elements and radar echoes into the weather real-time part of the thunderstorm and gale historical database and the weather real-time part of the thunderstorm and gale real-time database respectively; S2.4) Using the strong winds from the ground automatic station as the actual data, the thunderstorm strong winds are divided into three levels: maximum wind level 8, maximum wind level 9, and wind level 10 and above. The weather situation characteristics, favorable environmental physical quantity element threshold indicators, radar echoes and storm parameter characteristics when the thunderstorm strong wind occurs are respectively counted, and the statistical characteristics part of the thunderstorm strong wind historical database is entered into the system.

6. A thunderstorm gale monitoring, identification and graded early warning method according to claim 1, characterized in that: The lower layer of S3 has elevation angles of 0.5° and 1.5°, and the elevation angles are the scanning elevation angles in the vertical detection of the radar.

7. A thunderstorm gale monitoring, identification and graded early warning method according to claim 6, characterized in that: S3 includes the following steps: S3.1) The grid data preprocessing includes: using a two-dimensional discrete convolution method to convert CR ≥ 40dBZ and VIL ≥ 30kg / m 2 The grid point areas that are prone to thunderstorm gale are marked with distinguishing marks respectively; the radial velocity is quality controlled and defuzzified by using the two-step velocity defuzzification method, and the grid point data of radial velocity gale areas with V ≥ 17 or ≤ -17m / s are marked with distinguishing marks; S3.2) According to the latitude and longitude information of the site where the maximum wind is observed on the ground, the maximum wind sites of level 8, level 9 and ≥10 on the ground are marked with marks in the pre-processed radar grid data with a time difference of [-18min, 6min] from the time when the maximum wind occurs on the ground, and a high wind identification picture is drawn and saved to form a data set of thunderstorm high wind radar image products of different levels with identification.

8. A thunderstorm gale monitoring, identification and classification early warning method according to claim 1, characterized in that: S4 includes the steps: S4.1) using a two-step velocity deambiguation method to perform quality control on the radial velocities at 0.5° elevation angle and 1.5° elevation angle, and obtaining radar radial velocity grid point data after quality control; S4.2) spatially matching the longitude and latitude information of the maximum wind station on the ground to the radar radial velocity grid point, obtaining a matching grid point, taking the maximum absolute value of the radial velocity within a radius of 5 grid points with the matching grid point as the center, setting the matching grid point to be within 50 km of the radar, taking the maximum of the two layers of 0.5° and 1.5° elevation radial velocity, and taking the maximum radial velocity at an elevation angle of 0.5° within a range of 50-100 km from the matching grid point to the radar; S4.3) Based on S4.2, the low-level radial velocity thresholds corresponding to surface gale forces of 8, 9 and ≥10 are counted and extracted.

9. A thunderstorm gale monitoring, identification and graded early warning method according to claim 1, characterized in that: S5 includes the steps of: S5.1) performing a two-step velocity defuzzification method on the real-time low-level radial velocity to obtain radar low-level radial velocity grid point data after quality control; S5.2) Based on the radar low-layer radial velocity grid point data described in S5.1, set the radial velocity at 0.5° and 1.5° elevation angles within 50 km from the radar to take the maximum value of the two layers, take the radial velocity at 0.5° elevation angle within 50-100 km, and obtain the radial velocity values ​​of all grid points within 0-100 km; S5.3) Identify the CR and VIL high value areas in real time according to the identification method described in S3; S5.4) When the radial velocity in any marked area of ​​CR or VIL reaches the gale thresholds of different levels, it is automatically identified and alarmed, and different levels of thunderstorm gale identification warning products are output to realize thunderstorm gale monitoring, identification and graded warning.

10. A thunderstorm and gale monitoring, identification and classification warning system, characterized in that: The early warning system adopts the early warning method according to any one of claims 1 to 9, and the early warning system comprises: The information collection module is used to collect the weather conditions and disaster information of thunderstorms and gale, and obtain the meteorological element data of each layer at high and low altitudes and on the ground, the environmental physical quantity element data and radar data corresponding to the thunderstorms and gale; A preprocessing module is used to preprocess the meteorological element data of each layer at high and low altitude and on the ground, the environmental physical quantity element data and the radar data, wherein the preprocessing includes: summarizing the disaster information, analyzing the actual weather conditions and statistically analyzing the actual characteristics, and entering the results of the preprocessing into a thunderstorm and gale historical database and a thunderstorm and gale real-time database, wherein the thunderstorm and gale historical database includes the disaster information, the actual weather conditions and statistical characteristics; An identification module is used for thunderstorm and gale identification, which reads radar data in the thunderstorm and gale historical database to obtain CR, V and VIL grid data and performs grid data preprocessing to obtain preprocessed radar grid data, identifies the preprocessed radar grid data, marks the corresponding time and spatial positions of the maximum wind stations of level 8, level 9 and ≥10 on the ground in the thunderstorm and gale historical database to the preprocessed radar grid data, draws and saves gale identification pictures, and forms thunderstorm and gale radar image product data sets of different levels with identification, wherein CR is a combined reflectivity factor, V is a low-level horizontal radial velocity, and VIL is a vertically accumulated liquid water content; The threshold extraction module is used for extracting the radial velocity threshold of thunderstorm gale classification warning. Based on the latitude and longitude information of the maximum wind stations of level 8, level 9 and ≥10 on the ground, the module spatially matches the low-level radial velocity grid points of the preprocessed radar grid data described in S3, and counts and extracts the low-level radial velocity threshold indicators corresponding to level 8, level 9 and ≥10 ground gale. The monitoring and early warning module is used for real-time monitoring, identification and graded early warning of thunderstorms and gale. It identifies the CR and VIL large value areas in real time according to the identification method described in S3. When the actual low-level radial velocity in any identified area of ​​CR or VIL reaches the low-level radial velocity threshold index described in S4, it automatically identifies and issues an alarm, and outputs different levels of thunderstorm and gale identification and early warning products, thereby realizing real-time monitoring, identification and graded early warning of thunderstorms and gale.

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