WO2024098499A1 - 热带气旋对称性结构分析方法、装置、设备及存储介质 - Google Patents

热带气旋对称性结构分析方法、装置、设备及存储介质 Download PDF

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WO2024098499A1
WO2024098499A1 PCT/CN2022/138216 CN2022138216W WO2024098499A1 WO 2024098499 A1 WO2024098499 A1 WO 2024098499A1 CN 2022138216 W CN2022138216 W CN 2022138216W WO 2024098499 A1 WO2024098499 A1 WO 2024098499A1
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tropical
polar coordinate
tropical cyclone
cyclone
symmetry
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PCT/CN2022/138216
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English (en)
French (fr)
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李晴岚
张佳丽
朱港亚
赵玮
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中国科学院深圳先进技术研究院
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Publication of WO2024098499A1 publication Critical patent/WO2024098499A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

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  • the present application relates to the technical field of meteorological analysis, and in particular to a method, device, equipment and storage medium for analyzing the symmetric structure of a tropical cyclone.
  • Tropical cyclones are one of the most complex weather systems in the atmosphere, involving thermal and dynamic processes at multiple scales and interactions between different scales. With the development of observation methods, especially the application of unconventional observation data such as satellite radar, the accuracy of tropical cyclone path forecasts has been significantly improved, but the development of tropical cyclone intensity and structure forecasts is still slow. In coastal areas, with economic development, the disaster losses caused by tropical cyclones are gradually increasing, so the accuracy of tropical cyclone intensity forecasts is essential for tropical cyclone prevention and disaster reduction. Tropical cyclone intensity forecasting has always been a difficult point in forecasting, especially the rapid intensification of tropical cyclones has aggravated the difficulty of tropical cyclone intensity forecasting, which is a huge challenge in forecasting.
  • the research on the asymmetric characteristics of tropical cyclones mainly includes the following studies: (1) The GMS-5 satellite and radar data were used to study the asymmetric distribution of convection in tropical cyclones that landed on the coast of South China; (2) The probability density curve of the frequency of convection in tropical cyclones in the northwest Pacific is approximately a sine function along the azimuth angle, with obvious one-wave characteristics.
  • the first method only conducts comparative analysis on the asymmetric distribution of convection in different quadrants of typical tropical cyclones, and it is difficult to form a consistent measurement index for the asymmetric distribution of all tropical cyclones;
  • the second method uses the maximum amplitude of a wave of asymmetric values to represent the uniformity of convection distribution, and tends to study the asymmetric characteristics of convection in the spiral rain belt area outside the tropical cyclone;
  • the third method is easily affected by the interference of extreme brightness temperature values and easily produces large fluctuations.
  • the present invention provides a tropical cyclone symmetry structure analysis method, device, equipment and storage medium, defines the index parameters of the convective symmetry of the inner core area of the tropical cyclone, and analyzes the relationship between the convective symmetry index parameters of the inner core of the tropical cyclone and the evolution of the tropical cyclone intensity.
  • a technical solution adopted in the present application is: to provide a method for analyzing the symmetry structure of a tropical cyclone, the method comprising: obtaining the best path data set of multiple tropical cyclones within a preset time period, and obtaining the hourly center position and intensity value of the tropical cyclone based on the best path data set; creating a corresponding polar coordinate system with the center position of the tropical cyclone as the origin; obtaining the hourly infrared cloud top brightness temperature data of the tropical cyclone, and inserting the infrared cloud top brightness temperature data into the polar coordinate grid of the corresponding polar coordinate system by interpolation method based on the time correspondence, to obtain the infrared cloud top brightness temperature polar coordinate grid data; calculating the convective symmetry index parameters of the preset inner core area of the tropical cyclone based on the infrared cloud top brightness temperature polar coordinate grid data; and analyzing the relationship between the convective symmetry index parameters of all tropical cycl
  • the convective symmetry index parameters of the preset inner core area of the tropical cyclone are calculated based on the infrared cloud top brightness temperature polar coordinate grid data, including: calculating the 10% quantile and 90% quantile of the infrared cloud top brightness temperature polar coordinate grid data of the preset inner core area of the tropical cyclone; and calculating the convective symmetry index parameters of the tropical cyclone based on the difference between the 10% quantile and the 90% quantile.
  • the infrared cloud top brightness temperature data are interpolated into the polar coordinate grid of the corresponding polar coordinate system based on the time correspondence to obtain the infrared cloud top brightness temperature polar coordinate grid data, including: confirming the target polar coordinate grid points of each polar coordinate system with an interval of 4km in the radius r direction and 5° in the azimuth ⁇ direction; based on the time correspondence, the infrared cloud top brightness temperature data are interpolated into the target polar coordinate grid points of the corresponding polar coordinate system by the interpolation method to obtain the infrared cloud top brightness temperature polar coordinate grid data.
  • the preset inner core area of the tropical cyclone includes a circular area between a first preset radius and a second preset radius with the center of the tropical cyclone as the center, and the first preset radius is smaller than the second preset radius.
  • the relationship between the convective symmetry index parameters of all tropical cyclones and the intensity of the tropical cyclones is analyzed, including: comparing and analyzing the first characteristic of the convective symmetry index in the rapid intensification stage and the non-rapid intensification stage of the tropical cyclone, and constructing a first box plot for analysis, the rapid intensification stage and the non-rapid intensification stage are determined according to the magnitude of the continuously increasing wind speed of the maximum surface wind in a preset time period; comparing and analyzing the second characteristic of the convective symmetry index in the rapid intensification stage of tropical cyclones of different grades, and constructing a second box plot for analysis, the grade of the tropical cyclone is determined according to the magnitude of the maximum wind speed near the center of the tropical cyclone; comparing and analyzing the third characteristic of the convective symmetry index parameters changing with time in the rapid intensification stage of the tropical cyclone, and constructing a third box plot for analysis.
  • a convective symmetry index parameter is added as a prediction factor into the tropical cyclone intensity prediction model.
  • a tropical cyclone symmetry structure analysis device comprising: a first acquisition module, used to obtain the best path data set of multiple tropical cyclones within a preset time period, and obtain the hourly tropical cyclone position and intensity values based on the best path data set; a creation module, used to create a corresponding polar coordinate system with the center position of the tropical cyclone as the origin; a second acquisition module, used to obtain the hourly infrared cloud top brightness temperature data of the tropical cyclone, and based on the time correspondence, insert the infrared cloud top brightness temperature data into the polar coordinate grid of the polar coordinate system of the corresponding tropical cyclone by interpolation method to obtain the infrared cloud top brightness temperature polar coordinate grid data; a calculation module, used to calculate the convective symmetry index parameters of the preset inner core area of the tropical cyclone based on the infrared cloud top brightness temperature polar coordinate grid data; an
  • the computer device includes a processor and a memory coupled to the processor, the memory stores program instructions, and when the program instructions are executed by the processor, the processor executes the steps of the tropical cyclone symmetry structure analysis method as described in any one of the above items.
  • another technical solution adopted by the present application is: to provide a storage medium storing program instructions capable of implementing any of the above tropical cyclone symmetry structure analysis methods.
  • the tropical cyclone symmetry structure analysis method of the present application confirms the hourly tropical cyclone position and intensity values according to the optimal path data set of the tropical cyclone, creates a polar coordinate system with the tropical cyclone center position as the origin, and then obtains the hourly infrared cloud top brightness temperature data of the tropical cyclone, inserts the infrared cloud top brightness temperature data into the polar coordinate grid according to the temporal correspondence, obtains the infrared cloud top brightness temperature polar coordinate grid data, and then defines the convective symmetry index parameters of the inner core area of the tropical cyclone with the infrared cloud top brightness temperature polar coordinate grid data, and finally analyzes the relationship between the convective symmetry index parameters of the tropical cyclone and the intensity of the tropical cyclone, so that researchers can explore the application of the convective symmetry index in tropical cyclone intensity forecasting on this basis.
  • FIG1 is a schematic diagram of a process of a method for analyzing a tropical cyclone symmetry structure according to an embodiment of the present invention
  • Figure 2 is a statistical box plot of the convective symmetry index of the tropical cyclone in the northwest Pacific during the rapid intensification (RI) stage and the non-rapid intensification (No-RI) stage;
  • Figure 3 is a statistical box plot of the convective symmetry index of rapid intensification of tropical cyclones of different grades in the Northwest Pacific from 2009 to 2021;
  • Figure 4 is a statistical box plot of the changes in convective symmetry index over time during the rapid intensification of a tropical cyclone
  • FIG5 is a schematic diagram of functional modules of a tropical cyclone symmetry structure analysis device according to an embodiment of the present invention.
  • FIG6 is a schematic diagram of the structure of a computer device according to an embodiment of the present invention.
  • FIG. 7 is a schematic diagram of the structure of a storage medium according to an embodiment of the present invention.
  • first”, “second” and “third” in this application are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features.
  • the features defined as “first”, “second” and “third” can explicitly or implicitly include at least one of the features.
  • the meaning of “multiple” is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. All directional indications (such as up, down, left, right, front, back%) in the embodiments of this application are only used to explain the relative position relationship, movement, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication also changes accordingly.
  • FIG1 is a schematic flow chart of a method for analyzing the symmetric structure of a tropical cyclone according to an embodiment of the present invention. It should be noted that the method of the present invention is not limited to the flow sequence shown in FIG1 if substantially the same results are obtained. As shown in FIG1 , the method for analyzing the symmetric structure of a tropical cyclone comprises the following steps:
  • Step S101 obtaining optimal path data sets of multiple tropical cyclones within a preset time period, and obtaining hourly central positions and intensity values of tropical cyclones based on the optimal path data sets.
  • the best path data set (the element is the best path record of tropical cyclones) in the northwest Pacific Ocean (or the Atlantic Ocean, Indian Ocean, etc.) for many years can be downloaded from the official websites of Shanghai Typhoon Institute, the United States Joint Typhoon Warning Center, Japan Meteorological Agency, etc.
  • Each best path data set of tropical cyclones contains the longitude and latitude position and intensity of the center of the tropical cyclone every 6 hours from the formation to the extinction of the tropical cyclone. This embodiment assumes that the tropical cyclone is moving at a uniform speed and is evenly strengthened (or weakened) during the two recording times, and the center position and intensity values of the tropical cyclone per hour can be obtained by linear interpolation.
  • Step S102 creating a corresponding polar coordinate system with the center of the tropical cyclone as the origin.
  • Step S103 Obtain hourly infrared cloud top brightness temperature data of tropical cyclones during the study period, and insert the infrared cloud top brightness temperature data into the corresponding polar coordinate grid using the RBF interpolation method based on the time correspondence to obtain polar coordinate grid data of infrared cloud top brightness temperature.
  • the satellite observation range can cover most of the ocean surface area, it makes up for the lack of atmospheric detection capabilities on the ocean to a large extent, and provides more abundant remote sensing data for tropical cyclone research.
  • the infrared cloud top brightness temperature has a good correspondence with strong convection and precipitation caused by convection, so it can better indicate the strength of convection.
  • the lower the brightness temperature value the higher the cloud top extension height and the more vigorous the convection.
  • the faster the vortex rotates the better its symmetry.
  • this embodiment uses the brightness temperature value of the long-wave infrared channel of the FY-2 series satellites to analyze the asymmetric structural characteristics of the inner core convection of the tropical cyclone.
  • this embodiment downloads hourly Fengyun-2 full disk nominal image files and their latitude and longitude comparison tables during the occurrence of tropical cyclones from the Fengyun satellite remote sensing data service website, and then processes the downloaded data to obtain the brightness temperature value of the long-wave infrared channel (wavelength range: 10.3 - 11.3 ⁇ m). Then, the brightness temperature value of the hourly long-wave infrared channel is interpolated to the corresponding polar coordinate grid according to the time correspondence. Specifically, based on the time correspondence, the infrared cloud top brightness temperature data is interpolated into the corresponding tropical cyclone polar coordinate system by interpolation method to obtain the infrared cloud top brightness temperature coordinate data, which specifically includes:
  • the infrared cloud top brightness temperature data is interpolated into the target polar coordinate grid points of the corresponding polar coordinate system by interpolation method to obtain the infrared cloud top brightness temperature polar coordinate grid data.
  • Step S104 Calculate the convective symmetry index parameters of the preset inner core region of the tropical cyclone based on the infrared cloud top brightness temperature polar coordinate grid data.
  • the tropical cyclone convective activity studied in this embodiment is limited to the preset inner core area of the tropical cyclone.
  • the inner core area of a tropical cyclone is defined as: the area within a radius of 1° with the center of the tropical cyclone as the center of the circle (the tropical and subtropical regions are approximately within a radius of 100 km).
  • downward airflow prevails in the eye of the tropical cyclone, and the brightness temperature value is relatively large.
  • this embodiment sets the preset inner core area of the tropical cyclone to a circular area between the first preset radius and the second preset radius with the center of the tropical cyclone as the center of the circle, and the first preset radius is smaller than the second preset radius.
  • the first preset radius is preferably 50km
  • the second preset radius is preferably 100km.
  • step S104 specifically includes:
  • Symmetric Ratio 1-(90%TBB - 10% TBB)/maximum(90%TBB - 10% TBB);
  • Symmetric Ratio represents the convective symmetry index parameter
  • TBB represents the polar coordinate grid data of infrared cloud top brightness temperature
  • maximum (90%TBB - 10% TBB) represents the preset climate value. This embodiment is based on the tropical cyclone in the northwest Pacific from 2009 to 2021, so the preset climate value is set to 105.
  • Step S105 Analyze the relationship between the convective symmetry index parameters of all tropical cyclones and the intensity of the tropical cyclones.
  • step S105 specifically includes:
  • the rapid intensification stage and the non-rapid intensification stage are determined according to the maximum surface wind speed that continues to increase within the preset time period.
  • the most commonly used criterion for rapid intensification of tropical cyclones is that the maximum surface wind continues to increase to 15 m/s within 24 hours.
  • the 24-hour criterion tends to favor the rapid intensification of tropical cyclones with central winds less than 33 m/s, while for some tropical cyclones with intensities greater than 33 m/s, when rapid intensification occurs, the structure with the maximum wind speed radius in a stable state may not be able to last for 24 hours. Therefore, they define the continuous increase of the maximum surface wind to 10 m/s within 12 hours as a rapid intensification process.
  • the present invention uses this standard to calculate tropical cyclones that undergo a rapid intensification process during the study period, which can be applied to the rapid changes of tropical cyclones with a larger intensity range.
  • Figure 2 shows the statistical box plot of the convective symmetry indicators of tropical cyclones in the northwest Pacific in the rapid intensification (RI) stage and the non-rapid intensification (No-RI) stage from 2009 to 2021. It can be seen from Figure 2 that the median and minimum values of the convective symmetry indicators in the rapid intensification stage are greater than those in the non-rapid intensification stage, indicating that the better the symmetry of the tropical cyclone, the more likely it is to intensify rapidly.
  • the level of tropical cyclones is determined according to the maximum wind speed near the center of the tropical cyclone.
  • Figure 3 shows the statistical box plot of the rapidly enhanced convective symmetry indicators of tropical cyclones of different levels in the northwest Pacific from 2009 to 2021. From the statistical results, the higher the level of the tropical cyclone, the larger the median and minimum values of its convective symmetry index, indicating that the convection in its inner core is also more compact and symmetrical.
  • Figure 4 is a statistical box plot of the convective symmetry index changing with time during the rapid intensification of a tropical cyclone. It can be seen from Figure 4 that during the rapid intensification of a tropical cyclone, the median of its symmetry index gradually increases with time, indicating that the convection in the inner core of the tropical cyclone tends to be more symmetrical during the rapid intensification process.
  • the convective symmetry index parameter is used to add to the tropical cyclone intensity prediction model.
  • This embodiment obtains the hourly central position of the tropical cyclone according to the optimal path data of the tropical cyclone, creates a polar coordinate system with the central position of the tropical cyclone as the origin, obtains the hourly infrared cloud top brightness temperature data of the tropical cyclone, interpolates the infrared cloud top brightness temperature data into the polar coordinate grid points according to the corresponding relationship in time, obtains the infrared cloud top brightness temperature polar coordinate grid data, and then defines the convective symmetry index parameters of the inner core of the tropical cyclone with the infrared cloud top brightness temperature polar coordinate grid data.
  • the relationship between the index parameters and the intensity of the tropical cyclone is analyzed, which accurately reflects the changing characteristics of the convective symmetry of the inner core of the tropical cyclone during the intensity change of the tropical cyclone, so that researchers can explore the application of the convective symmetry index in the tropical cyclone intensity forecast on this basis.
  • Fig. 5 is a functional module diagram of a tropical cyclone symmetry structure analysis device according to an embodiment of the present invention.
  • the tropical cyclone symmetry structure analysis device 20 comprises a first acquisition module 21 , a creation module 22 , a second acquisition module 23 , a calculation module 24 and an analysis module 25 .
  • a first acquisition module 21 is used to acquire optimal path data sets of multiple tropical cyclones within a preset time period, and acquire hourly tropical cyclone positions and intensity values based on the optimal path data sets;
  • a creation module 22 used to create a corresponding polar coordinate system with the center position of the tropical cyclone as the origin;
  • the second acquisition module 23 is used to obtain the infrared cloud top brightness temperature data of the tropical cyclone hour by hour, and insert the infrared cloud top brightness temperature data into the polar coordinate grid of the polar coordinate system of the corresponding tropical cyclone by interpolation method based on the time correspondence, so as to obtain the infrared cloud top brightness temperature polar coordinate grid data;
  • a calculation module 24 configured to calculate a convective symmetry index parameter of a preset inner core region of a tropical cyclone based on the infrared cloud top brightness temperature polar coordinate grid data;
  • the analysis module 25 is used to analyze the relationship between the convective symmetry index parameters of all tropical cyclones and the intensity of the tropical cyclones.
  • the calculation module 24 performs an operation of calculating the convective symmetry index parameters of the preset inner core area of the tropical cyclone based on the infrared cloud top brightness temperature polar coordinate grid data, specifically including: calculating the 10% quantile and 90% quantile of the infrared cloud top brightness temperature polar coordinate grid data of the preset inner core area of the tropical cyclone; and calculating the convective symmetry index parameters of the tropical cyclone based on the difference between the 10% quantile and the 90% quantile.
  • the calculation formula of the convection symmetry index parameter is expressed as:
  • Symmetric Ratio 1-(90%TBB - 10% TBB)/maximum(90%TBB - 10% TBB);
  • Symmetric Ratio represents the convective symmetry index parameter
  • TBB represents the polar coordinate grid data of infrared cloud top brightness temperature
  • maximum (90%TBB - 10% TBB) represents the preset climate value.
  • the second acquisition module 23 performs an operation of inserting the infrared cloud top brightness temperature data into the polar coordinate grid of the corresponding polar coordinate system by interpolation based on the time correspondence to obtain the infrared cloud top brightness temperature polar coordinate grid data, specifically including: confirming the target polar coordinate grid points of each polar coordinate system with an interval of 4 km in the radius r direction and 5° in the azimuth ⁇ direction; inserting the infrared cloud top brightness temperature data into the target polar coordinate grid points of the corresponding polar coordinate system by interpolation based on the time correspondence to obtain the infrared cloud top brightness temperature polar coordinate grid data.
  • the preset inner core region of the tropical cyclone includes a circular ring region between a first preset radius and a second preset radius with the center of the tropical cyclone as the center, and the first preset radius is smaller than the second preset radius.
  • the analysis module 25 performs an operation of analyzing the relationship between the convective symmetry index parameters of all tropical cyclones and the intensity of the tropical cyclones, specifically including: comparing and analyzing the first feature of the convective symmetry index in the rapid intensification stage and the non-rapid intensification stage of the tropical cyclone, and constructing a first box plot for analysis, the rapid intensification stage and the non-rapid intensification stage are determined according to the magnitude of the maximum surface wind speed that continues to increase within a preset time period; comparing and analyzing the second feature of the convective symmetry index in the rapid intensification stage of tropical cyclones of different grades, and constructing a second box plot for analysis, the grade of the tropical cyclone is determined according to the magnitude of the maximum wind speed near the center of the tropical cyclone; comparing and analyzing the third feature of the convective symmetry index parameters changing with time in the rapid intensification stage of the tropical cyclone, and constructing a third box plot for analysis.
  • the convective symmetry index parameter is added as a prediction factor to the tropical cyclone intensity prediction model.
  • each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the embodiments can be referred to each other.
  • the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.
  • Fig. 6 is a schematic diagram of the structure of a computer device according to an embodiment of the present invention.
  • the computer device 30 includes a processor 31 and a memory 32 coupled to the processor 31, wherein the memory 32 stores program instructions, and when the program instructions are executed by the processor 31, the processor 31 executes the steps of the tropical cyclone symmetry structure analysis method described in any of the above embodiments.
  • the processor 31 may also be referred to as a CPU (Central Processing Unit).
  • the processor 31 may be an integrated circuit chip having the ability to process signals.
  • the processor 31 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
  • DSP digital signal processor
  • ASIC application-specific integrated circuit
  • FPGA field programmable gate array
  • the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.
  • FIG. 7 is a schematic diagram of the structure of the storage medium of the embodiment of the present invention.
  • the storage medium of the embodiment of the present invention stores program instructions 41 that can implement the above-mentioned tropical cyclone symmetry structure analysis method, wherein the program instructions 41 can be stored in the above-mentioned storage medium in the form of a software product, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application.
  • a computer device which can be a personal computer, server, or network device, etc.
  • the aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes, or computer devices such as computers, servers, mobile phones, tablets, etc.
  • the disclosed computer equipment, devices and methods can be implemented in other ways.
  • the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.
  • the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.
  • each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the above integrated unit may be implemented in the form of hardware or in the form of software functional units. The above is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the contents of the specification and drawings of this application, or directly or indirectly used in other related technical fields, is also included in the patent protection scope of the present application.

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Abstract

本发明公开了热带气旋对称性结构分析方法、装置、设备及存储介质，其中通过从热带气旋的最佳路径数据集中获取逐小时的热带气旋中心位置和强度数值，再以热带气旋中心位置为原点创建极坐标系，再获取热带气旋逐小时的红外云顶亮温数据，并将红外云顶亮温数据以插值法插入至对应的极坐标系的极坐标网格中，得到红外云顶亮温极坐标网格数据，再基于红外云顶亮温极坐标网格数据计算热带气旋的预设内核区域的对流对称性指标参数，最后分析所有热带气旋的对流对称性指标参数与热带气旋的强度之间的关系。本发明基于热带气旋的红外云顶亮温数据定义气旋内核的对流对称性指标，并探索其与气旋强度变化的关系，以便探索该指标在热带气旋强度预报中的应用。

Description

热带气旋对称性结构分析方法、装置、设备及存储介质 技术领域
本申请涉及气象分析技术领域，特别是涉及一种热带气旋对称性结构分析方法、装置、设备及存储介质。
 背景技术
热带气旋是大气中最复杂的天气系统之一，包含了多个尺度的热力和动力学过程以及不同尺度之间的相互作用。随着观测手段的发展，尤其是卫星雷达等非常规观测资料的应用使得热带气旋路径预报精度显著提高，但热带气旋强度和结构预报发展仍然进展缓慢。在沿海地区，随着经济发展，由热带气旋造成的灾害损失也逐渐增大，所以热带气旋强度预报的精度对于热带气旋防台减灾工作必不可少。热带气旋强度预报一直是预报中的难点，尤其热带气旋的快速增强加剧了热带气旋强度预报的难度，是预报中的巨大挑战。
几十年来，许多学者致力于热带气旋演变机制的研究工作，有研究发现，在大尺度环境有利于热带气旋强度发展的情况下，热带气旋自身的内核结构变化对快速增强具有重要的作用，进一步探究发生快速增强的热带气旋内核结构和演变特征对热带气旋快速增强预报十分必要。有关热带气旋增强机制研究结果表明：对流活动中水汽凝结潜热释放被认为是热带气旋二级环流发展和维持的主要能量源。然而，这种有组织的强对流活动在热带气旋环流中往往是以非对称形式出现，而且这种非对称性在热带气旋发展早期以及衰弱期尤为明显。因此，研究热带气旋非对称特征与热带气旋强度变化的关系对于完善热带气旋非对称增强机制具有重要的研究意义。
目前，对热带气旋非对称特征的研究主要有以下研究：（1）利用GMS-5卫星和雷达资料研究了登陆中国华南沿海热带气旋的对流非对称分布；（2）西北太平洋热带气旋内对流发生频率的概率密度曲线沿方位角近似为正弦函数，具有明显的一波特征，因此很多研究将TBB场沿方位角进行傅里叶展开，通过计算一波非对称值来表征对流的非对称程度；（3）在大西洋和东北太平洋的热带气旋快速增强预测模型中以红外云顶亮度温度为30摄氏度以下(PX30)覆盖半径50-200公里范围内的百分比，以及同一区域红外云顶亮度温度的标准偏差(SDBT)作为表明热带气旋中心周围对流对称性的预测因子。但上述三种方式中，第一种方式只针对典型热带气旋个例在不同象限的对流非对称分布进行比较分析，对所有热带气旋的非对称分布难以形成一致的衡量指标；第二种方式通过一波非对称值的最大振幅表示对流分布的均匀程度，倾向于研究热带气旋外螺旋雨带区的对流非对称特征；第三种方式受极端亮温值的干扰容易产生较大波动。
 技术问题
有鉴于此，本发明提供一种热带气旋对称性结构分析方法、装置、设备及存储介质，定义了热带气旋内核区域的对流对称性的指标参数，并分析热带气旋内核的对流对称性指标参数与热带气旋强度演变的关系。
 技术解决方案
为解决上述技术问题，本申请采用的一个技术方案是：提供一种热带气旋对称性结构分析方法，方法包括：获取预设时间段内多个热带气旋的最佳路径数据集，并基于最佳路径数据集获取逐小时的热带气旋中心位置和强度数值；以热带气旋中心位置为原点创建对应的极坐标系；获取热带气旋逐小时的红外云顶亮温数据，并基于时间对应关系将红外云顶亮温数据以插值法插入至对应的极坐标系的极坐标网格中，得到红外云顶亮温极坐标网格数据；基于红外云顶亮温极坐标网格数据计算热带气旋的预设内核区域的对流对称性指标参数；分析所有热带气旋的对流对称性指标参数与热带气旋的强度之间的关系。
作为本申请的进一步改进，基于红外云顶亮温极坐标网格数据计算热带气旋的预设内核区域的对流对称性指标参数，包括：计算热带气旋的预设内核区域的红外云顶亮温极坐标网格数据的10%分位数和90%分位数；结合10%分位数与90%分位数的差值计算热带气旋的对流对称性指标参数。
作为本申请的进一步改进，对流对称性指标参数的计算公式表示为：Symmetric Ratio = 1-（90%TBB - 10% TBB）/maximum（90%TBB - 10% TBB）；其中，Symmetric Ratio表示对流对称性指标参数，TBB表示红外云顶亮温极坐标网格数据，maximum（90%TBB - 10% TBB）表示预设气候值。
作为本申请的进一步改进，基于时间对应关系将红外云顶亮温数据以插值法插入至对应的极坐标系的极坐标网格中，得到红外云顶亮温极坐标网格数据，包括：确认每个极坐标系的半径r方向间隔4km、方位角θ方向间隔5°的目标极坐标网格格点；基于时间对应关系将红外云顶亮温数据以插值法插入至对应极坐标系的目标极坐标网格格点，得到红外云顶亮温极坐标网格数据。
作为本申请的进一步改进，热带气旋的预设内核区域包括以热带气旋的中心为圆心，第一预设半径和第二预设半径之间的圆环区域，第一预设半径小于第二预设半径。
作为本申请的进一步改进，分析所有热带气旋的对流对称性指标参数与热带气旋的强度之间的关系，包括：对比分析热带气旋发生快速增强阶段与非快速增强阶段的对流对称性指标的第一特征，并构建第一箱线图进行分析，快速增强阶段与非快速增强阶段根据预设时间段内最大地表风持续增加的风速大小确定；对比分析不同等级的热带气旋发生快速增强阶段的对流对称性指标的第二特征，并构建第二箱线图进行分析，热带气旋的等级根据热带气旋中心附近最大风速的大小确定；对比分析热带气旋发生快速增强阶段对流对称性指标参数随时间变化的第三特征，并构建第三箱线图进行分析。
作为本申请的进一步改进，对流对称性指标参数作为预测因子加入热带气旋的强度预测模型。
为解决上述技术问题，本申请采用的又一个技术方案是：提供一种热带气旋对称性结构分析装置，装置包括：第一获取模块，用于获取预设时间段内多个热带气旋的最佳路径数据集，并基于所述最佳路径数据集获取逐小时的热带气旋位置和强度数值；创建模块，用于以热带气旋中心位置为原点创建对应的极坐标系；第二获取模块，用于获取热带气旋逐小时的红外云顶亮温数据，并基于时间对应关系将所述红外云顶亮温数据以插值法插入至对应的热带气旋的极坐标系的极坐标网格中，得到红外云顶亮温极坐标网格数据；计算模块，用于基于所述红外云顶亮温极坐标网格数据计算热带气旋的预设内核区域的对流对称性指标参数；分析模块，用于分析所有热带气旋的对流对称性指标参数与热带气旋的强度之间的关系。
为解决上述技术问题，本申请采用的再一个技术方案是：提供一种计算机设备，所述计算机设备包括处理器、与所述处理器耦接的存储器，所述存储器中存储有程序指令，所述程序指令被所述处理器执行时，使得所述处理器执行如上述任一项的热带气旋对称性结构分析方法的步骤。
为解决上述技术问题，本申请采用的再一个技术方案是：提供一种存储介质，存储有能够实现上述任一项的热带气旋对称性结构分析方法的程序指令。
 有益效果
本申请的有益效果是：本申请的热带气旋对称性结构分析方法通过根据热带气旋的最佳路径数据集确认逐小时的热带气旋位置和强度数值，并以热带气旋中心位置为原点创建极坐标系，再获取热带气旋逐小时的红外云顶亮温数据，将红外云顶亮温数据按照时间上的对应关系插入极坐标网格中，得到红外云顶亮温极坐标网格数据，再以红外云顶亮温极坐标网格数据定义热带气旋内核区的对流对称性指标参数，最后分析热带气旋的对流对称性指标参数与热带气旋的强度之间的关系，以便研究人员在此基础上探索该对流对称性指标在热带气旋强度预报中的应用。
 附图说明
图1是本发明实施例的热带气旋对称性结构分析方法的一流程示意图；
图2是西北太平洋热带气旋在快速增强(RI)阶段与非快速增强(No-RI)阶段的对流对称性指标的统计箱线图；
图3是2009-2021年西北太平洋不同等级热带气旋发生快速增强的对流对称性指标的统计箱线图；
图4是热带气旋快速增强过程中对流对称性指标随时间变化的统计箱线图；
图5是本发明实施例的热带气旋对称性结构分析装置的功能模块示意图；
图6是本发明实施例的计算机设备的结构示意图；
图7是本发明实施例的存储介质的结构示意图。
 本发明的实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅是本申请的一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
本申请中的术语“第一”、“第二”、“第三”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”、“第三”的特征可以明示或者隐含地包括至少一个该特征。本申请的描述中，“多个”的含义是至少两个，例如两个，三个等，除非另有明确具体的限定。本申请实施例中所有方向性指示（诸如上、下、左、右、前、后……）仅用于解释在某一特定姿态（如附图所示）下各部件之间的相对位置关系、运动情况等，如果该特定姿态发生改变时，则该方向性指示也相应地随之改变。此外，术语“包括”和“具有”以及它们任何变形，意图在于覆盖不排他的包含。例如包含了一系列步骤或单元的过程、方法、系统、产品或设备没有限定于已列出的步骤或单元，而是可选地还包括没有列出的步骤或单元，或可选地还包括对于这些过程、方法、产品或设备固有的其它步骤或单元。
在本文中提及“实施例”意味着，结合实施例描述的特定特征、结构或特性可以包含在本申请的至少一个实施例中。在说明书中的各个位置出现该短语并不一定均是指相同的实施例，也不是与其它实施例互斥的独立的或备选的实施例。本领域技术人员显式地和隐式地理解的是，本文所描述的实施例可以与其它实施例相结合。
图1是本发明实施例的热带气旋对称性结构分析方法的流程示意图。需注意的是，若有实质上相同的结果，本发明的方法并不以图1所示的流程顺序为限。如图1所示，该热带气旋对称性结构分析方法包括步骤：
步骤S101：获取预设时间段内多个热带气旋的最佳路径数据集，并基于最佳路径数据集获取逐小时的热带气旋中心位置和强度数值。
需要说明的是，可以从上海台风所、美国联合台风预警中心、日本气象厅等的官方网站下载多年的西北太平洋（也可以是大西洋、印度洋等）的热带气旋最佳路径数据集（元素为热带气旋最佳路径记录）。每条热带气旋最佳路径数据集含该热带气旋从形成到消亡的全部时间内逐6小时的热带气旋中心经纬度位置以及强度等信息。本实施例假设在两次记录时间内热带气旋是匀速运动并均匀加强（或减弱），通过线性插值法即可得到每小时的热带气旋中心位置和强度数值。
步骤S102：以热带气旋的中心位置为原点创建对应的极坐标系。
步骤S103：获取研究期间内热带气旋逐小时的红外云顶亮温数据，并基于时间对应关系将红外云顶亮温数据利用RBF插值法插入至对应的极坐标网格，得到红外云顶亮温的极坐标网格数据。
需要说明的是，由于卫星观测范围可以覆盖大部分洋面区域，因此很大程度上弥补了海洋上大气探测能力的不足，为热带气旋研究提供了更加丰富的遥感资料，且红外云顶亮度温度与强对流及对流引起的降水有很好的对应关系，因此可以较好地表示对流强弱，亮温值越低表示云顶伸展高度越高，对流越旺盛。一般而言，无论是在大气还是海洋中，涡旋旋转越快其对称性就越好。非对称快速增强的热带气旋即使都处在中等切变环境下，在快速增强过程中都伴随着强对流气旋性旋转，从而使热带气旋结构在快速增强后期趋于对称的特征。因此本实施例利用FY-2系列卫星的长波红外通道的亮温值来分析热带气旋内核对流的非对称结构特征。
具体地，本实施例通过从风云卫星遥感数据服务网上下载热带气旋发生期间逐小时的风云二号全圆盘标称图像文件及其经纬度对照表等数据，再对下载的数据进行处理，获取长波红外通道（波长范围：10.3 - 11.3 µm）的亮温值。然后将所述逐小时的长波红外通道的亮温值按时间对应关系插值至对应的极坐标网格中，具体地，基于时间对应关系将红外云顶亮温数据以插值法插入至对应的热带气旋的极坐标系中，得到红外云顶亮温坐标数据的步骤，具体包括：
1、确认每个极坐标系的半径r方向间隔4km、方位角θ方向间隔5°的目标极坐标网格格点。
2、基于时间对应关系将红外云顶亮温数据以插值法插入至对应极坐标系的目标极坐标网格格点，得到红外云顶亮温极坐标网格数据。
步骤S104：基于红外云顶亮温极坐标网格数据计算热带气旋的预设内核区域的对流对称性指标参数。
需要说明的是，本实施例中研究的热带气旋对流活动仅限于热带气旋的预设内核区域内。通常地，热带气旋内核区定义为：以热带气旋中心为圆心，半径1°之内的区域（热带、亚热带地区约为半径100 km内范围）。但是，在有明显热带气旋眼的卫星云图中，热带气旋眼内盛行下沉气流，亮温值较大，为了消除热带气旋眼区干扰，本实施例将热带气旋的预设内核区域设置为以热带气旋的中心为圆心，第一预设半径和第二预设半径之间的圆环区域，第一预设半径小于第二预设半径。优选地，本实施例中第一预设半径优选为50km，第二预设半径优选为100km。
进一步的，步骤S104具体包括：
1、计算热带气旋的预设内核区域的红外云顶亮温极坐标网格数据的10%分位数和90%分位数。
2、结合10%分位数与90%分位数的差值计算热带气旋的对流对称性指标参数。
其中，对流对称性指标参数的计算公式表示为：
Symmetric Ratio = 1-（90%TBB - 10% TBB）/maximum（90%TBB - 10% TBB）；
其中，Symmetric Ratio表示对流对称性指标参数，TBB表示红外云顶亮温极坐标网格数据，maximum（90%TBB - 10% TBB）表示预设气候值，本实施例基于西北太平洋2009-2021年的热带气旋实现，因此该预设气候值设置为105。
步骤S105：分析所有热带气旋的对流对称性指标参数与热带气旋的强度之间的关系。
具体地，在得到所有热带气旋的对流对称性指标参数后，结合热带气旋的强度变化过程进行分析。
进一步的，步骤S105具体包括：
1、对比分析热带气旋发生快速增强阶段与非快速增强阶段的对流对称性指标的第一特征，并构建第一箱线图进行分析，快速增强阶段与非快速增强阶段根据预设时间段内最大地表风持续增加的风速大小确定。
需要说明的是，目前最常用的热带气旋发生快速增强判定标准是24小时内最大地面风持续增强达到15 m/s。然而，有研究指出，24小时的判定标准倾向于中心风力小于33m/s的热带气旋快速增强，而对于一些强度高于33m/s的热带气旋，发生快速增强时，最大风速半径处于稳定态的结构可能无法持续24小时。因此他们将12小时内最大地表风持续增加达到10 m/s亦定义为快速增强过程。本发明使用此标准计算研究期间发生快速增强过程的热带气旋，可以适用于更大强度范围的热带气旋的快速变化。
具体地，如图2所示，图2展示了2009-2021年西北太平洋热带气旋在快速增强(RI)阶段与非快速增强(No-RI)阶段的对流对称性指标的统计箱线图，从图2中可以看出，快速增强阶段的对流对称性指标的中位数及最小值都大于非快速增强阶段，说明热带气旋对称性越好，越容易发生快速增强。
2、对比分析不同等级的热带气旋发生快速增强过程的对流对称性指标的第二特征，并构建第二箱线图进行分析，热带气旋等级根据热带气旋中心附近最大风速的大小确定。
需要说明的是，根据我国《热带气旋等级》国家标准（GB/T 19201-2006），将热带气旋所对应的强度等级进行划分：中心附近最大风速在17.2~24.4 m/s的为热带风暴（TS），中心附近最大风速在24.5~32.6 m/s的为强热带风暴（STS），中心附近最大风速在32.7~41.4 m/s的为台风（TY），中心附近最大风速在41.5~50.9 m/s的为强台风（STY），中心附近最大风速大于51.0 m/s的为超强台风（SuperTY）。
具体地，如图3所示，图3展示了2009-2021年西北太平洋不同等级热带气旋发生快速增强的对流对称性指标的统计箱线图，从统计结果看，热带气旋等级越高，其对流对称性指标的中位数及最小值越大，说明其内核的对流也更加紧致和对称。
3、对比分析热带气旋发生快速增强阶段对流对称性指标参数随时间变化的第三特征，并构建第三箱线图进行分析。
具体地，为了分析热带气旋在快速增强过程中其对流对称性指标的变化特征，将快速增强过程分四个阶段进行统计分析，图4为热带气旋快速增强过程中对流对称性指标随时间变化的统计箱线图，从图4中可以看出，在热带气旋发生快速增强期间，其对称性指标的中位数随时间逐渐增加，说明热带气旋内核的对流在快速增强过程中趋于更对称。
进一步的，该对流对称性指标参数用于加入热带气旋的强度预测模型。
本实施例通过根据热带气旋的最佳路径数据得到逐小时的热带气旋中心位置，并以热带气旋中心位置为原点创建极坐标系，再获取热带气旋逐小时的红外云顶亮温数据，将红外云顶亮温数据按照时间上的对应关系分别插值到极坐标网格格点中，得到红外云顶亮温极坐标网格数据，再以红外云顶亮温极坐标网格数据定义热带气旋内核区的对流对称性指标参数，最后分析该指标参数与热带气旋的强度之间的关系，精准的反应了热带气旋发生强度变化过程中，其内核对流对称性的变化特征，以便研究人员在此基础上探索该对流对称性指标在热带气旋强度预报中的应用。
图5是本发明实施例的热带气旋对称性结构分析装置的功能模块示意图。如图5所示，该热带气旋对称性结构分析装置20包括第一获取模块21、创建模块22、第二获取模块23、计算模块24和分析模块25。
第一获取模块21，用于获取预设时间段内多个热带气旋的最佳路径数据集，并基于所述最佳路径数据集获取逐小时的热带气旋位置和强度数值；
创建模块22，用于以热带气旋中心位置为原点创建对应的极坐标系；
第二获取模块23，用于获取热带气旋逐小时的红外云顶亮温数据，并基于时间对应关系将所述红外云顶亮温数据以插值法插入至对应的热带气旋的极坐标系的极坐标网格中，得到红外云顶亮温极坐标网格数据；
计算模块24，用于基于所述红外云顶亮温极坐标网格数据计算热带气旋的预设内核区域的对流对称性指标参数；
分析模块25，用于分析所有热带气旋的对流对称性指标参数与热带气旋的强度之间的关系。
可选地，计算模块24执行基于所述红外云顶亮温极坐标网格数据计算热带气旋的预设内核区域的对流对称性指标参数的操作，具体包括：计算热带气旋的预设内核区域的红外云顶亮温极坐标网格数据的10%分位数和90%分位数；结合10%分位数与90%分位数的差值计算热带气旋的对流对称性指标参数。
可选地，对流对称性指标参数的计算公式表示为：
Symmetric Ratio = 1-（90%TBB - 10% TBB）/maximum（90%TBB - 10% TBB）；
其中，Symmetric Ratio表示对流对称性指标参数，TBB表示红外云顶亮温极坐标网格数据，maximum（90%TBB - 10% TBB）表示预设气候值。
可选地，第二获取模块23执行基于时间对应关系将红外云顶亮温数据以插值法插入至对应的极坐标系的极坐标网格中，得到红外云顶亮温极坐标网格数据的操作，具体包括：确认每个极坐标系的半径r方向间隔4km、方位角θ方向间隔5°的目标极坐标网格格点；基于时间对应关系将红外云顶亮温数据以插值法插入至对应极坐标系的目标极坐标网格格点，得到红外云顶亮温极坐标网格数据。
可选地，热带气旋的预设内核区域包括以热带气旋的中心为圆心，第一预设半径和第二预设半径之间的圆环区域，第一预设半径小于第二预设半径。
可选地，分析模块25执行分析所有热带气旋的对流对称性指标参数与热带气旋的强度之间的关系的操作，具体包括：对比分析热带气旋发生快速增强阶段与非快速增强阶段的对流对称性指标的第一特征，并构建第一箱线图进行分析，快速增强阶段与非快速增强阶段根据预设时间段内最大地表风持续增加的风速大小确定；对比分析不同等级的热带气旋发生快速增强阶段的对流对称性指标的第二特征，并构建第二箱线图进行分析，热带气旋的等级根据热带气旋中心附近最大风速的大小确定；对比分析热带气旋发生快速增强阶段对流对称性指标参数随时间变化的第三特征，并构建第三箱线图进行分析。
可选地，对流对称性指标参数作为预测因子加入热带气旋的强度预测模型。
关于上述实施例热带气旋对称性结构分析装置中各模块实现技术方案的其他细节，可参见上述实施例中的热带气旋对称性结构分析方法中的描述，此处不再赘述。
需要说明的是，本说明书中的各个实施例均采用递进的方式描述，每个实施例重点说明的都是与其他实施例的不同之处，各个实施例之间相同相似的部分互相参见即可。对于装置类实施例而言，由于其与方法实施例基本相似，所以描述的比较简单，相关之处参见方法实施例的部分说明即可。
请参阅图6，图6为本发明实施例的计算机设备的结构示意图。如图6所示，该计算机设备30包括处理器31及和处理器31耦接的存储器32，存储器32中存储有程序指令，程序指令被处理器31执行时，使得处理器31执行上述任一实施例所述的热带气旋对称性结构分析方法步骤。
其中，处理器31还可以称为CPU（Central Processing Unit，中央处理单元）。处理器31可能是一种集成电路芯片，具有信号的处理能力。处理器31还可以是通用处理器、数字信号处理器（DSP）、专用集成电路（ASIC）、现场可编程门阵列（FPGA）或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
参阅图7，图7为本发明实施例的存储介质的结构示意图。本发明实施例的存储介质存储有能够实现上述热带气旋对称性结构分析方法的程序指令41，其中，该程序指令41可以以软件产品的形式存储在上述存储介质中，包括若干指令用以使得一台计算机设备（可以是个人计算机，服务器，或者网络设备等）或处理器（processor）执行本申请各个实施方式所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器（ROM，Read-Only Memory）、随机存取存储器（RAM，Random Access Memory）、磁碟或者光盘等各种可以存储程序代码的介质，或者是计算机、服务器、手机、平板等计算机设备设备。
在本申请所提供的几个实施例中，应该理解到，所揭露的计算机设备，装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
另外，在本发明各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。以上仅为本申请的实施方式，并非因此限制本申请的专利范围，凡是利用本申请说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本申请的专利保护范围内。

Claims (10)

  1. 一种热带气旋对称性结构分析方法，其特征在于，所述方法包括：
    获取预设时间段内多个热带气旋的最佳路径数据集，并基于所述最佳路径数据集获取逐小时的热带气旋中心位置和强度数值；
    以热带气旋中心位置为原点创建对应的极坐标系；
    获取热带气旋逐小时的红外云顶亮温数据，并基于时间对应关系将所述红外云顶亮温数据以插值法插入至对应的极坐标系的极坐标网格中，得到红外云顶亮温极坐标网格数据；
    基于所述红外云顶亮温极坐标网格数据计算热带气旋的预设内核区域的对流对称性指标参数；
    分析所有热带气旋的对流对称性指标参数与热带气旋的强度之间的关系。
  2. 根据权利要求1所述的热带气旋对称性结构分析方法，其特征在于，所述基于所述红外云顶亮温极坐标网格数据计算热带气旋的预设内核区域的对流对称性指标参数，包括：
    计算热带气旋的预设内核区域的红外云顶亮温极坐标网格数据的10%分位数和90%分位数；
    结合所述10%分位数与所述90%分位数的差值计算热带气旋的对流对称性指标参数。
  3. 根据权利要求2所述的热带气旋对称性结构分析方法，其特征在于，所述对流对称性指标参数的计算公式表示为：
    Symmetric Ratio = 1-（90%TBB - 10% TBB）/maximum（90%TBB - 10% TBB）；
    其中，Symmetric Ratio表示所述对流对称性指标参数，TBB表示所述红外云顶亮温极坐标网格数据，maximum（90%TBB - 10% TBB）表示预设气候值。
  4. 根据权利要求1所述的热带气旋对称性结构分析方法，其特征在于，所述基于时间对应关系将所述红外云顶亮温数据以插值法插入至对应的极坐标系的极坐标网格中，得到红外云顶亮温极坐标网格数据，包括：
    确认每个极坐标系的半径r方向间隔4km、方位角θ方向间隔5°的目标极坐标网格格点；
    基于所述时间对应关系将所述红外云顶亮温数据以插值法插入至对应极坐标系的目标极坐标网格格点，得到所述红外云顶亮温极坐标网格数据。
  5. 根据权利要求1所述的热带气旋对称性结构分析方法，其特征在于，所述热带气旋的预设内核区域包括以所述热带气旋的中心为圆心，第一预设半径和第二预设半径之间的圆环区域，所述第一预设半径小于所述第二预设半径。
  6. 根据权利要求1所述的热带气旋对称性结构分析方法，其特征在于，所述分析所有热带气旋的对流对称性指标参数与所述热带气旋的强度之间的关系，包括：
    对比分析热带气旋发生快速增强阶段与非快速增强阶段的对流对称性指标的第一特征，并构建第一箱线图进行分析，所述快速增强阶段与所述非快速增强阶段根据预设时间段内最大地表风持续增加的风速大小确定；
    对比分析不同等级的热带气旋发生快速增强阶段的对流对称性指标的第二特征，并构建第二箱线图进行分析，所述热带气旋的等级根据所述热带气旋中心附近最大风速的大小确定；
    对比分析所述热带气旋发生快速增强阶段所述对流对称性指标参数随时间变化的第三特征，并构建第三箱线图进行分析。
  7. 根据权利要求1所述的热带气旋对称性结构分析方法，其特征在于，所述对流对称性指标参数作为预测因子加入热带气旋的强度预测模型。
  8. 一种热带气旋对称性结构分析装置，其特征在于，所述装置包括：
    第一获取模块，用于获取预设时间段内多个热带气旋的最佳路径数据集，并基于所述最佳路径数据集获取逐小时的热带气旋位置和强度数值；
    创建模块，用于以热带气旋中心位置为原点创建对应的极坐标系；
    第二获取模块，用于获取热带气旋逐小时的红外云顶亮温数据，并基于时间对应关系将所述红外云顶亮温数据以插值法插入至对应的热带气旋的极坐标系的极坐标网格中，得到红外云顶亮温极坐标网格数据；
    计算模块，用于基于所述红外云顶亮温极坐标网格数据计算热带气旋的预设内核区域的对流对称性指标参数；
    分析模块，用于分析所有热带气旋的对流对称性指标参数与热带气旋的强度之间的关系。
  9. 一种计算机设备，其特征在于，所述计算机设备包括处理器、与所述处理器耦接的存储器，所述存储器中存储有程序指令，所述程序指令被所述处理器执行时，使得所述处理器执行如权利要求1-7中任一项权利要求所述的热带气旋对称性结构分析方法的步骤。
  10. 一种存储介质，其特征在于，存储有能够实现如权利要求1-7中任一项所述的热带气旋对称性结构分析方法的程序指令。
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