CN116341287B - A track adaptive grid processing method based on optimal typhoon track data - Google Patents

A track adaptive grid processing method based on optimal typhoon track data Download PDF

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CN116341287B
CN116341287B CN202310592729.1A CN202310592729A CN116341287B CN 116341287 B CN116341287 B CN 116341287B CN 202310592729 A CN202310592729 A CN 202310592729A CN 116341287 B CN116341287 B CN 116341287B
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typhoon
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CN116341287A (en
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武则州
何兴举
李宏亮
张静静
宣基亮
陈建芳
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Second Institute of Oceanography MNR
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Abstract

The invention relates to a track self-adaptive gridding processing method based on optimal typhoon track data, which is characterized in that the calendar year optimal typhoon track data of a target area is processed to obtain the grid size of the target area so as to obtain the grid of the target area, the calendar year optimal typhoon track data is processed in a thinning way by utilizing the grid of the target area, the thinned typhoon tracks corresponding to the calendar year optimal typhoon track data of each year are respectively obtained, a statistical experience model is constructed according to the grid of the target area and all the thinned typhoon tracks, and finally, the typhoon track distribution characteristics of typhoons in the target area on the grid of the target area are obtained according to the statistical experience model, so that the self-adaptive gridding processing of calendar year typhoon data of the target area is realized, the interference of human factors is avoided, and the distribution characteristics of the typhoon tracks finally obtained are more true due to the fact that the calendar year typhoon data processing based on the real target area and the typhoon tracks pass through the same grid for a plurality of times.

Description

一种基于最优台风轨迹数据的轨迹自适应网格化处理方法A track adaptive grid processing method based on optimal typhoon track data

技术领域technical field

本发明涉及台风轨迹处理领域，尤其涉及一种基于最优台风轨迹数据的轨迹自适应网格化处理方法。The invention relates to the field of typhoon track processing, in particular to a track adaptive grid processing method based on optimal typhoon track data.

背景技术Background technique

台风作为自然界中的一种自然现象，其发生时以大风速和强降水为主要特征，并且还会在其途径地区产生直接或者间接的自然灾害。As a natural phenomenon in nature, typhoon is characterized by high wind speed and heavy precipitation when it occurs, and it will also cause direct or indirect natural disasters in the areas where it passes.

为了掌握目标区域的台风轨迹情况，现在的台风轨迹网格化处理方法主要通过人为定义网格化大小来处理台风轨迹数据，从而勾画出目标区域发生台风时的轨迹情况。In order to grasp the typhoon trajectory in the target area, the current typhoon track grid processing method mainly processes the typhoon track data by artificially defining the grid size, so as to outline the track situation when a typhoon occurs in the target area.

不过，现有的台风轨迹网格化处理方法存在不足：人工定义网格化大小存在很大的主观性，而且还会忽略台风轨迹多次经过同一网格的情况，无法客观真实地体现出台风轨迹，进而难以利用网格化处理方式来完整表征出台风轨迹的分布特征，不利于对台风轨迹情况的研究。However, there are deficiencies in the existing grid processing methods of typhoon tracks: manually defining the grid size is very subjective, and it will ignore the situation that the typhoon track passes through the same grid multiple times, which cannot objectively and truly reflect the typhoon. Therefore, it is difficult to use the grid processing method to fully characterize the distribution characteristics of typhoon trajectories, which is not conducive to the study of typhoon trajectories.

发明内容Contents of the invention

本发明所要解决的技术问题是针对上述现有技术提供一种基于最优台风轨迹数据的台风轨迹自适应网格化处理方法。该台风轨迹自适应网格化处理方法可以客观真实地体现出台风轨迹，完整表征出台风轨迹的分布特征。The technical problem to be solved by the present invention is to provide a typhoon track adaptive grid processing method based on the optimal typhoon track data in view of the above prior art. The typhoon track adaptive grid processing method can objectively and truly reflect the typhoon track, and completely characterize the distribution characteristics of the typhoon track.

本发明解决上述技术问题所采用的技术方案为：一种基于最优台风轨迹数据的轨迹自适应网格化处理方法，其特征在于，包括如下步骤S1~ S7：The technical solution adopted by the present invention to solve the above technical problems is: a trajectory adaptive grid processing method based on optimal typhoon trajectory data, which is characterized in that it includes the following steps S1~S7:

步骤S1，选定需要统计台风轨迹的目标区域；Step S1, select the target area where the typhoon track needs to be counted;

步骤S2，获取目标区域的历年最优台风轨迹数据；Step S2, obtaining the optimal typhoon track data over the years in the target area;

步骤S3，根据获取的历年最优台风轨迹数据，得到对应该目标区域的目标区域网格尺寸；Step S3, according to the obtained optimal typhoon track data over the years, obtain the grid size of the target area corresponding to the target area;

步骤S4，基于所得目标区域网格尺寸对目标区域做网格化处理，得到对应该目标区域的目标区域网格；Step S4, performing grid processing on the target area based on the obtained target area grid size, to obtain a target area grid corresponding to the target area;

步骤S5，利用目标区域网格对获取的历年最优台风轨迹数据做细化处理，分别得到对应该历年中每一年最优台风轨迹数据的细化后台风轨迹；Step S5, using the grid of the target area to refine the obtained optimal typhoon track data over the years, and respectively obtain the refined background cyclone track corresponding to the optimal typhoon track data of each year in the calendar year;

步骤S6，根据目标区域网格以及所得所有的细化后台风轨迹，构建统计目标区域网格内每一个网格被台风轨迹经过频次的统计经验模型；Step S6, according to the grid of the target area and all the obtained refined background wind tracks, construct a statistical empirical model for counting the frequency of each grid in the grid of the target area being passed by the typhoon track;

步骤S7，根据统计经验模型，得到目标区域内台风在目标区域网格上的台风轨迹分布特征；其中，台风轨迹分布特征包含目标区域网格内每一个网格被台风轨迹经过频次。In step S7, according to the statistical empirical model, the typhoon track distribution characteristics of the typhoon in the target area on the target area grid are obtained; wherein, the typhoon track distribution feature includes the frequency of each grid in the target area grid being passed by the typhoon track.

改进地，在所述基于最优台风轨迹数据的台风轨迹自适应网格化处理方法中，在步骤S2中，从中国气象局热带气旋资料中心获取所述目标区域的历年最优台风轨迹数据。Improvement, in the typhoon track adaptive grid processing method based on the optimal typhoon track data, in step S2, the historical optimal typhoon track data of the target area is obtained from the Tropical Cyclone Data Center of China Meteorological Administration.

进一步地，在所述基于最优台风轨迹数据的台风轨迹自适应网格化处理方法中，在步骤S3中，根据获取的历年最优台风轨迹数据得到所述目标区域网格尺寸的过程包括如下步骤S31~ S36：Further, in the typhoon track adaptive grid processing method based on the optimal typhoon track data, in step S3, the process of obtaining the grid size of the target area according to the obtained optimal typhoon track data over the years includes the following steps Steps S31~S36:

步骤S31，获取所述历年最优台风轨迹数据内任一最优台风轨迹的轨迹点信息；其中，轨迹点信息包括轨迹点位置和记载产生该轨迹点的轨迹点记录时间；标记该任一最优台风轨迹的轨迹点总数量为，该任一最优台风轨迹上的两个相邻轨迹点分别是和/>，/>为轨迹点/>的经度坐标，/>为轨迹点/>的维度坐标，/>为轨迹点/>的经度坐标，/>为轨迹点/>的维度坐标，轨迹点/>的轨迹点记录时间标记为/>，轨迹点/>的轨迹点记录时间标记为，/>；Step S31, obtaining the track point information of any optimal typhoon track in the optimal typhoon track data over the years; wherein, the track point information includes the track point position and the track point record time when the track point was generated; The total number of track points of the optimal typhoon track is , the two adjacent track points on any optimal typhoon track are and /> , /> for track point /> Longitude coordinates of , /> for track point /> The dimension coordinates of , /> for track point /> Longitude coordinates of , /> for track point /> The dimension coordinates of the track point /> The track point recording time is marked as /> , track point /> The track point recording time is marked as , /> ;

步骤S32，根据该任一最优台风轨迹上两个相邻轨迹点的轨迹点信息，得到该两个相邻轨迹点之间的距离；其中，相邻轨迹点和/>之间的距离标记为/>：Step S32, according to the track point information of two adjacent track points on any optimal typhoon track, the distance between the two adjacent track points is obtained; wherein, the adjacent track point and /> The distance between is marked as /> :

；其中，/>为地球半径； ; where /> is the radius of the earth;

步骤S33，根据该两个相邻轨迹点的轨迹点记录时间，得到产生该两个相邻轨迹点的时间间隔；其中，该两个相邻轨迹点和/>的时间间隔标记为/>，；Step S33, according to the track point recording time of the two adjacent track points, the time interval for generating the two adjacent track points is obtained; wherein, the two adjacent track points and /> time interval marked as /> , ;

步骤S34，根据所得相邻轨迹点之间的距离和对应的时间间隔，得到该任一最优台风轨迹所对应台风在该相邻轨迹点之间的台风平均移动速度；其中，该任一最优台风轨迹所对应台风在该相邻轨迹点和/>之间的台风平均移动速度标记为/>，；Step S34, according to the obtained distance between adjacent track points and the corresponding time interval, obtain the typhoon average moving speed of the typhoon corresponding to any optimal typhoon track between the adjacent track points; The typhoon corresponding to the optimal typhoon track is at the adjacent track point and /> The average moving speed of the typhoon between is marked as /> , ;

步骤S35，对所述历年最优台风轨迹数据内每一个最优台风轨迹数据遍历执行步骤S31和步骤S34，得到多个台风平均移动速度，且查找得到该多个台风平均移动速度中的平均移动速度中位数；其中，该多个台风平均移动速度中的平均移动速度中位数标记为；Step S35, traversing steps S31 and S34 for each optimal typhoon track data in the optimal typhoon track data over the years to obtain the average moving speed of multiple typhoons, and find the average moving speed of the multiple typhoon average moving speeds Speed median; wherein, the average moving speed median of the multiple typhoon average moving speed is marked as ;

步骤S36，根据所得平均移动速度中位数、预设时长以及预设网格单元所表征距离，得到目标区域网格尺寸；其中，目标区域网格尺寸标记为，/>；T为预设时长，L为预设网格单元所表征距离。In step S36, the grid size of the target area is obtained according to the obtained median moving speed, the preset duration, and the distance represented by the preset grid unit; wherein, the grid size of the target area is marked as , /> ; T is the preset time length, and L is the distance represented by the preset grid unit.

再进一步，在所述基于最优台风轨迹数据的台风轨迹自适应网格化处理方法中，所述预设时长T为6小时，所述预设网格单元为1°网格，该1°网格所表征距离L为110km。Still further, in the typhoon track adaptive grid processing method based on optimal typhoon track data, the preset time length T is 6 hours, the preset grid unit is a 1 ° grid, and the 1 ° The distance L represented by the grid is 110km.

改进地，在所述基于最优台风轨迹数据的台风轨迹自适应网格化处理方法中，在步骤S4中，所述目标区域网格按照如下方式处理得到：Improvement, in the typhoon track adaptive grid processing method based on the optimal typhoon track data, in step S4, the target area grid is processed as follows:

将所述目标区域进行网格化处理，得到具有多个小网格的目标区域网格；其中，该目标区域网格内小网格总数量为，目标区域网格的参数为/>，；该目标区域网格内第/>个小网格的经度范围为，第/>个小网格的纬度范围为/>，/>。The target area is gridded to obtain a target area grid with multiple small grids; wherein, the total number of small grids in the target area grid is , the parameter of the target area grid is /> , ;The first /> in the grid of the target area The longitude range of a small grid is , No. /> The latitude range of a small grid is /> , /> .

进一步地，在所述基于最优台风轨迹数据的台风轨迹自适应网格化处理方法中，在步骤S5中，得到对应该历年中每一年最优台风轨迹数据的细化后台风轨迹处理方式为：Further, in the typhoon track adaptive grid processing method based on the optimal typhoon track data, in step S5, the refinement background typhoon track processing method corresponding to the optimal typhoon track data of each year in the calendar year is obtained for:

计算所述多个台风平均移动速度中的最大平均移动速度值与所述平均移动速度中位数的商值，且得到该商值的取整值；其中，所述多个台风平均移动速度中的最大平均移动速度值标记为；Calculate the quotient of the maximum average moving speed value of the plurality of average moving speeds of typhoons and the median of the average moving speed, and obtain the rounded value of the quotient; wherein, among the plurality of average moving speeds of typhoons The maximum average moving speed value of is marked as ;

将所得取整值的4倍数值作为对每一个台风轨迹做轨迹等分处理的等分数量值；其中，对每一个台风轨迹做轨迹等分处理的等分数量值标记为，/>。The value of 4 times of the rounded value obtained is used as the number of equal parts for each typhoon track; wherein, the number of equal parts for each typhoon track is marked as , /> .

再改进，在所述基于最优台风轨迹数据的台风轨迹自适应网格化处理方法中，所述统计经验模型的构建过程包括如下步骤S61~ S69：Further improvement, in the typhoon track adaptive grid processing method based on the optimal typhoon track data, the construction process of the statistical empirical model includes the following steps S61~S69:

步骤S61，获取任一细化后台风轨迹上的轨迹点信息；其中，该任一细化后台风轨迹上的轨迹总数量标记为，该任一细化后台风轨迹上的轨迹点标记为，记载产生该轨迹点/>的轨迹点记录时间标记为/>；/>；Step S61, obtain the track point information on the wind track after any refinement; wherein, the total number of tracks on the wind track after any refinement is marked as , the track point on the wind track after any refinement is marked as , record the generated trajectory point /> The track point recording time is marked as /> ;/> ;

步骤S62，根据所得所有的轨迹点信息，得到该任一细化后台风轨迹落在目标区域网格内每个小网格上的轨迹点以及该轨迹点对应的轨迹点记录时间；其中，该任一细化后台风轨迹的轨迹点落在目标区域网格内小网格上的判断条件为：Step S62, according to all the track point information obtained, obtain the track point where any refined background wind track falls on each small grid in the target area grid and the track point recording time corresponding to the track point; wherein, the The judgment condition that the track point of any wind track after refinement falls on the small grid in the grid of the target area is as follows:

当轨迹点坐标满足时，判定该轨迹点/>落在目标区域网格内的小网格上；否则，判定该轨迹点没有落在目标区域网格内的小网格上；When the track point coordinates satisfy , determine the trajectory point /> falls on a small grid within the grid of the target area; otherwise, determine the trajectory point did not land on a small grid within the target area grid;

步骤S63，根据步骤S62所得所有轨迹点记录时间，得到目标区域网格内每个小网格所对应的轨迹点记录时间集，且计算细化后台风轨迹落在该小网格上的时间间隔；其中，细化后台风轨迹落在该小网格上的时间间隔标记为，/>；Step S63, according to the recording time of all track points obtained in step S62, obtain the record time set of track points corresponding to each small grid in the grid of the target area, and calculate the time interval of the wind track falling on the small grid after refinement ; Among them, the time interval when the wind track falls on the small grid after refinement is marked as , /> ;

步骤S64，根据所得细化后台风轨迹落在该小网格上的时间间隔以及两个相邻轨迹点记录时间之间的时间间隔，判断得到对应该小网格的同类时间分集和不同类时间分集；其中：Step S64, according to the time interval between the obtained refined background wind track falling on the small grid and the time interval between the recording times of two adjacent track points, it is judged to obtain the similar time diversity and different time of the corresponding small grid Diversity; where:

当两个相邻轨迹点记录时间之间的时间间隔大于该细化后台风轨迹落在该小网格上的时间间隔时，即，判定轨迹点记录时间/>和/>属于不同类时间分集；否则，判定轨迹点记录时间/>和/>属于同类时间分集；When the time interval between the recording times of two adjacent track points is greater than the time interval of the wind track falling on the small grid after the refinement, that is , determine the track point recording time /> and /> belong to different types of time diversity; otherwise, determine the record time of the track point /> and /> belong to the same time diversity;

步骤S65，根据所得同类时间分集和不同类时间分集，分别计算该小网格所对应同类时间分集的平均时间和不同类时间分集的平均时间；Step S65, according to the obtained time diversity of the same type and the time diversity of different types, respectively calculate the average time of the same type of time diversity and the average time of different types of time diversity corresponding to the small grid;

步骤S66，根据同类时间分集及该同类时间分集的平均时间，计算同类时间分集的平均时间总数量；以及，根据不同类时间分集及该不同类时间分集的平均时间，计算不同类时间分集的平均时间总数量；其中，同类时间分集的平均时间总数量标记为，同类时间分集中的第/>个平均时间标记为/>；/>；Step S66, according to the time diversity of the same type and the average time of the time diversity of the same type, calculate the total number of average time of the time diversity of the same type; and, according to the time diversity of different types and the average time of the time diversity of the different type, calculate the average total amount of time; where the average total amount of time for the same type of time diversity is marked as , the first /> in the same time diversity set average times marked as /> ;/> ;

步骤S67，根据所得各类时间集的平均时间做出判断处理：Step S67, making a judgment process according to the obtained average time of various time sets:

当同类时间集中的两个相邻平均时间之间大于1天时，即天，判定/>和/>属于台风轨迹在不同时间经过该目标区域网格内同一个小网格；否则，判定/>和属于台风轨迹在连续时间经过该目标区域网格内同一个小网格；When the interval between two adjacent average times in the same time set is greater than 1 day, that is God, judgment/> and /> Belonging to the typhoon track passing through the same small grid in the grid of the target area at different times; otherwise, determine and Belonging to the typhoon track passing through the same small grid in the grid of the target area in continuous time;

步骤S68，根据步骤S67的判定结果得到该任一细化后台风轨迹经过该小网格的真实频次；Step S68, according to the determination result of step S67, obtain the real frequency of the wind track passing through the small grid after any refinement;

步骤S69，按照步骤S61~ S68的方式对每一个细化后台风轨迹做遍历循环，得到目标区域网格内每一个小网格被台风轨迹经过的真实频次。Step S69, perform a traversal loop on each refined background wind track according to the method of steps S61~S68, and obtain the real frequency of each small grid in the target area grid being passed by the typhoon track.

与现有技术相比，本发明的优点在于：该发明中的台风轨迹自适应网格化处理方法通过对目标区域的历年最优台风轨迹数据做处理以得到目标区域网格尺寸，并基于目标区域网格尺寸对目标区域做网格化处理，得到对应目标区域的目标区域网格，再利用目标区域网格对历年最优台风轨迹数据做细化处理，分别得到对应该历年中每一年最优台风轨迹数据的细化后台风轨迹，进而根据目标区域网格以及所得所有的细化后台风轨迹构建统计目标区域网格内每一个网格被台风轨迹经过频次的统计经验模型，最终根据统计经验模型得到目标区域内台风在目标区域网格上的台风轨迹分布特征，实现了针对目标区域历年台风数据的自适应网格化处理，避免人为因素干扰，而且由于是基于目标区域真实的历年台风数据处理，并考虑了台风轨迹会多次经过同一网格的情况，使得最终所得台风轨迹分布特征更加真实合理。Compared with the prior art, the present invention has the advantage that: the typhoon track adaptive grid processing method in this invention obtains the grid size of the target area by processing the optimal typhoon track data of the target area over the years, and based on the target The regional grid size performs grid processing on the target area to obtain the target area grid corresponding to the target area, and then uses the target area grid to refine the optimal typhoon track data over the years to obtain the corresponding The optimal typhoon track data refines the background wind track, and then constructs a statistical empirical model for counting the frequency of each grid in the target area grid being passed by the typhoon track according to the grid of the target area and all the obtained refined background wind tracks, and finally according to The statistical empirical model obtains the typhoon trajectory distribution characteristics of the typhoon in the target area on the target area grid, and realizes the adaptive grid processing of the typhoon data in the target area over the years, avoiding human interference, and because it is based on the real calendar years of the target area Typhoon data processing, and considering the situation that the typhoon track will pass through the same grid many times, makes the distribution characteristics of the final typhoon track more realistic and reasonable.

附图说明Description of drawings

图1为本发明实施例中基于最优台风轨迹数据的轨迹自适应网格化处理方法流程示意图；FIG. 1 is a schematic flow diagram of a track adaptive grid processing method based on optimal typhoon track data in an embodiment of the present invention;

图2为2018年台风BERINCA的台风轨迹经过该实施例中台风轨迹自适应网格化处理后的台风轨迹示意图；Fig. 2 is the schematic diagram of the typhoon track after the typhoon track of the typhoon BERINCA in 2018 has been processed through the adaptive grid processing of the typhoon track in this embodiment;

图3为图2所示台风轨迹经统计经验模型处理后在目标区域网格上的统计情况。Figure 3 shows the statistical situation of the typhoon track shown in Figure 2 on the grid of the target area after being processed by the statistical empirical model.

具体实施方式Detailed ways

以下结合附图实施例对本发明作进一步详细描述。The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

本实施例提供一种基于最优台风轨迹数据的轨迹自适应网格化处理方法。参见图1所示，该基于最优台风轨迹数据的台风轨迹自适应网格化处理方法包括如下步骤S1~ S7：This embodiment provides a trajectory adaptive grid processing method based on optimal typhoon trajectory data. Referring to Figure 1, the typhoon track adaptive grid processing method based on the optimal typhoon track data includes the following steps S1 ~ S7:

步骤S1，选定需要统计台风轨迹的目标区域；例如，在该实施例中，选取中国南海北部（105°E ~ 121°E，8°N ~ 25°N）作为目标区域；Step S1, select the target area where the typhoon trajectory needs to be counted; for example, in this embodiment, select the northern part of the South China Sea (105°E ~ 121°E, 8°N ~ 25°N) as the target area;

步骤S2，获取目标区域的历年最优台风轨迹数据；具体地，此处可以从中国气象局热带气旋资料中心获取目标区域的历年最优台风轨迹数据，比如是当前起前70年的最优台风轨迹数据；经获取，该实施例获取到了历年的933个台风文件数据，也即933个最优台风轨迹数据；Step S2, obtain the optimal typhoon trajectory data of the target area over the years; specifically, the optimal typhoon trajectory data of the target area over the years can be obtained from the Tropical Cyclone Data Center of the China Meteorological Administration, for example, the optimal typhoon trajectory of the previous 70 years from now Trajectory data; After acquisition, this embodiment has obtained 933 typhoon file data over the years, that is, 933 optimal typhoon trajectory data;

步骤S3，根据获取的历年最优台风轨迹数据，得到对应该目标区域的目标区域网格尺寸；Step S3, according to the obtained optimal typhoon track data over the years, obtain the grid size of the target area corresponding to the target area;

步骤S4，基于所得目标区域网格尺寸对目标区域做网格化处理，得到对应该目标区域的目标区域网格；Step S4, performing grid processing on the target area based on the obtained target area grid size, to obtain a target area grid corresponding to the target area;

步骤S5，利用目标区域网格对获取的历年最优台风轨迹数据做细化处理，分别得到对应该历年中每一年最优台风轨迹数据的细化后台风轨迹；参见图2所示，在网格中，该图2中的圆点为台风轨迹；Step S5, use the grid of the target area to refine the obtained optimal typhoon track data over the years, and respectively obtain the refined background cyclone track corresponding to the optimal typhoon track data in each year in the past year; see Figure 2, in In the grid, the dots in Figure 2 are typhoon tracks;

步骤S6，根据目标区域网格以及所得所有的细化后台风轨迹，构建统计目标区域网格内每一个网格被台风轨迹经过频次的统计经验模型；Step S6, according to the grid of the target area and all the obtained refined background wind tracks, construct a statistical empirical model for counting the frequency of each grid in the grid of the target area being passed by the typhoon track;

步骤S7，根据统计经验模型，得到目标区域内台风在目标区域网格上的台风轨迹分布特征；其中，台风轨迹分布特征包含目标区域网格内每一个网格被台风轨迹经过频次。In step S7, according to the statistical empirical model, the typhoon track distribution characteristics of the typhoon in the target area on the target area grid are obtained; wherein, the typhoon track distribution feature includes the frequency of each grid in the target area grid being passed by the typhoon track.

具体地，在上述的步骤S3中，根据获取的历年最优台风轨迹数据得到目标区域网格尺寸的过程包括如下步骤S31~ S36：Specifically, in the above step S3, the process of obtaining the grid size of the target area according to the obtained optimal typhoon track data over the years includes the following steps S31~S36:

步骤S31，获取历年最优台风轨迹数据内任一最优台风轨迹的轨迹点信息；其中，轨迹点信息包括轨迹点位置和记载产生该轨迹点的轨迹点记录时间；标记该任一最优台风轨迹的轨迹点总数量为，该任一最优台风轨迹上的两个相邻轨迹点分别是和/>，/>为轨迹点/>的经度坐标，/>为轨迹点/>的维度坐标，/>为轨迹点/>的经度坐标，/>为轨迹点/>的维度坐标，轨迹点/>的轨迹点记录时间标记为/>，轨迹点/>的轨迹点记录时间标记为，/>；Step S31, obtain the track point information of any optimal typhoon track in the optimal typhoon track data over the years; wherein, the track point information includes the position of the track point and the recording time of the track point that records the track point; mark the track point of any optimal typhoon The total number of track points of the trajectory is , the two adjacent track points on any optimal typhoon track are and /> , /> for track point /> Longitude coordinates of , /> for track point /> The dimension coordinates of , /> for track point /> Longitude coordinates of , /> for track point /> The dimension coordinates of the track point /> The track point recording time is marked as /> , track point /> The track point recording time is marked as , /> ;

步骤S32，根据该任一最优台风轨迹上两个相邻轨迹点的轨迹点信息，得到该两个相邻轨迹点之间的距离；其中，相邻轨迹点和/>之间的距离标记为/>：Step S32, according to the track point information of two adjacent track points on any optimal typhoon track, the distance between the two adjacent track points is obtained; wherein, the adjacent track point and /> The distance between is marked as /> :

；其中，R为地球半径，地球半径R具体是6371.393km； ; Wherein, R is the radius of the earth, and the radius of the earth R is specifically 6371.393km;

步骤S33，根据该两个相邻轨迹点的轨迹点记录时间，得到产生该两个相邻轨迹点的时间间隔；其中，该两个相邻轨迹点和/>的时间间隔标记为/>，；Step S33, according to the track point recording time of the two adjacent track points, the time interval for generating the two adjacent track points is obtained; wherein, the two adjacent track points and /> time interval marked as /> , ;

步骤S34，根据所得相邻轨迹点之间的距离和对应的时间间隔，得到该任一最优台风轨迹所对应台风在该相邻轨迹点之间的台风平均移动速度；其中，该任一最优台风轨迹所对应台风在该相邻轨迹点和/>之间的台风平均移动速度标记为/>，；Step S34, according to the obtained distance between adjacent track points and the corresponding time interval, obtain the typhoon average moving speed of the typhoon corresponding to any optimal typhoon track between the adjacent track points; The typhoon corresponding to the optimal typhoon track is at the adjacent track point and /> The average moving speed of the typhoon between is marked as /> , ;

步骤S35，对上述历年最优台风轨迹数据内每一个最优台风轨迹数据遍历执行步骤S31和步骤S34，得到多个台风平均移动速度，且查找得到该多个台风平均移动速度中的平均移动速度中位数；其中，该多个台风平均移动速度中的平均移动速度中位数标记为；经基于该实施例所获取到的历年最优台风轨迹数据做计算处理，得到该多个台风平均移动速度中的平均移动速度中位数/>=4.0273m/s；Step S35, execute step S31 and step S34 for each optimal typhoon track data in the above-mentioned optimal typhoon track data over the years, obtain the average moving speed of multiple typhoons, and find the average moving speed among the average moving speeds of the multiple typhoons Median; Among them, the median of the average moving speed of the multiple typhoons is marked as ; Through calculation and processing based on the optimal typhoon trajectory data obtained in this embodiment over the years, the average moving speed median in the average moving speed of the plurality of typhoons is obtained. =4.0273m/s;

步骤S36，根据所得平均移动速度中位数、预设时长以及预设网格单元所表征距离，得到目标区域网格尺寸；其中，目标区域网格尺寸标记为，/>；T为预设时长，L为预设网格单元所表征距离。比如说，在该实施例中，此处的预设时长T为6小时，预设网格单元为1°网格，该1°网格所表征距离L为110km，计算得到目标区域网格尺寸G=0.7908°。In step S36, the grid size of the target area is obtained according to the obtained median moving speed, the preset duration, and the distance represented by the preset grid unit; wherein, the grid size of the target area is marked as , /> ; T is the preset time length, and L is the distance represented by the preset grid unit. For example, in this embodiment, the preset duration T here is 6 hours, the preset grid unit is a 1 ° grid, and the distance L represented by the 1 ° grid is 110km, and the grid size of the target area is calculated G=0.7908 ° .

当然，针对上述的步骤S4，上述目标区域网格按照如下方式处理得到：Of course, for the above-mentioned step S4, the above-mentioned target area grid is processed as follows:

将目标区域（即中国南海北部）进行网格化处理，得到具有多个小网格的目标区域网格；其中，该目标区域网格内小网格总数量为M，目标区域网格的参数为，/>；该目标区域网格内内第m个小网格的经度范围为/>，第m个小网格的纬度范围为/>，/>。The target area (i.e. the northern part of the South China Sea) is gridded to obtain a target area grid with multiple small grids; wherein, the total number of small grids in the target area grid is M, and the parameters of the target area grid for , /> ;The longitude range of the mth small grid in the grid of the target area is /> , the latitude range of the mth small grid is /> , /> .

针对上述步骤S5，该实施例得到对应该历年中每一年最优台风轨迹数据的细化后台风轨迹处理方式为：For the above-mentioned step S5, this embodiment obtains the processing method of the refined background cyclone track corresponding to the optimal typhoon track data of each year in the calendar year as follows:

计算所述多个台风平均移动速度中的最大平均移动速度值与所述平均移动速度中位数的商值，且得到该商值的取整值；其中，该多个台风平均移动速度中的最大平均移动速度值标记为；Calculate the quotient of the maximum average moving speed value among the multiple typhoon average moving speeds and the median of the average moving speed, and obtain the rounded value of the quotient; wherein, among the multiple typhoon average moving speeds, The maximum average moving speed value is marked as ;

将所得取整值的4倍数值作为对每一个台风轨迹做轨迹等分处理的等分数量值；其中，对每一个台风轨迹做轨迹等分处理的等分数量值标记为H，。经计算处理，等分数量值H为20，目标区域网格范围是：Lon=105:0.8:121，Lat=8:0.8:25，然后基于该等分数量值H，把上述的目标区域网格范围分成了21×22个小网格；Take the 4 times value of the rounded value obtained as the number of equal parts for each typhoon track; wherein, the number of equal parts for each typhoon track is marked as H, . After calculation and processing, the number of equal parts H is 20, the grid range of the target area is: Lon=105:0.8:121, Lat=8:0.8:25, and then based on the number of equal parts H, the above target area network The grid range is divided into 21×22 small grids;

针对上述的统计经验模型，该实施例针对统计经验模型的构建过程包括如下步骤S61~ S69：For the above-mentioned statistical empirical model, this embodiment includes the following steps S61 to S69 for the construction process of the statistical empirical model:

步骤S61，获取任一细化后台风轨迹上的轨迹点信息；其中，该任一细化后台风轨迹上的轨迹总数量标记为J，该任一细化后台风轨迹上的轨迹点标记为，记载产生该轨迹点/>的轨迹点记录时间标记为/>；/>；Step S61, obtain track point information on any thinning background wind track; wherein, the total number of tracks on any thinning background wind track is marked as J, and the track points on any thinning background wind track are marked as , record the generated trajectory point /> The track point recording time is marked as /> ;/> ;

步骤S62，根据所得所有的轨迹点信息，得到该任一细化后台风轨迹落在目标区域网格内每个小网格上的轨迹点以及该轨迹点对应的轨迹点记录时间；其中，该任一细化后台风轨迹的轨迹点落在目标区域网格内小网格上的判断条件为：Step S62, according to all the track point information obtained, obtain the track point where any refined background wind track falls on each small grid in the target area grid and the track point recording time corresponding to the track point; wherein, the The judgment condition that the track point of any wind track after refinement falls on the small grid in the grid of the target area is as follows:

当轨迹点坐标满足时，判定该轨迹点/>落在目标区域网格内的小网格上；否则，判定该轨迹点没有落在目标区域网格内的小网格上；When the track point coordinates satisfy , determine the trajectory point /> falls on a small grid within the grid of the target area; otherwise, determine the trajectory point did not land on a small grid within the target area grid;

步骤S63，根据步骤S62所得所有轨迹点记录时间，得到目标区域网格内每个小网格所对应的轨迹点记录时间集，且计算细化后台风轨迹落在该小网格上的时间间隔；其中，细化后台风轨迹落在该小网格上的时间间隔标记为h，；Step S63, according to the recording time of all track points obtained in step S62, obtain the record time set of track points corresponding to each small grid in the grid of the target area, and calculate the time interval of the wind track falling on the small grid after refinement ; Among them, the time interval when the wind track falls on the small grid after refinement is marked as h, ;

步骤S64，根据所得细化后台风轨迹落在该小网格上的时间间隔以及两个相邻轨迹点记录时间之间的时间间隔，判断得到对应该小网格的同类时间分集和不同类时间分集；其中：Step S64, according to the time interval between the obtained refined background wind track falling on the small grid and the time interval between the recording times of two adjacent track points, it is judged to obtain the similar time diversity and different time of the corresponding small grid Diversity; where:

当两个相邻轨迹点记录时间之间的时间间隔大于该细化后台风轨迹落在该小网格上的时间间隔时，即，判定轨迹点记录时间/>和/>属于不同类时间分集；否则，判定轨迹点记录时间/>和/>属于同类时间分集；When the time interval between the recording times of two adjacent track points is greater than the time interval of the wind track falling on the small grid after the refinement, that is , determine the track point recording time /> and /> belong to different types of time diversity; otherwise, determine the record time of the track point /> and /> belong to the same time diversity;

步骤S65，根据所得同类时间分集和不同类时间分集，分别计算该小网格所对应同类时间分集的平均时间和不同类时间分集的平均时间；Step S65, according to the obtained time diversity of the same type and the time diversity of different types, respectively calculate the average time of the same type of time diversity and the average time of different types of time diversity corresponding to the small grid;

步骤S66，根据同类时间分集及该同类时间分集的平均时间，计算同类时间分集的平均时间总数量；以及，根据不同类时间分集及该不同类时间分集的平均时间，计算不同类时间分集的平均时间总数量；其中，同类时间分集的平均时间总数量标记为K，同类时间分集中的第k个平均时间标记为；/>；也就是说，假设得到的这K个平均时间分别是、/>、…、/>和/>；Step S66, according to the time diversity of the same type and the average time of the time diversity of the same type, calculate the total number of average time of the time diversity of the same type; and, according to the time diversity of different types and the average time of the time diversity of the different type, calculate the average The total number of times; wherein, the total number of average times of the same kind of time diversity is marked as K, and the kth average time of the same kind of time diversity is marked as ;/> ; That is to say, assuming that the obtained K average times are , /> ,..., /> and /> ;

步骤S67，根据所得各类时间集的平均时间做出判断处理：Step S67, making a judgment process according to the obtained average time of various time sets:

当同类时间集中的两个相邻平均时间之间大于1天时，即天，判定/>和/>属于台风轨迹在不同时间经过该目标区域网格内同一个小网格；否则，判定/>和属于台风轨迹在连续时间经过该目标区域网格内同一个小网格；When the interval between two adjacent average times in the same time set is greater than 1 day, that is God, judgment/> and /> Belonging to the typhoon track passing through the same small grid in the grid of the target area at different times; otherwise, determine and Belonging to the typhoon track passing through the same small grid in the grid of the target area in continuous time;

步骤S68，根据步骤S67的判定结果得到该任一细化后台风轨迹经过该小网格的真实频次；Step S68, according to the determination result of step S67, obtain the real frequency of the wind track passing through the small grid after any refinement;

步骤S69，按照步骤S61~ S68的方式对每一个细化后台风轨迹做遍历循环，得到目标区域网格内每一个小网格被台风轨迹经过的真实频次。其中，台风轨迹经统计经验模型处理后在目标区域网格上的统计情况参见图3所示，附图3中的频次是指真实合理的台风轨迹经过小网格的次数。Step S69, perform a traversal loop on each refined background wind track according to the method of steps S61~S68, and obtain the real frequency of each small grid in the target area grid being passed by the typhoon track. Among them, the statistical situation of the typhoon track on the grid of the target area after being processed by the statistical empirical model is shown in Figure 3. The frequency in Figure 3 refers to the number of times that the real and reasonable typhoon track passes through the small grid.

尽管以上详细地描述了本发明的优选实施例，但是应该清楚地理解，对于本领域的技术人员来说，本发明可以有各种更改和变化。凡在本发明的精神和原则之内所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。Although the preferred embodiments of the present invention have been described in detail above, it should be clearly understood that various modifications and variations of the present invention will occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims (5)

1. A track self-adaptive gridding processing method based on optimal typhoon track data is characterized by comprising the following steps:
step S1, selecting a target area in which typhoon tracks need to be counted;
s2, acquiring annual optimal typhoon track data of a target area;
step S3, obtaining the grid size of the target area corresponding to the target area according to the acquired annual optimal typhoon track data;
step S4, performing gridding treatment on the target area based on the obtained target area grid size to obtain a target area grid corresponding to the target area;
s5, refining the acquired annual optimal typhoon track data by utilizing the target area grid to respectively obtain refined typhoon tracks corresponding to the annual optimal typhoon track data;
s6, constructing a statistical experience model for counting the passing frequency of each grid in the target area grid by the typhoon track according to the target area grid and all the obtained refined typhoon tracks;
s7, obtaining typhoon track distribution characteristics of typhoons in the target area on the grid of the target area according to the statistical experience model; the typhoon track distribution characteristics comprise the frequency of each grid in the target area grid to be passed by the typhoon track;
in step S3, the process of obtaining the mesh size of the target area according to the acquired annual optimal typhoon track data includes the following steps S31 to S36:
step S31, track point information of any optimal typhoon track in the annual optimal typhoon track data is obtained; the track point information comprises track point positions and track point recording time for recording the track points; marking the total number of track points of any optimal typhoon track as N, wherein two adjacent track points on any optimal typhoon track are respectivelyAnd->，/>Is track point->Longitude coordinates of>Is track point->Dimension coordinates of>Is track point->Longitude coordinates of>Is track point->Dimension coordinates of (2), track points->The track point recording time mark of (2) is +.>Track point->The track point recording time mark of (2) is +.>，/>；
Step S32, obtaining two adjacent tracks according to the track point information of the two adjacent track points on any optimal typhoon trackThe distance between the points; wherein, adjacent track pointsAnd->The distance between them is marked->：
The method comprises the steps of carrying out a first treatment on the surface of the Wherein,,is the earth radius;
step S33, obtaining the time interval for generating the two adjacent track points according to the track point recording time of the two adjacent track points; wherein the two adjacent track pointsAnd->The time interval of (2) is marked->，/>；
Step S34, according to the obtained distance between adjacent track points and the corresponding time interval, obtaining the typhoon average moving speed of typhoons corresponding to any optimal typhoon track between the adjacent track points; wherein typhoons corresponding to any optimal typhoon track are positioned at the adjacent track pointsAnd->The typhoon average moving speed between is marked as +.>，/>；
Step S35, traversing and executing step S31 and step S34 on each piece of optimal typhoon track data in the annual optimal typhoon track data to obtain a plurality of average typhoon moving speeds, and searching to obtain the average moving speed median in the plurality of average typhoon moving speeds; wherein the average moving speed median of the plurality of typhoons is marked as；
Step S36, obtaining the grid size of the target area according to the median of the obtained average moving speed, the preset duration and the distance represented by the preset grid unit; wherein the mesh size of the target area is marked as，/>；/>For a preset time length, < >>The distance represented by the preset grid unit is calculated;
the construction process of the statistical experience model comprises the following steps S61-S69:
step S61, track point information on any thinned background wind track is obtained; wherein the total number of tracks on any one of the refined background wind tracks is marked asThe track point mark on any thinned background wind track is +.>Record the generation of the trace point->The track point recording time mark of (2) is +.>；/>；
Step S62, according to all the obtained track point information, track points of any thinned background wind track falling on each small grid in the target area grid and track point recording time corresponding to the track points are obtained; the judging condition that the track points of any thinned background wind track fall on the small grids in the target area grid is as follows:
when the coordinates of the track points are satisfiedAt this time, the trace point is judged +.>Falling on a small grid within the target area grid; otherwise, determining the track pointNot falling on the small grid within the target area grid;
step S63, obtaining a track point recording time set corresponding to each small grid in the target area grid according to all track point recording times obtained in the step S62, and calculating the time interval of the thinned typhoon track falling on the small grid; wherein the time interval of the thinned background wind track falling on the small grid is marked as，/>；
Step S64, judging and obtaining similar time diversity and different time diversity corresponding to the small grid according to the time interval of the thinned background wind track falling on the small grid and the time interval between the recording times of two adjacent track points; wherein:
when the time interval between the recording time of two adjacent track points is larger than the time interval of the thinned typhoon track falling on the small grid, namelyDetermining track point recording time->And->Belongs to different types of time diversity; otherwise, determine track point recording time +.>And->Belongs to the similar time diversity;
step S65, according to the obtained similar time diversity and different time diversity, respectively calculating the average time of the similar time diversity and the average time of the different time diversity corresponding to the small grid;
step S66, calculating the average time total number of the same kind of time diversity according to the same kind of time diversity and the average time of the same kind of time diversity; and calculating the average time total number of the different types of time diversity according to the different types of time diversity and the average time of the different types of time diversity; wherein the average total number of times of the same kind of time diversity is marked asThe +.f in the time-sharing of the same class>The average time is marked->；/>；
Step S67, judging processing is carried out according to the average time of the obtained time sets:
when the average time between two adjacent times in the same class time set is greater than 1 day, i.eDay, determine->And->Belongs to the same small grid in the grid of the target area when typhoon tracks pass through at different times; otherwise, determine->And->Belongs to the same small grid in the grid of the target area, through which the typhoon track passes in continuous time;
step S68, obtaining the real frequency of the any thinned background wind track passing through the small grid according to the judging result of the step S67;
and step S69, performing traversal circulation on each thinned background wind track according to the mode of steps S61-S68 to obtain the real frequency of each small grid in the target area grid passing by the typhoon track.
2. The track adaptive meshing processing method based on optimal typhoon track data according to claim 1, wherein in step S2, the annual optimal typhoon track data of the target area is acquired from a tropical cyclone data center of the national weather service.
3. The track self-adaptive gridding processing method based on optimal typhoon track data according to claim 1, wherein the preset duration is as followsFor 6 hours, the preset grid unit is 1 ° Grid, 1 ° Grid-characterized distance->110km.
4. The track adaptive meshing processing method based on the optimal typhoon track data according to claim 1, wherein in step S4, the target area mesh is obtained by processing in the following manner:
performing gridding treatment on the target area to obtain a target area grid with a plurality of small grids; wherein the total number of small grids in the target area grid isThe parameters of the target area grid are +.>， The method comprises the steps of carrying out a first treatment on the surface of the The>Longitude range of each small grid isFirst->The latitude of the individual cells is +.>，/>。
5. The track self-adaptive gridding processing method based on the optimal typhoon track data according to claim 4, wherein in step S5, a refined typhoon track processing mode for obtaining the optimal typhoon track data corresponding to each year of the calendar year is as follows:
calculating the quotient of the maximum average moving speed value in the plurality of typhoons average moving speeds and the median of the average moving speeds, and obtaining the rounding value of the quotient; wherein a maximum average moving speed value of the typhoons average moving speeds is marked as；
Taking the 4 times value of the obtained rounding value as an equal score value for carrying out track equal score processing on each typhoon track; wherein, the dividing number value of the track dividing treatment of each typhoon track is marked as，/>。
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