WO2023155179A1 - Method and system for calculating correlation between lightning and temperature in specific area under influence of tropical cyclones - Google Patents
Method and system for calculating correlation between lightning and temperature in specific area under influence of tropical cyclones Download PDFInfo
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- WO2023155179A1 WO2023155179A1 PCT/CN2022/076976 CN2022076976W WO2023155179A1 WO 2023155179 A1 WO2023155179 A1 WO 2023155179A1 CN 2022076976 W CN2022076976 W CN 2022076976W WO 2023155179 A1 WO2023155179 A1 WO 2023155179A1
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- the invention relates to a method and system for calculating the correlation between lightning and temperature in a specific area under the influence of a tropical cyclone.
- Lightning is a strong discharge process that occurs between clouds or between clouds and the ground. It is also a serious natural disaster and has been rated as one of the ten most serious natural disasters. Forest and building fires caused by lightning not only cause huge economic losses, but also endanger people's lives.
- the invention provides a method for calculating the correlation between lightning and temperature in a specific area under the influence of a tropical cyclone.
- the abnormal data in the tropical cyclone data set, lightning data set and temperature data set are replaced or deleted;
- b. Screen the tropical cyclones within a certain range from a specific area, group them according to the level of the tropical cyclone, and count the specific area within an hour The number of lightning that occurred; c.
- the longitude and latitude coordinates of the tropical cyclone the occurrence The number of lightning that occurs in a specific area within one hour is interpolated using the inverse distance weighting method to obtain the lightning spatial distribution map of a specific area under the influence of a tropical cyclone; according to the level of the tropical cyclone, the latitude and longitude coordinates of the tropical cyclone, and the temperature of the specific area at the time when the tropical cyclone occurs , use the inverse distance weighting method to interpolate to obtain the temperature spatial distribution map of a specific area under the influence of tropical cyclones; e. read the data in the lightning spatial distribution map and the data in the temperature spatial distribution map, and calculate the Dependence of lightning and temperature in a specific area.
- said step a includes:
- said step b includes:
- the geographical space distance is obtained by the following calculation formula:
- S is the distance between two points on the earth (km); R is the radius of the earth (km); L 1 and are the longitude and latitude of point A, L2 and are the longitude and latitude of point B.
- said step b also includes:
- said step d includes:
- said step d also includes:
- the obtained data that is, the grade of tropical cyclone, the latitude and longitude coordinates of tropical cyclone, the total number of lightning in the specific area within one hour of the occurrence of the tropical cyclone, the lightning space distribution map of the specific area under the influence of the tropical cyclone is obtained by interpolation using the inverse distance weight method .
- said step d also includes:
- the inverse distance weighting method is used to interpolate to obtain the temperature spatial distribution map of the specific area under the influence of the tropical cyclone.
- said step e specifically includes:
- the spatial correlation between lightning and temperature in a specific area under the influence of tropical cyclones is calculated .
- the invention provides a calculation system for the correlation between lightning and temperature in a specific area under the influence of a tropical cyclone.
- the system includes an identification module, a grouping module, a merging module, an interpolation module and a correlation module, wherein: the identification module is used for time series Read in the tropical cyclone data set, lightning data set and temperature data set in batches, identify the abnormal data in the tropical cyclone data set, lightning data set and temperature data set, and replace or delete them; the grouping module is used to filter the distance Tropical cyclones within a certain range in a specific area are grouped according to the level of the tropical cyclone, and the number of lightning that occurs in a specific area per hour is counted; Merge to get the level of tropical cyclone at this moment, latitude and longitude coordinates and the total number of lightning in a specific area within one hour; and merge the processed tropical cyclone data set and temperature data set according to the time series to get the Level, latitude and longitude coordinates and the temperature of a specific area
- the lightning spatial distribution map of a specific area under the influence of a tropical cyclone according to the level of the tropical cyclone, the latitude and longitude coordinates of the tropical cyclone, and the temperature of the specific area at the time when the tropical cyclone occurs, use the inverse distance weighting method to interpolate to obtain the temperature space of the specific area under the influence of the tropical cyclone Distribution diagram; the correlation module is used to read the data in the lightning spatial distribution diagram and the data in the temperature spatial distribution diagram, and calculate the correlation between lightning and temperature in the specific area.
- the invention can calculate the correlation between lightning and temperature in a specific area when a tropical cyclone occurs, and has universality.
- the present invention obtains the spatial distribution map of the two data sets through interpolation processing, and reads the data of every 0.1° ⁇ 0.1° grid point in the spatial distribution map to calculate the correlation between the two.
- the present invention classifies tropical cyclones into different grades, and calculates the correlation between lightning and temperature in a specific area under the influence of different grades of tropical cyclones.
- the invention has important reference value for forecasting regional lightning activities under the influence of tropical cyclones.
- Fig. 1 is the flow chart of the calculation method of lightning and temperature correlation in specific area under the influence of tropical cyclone of the present invention
- Fig. 2 is a schematic diagram of the spatial distribution of lightning in Shenzhen under the influence of tropical cyclones of different grades provided by the embodiment of the present invention: wherein, (a) SSTY; (b) TY; (c) STS; (d) TS; (e) TD; (f) ALL TC;
- Fig. 3 is a schematic diagram of spatial distribution of temperature in Shenzhen under the influence of different levels of tropical cyclones provided by the embodiment of the present invention: wherein, (a) SSTY; (b) TY; (c) STS; (d) TS; (e) TD; (f )ALL TC;
- FIG. 4 is a hardware architecture diagram of a computing system for calculating the correlation between lightning and temperature in a specific area under the influence of a tropical cyclone according to the present invention.
- FIG. 1 it is a flow chart of a preferred embodiment of the method for calculating the correlation between lightning and temperature in a specific area under the influence of a tropical cyclone according to the present invention.
- the Shenzhen area is taken as an example to study the correlation between lightning and temperature in the Shenzhen area under the influence of tropical cyclones. It is worth noting that this method is versatile, not only suitable for studying the correlation between lightning and temperature in Shenzhen, but also suitable for other regions.
- Step S1 read in batches of tropical cyclone data sets, lightning data sets and temperature data sets according to time series, identify abnormal data in the tropical cyclone data sets, the lightning data sets and the temperature data sets, and replace or delete.
- Step S1 read in batches of tropical cyclone data sets, lightning data sets and temperature data sets according to time series, identify abnormal data in the tropical cyclone data sets, the lightning data sets and the temperature data sets, and replace or delete.
- this embodiment reads the tropical cyclone data set, the lightning data set, and the temperature data set in time series. Delete the data with null values after the temperature data set, and unify the time format of the tropical cyclone data set, the lightning data set and the temperature data set into: hour-minute-second.
- Step S2 screen the tropical cyclones within 1000km from the Shenzhen Meteorological Station, group them according to the level of the tropical cyclones, and count the number of lightnings that occurred in the Shenzhen area per hour. in particular:
- this embodiment selects the tropical cyclones within 1000km from the Shenzhen weather station. According to the latitude and longitude coordinates of the Shenzhen meteorological station and the latitude and longitude coordinates of the tropical cyclone, the geographical space distance between the two is calculated. According to the different intensities of the life history of tropical cyclones, namely tropical depression (tropical depression, TD), tropical storm (tropical storm, TS), severe tropical storm (severe tropical storm, STS), typhoon (typhoon, TY), severe typhoon (severe typhoon) typhoon,
- S is the distance between two points on the earth (km); R is the radius of the earth (km); L 1 and are the longitude and latitude of point A, L2 and are the longitude and latitude of point B.
- the lightning data set is not limited to the lightning located in Shenzhen, it is necessary to filter out the lightning located only in the Shenzhen area. According to the longitude and latitude coordinates when the lightning occurs, it is judged one by one whether the lightning is located in the Shenzhen area. Make hourly statistics on the filtered data set, which is divided into 24 hours (Beijing time) such as: 0:00-1:00, 1:00-2:00...23:00-24:00 (Beijing time). The total number of lightning strikes in the Shenzhen area within an hour.
- Step S3 merging the tropical cyclone data set and the lightning data set, the tropical cyclone data set and the temperature data set respectively in time series.
- the processed tropical cyclone data set and lightning data set were merged according to the time series to obtain the level of tropical cyclone, latitude and longitude coordinates and the total number of lightning in Shenzhen within one hour at that moment.
- the processed tropical cyclone data set and temperature data set were merged according to the time series to obtain the grade, latitude and longitude coordinates of the tropical cyclone and the temperature in Shenzhen at the same time.
- step S4 interpolation is performed with the inverse distance weighting method based on the existing data to obtain the lightning spatial distribution map and temperature spatial distribution map in Shenzhen under the influence of tropical cyclones.
- the inverse distance weighting method assumes that all known points will have a certain effect on the value of the predicted point, and the effect of the value of any known point on the value of the predicted point is related to the distance. The closer the known point is to the predicted point, the greater the effect, and the farther the distance, the smaller the effect.
- the N known points closest to the estimated predicted point have an effect on the predicted point, and the effect of the N known points on the predicted point is inversely proportional to the distance between them.
- the weight of known points closer to the predicted point is greater, and the weight sum of all known points is 1.
- the spatial distribution map of lightning in Shenzhen area under the influence of tropical cyclone is obtained by interpolating with the inverse distance weight method (please See Figure 2).
- the inverse distance weighting method was used to interpolate to obtain the temperature spatial distribution map of the Shenzhen area under the influence of the tropical cyclone (see Figure 3).
- Step S5 read the data of every 0.1*0.1 grid point in the lightning spatial distribution map and the data of every 0.1*0.1 grid point in the temperature spatial distribution map, and calculate the correlation between lightning and temperature.
- the spatial correlation between lightning and temperature in Shenzhen under the influence of tropical cyclones can be calculated.
- the spatial distribution map of tropical cyclone lightning with grade TD has a value for each grid point of 0.1° ⁇ 0.1° in 104.6°E-123.7°E and 13.6°N-30.8°N, indicating that the The number of lightning strikes in the Shenzhen area.
- FIG. 4 it is a hardware architecture diagram of the calculation system 10 for the correlation between lightning and temperature in a specific area under the influence of tropical cyclones of the present invention.
- the system includes: an identification module 101 , a grouping module 102 , a combining module 103 , an interpolation module 104 and a correlation module 105 . in:
- the identification module 101 is used to read in batches of tropical cyclone data sets, lightning data sets and temperature data sets in time series, identify abnormal data in the tropical cyclone data sets, lightning data sets and temperature data sets, and replace or delete;
- the grouping module 102 is used to filter tropical cyclones within a certain range from a specific area, group them according to the level of the tropical cyclone, and count the number of lightnings that occur in a specific area per hour;
- the merging module 103 is used to merge the processed tropical cyclone data set and the lightning data set according to the time series to obtain the level of the tropical cyclone at this moment, the latitude and longitude coordinates and the total number of lightning in a specific area within one hour;
- the interpolation module 104 is used to perform interpolation using the inverse distance weighting method according to the level of the tropical cyclone, the latitude and longitude coordinates of the tropical cyclone, and the number of lightnings that occurred in a specific area within one hour of the occurrence of the tropical cyclone, so as to obtain the spatial distribution of lightning in a specific area under the influence of the tropical cyclone Figure: According to the tropical cyclone level, the latitude and longitude coordinates of the tropical cyclone, and the temperature of the specific area at the time when the tropical cyclone occurs, the inverse distance weighting method is used to interpolate to obtain the temperature spatial distribution map of the specific area under the influence of the tropical cyclone;
- the correlation module 105 is used to read the data in the lightning spatial distribution map and the data in the temperature spatial distribution map, and calculate the correlation between lightning and temperature in the specific area.
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Abstract
The present invention relates to a method for calculating the correlation between lightning and temperature in a specific area under the influence of tropical cyclones, which comprises: reading in a tropical cyclone data set, a lightning data set, and a temperature data set, and identifying abnormal data in the data sets; selecting tropical cyclones within a certain distance of a specific area, performing grouping, and counting the number of lightning strikes occurring in the specific area each hour; separately combining the tropical cyclone data set with the lightning data set and the tropical cyclone data set with the temperature data set; obtaining a lightning strike spatial distribution map and a temperature spatial distribution map of the Shenzhen area under the influence of tropical cyclones; reading in data in the lightning strike spatial distribution diagram and data in the temperature spatial distribution diagram, and performing calculation to obtain the correlation between lightning and temperature in the specific area. The present invention further relates to a system for calculating the correlation between lightning and temperature in a specific area under the influence of tropical cyclones. The present invention is able to calculate the correlation of lightning and temperature of a specific area when a tropical cyclone occurs, and has general usability.
Description
本发明涉及一种热带气旋影响下特定区域闪电与温度相关性的计算方法及系统。The invention relates to a method and system for calculating the correlation between lightning and temperature in a specific area under the influence of a tropical cyclone.
闪电是发生在云与云或云与地之间的强放电过程，也是一种严重的自然灾害，曾被评为十大最严重的自然灾害之一。闪电引发的森林和建筑火灾不仅对经济造成巨大的损失，更是危害人民生命安全。Lightning is a strong discharge process that occurs between clouds or between clouds and the ground. It is also a serious natural disaster and has been rated as one of the ten most serious natural disasters. Forest and building fires caused by lightning not only cause huge economic losses, but also endanger people's lives.
据相关资料统计，全球每年因闪电造成的经济损失高达数十亿美元以上，每年因闪电造成的伤亡人数达万人之巨。许多观测和研究证明，热带气旋系统常常发生闪电活动。因此，研究热带气旋影响下的区域闪电特征对经济发展具有重要现实意义。According to relevant statistics, the economic losses caused by lightning every year in the world are as high as billions of dollars, and the number of casualties caused by lightning every year reaches 10,000. Many observations and studies have proved that lightning activities often occur in tropical cyclone systems. Therefore, the study of regional lightning characteristics under the influence of tropical cyclones has important practical significance for economic development.
然而，现有技术在研究热带气旋影响下特定区域闪电与温度相关性的计算时，都是针对数据集大小一致的情况，而当数据集大小不一致时，无法计算相关性。目前，尚未出现一种涉及热带气旋影响下区域闪电数据集和温度数据集不一致时，计算二者相关性的方法或系统。However, when the existing technology studies the calculation of the correlation between lightning and temperature in a specific area under the influence of tropical cyclones, it is all for the case that the size of the data set is consistent, and when the size of the data set is inconsistent, the correlation cannot be calculated. At present, there is no method or system for calculating the correlation between the regional lightning data set and the temperature data set under the influence of tropical cyclones when they are inconsistent.
发明内容Contents of the invention
有鉴于此，有必要提供一种热带气旋影响下特定区域闪电与温度相关性的计算方法及系统。In view of this, it is necessary to provide a method and system for calculating the correlation between lightning and temperature in a specific area under the influence of tropical cyclones.
本发明提供一种热带气旋影响下特定区域闪电与温度相关性的计算方法，该方法包括如下步骤：a.按时间序列分批读入热带气旋数据集、闪电数据集和温度数据集，识别所述热带气旋数据集、闪电数据集和温度数据集中的异常数据，并进行替代或删除；b.筛选距离特定区域一定范围内的热带气旋，按热带气旋等级进行分组，并统计每小时内特定区域发生的闪电数；c.将处理后的热带气旋数据集和闪电数据集根据时间序列进行合并，得到该时刻下热带气旋的 等级、经纬度坐标及一小时内特定区域发生的闪电总数；将处理后的热带气旋数据集和温度数据集根据时间序列进行合并，得到该时刻下热带气旋的等级、经纬度坐标及同时刻特定区域的温度；d.根据热带气旋等级、热带气旋经纬度坐标、该热带气旋发生一小时内特定区域发生的闪电数，利用反距离权重法进行插值，得到热带气旋影响下特定区域的闪电空间分布图；根据热带气旋等级、热带气旋经纬度坐标、该热带气旋发生时刻特定区域的温度，用反距离权重法进行插值得到热带气旋影响下特定区域的温度空间分布图；e.读取所述闪电空间分布图中的数据和所述温度空间分布图中的数据，并计算得到所述特定区域闪电与温度的相关性。The invention provides a method for calculating the correlation between lightning and temperature in a specific area under the influence of a tropical cyclone. The abnormal data in the tropical cyclone data set, lightning data set and temperature data set are replaced or deleted; b. Screen the tropical cyclones within a certain range from a specific area, group them according to the level of the tropical cyclone, and count the specific area within an hour The number of lightning that occurred; c. Merge the processed tropical cyclone data set and lightning data set according to the time series to obtain the level of tropical cyclone at that moment, the latitude and longitude coordinates and the total number of lightning that occurred in a specific area within one hour; the processed The tropical cyclone data set and the temperature data set are merged according to the time series to obtain the level of the tropical cyclone, the longitude and latitude coordinates and the temperature of a specific area at the same time; d. According to the tropical cyclone level, the longitude and latitude coordinates of the tropical cyclone, the occurrence The number of lightning that occurs in a specific area within one hour is interpolated using the inverse distance weighting method to obtain the lightning spatial distribution map of a specific area under the influence of a tropical cyclone; according to the level of the tropical cyclone, the latitude and longitude coordinates of the tropical cyclone, and the temperature of the specific area at the time when the tropical cyclone occurs , use the inverse distance weighting method to interpolate to obtain the temperature spatial distribution map of a specific area under the influence of tropical cyclones; e. read the data in the lightning spatial distribution map and the data in the temperature spatial distribution map, and calculate the Dependence of lightning and temperature in a specific area.
优选地，所述的步骤a包括：Preferably, said step a includes:
按时间序列读取所述热带气旋数据集、闪电数据集和温度数据集后对存在空值的数据进行删除，并将所述热带气旋数据集、闪电数据集和温度数据集的时间格式统一为：时-分-秒。After reading the tropical cyclone data set, lightning data set and temperature data set in time series, the data with null values is deleted, and the time format of the tropical cyclone data set, lightning data set and temperature data set is unified as :Minutes and seconds.
优选地，所述的步骤b包括：Preferably, said step b includes:
根据所述特定区域的经纬度坐标和热带气旋的经纬度坐标，计算所述特定区域与热带气旋之间的地理空间距离；calculating the geospatial distance between the specific area and the tropical cyclone according to the latitude and longitude coordinates of the specific area and the latitude and longitude coordinates of the tropical cyclone;
根据热带气旋等级，即热带低压、热带风暴、强热带风暴、台风、强台风、超强台风进行分组；According to the level of tropical cyclone, namely tropical depression, tropical storm, severe tropical storm, typhoon, strong typhoon, super typhoon;
由于超强台风和强台风样本数相对于其他强度类别的热带气旋要少一些，故将超强台风和强台风合并为一类，将其命名为SSTY，最终得到五类不同等级的热带气旋数据集。Since the number of samples of super typhoon and strong typhoon is less than that of tropical cyclones of other intensity categories, super typhoon and strong typhoon are combined into one category, named SSTY, and finally five types of tropical cyclone data of different levels are obtained set.
优选地，其特征在于：Preferably, it is characterized in that:
所述地理空间距离通过如下计算公式得到：The geographical space distance is obtained by the following calculation formula:
其中，S是地球上两点间距离(km)；R是地球的半径(km)；L
1和
是A点的经度和纬度，L
2和
是B点的经度和纬度。
Among them, S is the distance between two points on the earth (km); R is the radius of the earth (km); L 1 and are the longitude and latitude of point A, L2 and are the longitude and latitude of point B.
优选地，所述的步骤b还包括：Preferably, said step b also includes:
根据闪电发生时的经纬度坐标来逐一判断该闪电是否位于所述特定区域；Judging whether the lightning is located in the specific area one by one according to the latitude and longitude coordinates when the lightning occurs;
对筛选后的数据集做逐时统计，即分为：0:00-1:00，1:00-2:00…23:00-24:00二十四个时次，统计每小时内所述特定区域的闪电总数。Make hourly statistics on the filtered data set, which is divided into twenty-four hours: 0:00-1:00, 1:00-2:00...23:00-24:00, and count all The total number of lightning bolts in the specified area.
优选地，所述的步骤d包括：Preferably, said step d includes:
将处理后的热带气旋数据集和闪电数据集根据时间序列进行合并，得到该时刻下热带气旋的等级、经纬度坐标及一小时内所述特定区域发生的闪电总数。Merge the processed tropical cyclone data set and lightning data set according to the time series to obtain the level of tropical cyclone, latitude and longitude coordinates and the total number of lightning in the specific area within one hour at that moment.
优选地，所述的步骤d还包括：Preferably, said step d also includes:
根据已得到的数据，即热带气旋等级、热带气旋经纬度坐标、该热带气旋发生一小时内所述特定区域的闪电总数，利用反距离权重法进行插值得到热带气旋影响下特定区域的闪电空间分布图。According to the obtained data, that is, the grade of tropical cyclone, the latitude and longitude coordinates of tropical cyclone, the total number of lightning in the specific area within one hour of the occurrence of the tropical cyclone, the lightning space distribution map of the specific area under the influence of the tropical cyclone is obtained by interpolation using the inverse distance weight method .
优选地，所述的步骤d还包括：Preferably, said step d also includes:
根据热带气旋等级、热带气旋经纬度坐标、该热带气旋发生时刻特定区域的温度，用反距离权重法进行插值得到热带气旋影响下特定区域的温度空间分布图。According to the tropical cyclone level, the latitude and longitude coordinates of the tropical cyclone, and the temperature of the specific area at the time when the tropical cyclone occurs, the inverse distance weighting method is used to interpolate to obtain the temperature spatial distribution map of the specific area under the influence of the tropical cyclone.
优选地，所述的步骤e具体包括：Preferably, said step e specifically includes:
根据所述闪电空间分布图中每0.1*0.1格点存在的值和所述温度空间分布图中每0.1*0.1格点存在的值，计算得到热带气旋影响下特定区域闪电和温度的空间相关性。According to the value existing at every 0.1*0.1 grid point in the lightning spatial distribution map and the value at every 0.1*0.1 grid point in the temperature spatial distribution map, the spatial correlation between lightning and temperature in a specific area under the influence of tropical cyclones is calculated .
本发明提供一种热带气旋影响下特定区域闪电与温度相关性的计算系统，该系统包括识别模块、分组模块、合并模块、插值模块以及相关性模块，其中：所述识别模块用于按时间序列分批读入热带气旋数据集、闪电数据集和温度数据集，识别所述热带气旋数据集、闪电数据集和温度数据集中的异常数据，并进行替代或删除；所述分组模块用于筛选距离特定区域一定范围内的热带气旋，按热带气旋等级进行分组，并统计每小时内特定区域发生的闪电数；所述合并模块用于将处理后的热带气旋数据集和闪电数据集根据时间序列进行合并，得 到该时刻下热带气旋的等级、经纬度坐标及一小时内特定区域发生的闪电总数；以及将处理后的热带气旋数据集和温度数据集根据时间序列进行合并，得到该时刻下热带气旋的等级、经纬度坐标及同时刻特定区域的温度；所述插值模块用于根据热带气旋等级、热带气旋经纬度坐标、该热带气旋发生一小时内特定区域发生的闪电数，利用反距离权重法进行插值，得到热带气旋影响下特定区域的闪电空间分布图；根据热带气旋等级、热带气旋经纬度坐标、该热带气旋发生时刻特定区域的温度，用反距离权重法进行插值得到热带气旋影响下特定区域的温度空间分布图；所述相关性模块用于读取所述闪电空间分布图中的数据和所述温度空间分布图中的数据，并计算得到所述特定区域闪电与温度的相关性。The invention provides a calculation system for the correlation between lightning and temperature in a specific area under the influence of a tropical cyclone. The system includes an identification module, a grouping module, a merging module, an interpolation module and a correlation module, wherein: the identification module is used for time series Read in the tropical cyclone data set, lightning data set and temperature data set in batches, identify the abnormal data in the tropical cyclone data set, lightning data set and temperature data set, and replace or delete them; the grouping module is used to filter the distance Tropical cyclones within a certain range in a specific area are grouped according to the level of the tropical cyclone, and the number of lightning that occurs in a specific area per hour is counted; Merge to get the level of tropical cyclone at this moment, latitude and longitude coordinates and the total number of lightning in a specific area within one hour; and merge the processed tropical cyclone data set and temperature data set according to the time series to get the Level, latitude and longitude coordinates and the temperature of a specific area at the same moment; the interpolation module is used to perform interpolation using the inverse distance weighting method according to the tropical cyclone level, the latitude and longitude coordinates of the tropical cyclone, and the number of lightnings that occurred in a specific area within one hour of the tropical cyclone. Obtain the lightning spatial distribution map of a specific area under the influence of a tropical cyclone; according to the level of the tropical cyclone, the latitude and longitude coordinates of the tropical cyclone, and the temperature of the specific area at the time when the tropical cyclone occurs, use the inverse distance weighting method to interpolate to obtain the temperature space of the specific area under the influence of the tropical cyclone Distribution diagram; the correlation module is used to read the data in the lightning spatial distribution diagram and the data in the temperature spatial distribution diagram, and calculate the correlation between lightning and temperature in the specific area.
本发明能够在一种热带气旋发生时，计算某一特定区域的闪电和温度相关性，具有通用性。本发明通过对两者的数据集进行插值处理得到两者的空间分布图，读取空间分布图中每0.1°×0.1°的格点的数据从而计算两者之间的相关性。且本发明将热带气旋分为不同等级，分别计算不同等级的热带气旋影响下特定区域闪电与温度之间的相关性。本发明对热带气旋影响下区域闪电活动的预报有重要参考价值。The invention can calculate the correlation between lightning and temperature in a specific area when a tropical cyclone occurs, and has universality. The present invention obtains the spatial distribution map of the two data sets through interpolation processing, and reads the data of every 0.1°×0.1° grid point in the spatial distribution map to calculate the correlation between the two. Moreover, the present invention classifies tropical cyclones into different grades, and calculates the correlation between lightning and temperature in a specific area under the influence of different grades of tropical cyclones. The invention has important reference value for forecasting regional lightning activities under the influence of tropical cyclones.
图1为本发明热带气旋影响下特定区域闪电与温度相关性的计算方法的流程图；Fig. 1 is the flow chart of the calculation method of lightning and temperature correlation in specific area under the influence of tropical cyclone of the present invention;
图2为本发明实施例提供的不同等级热带气旋影响下深圳闪电空间分布图的示意图：其中，(a)SSTY；(b)TY；(c)STS；(d)TS；(e)TD；(f)ALL TC；Fig. 2 is a schematic diagram of the spatial distribution of lightning in Shenzhen under the influence of tropical cyclones of different grades provided by the embodiment of the present invention: wherein, (a) SSTY; (b) TY; (c) STS; (d) TS; (e) TD; (f) ALL TC;
图3为本发明实施例提供的不同等级热带气旋影响下深圳温度空间分布示意图：其中，(a)SSTY；(b)TY；(c)STS；(d)TS；(e)TD；(f)ALL TC；Fig. 3 is a schematic diagram of spatial distribution of temperature in Shenzhen under the influence of different levels of tropical cyclones provided by the embodiment of the present invention: wherein, (a) SSTY; (b) TY; (c) STS; (d) TS; (e) TD; (f )ALL TC;
图4为本发明热带气旋影响下特定区域闪电与温度相关性的计算系统的硬件架构图。FIG. 4 is a hardware architecture diagram of a computing system for calculating the correlation between lightning and temperature in a specific area under the influence of a tropical cyclone according to the present invention.
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处所描述的具体实施例仅用以解释本申请，并不用于限定本申请。In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, not to limit the present application.
参阅图1所示，是本发明热带气旋影响下特定区域闪电与温度相关性的计算方法较佳实施例的作业流程图。Referring to FIG. 1 , it is a flow chart of a preferred embodiment of the method for calculating the correlation between lightning and temperature in a specific area under the influence of a tropical cyclone according to the present invention.
本实施例以深圳地区为例，研究深圳地区在热带气旋影响下的闪电与温度相关性。值得说明的是，该方法具有通用性，不仅适合对深圳地区的闪电与温度相关性进行研究，也适合于其他地区。In this embodiment, the Shenzhen area is taken as an example to study the correlation between lightning and temperature in the Shenzhen area under the influence of tropical cyclones. It is worth noting that this method is versatile, not only suitable for studying the correlation between lightning and temperature in Shenzhen, but also suitable for other regions.
步骤S1，按时间序列分批读入热带气旋数据集、闪电数据集和温度数据集，识别所述热带气旋数据集、所述闪电数据集和所述温度数据集中的异常数据，并进行替代或删除。具体而言：Step S1, read in batches of tropical cyclone data sets, lightning data sets and temperature data sets according to time series, identify abnormal data in the tropical cyclone data sets, the lightning data sets and the temperature data sets, and replace or delete. in particular:
由于热带气旋数据集、所述闪电数据集和所述温度数据集中的原始数据可能存在数据缺失或数据异常，本实施例按时间序列读取所述热带气旋数据集、所述闪电数据集和所述温度数据集后对存在空值的数据进行删除，并将所述热带气旋数据集、所述闪电数据集和所述温度数据集的时间格式统一为：时-分-秒。Since the original data in the tropical cyclone data set, the lightning data set, and the temperature data set may have data missing or abnormal data, this embodiment reads the tropical cyclone data set, the lightning data set, and the temperature data set in time series. Delete the data with null values after the temperature data set, and unify the time format of the tropical cyclone data set, the lightning data set and the temperature data set into: hour-minute-second.
步骤S2，筛选距离深圳气象站1000km范围内的热带气旋，按热带气旋等级进行分组，并统计每小时内深圳地区发生的闪电数。具体而言：Step S2, screen the tropical cyclones within 1000km from the Shenzhen Meteorological Station, group them according to the level of the tropical cyclones, and count the number of lightnings that occurred in the Shenzhen area per hour. in particular:
由于距离太远的热带气旋对深圳地区影响较弱，所以本实施例选取距离深圳气象站1000km范围内的热带气旋。根据深圳气象站的经纬度坐标和热带气旋的经纬度坐标计算两者的地理空间距离。根据热带气旋生命史的不同强度，即热带低压(tropical depression,TD)、热带风暴(tropical storm,TS)、强热带风暴(severe tropical storm,STS)、台风(typhoon,TY)、强台风(severe typhoon,Since the tropical cyclones that are too far away have a weak impact on the Shenzhen area, this embodiment selects the tropical cyclones within 1000km from the Shenzhen weather station. According to the latitude and longitude coordinates of the Shenzhen meteorological station and the latitude and longitude coordinates of the tropical cyclone, the geographical space distance between the two is calculated. According to the different intensities of the life history of tropical cyclones, namely tropical depression (tropical depression, TD), tropical storm (tropical storm, TS), severe tropical storm (severe tropical storm, STS), typhoon (typhoon, TY), severe typhoon (severe typhoon) typhoon,
STY)、超强台风(super typhoon,Super TY)进行分组。由于超强台风和强台风样本数相对于其他强度类别的热带气旋要少一些，所以本实施例将超强台风和强台风合并为一类，将其命名为SSTY。最终得到五类不同等级的热带气旋数据集。STY) and super typhoon (Super TY). Since the number of samples of super typhoon and strong typhoon is less than that of tropical cyclones of other intensity categories, this embodiment combines super typhoon and strong typhoon into one category and names it SSTY. Finally, five types of tropical cyclone datasets of different grades were obtained.
地理空间距离计算公式如下：The formula for calculating the geospatial distance is as follows:
其中，S是地球上两点间距离(km)；R是地球的半径(km)；L
1和
是A点的经度和纬度，L
2和
是B点的经度和纬度。
Among them, S is the distance between two points on the earth (km); R is the radius of the earth (km); L 1 and are the longitude and latitude of point A, L2 and are the longitude and latitude of point B.
由于所述闪电数据集不只是位于深圳的闪电，故需要筛选出只位于深圳地区的闪电。根据闪电发生时的经纬度坐标来逐一判断该闪电是否位于深圳地区。对筛选后的数据集做逐时统计，即分为：0:00-1:00，1:00-2:00…23:00-24:00等24个时次(北京时)，统计每小时内深圳地区的闪电总数。Since the lightning data set is not limited to the lightning located in Shenzhen, it is necessary to filter out the lightning located only in the Shenzhen area. According to the longitude and latitude coordinates when the lightning occurs, it is judged one by one whether the lightning is located in the Shenzhen area. Make hourly statistics on the filtered data set, which is divided into 24 hours (Beijing time) such as: 0:00-1:00, 1:00-2:00...23:00-24:00 (Beijing time). The total number of lightning strikes in the Shenzhen area within an hour.
步骤S3，按时间序列分别合并热带气旋数据集和闪电数据集、热带气旋数据集和温度数据集。具体而言：Step S3, merging the tropical cyclone data set and the lightning data set, the tropical cyclone data set and the temperature data set respectively in time series. in particular:
将处理后的热带气旋数据集和闪电数据集根据时间序列进行合并，得到该时刻下热带气旋的等级、经纬度坐标及一小时内深圳地区发生的闪电总数。The processed tropical cyclone data set and lightning data set were merged according to the time series to obtain the level of tropical cyclone, latitude and longitude coordinates and the total number of lightning in Shenzhen within one hour at that moment.
将处理后的热带气旋数据集和温度数据集根据时间序列进行合并，得到该时刻下热带气旋的等级、经纬度坐标及同时刻深圳地区的温度。The processed tropical cyclone data set and temperature data set were merged according to the time series to obtain the grade, latitude and longitude coordinates of the tropical cyclone and the temperature in Shenzhen at the same time.
步骤S4，根据已有数据用反距离权重法进行插值，得到热带气旋影响下深圳地区的闪电空间分布图和温度空间分布图。In step S4, interpolation is performed with the inverse distance weighting method based on the existing data to obtain the lightning spatial distribution map and temperature spatial distribution map in Shenzhen under the influence of tropical cyclones.
反距离权重法假设所有的已知点对于预测点的值都会有一定作用，任意一个已知点的值对预测点值的作用与距离有关。已知点距离预测点越近作用越大，距离越远作用越小。The inverse distance weighting method assumes that all known points will have a certain effect on the value of the predicted point, and the effect of the value of any known point on the value of the predicted point is related to the distance. The closer the known point is to the predicted point, the greater the effect, and the farther the distance, the smaller the effect.
在估计预测点数值时，假设距离估计预测点最近的N个已知点对该预测点有作用，则所述N个已知点对预测点的作用和它们之间的距离成反比。距离预测点更近的已知点的权重更大，所有已知点的权重和为1。When estimating the value of the predicted point, it is assumed that the N known points closest to the estimated predicted point have an effect on the predicted point, and the effect of the N known points on the predicted point is inversely proportional to the distance between them. The weight of known points closer to the predicted point is greater, and the weight sum of all known points is 1.
根据已得到的数据，即热带气旋等级、热带气旋经纬度坐标、该热带气旋发生一小时内深圳地区的闪电总数，用反距离权重法进行插值得到热带气旋影响下深圳地区的闪电空间分布图(请参阅图2)。根据热带气旋等级、热带气旋经纬度坐标、该热带气旋发生时刻深圳地区的温度，用反距离权重法进行插值得到热带气旋影响下深圳地区的温度空间分布图(请参阅图3)。According to the obtained data, that is, the grade of tropical cyclone, the latitude and longitude coordinates of tropical cyclone, and the total number of lightning in Shenzhen area within one hour of the occurrence of the tropical cyclone, the spatial distribution map of lightning in Shenzhen area under the influence of tropical cyclone is obtained by interpolating with the inverse distance weight method (please See Figure 2). According to the tropical cyclone level, the latitude and longitude coordinates of the tropical cyclone, and the temperature in Shenzhen when the tropical cyclone occurred, the inverse distance weighting method was used to interpolate to obtain the temperature spatial distribution map of the Shenzhen area under the influence of the tropical cyclone (see Figure 3).
步骤S5，读取所述闪电空间分布图中每0.1*0.1格点的数据和所述温度空间分布图中每0.1*0.1格点的数据，并计算得到闪电与温度的相关性。Step S5, read the data of every 0.1*0.1 grid point in the lightning spatial distribution map and the data of every 0.1*0.1 grid point in the temperature spatial distribution map, and calculate the correlation between lightning and temperature.
在本实施例中，图2、图3中每0.1°×0.1°的格点存在一个值，则可以计算热带气旋影响下深圳地区闪电和温度的空间相关性。例如图2(e)等级为TD的热带气旋闪电空间分布图范围为104.6°E-123.7°E、13.6°N-30.8°N中每0.1°×0.1°的格点都有一个值，表示该点深圳地区闪电的次数。同样读取图3(e)等级为TD的热带气旋温度空间分布图范围为104.6°E-123.7°E、13.6°N-30.8°N中每0.1°×0.1°格点的值，表示该点深圳地区的温度。如此计算得到热带气旋期间深圳地区闪电与温度的相关性，如表1所示。In this embodiment, there is a value for each grid point of 0.1°×0.1° in Fig. 2 and Fig. 3 , then the spatial correlation between lightning and temperature in Shenzhen under the influence of tropical cyclones can be calculated. For example, in Fig. 2(e), the spatial distribution map of tropical cyclone lightning with grade TD has a value for each grid point of 0.1°×0.1° in 104.6°E-123.7°E and 13.6°N-30.8°N, indicating that the The number of lightning strikes in the Shenzhen area. Also read the value of each 0.1°×0.1° grid point in the temperature spatial distribution map of the tropical cyclone whose grade is TD in Figure 3(e) ranges from 104.6°E-123.7°E and 13.6°N-30.8°N, indicating the point temperature in Shenzhen. In this way, the correlation between lightning and temperature in Shenzhen during tropical cyclones is obtained, as shown in Table 1.
表1热带气旋影响下深圳闪电和温度的相关性Table 1 Correlation between lightning and temperature in Shenzhen under the influence of tropical cyclone
参阅图4所示，是本发明热带气旋影响下特定区域闪电与温度相关性的计 算系统10的硬件架构图。该系统包括：识别模块101、分组模块102、合并模块103、插值模块104以及相关性模块105。其中：Referring to Fig. 4, it is a hardware architecture diagram of the calculation system 10 for the correlation between lightning and temperature in a specific area under the influence of tropical cyclones of the present invention. The system includes: an identification module 101 , a grouping module 102 , a combining module 103 , an interpolation module 104 and a correlation module 105 . in:
所述识别模块101用于按时间序列分批读入热带气旋数据集、闪电数据集和温度数据集，识别所述热带气旋数据集、闪电数据集和温度数据集中的异常数据，并进行替代或删除；The identification module 101 is used to read in batches of tropical cyclone data sets, lightning data sets and temperature data sets in time series, identify abnormal data in the tropical cyclone data sets, lightning data sets and temperature data sets, and replace or delete;
所述分组模块102用于筛选距离特定区域一定范围内的热带气旋，按热带气旋等级进行分组，并统计每小时内特定区域发生的闪电数；The grouping module 102 is used to filter tropical cyclones within a certain range from a specific area, group them according to the level of the tropical cyclone, and count the number of lightnings that occur in a specific area per hour;
所述合并模块103用于将处理后的热带气旋数据集和闪电数据集根据时间序列进行合并，得到该时刻下热带气旋的等级、经纬度坐标及一小时内特定区域发生的闪电总数；以及The merging module 103 is used to merge the processed tropical cyclone data set and the lightning data set according to the time series to obtain the level of the tropical cyclone at this moment, the latitude and longitude coordinates and the total number of lightning in a specific area within one hour; and
将处理后的热带气旋数据集和温度数据集根据时间序列进行合并，得到该时刻下热带气旋的等级、经纬度坐标及同时刻特定区域的温度；Merge the processed tropical cyclone data set and temperature data set according to the time series to obtain the level of tropical cyclone, latitude and longitude coordinates and the temperature of a specific area at the same time;
所述插值模块104用于根据热带气旋等级、热带气旋经纬度坐标、该热带气旋发生一小时内特定区域发生的闪电数，利用反距离权重法进行插值，得到热带气旋影响下特定区域的闪电空间分布图；根据热带气旋等级、热带气旋经纬度坐标、该热带气旋发生时刻特定区域的温度，用反距离权重法进行插值得到热带气旋影响下特定区域的温度空间分布图；The interpolation module 104 is used to perform interpolation using the inverse distance weighting method according to the level of the tropical cyclone, the latitude and longitude coordinates of the tropical cyclone, and the number of lightnings that occurred in a specific area within one hour of the occurrence of the tropical cyclone, so as to obtain the spatial distribution of lightning in a specific area under the influence of the tropical cyclone Figure: According to the tropical cyclone level, the latitude and longitude coordinates of the tropical cyclone, and the temperature of the specific area at the time when the tropical cyclone occurs, the inverse distance weighting method is used to interpolate to obtain the temperature spatial distribution map of the specific area under the influence of the tropical cyclone;
所述相关性模块105用于读取所述闪电空间分布图中的数据和所述温度空间分布图中的数据，并计算得到所述特定区域闪电与温度的相关性。The correlation module 105 is used to read the data in the lightning spatial distribution map and the data in the temperature spatial distribution map, and calculate the correlation between lightning and temperature in the specific area.
对所公开的实施例的上述说明，使本领域专业技术人员能够实现或使用本发明。对这些实施例的多种修改对本领域的专业技术人员来说将是显而易见的，本发明中所定义的一般原理可以在不脱离本发明的精神或范围的情况下，在其它实施例中实现。因此，本发明将不会被限制于本发明所示的这些实施例，而是要符合与本发明所公开的原理和新颖特点相一致的最宽的范围。The above description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined in this invention may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention will not be limited to these embodiments shown in the present invention, but will conform to the widest scope consistent with the principles and novel features disclosed in the present invention.
Claims (10)
- 一种热带气旋影响下特定区域闪电与温度相关性的计算方法，其特征在于，该方法包括如下步骤：A method for calculating the correlation between lightning and temperature in a specific area under the influence of a tropical cyclone, characterized in that the method includes the following steps:a.按时间序列分批读入热带气旋数据集、闪电数据集和温度数据集，识别所述热带气旋数据集、闪电数据集和温度数据集中的异常数据，并进行替代或删除；a. Read in batches of tropical cyclone data sets, lightning data sets and temperature data sets according to time series, identify abnormal data in the tropical cyclone data sets, lightning data sets and temperature data sets, and replace or delete them;b.筛选距离特定区域一定范围内的热带气旋，按热带气旋等级进行分组，并统计每小时内特定区域发生的闪电数；b. Screen the tropical cyclones within a certain range from a specific area, group them according to the level of tropical cyclones, and count the number of lightning that occurs in a specific area per hour;c.将处理后的热带气旋数据集和闪电数据集根据时间序列进行合并，得到该时刻下热带气旋的等级、经纬度坐标及一小时内特定区域发生的闪电总数；c. Merge the processed tropical cyclone data set and lightning data set according to the time series to obtain the level of tropical cyclone, latitude and longitude coordinates and the total number of lightning in a specific area within one hour at that moment;将处理后的热带气旋数据集和温度数据集根据时间序列进行合并，得到该时刻下热带气旋的等级、经纬度坐标及同时刻特定区域的温度；Merge the processed tropical cyclone data set and temperature data set according to the time series to obtain the level of tropical cyclone, latitude and longitude coordinates and the temperature of a specific area at the same time;d.根据热带气旋等级、热带气旋经纬度坐标、该热带气旋发生一小时内特定区域发生的闪电数，利用反距离权重法进行插值，得到热带气旋影响下特定区域的闪电空间分布图；根据热带气旋等级、热带气旋经纬度坐标、该热带气旋发生时刻特定区域的温度，用反距离权重法进行插值得到热带气旋影响下特定区域的温度空间分布图；d. According to the tropical cyclone level, the latitude and longitude coordinates of the tropical cyclone, and the number of lightning that occurred in a specific area within one hour of the tropical cyclone, use the inverse distance weighting method to interpolate to obtain the lightning spatial distribution map of the specific area under the influence of the tropical cyclone; according to the tropical cyclone Level, latitude and longitude coordinates of tropical cyclones, temperature in a specific area at the moment of occurrence of the tropical cyclone, interpolated with the inverse distance weighting method to obtain a temperature spatial distribution map of a specific area under the influence of the tropical cyclone;e.读取所述闪电空间分布图中的数据和所述温度空间分布图中的数据，并计算得到所述特定区域闪电与温度的相关性。e. Read the data in the lightning spatial distribution map and the data in the temperature spatial distribution map, and calculate the correlation between lightning and temperature in the specific area.
- 如权利要求1所述的方法，其特征在于，所述的步骤a包括：The method according to claim 1, wherein said step a comprises:按时间序列读取所述热带气旋数据集、闪电数据集和温度数据集后对存在空值的数据进行删除，并将所述热带气旋数据集、闪电数据集和温度数据集的时间格式统一为：时-分-秒。After reading the tropical cyclone data set, lightning data set and temperature data set in time series, the data with null values is deleted, and the time format of the tropical cyclone data set, lightning data set and temperature data set is unified as :Minutes and seconds.
- 如权利要求2所述的方法，其特征在于，所述的步骤b包括：The method according to claim 2, wherein said step b comprises:根据所述特定区域的经纬度坐标和热带气旋的经纬度坐标，计算所述特定区域与热带气旋之间的地理空间距离；calculating the geospatial distance between the specific area and the tropical cyclone according to the latitude and longitude coordinates of the specific area and the latitude and longitude coordinates of the tropical cyclone;根据热带气旋等级，即热带低压、热带风暴、强热带风暴、台风、强台风、超强台风进行分组；According to the level of tropical cyclone, namely tropical depression, tropical storm, severe tropical storm, typhoon, strong typhoon, super typhoon;由于超强台风和强台风样本数相对于其他强度类别的热带气旋要少一些，故将超强台风和强台风合并为一类，将其命名为SSTY，最终得到五类不同等级的热带气旋数据集。Since the number of samples of super typhoon and strong typhoon is less than that of tropical cyclones of other intensity categories, super typhoon and strong typhoon are combined into one category, named SSTY, and finally five types of tropical cyclone data of different levels are obtained set.
- 如权利要求3所述的方法，其特征在于：The method of claim 3, characterized in that:所述地理空间距离通过如下计算公式得到：The geographical space distance is obtained by the following calculation formula:
其中，S是地球上两点间距离；R是地球的半径；L 1和是A点的经度和纬度，L 2和
是B点的经度和纬度。 Among them, S is the distance between two points on the earth; R is the radius of the earth; L 1 and
are the longitude and latitude of point A, L2 andare the longitude and latitude of point B. - 如权利要求4所述的方法，其特征在于，所述的步骤b还包括：The method according to claim 4, wherein said step b further comprises:根据闪电发生时的经纬度坐标来逐一判断该闪电是否位于所述特定区域；Judging whether the lightning is located in the specific area one by one according to the latitude and longitude coordinates when the lightning occurs;对筛选后的数据集做逐时统计，即分为：0:00-1:00，1:00-2:00…23:00-24:00二十四个时次，统计每小时内所述特定区域的闪电总数。Make hourly statistics on the filtered data set, which is divided into twenty-four hours: 0:00-1:00, 1:00-2:00...23:00-24:00, and count all The total number of lightning bolts in the specified area.
- 如权利要求5所述的方法，其特征在于，所述的步骤d包括：The method according to claim 5, wherein said step d comprises:在估计预测点数值时，假设距离估计预测点最近的N个已知点对该预测点有作用，则所述N个已知点对预测点的作用和它们之间的距离成反比，距离预测点更近的已知点的权重更大，所有已知点的权重和为1。When estimating the value of the predicted point, assuming that the N known points closest to the estimated predicted point have an effect on the predicted point, the effect of the N known points on the predicted point is inversely proportional to the distance between them, and the distance predicted The weight of known points closer to the point is greater, and the weight sum of all known points is 1.
- 如权利要求6所述的方法，其特征在于，所述的步骤d还包括：The method according to claim 6, wherein said step d further comprises:根据已得到的数据，即热带气旋等级、热带气旋经纬度坐标、该热带气旋发生一小时内所述特定区域的闪电总数，利用反距离权重法进行插值得到热带气旋影响下特定区域的闪电空间分布图。According to the obtained data, that is, the grade of tropical cyclone, the latitude and longitude coordinates of tropical cyclone, the total number of lightning in the specific area within one hour of the occurrence of the tropical cyclone, the lightning space distribution map of the specific area under the influence of the tropical cyclone is obtained by interpolation using the inverse distance weight method .
- 如权利要求7所述的方法，其特征在于，所述的步骤d还包括：The method according to claim 7, wherein said step d further comprises:根据热带气旋等级、热带气旋经纬度坐标、该热带气旋发生时刻特定区域的温度，用反距离权重法进行插值得到热带气旋影响下特定区域的温度空间分布图。According to the tropical cyclone level, the latitude and longitude coordinates of the tropical cyclone, and the temperature of the specific area at the time when the tropical cyclone occurs, the inverse distance weighting method is used to interpolate to obtain the temperature spatial distribution map of the specific area under the influence of the tropical cyclone.
- 如权利要求8所述的方法，其特征在于，所述的步骤e具体包括：The method according to claim 8, wherein said step e specifically comprises:根据所述闪电空间分布图中每0.1*0.1格点存在的值和所述温度空间分布图中每0.1*0.1格点存在的值，计算得到热带气旋影响下特定区域闪电和温度的空间相关性。According to the value existing at every 0.1*0.1 grid point in the lightning spatial distribution map and the value at every 0.1*0.1 grid point in the temperature spatial distribution map, the spatial correlation between lightning and temperature in a specific area under the influence of tropical cyclones is calculated .
- 一种热带气旋影响下特定区域闪电与温度相关性的计算系统，其特征在于，该系统包括识别模块、分组模块、合并模块、插值模块以及相关性模块，其中：A calculation system for the correlation between lightning and temperature in a specific area under the influence of a tropical cyclone is characterized in that the system includes an identification module, a grouping module, a merging module, an interpolation module and a correlation module, wherein:所述识别模块用于按时间序列分批读入热带气旋数据集、闪电数据集和温度数据集，识别所述热带气旋数据集、闪电数据集和温度数据集中的异常数据，并进行替代或删除；The identification module is used to read in batches of tropical cyclone data sets, lightning data sets and temperature data sets according to time series, identify abnormal data in the tropical cyclone data sets, lightning data sets and temperature data sets, and replace or delete them ;所述分组模块用于筛选距离特定区域一定范围内的热带气旋，按热带气旋等级进行分组，并统计每小时内特定区域发生的闪电数；The grouping module is used to screen tropical cyclones within a certain range from a specific area, group them according to the level of the tropical cyclone, and count the number of lightnings that occur in a specific area per hour;所述合并模块用于将处理后的热带气旋数据集和闪电数据集根据时间序列进行合并，得到该时刻下热带气旋的等级、经纬度坐标及一小时内特定区域发生的闪电总数；以及The merging module is used to merge the processed tropical cyclone data set and the lightning data set according to the time series to obtain the level of the tropical cyclone at this moment, the latitude and longitude coordinates and the total number of lightning in a specific area within one hour; and将处理后的热带气旋数据集和温度数据集根据时间序列进行合并，得到该时刻下热带气旋的等级、经纬度坐标及同时刻特定区域的温度；Merge the processed tropical cyclone data set and temperature data set according to the time series to obtain the level of tropical cyclone, latitude and longitude coordinates and the temperature of a specific area at the same time;所述插值模块用于根据热带气旋等级、热带气旋经纬度坐标、该热带气旋发生一小时内特定区域发生的闪电数，利用反距离权重法进行插值，得到热带气旋影响下特定区域的闪电空间分布图；根据热带气旋等级、热带气旋经纬度坐标、该热带气旋发生时刻特定区域的温度，用反距离权重法进行插值得到热带气旋影响下特定区域的温度空间分布图；The interpolation module is used to perform interpolation using the inverse distance weighting method according to the tropical cyclone level, the latitude and longitude coordinates of the tropical cyclone, and the number of lightnings that occurred in a specific area within one hour of the occurrence of the tropical cyclone, so as to obtain the spatial distribution map of lightning in a specific area under the influence of the tropical cyclone ;According to the tropical cyclone level, the latitude and longitude coordinates of the tropical cyclone, and the temperature of the specific area at the time when the tropical cyclone occurs, the inverse distance weighting method is used to interpolate to obtain the temperature spatial distribution map of the specific area under the influence of the tropical cyclone;所述相关性模块用于读取所述闪电空间分布图中的数据和所述温度空间分布图中的数据，并计算得到所述特定区域闪电与温度的相关性。The correlation module is used to read the data in the lightning spatial distribution map and the data in the temperature spatial distribution map, and calculate the correlation between lightning and temperature in the specific area.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003302479A (en) * | 2002-02-08 | 2003-10-24 | Kyushu Electric Power Co Inc | Method and device for predicting wind velocity of tropical cyclone |
| CN106447126A (en) * | 2016-10-20 | 2017-02-22 | 中国科学院深圳先进技术研究院 | Determining and forecasting methods and determining and forecasting systems for visibility change, caused by tropical cyclone, in coastal area |
| JP2019138737A (en) * | 2018-02-08 | 2019-08-22 | 国立研究開発法人防災科学技術研究所 | Thunder risk determination device |
| CN111897030A (en) * | 2020-07-17 | 2020-11-06 | 国网电力科学研究院有限公司 | Thunderstorm early warning system and method |
-
2022
- 2022-02-19 WO PCT/CN2022/076976 patent/WO2023155179A1/en unknown
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003302479A (en) * | 2002-02-08 | 2003-10-24 | Kyushu Electric Power Co Inc | Method and device for predicting wind velocity of tropical cyclone |
| CN106447126A (en) * | 2016-10-20 | 2017-02-22 | 中国科学院深圳先进技术研究院 | Determining and forecasting methods and determining and forecasting systems for visibility change, caused by tropical cyclone, in coastal area |
| JP2019138737A (en) * | 2018-02-08 | 2019-08-22 | 国立研究開発法人防災科学技術研究所 | Thunder risk determination device |
| CN111897030A (en) * | 2020-07-17 | 2020-11-06 | 国网电力科学研究院有限公司 | Thunderstorm early warning system and method |
Non-Patent Citations (1)
| Title |
|---|
| TENG-FEI ZHANG, DUAN XU, ZHANG JIE, YIN LI-YUN, LIU LE: "CHARACTERISTCS OF LIGHTNING AND RADAR ECHOES AND RELATIONS BETWEEN THEM FOR STRONG CONVECTIVE RAINSTROM IN YUNNAN", JOURNAL OF TROPICAL METEOROLOGY, 云南省气象台,云南昆明,650034%云南省气象科学研究所,云南昆明,650034, vol. 27, no. 3, 15 June 2011 (2011-06-15), pages 379 - 386, XP093085208, ISSN: 1004-4965, DOI: 10.3969/j.issn.1004-4965.2011.03.011 * |
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