In this paper,the clustering analysis is applied to the satellite image segmentation,and a cloud-based thunderstorm cloud recognition method is proposed in combination with the strong cloud computing power.The method ...In this paper,the clustering analysis is applied to the satellite image segmentation,and a cloud-based thunderstorm cloud recognition method is proposed in combination with the strong cloud computing power.The method firstly adopts the fuzzy C-means clustering(FCM)to obtain the satellite cloud image segmentation.Secondly,in the cloud image,we dispose the‘high-density connected’pixels in the same cloud clusters and the‘low-density connected’pixels in different cloud clusters.Therefore,we apply the DBSCAN algorithm to the cloud image obtained in the first step to realize cloud cluster knowledge.Finally,using the method of spectral threshold recognition and texture feature recognition in the steps of cloud clusters,thunderstorm cloud clusters are quickly and accurately identified.The experimental results show that cluster analysis has high research and application value in the segmentation processing of meteorological satellite cloud images.展开更多
The LS-SVM(Least squares support vector machine) method is presented to set up a model to forecast the occurrence of thunderstorms in the Nanjing area by combining NCEP FNL Operational Global Analysis data on 1.0°...The LS-SVM(Least squares support vector machine) method is presented to set up a model to forecast the occurrence of thunderstorms in the Nanjing area by combining NCEP FNL Operational Global Analysis data on 1.0°×1.0° grids and cloud-to-ground lightning data observed with a lightning location system in Jiangsu province during 2007-2008.A dataset with 642 samples,including 195 thunderstorm samples and 447 non-thunderstorm samples,are randomly divided into two groups,one(having 386 samples) for modeling and the rest for independent verification.The predictors are atmospheric instability parameters which can be obtained from the NCEP data and the predictand is the occurrence of thunderstorms observed by the lightning location system.Preliminary applications to the independent samples for a 6-hour forecast of thunderstorm events show that the prediction correction rate of this model is 78.26%,false alarm rate is 21.74%,and forecasting technical score is 0.61,all better than those from either linear regression or artificial neural network.展开更多
The electrical characteristics of thunderstorms in three different altitude regions of the Chinese inland plateau have been analyzed in this paper. The results show, according to the polarity of the surface electric ...The electrical characteristics of thunderstorms in three different altitude regions of the Chinese inland plateau have been analyzed in this paper. The results show, according to the polarity of the surface electric （E） field, that the thunderstorms can be divided into two categories in the study regions： one showing the normal tripole electrical charge structure （normal-type）, and the other showing the special tripole charge structure with a larger-than-usual lower positive charge center （LPCC） at the base of thunderstorm （special-type）, where the induced surface E field is controlled by the LPCC when a thunderstorm is overhead. We find that the two types of thunderstorms have different occurrences in different regions, and the percentage of special-type thunderstorms increases with the altitude. On the whole, the flash rate of thunderstorms is quite low, and the mean value is about 1-3 fl/min, while the flash rate of special-type is slightly greater than that of the normal-type thunderstorm. The statistical results of cloud-to-ground flash （CG） numbers indicate that the ratio of ＋CG flash increases with the altitude, with the value about 14.7 percent through 25.4 percent.展开更多
基金This work was supported in part by the National Natural Science Foundation of China(51679105,61672261,51409117)Jilin Province Department of Education Thirteen Five science and technology research projects[2016]No.432,[2017]No.JJKH20170804KJ.
文摘In this paper,the clustering analysis is applied to the satellite image segmentation,and a cloud-based thunderstorm cloud recognition method is proposed in combination with the strong cloud computing power.The method firstly adopts the fuzzy C-means clustering(FCM)to obtain the satellite cloud image segmentation.Secondly,in the cloud image,we dispose the‘high-density connected’pixels in the same cloud clusters and the‘low-density connected’pixels in different cloud clusters.Therefore,we apply the DBSCAN algorithm to the cloud image obtained in the first step to realize cloud cluster knowledge.Finally,using the method of spectral threshold recognition and texture feature recognition in the steps of cloud clusters,thunderstorm cloud clusters are quickly and accurately identified.The experimental results show that cluster analysis has high research and application value in the segmentation processing of meteorological satellite cloud images.
基金China Social Welfare Research Project (GYHY200806014)
文摘The LS-SVM(Least squares support vector machine) method is presented to set up a model to forecast the occurrence of thunderstorms in the Nanjing area by combining NCEP FNL Operational Global Analysis data on 1.0°×1.0° grids and cloud-to-ground lightning data observed with a lightning location system in Jiangsu province during 2007-2008.A dataset with 642 samples,including 195 thunderstorm samples and 447 non-thunderstorm samples,are randomly divided into two groups,one(having 386 samples) for modeling and the rest for independent verification.The predictors are atmospheric instability parameters which can be obtained from the NCEP data and the predictand is the occurrence of thunderstorms observed by the lightning location system.Preliminary applications to the independent samples for a 6-hour forecast of thunderstorm events show that the prediction correction rate of this model is 78.26%,false alarm rate is 21.74%,and forecasting technical score is 0.61,all better than those from either linear regression or artificial neural network.
基金supported by National Natural Science Foundation of China (Grant No. 40905001, 40775004)the Main Direction Program of the Knowledge Innovation of Chinese Academy of Sciences (Grant No.KZCX2-YW-206)
文摘The electrical characteristics of thunderstorms in three different altitude regions of the Chinese inland plateau have been analyzed in this paper. The results show, according to the polarity of the surface electric （E） field, that the thunderstorms can be divided into two categories in the study regions： one showing the normal tripole electrical charge structure （normal-type）, and the other showing the special tripole charge structure with a larger-than-usual lower positive charge center （LPCC） at the base of thunderstorm （special-type）, where the induced surface E field is controlled by the LPCC when a thunderstorm is overhead. We find that the two types of thunderstorms have different occurrences in different regions, and the percentage of special-type thunderstorms increases with the altitude. On the whole, the flash rate of thunderstorms is quite low, and the mean value is about 1-3 fl/min, while the flash rate of special-type is slightly greater than that of the normal-type thunderstorm. The statistical results of cloud-to-ground flash （CG） numbers indicate that the ratio of ＋CG flash increases with the altitude, with the value about 14.7 percent through 25.4 percent.
