# Classification of Tropical Cyclone Tracks in the Northwest Pacific Based on the SD-K-Means Model
## 5 Conclusions  
This study proposes an improved SD-K-Means clustering model for the classification of TC tracks. Using TC track data from 2000 to 2022, the model integrates key track characteristics such as movement speed and directional changes, thereby enhancing its capability to describe track morphology and improving the rationality of the clustering results. Experimental comparisons demonstrate that the proposed method outperforms traditional K-Means, DTW-K-Means, and DBSCAN algorithms in terms of mainstream evaluation metrics, including the CH index and DBI, verifying its effectiveness and superiority in TC track pattern recognition. Based on the optimal clustering results, the characteristics of different TC clusters were further analyzed, leading to the following main conclusions:  
1. Track Typology: TCs were classified into four distinct clusters--those turning near the east of China and those generated in the NWP and landing in Hainan, those moving straight in the northeast and those generated in the SCS and landing in Hainan, and those turning and those of a few. These clusters show clear differences in spatial activity ranges, intensity levels, seasonal activity, and landfall characteristics.
2. Intensity and Destructiveness: TCs in Clusters 1 and 2 exhibit higher intensities, with over 50% reaching level 6 or above. Notably, Cluster 2 contains no TCs below level 4 and exhibits the highest potential destructiveness, followed closely by Cluster 1. The average Power Dissipation Index (PDI) values of these two clusters are close, whereas Cluster 3 has the weakest intensity and lowest destructiveness.
3. Seasonal Patterns: Although TCs can form in all 12 months of the year, peak activity occurs between July and October. Cluster 3 shows minimal formation from January to March, and Cluster 1 exhibits unusually low activity in September--possibly linked to environmental conditions during that period.
4. Landfall Distribution: Cluster 0 accounts for the highest proportion of landfalling TCs in more than 72.7% of the years, with most making landfall along China's eastern coastal provinces. Cluster 3 ranks second in landfall frequency and primarily affects southeastern coastal areas such as Hainan and Guangdong. In contrast, Clusters 1 and 2 contribute relatively fewer landfalls.
5. Hainan-Focused Analysis: All TCs making landfall in Hainan belong to either Cluster 0 or Cluster 3. Those originating in the NWP are almost exclusively classified into Cluster 0, while those formed in the SCS fall into Cluster 3. The two exceptions from the Northwest Pacific initially exhibited weak intensity and minimal destructive power, but strengthened significantly after entering the SCS. Compared with SCS-originating TCs, those from the NWP that make landfall in Hainan generally have longer lifespans, longer development tracks, stronger intensities, and longer durations of high intensity.  
This study focuses on the NWP region, but future research can expand the spatial scope to include other ocean basins worldwide. Moreover, the current seasonal analysis does not account for the influence of large-scale climatic phenomena such as the El Nino-Southern Oscillation (ENSO). Future studies should incorporate ENSO phases--including El Nino, La Nina, and neutral conditions--to better understand their impact on TC formation and seasonal distribution.  
Conceptualization, N.X.; methodology, N.X.; validation, N.X. and B.Y.; writing--original draft preparation, N.X.; writing--proofreading, N.X. and B.Y.; writing--review and editing, [PERSON]; visualization, N.X.; project administration, J.R.; funding acquisition, J.R. All authors have read and agreed to the published version of the manuscript.  
This work is supported by the National Natural Science Foundation of China (62262016, 62302132), 14 th Five-Year Plan Civil Aerospace Technology Preliminary Research Project (D040405).