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Historical Typhoon Search Engine Based on Track Similarity

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Historical Typhoon Search Engine Based on Track Similarity

Meng-Han Tsai et al. Int J Environ Res Public Health.

Abstract

The potential effect of a typhoon track on the extent of damage makes the track a critical factor during the emergency response phase. Historical typhoon data may provide information for decision makers to anticipate the impact of an upcoming typhoon and develop prevention strategies to reduce the damage. In our preliminary work, we proposed a track similarity algorithm and implemented a real-time search engine for past typhoon events. However, the proposed algorithm was not discussed thoroughly in the preliminary work, and the great number of historical typhoon track records slowed down the similarity calculations. In addition, the tool did not feature the option of automatically importing upcoming typhoon track predictions. This research introduces the assumption of the recentness dominance principle (RDP), explores the details of the track similarity algorithm of the preliminary work, completes the discussion of parameter setting, and developed a method to improve the efficiency of the similarity calculation. In this research, we implemented the proposed advanced methodology by developing a new information display panel featuring the ability to auto-import forecast data. The results of this study provide decision makers and the public with a concise and handy search engine for searching similar historical typhoon records.

Keywords: decision support; search engine; typhoon track similarity; user interface design.

Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
An example of the tracks of Typhoon Morakot (2009) and Typhoon Haitang (2005).
Figure 2
Figure 2
An example of two typhoon tracks for the similarity comparison demonstrating increased complexity over the example in Figure 1.
Figure 3
Figure 3
Visualization of the relationship between M and global recentness dominance time weighting (gRDW).
Figure 4
Figure 4
A sample of the Japan Meteorological Agency (JMA) best track data.
Figure 5
Figure 5
The information display panel.
Figure 6
Figure 6
The query result using Typhoon Hagibis (2019).
Figure 7
Figure 7
An example of the case of repulsion force weighting.

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References

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