EMS Annual Meeting Abstracts
Vol. 20, EMS2023-586, 2023, updated on 06 Jul 2023
https://doi.org/10.5194/ems2023-586
EMS Annual Meeting 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Digitization and reconstruction of typhoon along the southern coastal regions in Qing China

Qing Pei
Qing Pei
  • Education University of Hong Kong, Department of Social Sciences, Hong Kong (qingpei@eduhk.hk)

During the Qing Dynasty (1644–1911AD), there were more migrants toward southern coastal China, which contributed to the enough records for empirical analysis. In the meantime, the Qing period of China overlapped with Little Ice Age (LIA, 1400–1900AD), a period of abnormal climate with prolonged cooling and persistent hydroclimatic anomalies. Therefore, under this climatic background, the work to reconstruct the typhoon in southern coastal China will help to understand the linkage between natural disasters and abnormal climatic conditions, which has been insufficiently examined so far. 

To reconstruct the typhoon along the southern coastal regions in Qing China, both narrative and quantitative methods will be used. Based on the content of records, the typhoon occurrence will be identified. Furthermore, the consequence of typhoon event will be used to identify the strength of typhoon. Then, the occurrence and strength of past typhoon will be digitized and reconstructed based on the historical records. According to the digitized information, statistical methods and Geographic Information System (GIS) will enable spatiotemporal analysis on those numerical datasets.  

I will finally discuss the possibility to adopt a digitization approach for typhoon reconstruction. Current methods usually make use of natural archives/proxies and thus cannot fully consider the special features of archives of societies, although environmental studies should be guided by humanities. Therefore, I would like to develop some new digitization methods, such as text recognition methods to digitize the descriptive content of historical records into numerical data. It is thus a promising and innovative attempt to adopt a Machine Learning approach to recognize, digitize, and quantify the historical records, including the occurrence, duration, and severity of typhoon. 

How to cite: Pei, Q.: Digitization and reconstruction of typhoon along the southern coastal regions in Qing China, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-586, https://doi.org/10.5194/ems2023-586, 2023.