Climate event classification based on historical meteorological records and its presentation on a Spatio-Temporal research platform

Climate change has become a serious issue, and tracing climate events from historical records could be a solution to find a way to deal with it. This study conducted two experiments for classifying metrological text data-one unsupervised method for exploring a solution in the lack of labeled data and another supervised method for achieving high-performance classification. Both experiments took the meteorological text records as material in the early Qing Dynasty (1644 C.E. to 1795 C.E.) from the REACHES database. We also integrated the classification results to develop a Spatio-Temporal research platform with an instant response front-end interface to help humanity researchers access and analyze data according to the three dimensions of time, area, and event categories. With our Spatio-Temporal research platform, we had the ability with ease to analyze the meteorological records during 1650 C.E. to 1700 C.E., the late stage of the Little Ice Age, to investigate the phenomenon of climate change in the Qing Dynasty of China. We will continue to expand the capacity of the database and establish a mature Spatio-Temporal research platform in the future.