Reconstruction of Japan's Cold-Season Climate in the Past Few Hundred Years Using High-Resolution Multi-Proxy

To understand the climate conditions in Japan before the commencement of modern official meteorological observations, it is necessary to indirectly estimate them using proxy data that serve as climate indicators.In Japan, there is a nearly continuous annual dataset of Lake Suwa's freezing records spanning over 580 years. Furthermore, diaries from various parts of Japan contain daily weather records. By utilizing these records, daily climate data with the minimum temporal resolution can be obtained. By leveraging these proxies, it is possible to reconstruct the climate of the cold season, which has been previously less understood, across various temporal and spatial scales.The objective of this study is to reconstruct the changes in cold-season climate in Japan over the past several hundred years with high temporal resolution.The proxy data currently used include: lake and terrestrial sediments (Lake Suwa, approximately 1000 years), records of cherry blossom flowering and full bloom dates primarily collected in Kyoto (approximately 1000 years), tree rings (approximately 300 years), daily weather records from diaries (approximately 200 years), freezing records of Lake Suwa and Lake Jusan (approximately 580 and 150 years, respectively), early-meteorological observation data (approximately 50 years), and Japan Meteorological Agency observation data (approximately 150 years).Firstly, the most extensive dataset, the cherry blossom flowering data, is used as a reference. Next, proxy variables are standardized after removing trends caused by human activities. Subsequently, regression analysis is performed for each period where variations either coincide or do not coincide. Furthermore, for each proxy variable, spatial correlations were calculated using 20th-century meteorological observation data to identify the regions represented by that proxy variable.(This research was funded by JSPS Grant-in-Aid for Scientific Research (24H00118).