Synergistic Integration of Detailed Meteorological and Community Information for Evacuation from Weather-Related Disasters: Proposal of a ‘‘Disaster Response Switch’’

作     者：Kensuke Takenouchi Katsuya Yamori Kensuke Takenouchi;Katsuya Yamori

作者机构：Disaster Prevention Research InstituteKyoto UniversityUji Kyoto 606-0011Japan 

出 版 物：《International Journal of Disaster Risk Science》 (国际灾害风险科学学报（英文版）)

年 卷 期：2020年第11卷第6期

页      面：762-775页

核心收录：

学科分类：07[理学] 070601[理学-气象学] 0706[理学-大气科学] 

基　　金：Japan Society for the Promotion of Science  JSPS  (20K20338) 

主　　题：Community disaster prevention Disaster response High-resolution forecasting model Japan Meteorological information Risk communication 

摘      要：Meteorological information used for disaster prevention has developed rapidly in terms of both type and *** latest forecasting models can predict weather with very high resolutions that can characterize disaster risk at the local ***,this development can lead to an overdependency on the information and a wait-and-see attitude by the *** the same time,residents share and use various types of information for disaster response,such as local conditions,in addition to official disaster *** research in Japan verified the practicality and efficiency of synergistically integrating these types of information by examining actual evacuation *** current numerical forecasting models sufficiently identify locality from the viewpoint of various administrative scales such as prefectures,municipalities,and school districts,but the improvements to these models have failed to improve residents’judgment in successful evacuation *** therefore analyzed the relationship between meteorological information and residents’disaster response and confirmed that they were strongly correlated and were contributing factors in preventing *** revealed differences between a community’s disaster prevention culture and the disaster information *** led us to propose a new concept in community disaster prevention that we call the‘‘disaster response switch,’’which can serve as a data-driven risk management tool for communities when used in combination with advanced meteorological disaster information.