Editorial: Risk Assessment and Resilience of Extreme Weatherinduced Disasters

Yanfang Sang^1*Lingling Shen²Xiya Zhang³Wentao Yang⁴

• ¹Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources (CAS), Beijing, China
• ²Beijing Meteorological Information Center, Beijing, China
• ³Institute of Urban Meteorology, China Meteorological Administration, Beijing, China
• ⁴University of Leeds, Leeds, United Kingdom

Extreme weather events include unexpected, unusual, severe, or unseasonal rainstorms, droughts, extreme temperatures and other types. They are important triggering factors causing diverse natural hazards, including mountain flash floods (Figure 1), landslides, debris flows, urban flooding and waterlogging, agro-meteorological hazards, etc (Field et al., 2012;Sang et al., 2018;Sajadi, et al., 2022;Ren et al., 2024;Shi, et al., 2024). Such extreme weather-induced hazards have become a significant global threat to sustainable socio-economic development. For instance, flooding generated by heavy rainstorms has become a serious "urban disease" in many cities worldwide, posing serious threat to the safety of people's lives and property and normal operation of cities (Yang et al., 2020). Under the impacts of climate change, the frequency and intensity of extreme weather events and related disasters would worsen (Stott, 2016). Thereby, it is vital to focus on risk assessment and resilience management of extreme weatherinduced disasters (Easterling et al., 2000), as a basis of policymaking and mitigation of natural disasters. It is just the motivation of proposing this Research Topic. In this Research Topic, researchers contributed their latest research findings related to useful methods and techniques for forecasting, early warning and risk assessment of extreme weather-induced disasters. Moreover, researchers also provided deep scientific propositions and improved understanding on the resilience and mitigation of extreme weather-induced disasters. They gave solid scientific contribution which would significantly promote the research of extreme weather-induced disasters.As guest editors, we would like to thank the authors who worked hard to submit very interesting articles for this Research Topic. Following valuable collaboration between the reviewers and authors, eight articles are covered in this SI, which are briefly summarized below.In the first paper "Objective identification and forecast method of PM2.5 pollution based on medium-and long-term ensemble forecasts in Beijing-Tianjin-Hebei region and its surrounding areas", Liu et al. developed an objective identification and forecast method for PM2.5 pollution (OIF-PM2.5) in Beijing-Tianjin-Hebei region and its surrounding areas. They reported that the observed PM2.5 pollution ratio increased with the aggravating PM2.5 pollution. Statistical results indicated that the OIF-PM2.5 method has a high reliability in forecasts with the leading forecasting period of 1-15 days.The second paper by Assi et al. is titled "Homeowner flood risk and risk reduction from home elevation between the limits of the 100-and 500-year floodplains". They proposed a systematic approach to predict flood risk for a single-family home using average annual loss in the shaded X Zone-the area immediately outside the Special Flood Hazard Area (i.e., the 500-year floodplain) in United States of America. The results enhanced understanding of flood risk and benefits of elevating homes above first-floor height in the shaded X Zone.The third paper "Gaps in the governance of floods, droughts, and heatwaves in the United Kingdom" is contributed by Carvalho and Spataru. They presented the current state of the art of the governance of floods, droughts, and heatwaves in the United Kingdom, with a focus on pre-emergency phases and the shortage of indicators for assessment of the effectiveness of adaptation for all three disasters. Gaps and challenges were discussed, and actions for the adaptation and resilience of three disasters were provided.In the fourth paper "Analysis of urban necessities reserve index and reserve quantity under emergency conditions", Jiang et al. concerned urban safety, and classified the emergency materials of urban necessities in Shanghai, by establishing a corresponding reserve list. To better handle emergencies, they gave countermeasures and suggestions: optimizing material structure of emergency reserves, managing material reserves at different levels, reasonably planning the amount of emergency materials, and reducing the cost of reserves and improving the efficiency of emergency reserves.The fifth paper "Sedimentary records of giant landslide-dam breach events in western Sichuan, China" is contributed by Ma et al. They did a detailed investigation of the large-scale landslide-dammed lake outburst deposits in two typical River Basins in West Sichuan Plateau, China. They found that the sedimentary characteristics of outburst deposits (ODs) explained the hydrodynamic changes during the propagation of outburst floods, as important records for distinguishing ODs and "normal" floods.The sixth paper by Liu et al. is titled "A comparative study of regional rainfall-induced landslide early warning models based on RF, CNN and MLP algorithms". They focused on Fujian Province, China, and proposed a four-step process for building a regional landslide early warning model based on machine learning. The process included data integration and cleaning, sample set construction, model training and validation, and practical application. This study can valuably support landslide disaster warning research.In the seventh paper "Construction and preliminary analysis of landslide database triggered by heavy storm in the parallel range-valley area of western Chongqing, China, on 8 June 2017", Liu and Xu identified the landslides disasters triggered by extreme rainfall events in the parallel range-valley area of western Chongqing, China, and established a historical landslide database. The database provides scientific support for exploring the mechanism of landslides in western Chongqing and reducing the risk of landslide hazards.The eighth paper "Exploring Bayesian network model with noise filtering for rainfallinduced landslide susceptibility assessment in Fujian, China" is contributed by Zhou et al. They employed a Bayesian network to analyze influencing factors on landslides in Fujian Province, China, prone to typhoons and landslides. They introduced a progressive noise filtering method to mitigate the mislabeling effects of non-landslide points. This study provided a useful guidance for reliable landslide susceptibility mapping in the study area.For this Research Topic, further critical and constructive debate, viewpoints and opinions are welcome, which will absolutely contribute toward more resilient and sustainable strategies and practices in the adaptation of extreme weatherinduced disasters. We suggest you freely use and discuss these articles-their methods, solid dataset, key findings and propositions, for promoting the hot research of extreme weather-induced disasters.