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extreme weather Disruptions and Emergency Preparedness Among Older Adults in Ohio: An Eight-County Assessment

International Journal of Disaster Risk Science 2024年第2期15卷 213-225页

作者： Smitha Rao Fiona C.Doherty Anthony Traver Marisa Sheldon Emma Sakulich Holly Dabelko-Schoeny College of Social Work The Ohio State University Age Friendly Innovation Center College of Social Work The Ohio State University College of Public Health The Ohio State University

The disproportionate risks and impacts of climate change and extreme weather on older adults are increasingly evident. While especially true in disaster-prone areas, human-caused climate change introduces an element of uncertainty even in previously identified “safe” regions such as the Midwestern United States. Using a cumulative disadvantage and vulnerability-informed framework and descriptive statistics from multiple data sources, this article provides an overview of climate impacts, vulnerabilities, and county-level characteristics, focusing on older adults living in Central Ohio. A comparative multiple-case study methodology was used to triangulate regionally representative primary and secondary data sources to examine state and county-level measures of vulnerability, emergency preparedness, and disruptions caused by extreme weather among older adults across eight counties in Central Ohio. Seventy-eight percent of older adults in the sample reported being prepared for emergencies per Federal Emergency Management Agency guidelines. Older adults in Union County reported the highest rates of preparedness, while those in Fayette County reported the lowest. County-level rates of disruption of life activities by extreme weather ranged widely. Among the most rural in the region, Fayette County emerged as uniquely disadvantaged, with the lowest median income, the most vulnerable across multiple social vulnerability dimensions, and the most reported disruptions to life activities from extreme weather. County profiles offer a snapshot of existing vulnerabilities, socioeconomic conditions, special needs, preparedness, and current disruptions among older adults in the region and can inform resource mobilization across community and policy contexts.

关键词： Disaster preparedness extreme weather Midwestern United States Older adults Regional assessment Social vulnerability

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extreme weather Loss and Damage Estimation Using a Hybrid Simulation Technique

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International Journal of Disaster Risk Science 2022年第4期13卷 592-601页

作者： Charles Doktycz Mark Abkowitz Hiba Baroud School of Civil and Environmental Engineering Vanderbilt UniversityNashvilleTN 37235USA

History has shown that occurrences of extreme weather are becoming more frequent and with greater impact,regardless of one's geographical location.In a risk analysis setting,what will happen,how likely it is to happen,and what are the consequences,are motivating questions searching for answers.To help address these considerations,this study introduced and applied a hybrid simulation model developed for the purpose of improving understanding of the costs of extreme weather events in the form of loss and damage,based on empirical data in the contiguous United States.Model results are encouraging,showing on average a mean cost estimate within 5%of the historical cost.This creates opportunities to improve the accuracy in estimating the expected costs of such events for a specific event type and geographic location.In turn,by having a more credible price point in determining the cost-effectiveness of various infrastructure adaptation strategies,it can help in making the business case for resilience investment.

关键词： Climate change Cost estimation extreme weather Loss and damage Loss normalization Monte Carlo simulation

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extreme weather as a window:Exploring the seek and supply of climate change information during meteorological disasters in China

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气候变化研究进展:英文版 2023年第4期14卷 615-623页

作者： Wen SHI San-Mei WEN Jing ZHANG Bowering DANNA Chen-Chen HOU Jing YANG Jing SU School of Journalism and Communication Jinan UniversityGuangzhou 510632China School of Journalism and Communication Tsinghua UniversityBeijing 100084China Journalism School Fudan UniversityShanghai 200433China School of Humanities Tsinghua UniversityBeijing 100084China School of Culture and Media Xinjiang University of Finance&EconomicsUrumqi 830012China

Public engagement is essential for China to address climate change;however,few studies have explored how to encourage climate awareness among Chinese residents.The objective of this study is to explore the role of local extreme weather in advancing Chinese people's climate change awareness.Whether local extreme weather functions as an opportunity to trigger the public's interest in climate change across China and whether the local online information environment resonances with extreme weather by providing climate change news feeds have been examined by a combination of city-level meteorological warnings and search engine data.The results have verified that residents from 50 of the 360 cities show increasing concern for climate change when an extreme weather event occurs locally;however,only the online information environment of two cities echoes local extreme weather by providing more information about climate change or global warming.Correlations between extreme weather events such as heavy rain,an extreme weather event that has occurred in China,and climate change are underestimated.The effect of extreme cold events and snowfall on climate change awareness should also be noted more in China.This study suggests there is still a lot of room for improvement regarding both increasing and satisfying the public's pre-existing climate change-related concerns.A promising approach would be adopting climate change prevention and adaptation as a news report framework for extreme weather events.

关键词： Climate change extreme weather Public engagement Search engine

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Urbanization Impact on Regional Climate and extreme weather:Current Understanding,Uncertainties,and Future Research Directions

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Advances in Atmospheric Sciences 2022年第6期39卷 819-860页

作者： Yun QIAN TC CHAKRABORTY Jianfeng LI Dan LI Cenlin HE Chandan SARANGI Fei CHEN Xuchao YANG L.Ruby LEUNG Pacific Northwest National Laboratory RichlandWA 99354USA Yale University New HavenCT 06520USA Department of Earth and Environment Boston UniversityMA 02215USA National Center for Atmospheric Research BoulderCO 80301USA Indian Institute of Technology MadrasChennaiTamil Nadu 600036India Zhejiang University Hangzhou 310027China

Urban environments lie at the confluence of social,cultural,and economic activities and have unique biophysical characteristics due to continued infrastructure development that generally replaces natural landscapes with built-up structures.The vast majority of studies on urban perturbation of local weather and climate have been centered on the urban heat island(UHI)effect,referring to the higher temperature in cities compared to their natural surroundings.Besides the UHI effect and heat waves,urbanization also impacts atmospheric moisture,wind,boundary layer structure,cloud formation,dispersion of air pollutants,precipitation,and storms.In this review article,we first introduce the datasets and methods used in studying urban areas and their impacts through both observation and modeling and then summarize the scientific insights on the impact of urbanization on various aspects of regional climate and extreme weather based on more than 500 studies.We also highlight the major research gaps and challenges in our understanding of the impacts of urbanization and provide our perspective and recommendations for future research priorities and directions.

关键词： urbanization regional climate extreme weather urban heat island urban flooding

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Towards hydrometeorological thresholds of reservoir-induced landslide from subsurface strain observations

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Science China Technological Sciences 2024年第6期67卷 1907-1922页

作者： YE Xiao ZHU HongHu WANG Jia ZHENG WanJi ZHANG Wei SCHENATO Luca PASUTO Alessandro CATANI Filippo School of Earth Sciences and Engineering Nanjing University Department of Geosciences University of Padova School of Geosciences and Info-Physics Central South University Department of Information Engineering University of Padova National Research Council-Research Institute for Geo-Hydrological Protection(CNR-IRPI)

Synergistic multi-factor early warning of large-scale landslides is a crucial component of geohazard prevention and mitigation efforts in reservoir areas. Landslide forecasting and early warning based on surface displacements have been widely investigated.However, the lack of direct subsurface real-time observations limits our ability to predict critical hydrometeorological conditions that trigger landslide acceleration. In this paper, we leverage subsurface strain data measured by high-resolution fiber optic sensing nerves that were installed in a giant reservoir landslide in the Three Gorges Reservoir(TGR) region, China, spanning a whole hydrologic year since February 2021. The spatiotemporal strain profile has preliminarily identified the slip zones and potential drivers, indicating that high-intensity short-duration rainstorms controlled the landslide kinematics from an observation perspective. Considering the time lag effect, we reexamined and quantified potential controls of accelerated movements using a data-driven approach, which reveals immediate response of landslide deformation to extreme rainfall with a zero-day shift. To identify critical hydrometeorological rules in accelerated movements, accounting for the dual effect of rainfall and reservoir water level variations, we thus construct a landslide prediction model that relies upon the boosting decision tree(BDT) algorithm using a dataset comprising daily rainfall, rainfall intensity, reservoir water level, water level fluctuations, and slip zone strain time series. The results indicate that landslide acceleration is most likely to occur under the conditions of mid-low water levels(i.e., 57.9 mm and rainfall intensity> 24.4 mm/h). Moreover, this prediction model allows us to update hydrometeorological thresholds by incorporating the latest monitoring dataset. Standing on the shoulder of this landslide case, our study informs a practical and reliable pathway for georisk

关键词： slow-moving landslide fiber-optic monitoring subsurface strain hydrometeorological threshold extreme weather

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Sustainable city development challenged by extreme weather in a warming world

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Geography and Sustainability 2022年第2期3卷 114-118页

作者： Changjia Li Tong Lu Bojie Fu Shuai Wang Joseph Holden State Key Laboratory of Earth Surface Processes and Resource Ecology Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Institute of Land Surface System and Sustainable Development Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China water@leeds School of GeographyUniversity of LeedsLeedsUK

The year of 2021 has witnessed many extreme weather events across the world that have shocked and challenged human society,in particular for the populous cities,challenging progress on sustainable city development.In the comment we highlighted the record-breaking rainstorm that is considered to happen only“once-in-a-thousand-years”on 20 July 2021 in Zhengzhou,China;and a series of short and long-term resilience enhancement and risk reducing measures to climate change and natural hazard risks.We found that increasing frequency and intensity of extreme weather events caused by human-induced climate change challenges progress on sustainable city development,but could also accelerate activities to enable cities to become more resilient.This comment is essential to advance towards the sustainable city development goal(SDG 11)in China’s mega cities,as well as informing progress for other global cities.

关键词： extreme weather Flood Sponge city Sustainable urban development

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Probing multi-physical process and deformation mechanism of a largescale landslide using integrated dual-source monitoring

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Geoscience Frontiers 2024年第2期15卷 417-432页

作者： Hong-Hu Zhu Xiao Ye Hua-Fu Pei Wei Zhang Gang Cheng Zi-Li Li School of Earth Sciences and Engineering Nanjing UniversityNanjing 210023China Department of Geotechnical Engineering Dalian University of TechnologyDalian 116024China Civil Structural&Environmental EngineeringSchool of Engineering and ArchitectureUniversity College CorkCorkIreland Department of Civil&Environmental Engineering Massachusetts Institute of TechnologyCambridgeMA 02139-4307United States

The implementation of isolated heterologous monitoring systems for spatially distant borehole deployments often comes with substantial equipment costs,which can limit the effectiveness of geohazard mitigation and georisk management efforts.To address this,we have developed a novel monitoring system that integrates fiber Bragg grating(FBG)and microelectromechanical system(MEMS)techniques to capture soil moisture,temperature,sliding resistance,strain,surface tilt,and deep-seated inclination.This system enables real-time,simultaneous data acquisition and cross-validation analyses,offering a costeffective solution for monitoring critical parameters in geohazard-prone areas.We successfully applied this integrated monitoring system to the Xinpu landslide,an active super-large landslide located in the Three Gorges Reservoir Area(TGRA)of China.The resulting strain profile confirmed the presence of two shallow secondary sliding surfaces at depths of approximately 7 m and 12 m,respectively,in addition to the deep-seated sliding surface at a depth of28 m.The lower secondary sliding surface was activated by extreme precipitation,while the upper one was primarily driven by significant changes in reservoir water levels and secondarily triggered by concentrated rainfalls.Anti-slide piles have remarkably reinforced the upper moving masses but failed to control the lower ones.The gap between the pile heads and the soil amplified the rainwater erosion effect,creating a preferential channel for rainwater infiltration.Multi-physical measurements revealed a mixture of seepage-driven and buoyancy-driven behaviors within the landslide.This study offers an integrated dual-source multi-physical monitoring paradigm that enables collaborative management of multiple crucial boreholes on a large-scale landslide,and contributes to the evaluation and improvement of engineering measures in similar geological settings.

关键词： Reservoir landslide Multi-physical process Integrated dual-source monitoring Fiber optic extreme weather

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Eternal Climate Change Patterns and the Causes and Countermeasures of Global Climate Change

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Journal of Environmental Science and Engineering(B) 2024年第1期13卷 9-20页

作者： Cuixiang Zhong Jiangxi Normal University NanchangChina

It is an objective fact that the weather is unpredictable.Even the famous meteorologist,Academician Chu Ko Chen,has only a partial understanding of the changing laws of wind and rain.Even though ancient people summarized the 24 solar terms by observing the annual activities of the sun for a long time,because they ignored the impact of the activities of the moon on the Earth’s climate change on a small scale,the 24 solar terms they summarized often could not accurately predict the change of the Earth’s climate.Therefore,the author studied the influence of lunar activities on the Earth’s climate change,finds out the law of the influence of lunar activities on the Earth’s climate change on a small scale,and summarizes the eternal climate change pattern determined by the activities of the sun and the moon.In addition,the author also reveals the causes and countermeasures of global warming and the frequent occurrence of extreme weather as well as environmental change.

关键词： Eternal climate change patterns global warming extreme weather abrupt environmental changes causes countermeasures.

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Driving role of climatic and socioenvironmental factors on human brucellosis in China:machine-learning-based predictive analyses

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Infectious Diseases of Poverty 2023年第2期12卷 87-100页

作者： Hui Chen Meng-Xuan Lin Li-Ping Wang Yin-Xiang Huang Yao Feng Li-Qun Fang Lei Wang Hong-Bin Song Li-Gui Wang Center for Disease Control and Prevention of Chinese People’s Liberation Army 20 Dong-Da-Jie StreetFengtai DistrictBeijing100071China Academy of Military Medical Sciences Academy of Military Science of Chinese People’s Liberation Army27 Taiping RoadHaidian DistrictBeijing100036China Chinese Centre for Disease Control and Prevention No.155 Changbai RoadChangping DistrictBeijing102206China School of Biological Science and Medical Engineering Beihang University37 Xueyuan RoadHaidian DistrictBeijing100191China Key Laboratory of Water Cycle and Related Land Surface Processes Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina State Key Laboratory of Pathogen and Biosecurity Beijing Institute of Microbiology and Epidemiology20 Dong-Da StreetFengtai DistrictBeijing100071China

Background Brucellosis is a common zoonotic infectious disease in China.This study aimed to investigate the incidence trends of brucellosis in China,construct an optimal prediction model,and analyze the driving role of climatic factors for human brucellosis.Methods Using brucellosis incidence,and the socioeconomic and climatic data for 2014–2020 in China,we performed spatiotemporal analyses and calculated correlations with brucellosis incidence in China,developed and compared a series of regression and Seasonal Autoregressive Integrated Moving Average X(SARIMAX)models for brucellosis prediction based on socioeconomic and climatic data,and analyzed the relationship between extreme weather conditions and brucellosis incidence using copula models.Results In total,327,456 brucellosis cases were reported in China in 2014–2020(monthly average of 3898 cases).The incidence of brucellosis was distinctly seasonal,with a high incidence in spring and summer and an average annual peak in May.The incidence rate was highest in the northern regions’arid and continental climatic zones(1.88 and 0.47 per million people,respectively)and lowest in the tropics(0.003 per million people).The incidence of brucellosis showed opposite trends of decrease and increase in northern and southern China,respectively,with an overall severe epidemic in northern China.Most regression models using socioeconomic and climatic data cannot predict brucellosis incidence.The SARIMAX model was suitable for brucellosis prediction.There were significant negative correlations between the proportion of extreme weather values for both high sunshine and high humidity and the incidence of brucellosis as follows:high sunshine,r=−0.59 and−0.69 in arid and temperate zones;high humidity,r=−0.62,−0.64,and−0.65 in arid,temperate,and tropical zones.Conclusions Significant seasonal and climatic zone differences were observed for brucellosis incidence in China.Sunlight,humidity,and wind speed significantly influenced brucellosis.The SARIMAX model performed better for bruce

关键词： Human brucellosis Socioeconomics Climatic extreme weather Copula model

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Improving risk reduction potential of weather index insurance by spatially downscaling gridded climate data-a machine learning approach

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Big Earth Data 2023年第4期7卷 937-960页

作者： Sarvarbek Eltazarov Ihtiyor Bobojonov Lena Kuhn Thomas Glauben Department of Agricultural Markets Marketing and World Agricultural TradeLeibniz Institute of Agricultural Development in Transition Economies(IAMO)HalleGermany

Open-access gridded climate products have been suggested as a potential source of data for index insurance design and operation in data-limited regions.However,index insurance requires climate data with long historical records,global geographical coverage and fine spatial resolution at the same time,which is nearly impossible to satisfy,especially with open-access data.In this paper,we spatially downscaled gridded climate data(precipitation,temperature,and soil moisture)in coarse spatial resolution with globally available longterm historical records to finer spatial resolution,using satellite-based data and machine learning algorithms.We then investigated the effect of index insurance contracts based on downscaled climate data for hedging spring wheat yield.This study employed countylevel spring wheat yield data between 1982 and 2018 from 56 counties overall in Kazakhstan and Mongolia.The results showed that in the majority of cases(70%),hedging effectiveness of index insurances increases when climate data is spatially downscaled with a machine learning approach.These improvements are statistically significant(p≤0.05).Among other climate data,more improvements in hedging effectiveness were observed when the insurance design was based on downscaled temperature and precipitation data.Overall,this study highlights the reasonability and benefits of downscaling climate data for insurance design and operation.

关键词： Climate risk management risk reduction extreme weather random forest ESA parametric insurance

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