Extreme Weather Disasters Research Articles

Spatial correlation evolution and prediction scenario of land use carbon emissions in China

Carbon dioxide emissions are the main drivers of global warming and extreme weather disasters caused by global warming have posed a threat to sustainable development and even to human survival. Land use has an important impact on carbon emissions and carbon storage. This study quantified land use carbon emissions, constructed land use carbon emission grid, and simulated future land use patterns under different scenarios in China during 2000–2018. Land use carbon emissions were found to increase by 400.29% in this period and were higher in the northeast. We discerned obvious spatial correlations between land use carbon emissions in various provinces of China and thus, recommended stronger inter-provincial cooperation in China to achieve overall emission reduction in the country. The carbon emissions spatial correlation network revealed that regions with superior economic and geographical location were in the center of the network. Compared with the carbon emissions in 2018, the simulated natural development scenario and ecological protection scenario indicated that the China's land use carbon emissions decreased in 2030. Thus, the results indicate that the individual provincial governance mode overlooked the spatial correlation between land use carbon emissions across various provinces, due to which these carbon emissions were not effectively reduced. The study highlighted the importance of ecological land protection, which is significant for promoting sustainable land use, increasing land use carbon sink, and reducing carbon emissions.

Resilient power grid for smart city

Modern power grid has a fundamental role in the operation of smart cities. However, high impact low probability extreme events bring severe challenges to the security of urban power grid. With an increasing focus on these threats, the resilience of urban power grid has become a prior topic for a modern smart city. A resilient power grid can resist, adapt to, and timely recover from disruptions. It has four characteristics, namely anticipation, absorption, adaptation, and recovery. This paper aims to systematically investigate the development of resilient power grid for smart city. Firstly, this paper makes a review on the high impact low probability extreme events categories that influence power grid, which can be divided into extreme weather and natural disaster, human-made malicious attacks, and social crisis. Then, resilience evaluation frameworks and quantification metrics are discussed. In addition, various existing resilience enhancement strategies, which are based on microgrids, active distribution networks, integrated and multi energy systems, distributed energy resources and flexible resources, cyber-physical systems, and some resilience enhancement methods, including probabilistic forecasting and analysis, artificial intelligence driven methods, and other cutting-edge technologies are summarized. Finally, this paper presents some further possible directions and developments for urban power grid resilience research, which focus on power-electronized urban distribution network, flexible distributed resource aggregation, cyber-physical-social systems, multi-energy systems, intelligent electrical transportation and artificial intelligence and Big Data technology.

Improvement of the Resilience of a Microgrid Using Fragility Modeling and Simulation

The modern microgrid is designed to withstand various disruptive events that have a high probability of occurrence but have a low impact on the system. This improves the reliability of the system but does not take into consideration the disruptive events that have a low probability of occurrence but have a large impact on the system, such as extreme weather or natural disasters. Redesigning a microgrid to withstand low probability high impact events is very costly and is not a feasible solution to existing microgrids. This paper proposes a method to improve the resilience of an existing microgrid to quickly recover from low probability high impact events. The method used for this purpose is a combination of Monte Carlo simulation and prioritization of load of the microgrid. The efficacy of the method is examined by modeling microgrids using a fragility model. Using the proposed novel resilience index, the resilience of the IEEE 5-Bus system and IEEE 14-Bus system and the effect of load shedding on the resilience of the microgrid are analyzed and presented. The effect on smaller and larger grids and their resilience is examined. A novel resilience index is used to quantify the improvement of resilience of the proposed method when compared to other methods available in the literature.

The Annual Global Incidence Rate of Extreme Weather Event Disasters Appears Positively Correlated with World GDP, 1961-2020.

This study compared the per capita annual global incidence rate of disasters caused by natural hazards with the annual world real gross domestic product, GDP (per global capita), as reported during 1961 through 2020. Sixty (60) values for the world real GDP per global capita (in constant 2015 $USD) were compared to corresponding annual values for global incidence rates for five natural disaster subgroups and then for a total of twelve individual disaster types that comprise the subgroups; each expressed as an annual global incidence rate (in terms of annual incidence per 100,000 persons). Calculations of multiple linear regression, ANOVA, and Pearson's correlation coefficient were performed for comparing population-adjusted values for GDP to corresponding values. Four out of five hydrological and meteorological disasters were found to have a positive correlation with GDP. Results of the analysis revealed a relatively high degree of correlation between world GDP and the annual incidence of flood and storm disasters (P = 6.21 × 10-10 and P = 4.23 × 10-4, respectively). The annual incidence of heat waves and cold weather disasters also appeared to correlate with GDP (P = .002 and P = .019, respectively). In comparison, wet landslides indicated no such correlation (P = .862). No significant associations were found among the seven other individual biological, climatological, and geophysical disasters and GDP. The global incidence of four extreme weather (hydrometeorological) disasters appear to be positively associated with world real GDP during 1961-2020. These findings contradict previous postulates that the risk of disaster incidence is inversely associated with the capacity of the population.

Impact of Extreme Weather Disasters on China's Barley Industry under the Background of Trade Friction-Based on the Partial Equilibrium Model.

The world has entered a compound risk era with multiple crises, and the adverse impact of trade friction and extreme weather disasters on China’s barley import has become increasingly prominent. In this context, this study uses superimposed epoch analysis and partial equilibrium model to evaluate the impact of extreme weather disasters in China’s major barley-exporting countries on China’s barley industry in the course of China–Australia trade friction. The results show that: (1) extreme weather disaster caused barley production in France and Canada to decrease by 7.95% and 18.36% respectively; (2) when the two external shocks occur at the same time, China’s barley import volume tends to decline compared with the basic scenario, the import price rises sharply, there are certain trade-diverting effects in barley import, and China’s imports from countries not affected by extreme weather disasters will increase to a certain extent; (3) China’s barley production remains at a low rate of growth and is vulnerable to external shocks, facing certain import risks. This study provides important policy implications for preventing import risks and ensuring the sufficient supply of domestic barley.

Distributionally Robust Joint Chance-Constrained Optimization for Networked Microgrids Considering Contingencies and Renewable Uncertainty

In light of a reliable and resilient power system under extreme weather and natural disasters, networked microgrids integrating local renewable resources have been adopted extensively to supply demands when the main utility experiences blackouts. However, the stochastic nature of renewables and unpredictable contingencies are difficult to address with the deterministic energy management framework. The paper proposes a comprehensive distributionally robust joint chance-constrained (DR-JCC) framework that incorporates microgrid island, power flow, distributed batteries and voltage control constraints. All chance constraints are solved <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">jointly</i> and each one is assigned to an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">optimized</i> violation rate. To highlight, the JCC problem with the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">optimized</i> violation rates has been recognized as NP-hard and challenging to solve. This paper proposes a novel evolutionary algorithm that successfully solves this problem and reduces the solution conservativeness (i.e., operation cost) by around 50% compared with the baseline <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Bonferroni Approximation</i> . We construct three data-driven ambiguity sets to model uncertain solar forecast error distributions. The solution is thus robust for any distribution in sets with the shared moments and shape assumptions. The proposed method is validated by robustness tests based on these sets and firmly secures the solution robustness.

Cascading effects of the Changbai Mountains on an extreme weather disaster in northern Japan in January 2021

A sequence of a snowstorm, a quasi-stationary convergence zone (Japan Sea polar airmass convergence zone, JPCZ) and a mesoscale coastal front (MCF) caused an extreme weather disaster along the Sea of Japan (SOJ) coast in northern Japan from January 7 to 11, 2021. To examine how the presence of the Changbai Mountains (CMs) affects these multi-scale successive phenomena, we conducted numerical simulations with and without modified topography of the CMs and their surrounding regions using a regional atmospheric model with a horizontal resolution of 4 km. Backward-trajectory analyses and an additional experiment that removed the sublimation process of snow were also performed to clarify the formation and maintenance processes of the MCF. The CMs lead to the structural change of the snowstorm developing over the SOJ, enhancement of the JPCZ, and formation of the MCF, affecting heavy snowfall in the SOJ coastal areas. The MCF, which is a mesoscale phenomenon smaller than the JPCZ, is formed and maintained by the monsoonal flows that detour from the north and south of the CMs. Several of the parcels that detour from north of the CMs intrude into the MCF through the boundary layer, which is thermodynamically modified by the heat and moisture supply from the sea, whereas the inland flows that penetrate the MCF from its south are composed of two major routes: one is the flow detouring from south of the CMs that crosses the high mountains on the mainland of Japan, and the other is the parcels detouring from north of the CMs that penetrate from the inland after they land on the northern coast. The difference in equivalent potential temperature between the inland flows and the monsoonal flow from the sea is responsible for the MCF formation. A cold pool near the surface also contributes to the prolonged MCF. Understanding of the CMs’ cascading effects on multi-scale phenomena from synoptic scale to mesoscale is necessary for the prediction of extreme weather disasters over Japan in winter.

THE EUROPEAN EXPERIENCE OF THE SUSTAINABLE DEVELOPMENT OF THE AGRICULTURAL SECTOR IN RURAL AREAS

The article examines the European experience of agricultural policy aimed at increasing productivity and production in general, helping to maintain ecosystems and strengthen the industry's ability to adapt to climate change, extreme weather, drought, floods and other disasters while gradually improving land quality, resources and soils. It is substantiated that since the main means of agriculture is land resources, the main practices of sustainable development of the industry are related to the ability to improve soil quality. The main types of soil degradation, their consequences and costs in the EU countries are identified. It is established that the framework and specific measures for the protection and restoration of soils, as well as ensuring their rational use in the EU is determined by the new EU Soil Strategy for 2030, which replaced the Soil Thematic Strategy (STS) in 2006. The new Strategy is based on several goals of the Green Agreement and the Sustainable Development Goals by 2030 and sets medium-term (2030) and long-term (2050) goals. The implementation of the Strategy envisages framework actions and implementation of specific policies in nine areas: organic content in soil and climate change; test-soil-for-free initiative; closed-loop economy and soil; organic farming, soil health and climate change; soil biodiversity for ecosystems and human health; prevention of soil contamination; reclamation of disturbed and contaminated lands; soil and digital agenda; soil monitoring. The main activators (drivers) of the Strategy are financing, management, promotion and participation in global actions, which are systematized by funding for sustainable management and restoration of soils at the EU level, institutions of management and restoration of soils in the EU, areas of promotion and participation in global actions on soils in the EU.

The role of water in environmental migration

AbstractWater has always been a driver of human mobility, migration, and displacement. But water is increasingly central to explaining environmental migration in the context of climate change. Most studies of the relationship between water and environmental migration are framed around punctuated, extreme weather events and disasters that either limit agricultural or livestock productivity or make a community physically unlivable. The chronic experiences of household water insecurity and poor water governance also shape migration decision‐making through a variety of social, political, and economic factors, but these relationships have received considerably less attention. This article provides an overview of punctuated and chronic water‐related triggers of environmental migration at the household level. We also offer a conceptual framework based on multiphasic response theory that highlights water's multiple roles in migration decision‐making. We close by reflecting on key gaps in the climate‐water‐migration literature, identifying research questions that might help us better understand these relationships, and considering the implications for sustainable development policies that could potentially ease pressures on water‐related displacement.

Impact of Climate Change on Rural Poverty Vulnerability from an Income Source Perspective: A Study Based on CHIPS2013 and County-Level Temperature Data in China.

Harsh natural climatic environments, such as extreme weather and natural disasters, cause devastating blows to production activities and increase the probability of geographic poverty, climate poverty, and return to poverty. Thus, this study uses climate data and micro survey data (CHIPS2013) to examine the impact of climate on vulnerability to individual poverty in rural China. The results demonstrated that extreme temperatures (hotter summers, colder winters, and greater day-to-day temperature gaps) reduce vulnerability to poverty. This was also supported by the median and average temperatures. Second, there is an association between poverty vulnerability and poverty; that is, poorer people will become poorer with an increase in poverty vulnerability. In fact, in the case of higher income, the higher the probability of returning to poverty, the higher the vulnerability. Policy formulation processes should take into consideration different types of impacts from harsh climate on different vulnerable groups. No single action might be adequate and an integrative approach integrating various strategies and actions are required to overcome challenges posed by climate change and poverty vulnerabilities.

Critical climate issues toward carbon neutrality targets

In 2020, China announced the "emission peak, carbon neutrality" policy, that is, China aims to have CO2 emissions peak before 2030 and achieve carbon neutrality before 2060. The scenario of carbon neutrality will be significantly distinguished from the scenario we experienced since the industrial revolution. However, instrumental data are unavailable in the future carbon-neutral scenario. Earth system models and climate dynamics theory are needed to comprehend and project the climate change. In this paper, we illustrate our perspective of the issues related to "emission peak, carbon neutrality", including climate dynamics, climate-carbon feedback, interaction between China and global climate and carbon emissions and solutions, etc. We highlight that climate change has profoundly affected human production and life. The frequent occurrence of extreme weather disasters in recent years, together with the impact of epidemics, make the future "carbon peak & carbon-neutral" scenario more complex. There is whopping uncertainty but also a massive challenge to the scientific community. Thus, carbon neutrality is closely related to domestic production and lives, and there is little time left for planning. We believe that we will make a breakthrough in climate dynamics in the context of carbon neutrality with our joint efforts, which will serve our country's carbon emission policy at different stages.

Urban climate-health governance: Charting the role of public health in large global city adaptation plans

Over the last decade many large world cities have scaled up efforts at climate adaptation, a primary focus of which is protecting population health. With extreme weather disasters increasing worldwide, public health agencies are among local institutions under greatest stress; the Covid-19 pandemic has only heightened pressure on these agencies. Yet the limited literature examining adaptation actions across world cities suggest few, mainly high-income cities report health-related adaptation, while city public health agency engagement in adaptation has received little research attention. In this comparative review, we aimed to characterize the public health role in the adaptation plans of 22 large cities pre-identified as highly health-adaptive, by examining five health-associated adaptation activities chosen as “promising practice” based on evidence synthesized from evaluation research and practical experience: (i) hazard and vulnerability mapping; (ii) extreme weather preparedness and response; (iii) extreme heat plans (including heat early warning); (iv) non-heat early warning (e.g., flooding, vector-borne disease); and (v) climate-health monitoring and outcome surveillance. We found most (90%) city adaptation plans reported actions in at least three of these five activity areas. However, only 73% of these health-focused plans reported involvement of a public health agency (though the share was higher for cities in low- and middle-income countries). We detected differences across the five activities, including an ascending pattern of public health engagement starting with heat plans and including activities such as preparedness and mapping as health agency involvement increased. We also identified substantial presence of other city agencies–notably urban planning, emergency management and public utilities–in implementing these health-associated activities. With every world region likely to experience more widespread and intensifying climate impacts, and growing pressure on local public health agencies in conjunction with the Covid-19 pandemic, we identify opportunities for enhancing public health engagement in climate adaptation in large cities with a view to scaling up their ability to contribute to climate adaptation goals.

Extreme and Severe Convective Weather Disasters: A Dual-Polarization Radar Nowcasting Method Based on Physical Constraints and a Deep Neural Network Model

Extreme and Severe Convective Weather Disasters: A Dual-Polarization Radar Nowcasting Method Based on Physical Constraints and a Deep Neural Network Model

Extreme weather and the politics of climate change: A study of campaign finance and elections

This paper studies how extreme weather and natural disasters affect campaign contributions and elections. Weather events associated with climate change may influence these outcomes by leading voters to re-evaluate the incumbent politician’s environmental position. In a short-run analysis, we find that the number of online contributions to the Democratic Party increases in response to higher weekly temperature, with a larger effect in counties with more anti-environment incumbent politicians. In a medium-run analysis, we find that, when a natural disaster strikes, the election becomes more competitive if the incumbent leans more anti-environment: total campaign contributions increase for both candidates and the increase is skewed toward the challenger, the race is more likely to be contested, and the incumbent is less likely to be re-elected. These results suggest that extreme weather events carry a moderate electoral penalty for anti-environment incumbents during 1990–2012. This mechanism will likely play a more important role as the public awareness of climate change continues to increase.

Durability and Abrasion Resistance of Innovative Recycled Pervious Concrete with Recycled Coarse Aggregate of Different Quality under Sulfate Attack

Construction and demolition wastes (C&amp;DWs) have raised a large number of ecological and environmental problems. Recycling C&amp;DWs into arecycled concrete aggregate (RCA) will help save natural resources effectively and reduce the negative impact of C&amp;DW on the environment. Innovative pervious concrete (IPC) can mitigate extreme weather disasters, such as rainstorms, and overcome the low strength and poor durability of traditional pervious concrete. In this study, innovative recycled pervious concrete (IRPC) is prepared by combining RCA with IPC, which has broad application prospects and ecological friendliness. This study investigates the effect of RCA quality grades and replacement rates on the mechanical property, permeability, sulfate resistance and abrasion resistance of IRPC. IRPC mixtures were prepared with three different quality grades (high, medium and low qualities) of aggregates named as NA, RCA1 and RCA2. Moreover, the replacement rate of RCA for NA varied as 0%, 25%, 50%, 75% and 100%. The IRPC specimens were tested for compressive strength, mass loss and abrasion resistance after different sulfate wetting-drying cycles of 0, 30 and 60. The results exhibited that the initial compressive strength of all types of IRPC was more than 40 MPa. The compressive strength and mass of most IRPC increased first and then decreased slightly with the passage of a number of sulfate wetting-drying cycles, indicating IRPC has good resistance to sulfate attack. Sulfate attack and the addition of RCA will reduce the abrasion resistance of IRPC. However, when the replacement rate is lower than 50%, and the RCA quality is better (attached mortar content &lt; 25%), the abrasion resistance of IRPC will be improved under sulfate attack. The experimental results might be useful as a reference and design methodology for employing IRPC in pavement applications in the future.

71Advanced Environmental Epidemiology for Health and Climate Research

Abstract Focus and outcomes for participants The symposium will focus on insights and applications of advanced environmental epidemiology methods in health and climate research. The symposium will help the participants Rationale for the symposium, including for its inclusion in the Congress Climate change is the greatest health challenge in the 21st century. The most recent Lancet Countdown report (Watts et al. 2019) and the MJA-Lancet Countdown Australian reports (Zhang et al. 2018; Beggs et al. 2019) on health and climate change research have once again highlighted the global vulnerability to health risks from climate change. Epidemiology plays an important role in informing policy to protect the public’s health from a changing climate. However, limited research has been conducted in the field, which may be due to the methodological challenges to conducting research in climate change epidemiology (Xun et al. 2010). However, there are opportunities for advancing epidemiological research in the context of climate change, as highlighted in the recent paper published in the American Journal of Epidemiology (Anderson et al. 2019). The proposed symposium aligns precisely with the conference theme on methodological innovations in epidemiology and the need for epidemiologists who are keen to address non-traditional epidemiological health risks to support decision-making under a changing climate. This symposium will be a timely event to build capacity needed to address more extreme weather events and disasters related to climate change in Australia and globally. Presentation program (90 minutes) The symposium will have 6 presentations, 15 minutes each including Q&amp;A. Names and short biography of presenters

Severity of drought and heatwave crop losses tripled over the last five decades in Europe

Extreme weather disasters (EWDs) can jeopardize domestic food supply and disrupt commodity markets. However, historical impacts on European crop production associated with droughts, heatwaves, floods, and cold waves are not well understood—especially in view of potential adverse trends in the severity of impacts due to climate change. Here, we combine observational agricultural data (FAOSTAT) with an extreme weather disaster database (EM-DAT) between 1961 and 2018 to evaluate European crop production responses to EWD. Using a compositing approach (superposed epoch analysis), we show that historical droughts and heatwaves reduced European cereal yields on average by 9% and 7.3%, respectively, associated with a wide range of responses (inter-quartile range +2% to −23%; +2% to −17%). Non-cereal yields declined by 3.8% and 3.1% during the same set of events. Cold waves led to cereal and non-cereal yield declines by 1.3% and 2.6%, while flood impacts were marginal and not statistically significant. Production losses are largely driven by yield declines, with no significant changes in harvested area. While all four event frequencies significantly increased over time, the severity of heatwave and drought impacts on crop production roughly tripled over the last 50 years, from −2.2% (1964–1990) to −7.3% (1991–2015). Drought-related cereal production losses are shown to intensify by more than 3% yr−1. Both the trend in frequency and severity can possibly be explained by changes in the vulnerability of the exposed system and underlying climate change impacts.

“What’s Up with the Weather?” Public Engagement with Extreme Event Attribution in the United Kingdom

AbstractThe science of extreme event attribution (EEA)—which connects specific extreme weather events with anthropogenic climate change—could prove useful for engaging the public about climate change. However, there is limited empirical research examining EEA as a climate change communication tool. To help fill this gap, we conducted focus groups with members of the U.K. public to explore benefits and challenges of utilizing EEA results in climate change advocacy messages. Testing a range of verbal and visual approaches for communicating EEA, we found that EEA shows significant promise for climate change communication because of its ability to connect novel, attention-grabbing, and event-specific scientific information to personal experiences and observations of extreme events. Communication challenges include adequately capturing nuances around extreme weather risks, vulnerability, adaptation, and disaster risk reduction; expressing scientific uncertainty without undermining accessibility of key findings; and difficulties interpreting mathematical aspects of EEA results. On the basis of our findings, we provide recommendations to help address these challenges when communicating EEA results beyond the climate science community. We conclude that EEA can help catalyze important dialogues about the links between extreme weather and human-driven climate change.

Unprecedented Migratory Bird Die-Off: A Citizen-Based Analysis on the Spatiotemporal Patterns of Mass Mortality Events in the Western United States.

Extensive, severe wildfires, and wildfire‐induced smoke occurred across the western and central United States since August 2020. Wildfires resulting in the loss of habitats and emission of particulate matter and volatile organic compounds pose serious threatens to wildlife and human populations, especially for avian species, the respiratory system of which are sensitive to air pollutions. At the same time, the extreme weather (e.g., snowstorms) in late summer may also impact bird migration by cutting off their food supply and promoting their migration before they were physiologically ready. In this study, we investigated the environmental drivers of massive bird die‐offs by combining socioecological earth observations data sets with citizen science observations. We employed the geographically weighted regression models to quantitatively evaluate the effects of different environmental and climatic drivers, including wildfire, air quality, extreme weather, drought, and land cover types, on the spatial pattern of migratory bird mortality across the western and central US during August‐September 2020. We found that these drivers affected the death of migratory birds in different ways, among which air quality and distance to wildfire were two major drivers. Additionally, there were more bird mortality events found in urban areas and close to wildfire in early August. However, fewer bird deaths were detected closer to wildfires in California in late August and September. Our findings highlight the important impact of extreme weather and natural disasters on bird biology, survival, and migration, which can provide significant insights into bird biodiversity, conservation, and ecosystem sustainability.

Wildfire Response Operations: Intentional Fear Reduction through Social Media Updates

The increase in extreme weather disasters over the past ten years, combined with the increased usage of social media in transmitting information during these disasters, has led to a growing need to understand the implications and best practices in utilizing social media to inform those at-risk. People panic during natural disasters, and a first method to enable rational response is to reduce fear and anxiety. We examine whether the information provided from an organization with an authoritative, reliable reputation through social media could help reduce public fear. Two studies form our research. First, through an exploratory study on wildfires in California, we find empirical evidence that increased operational transparency, i.e., informing the public about the operation activities, does negatively influence fear, such that fear decreases when information is posted by the premier authority on wildfire fighting. Second, drawing from operational transparency theory and theories on expertise and reputation, we conduct an online experiment to reveal underlying mechanisms that are effective in reducing fear. Our results suggest that highlighting expertise in social media posts reduces fear. This same information also increases user intention to heed warnings from this authority. Our findings provide actionable strategies to relief organizations. Of particular import is that this intervention requires little or no additional cost to organizations, making it a feasible solution for agencies that face budget shortages while they struggle to fight the consequences of climate change.