Analysis of Temporal and Spatial Distribution and Large-Scale Circulation Features of Extreme Weather Events in Shanxi Province, China in Recent 30 Years

The study of the characteristic of aquatic traffic accidents is significant for avoiding accidents effectively and guiding the supervision of water traffic safety and the search and rescue of water accidents. In this paper, the temporal and spatial characteristics of aquatic accidents from the aspects of accident occurrence and accident consequences were studied. The results indicated that the total number of verified distress incidents has significant temporal and spatial distribution characteristics; the number of verified distress incidents in coastal areas is significantly higher than that of inland rivers; the main causes of water accidents include collisions, stranding, fires and windstorm, all of which have a significant temporal distribution. In terms of accident consequences, the number of general danger is significantly higher than that of other levels of risk, and there is a significant temporal distribution characteristics on four danger levels. The main types of ships in distress are transporting ships, agricultural vessels, fishing boats and official ships. The number of transporting ships and fishing boats both fluctuated greatly in some months; there was no difference on the temporal distribution for the number of agricultural vessels and official ships in a year. There is no significant linear relationship between the number of distressed people and ships; the number of people in distress on the four types of ships all showed a certain time distribution characteristics; the number of deaths and disappearances in the main rivers rose sharply in June. By analyzing the temporal and spatial distribution characteristics of accidents and their consequences, this paper provides a basis for the relevant authorities to optimize the prevention and control of water accidents, the layout of water search and rescue forces and the timeliness of target searches.

The most severe impacts of climate on human society and infrastructure as well as on ecosystems and wildlife arise from the occurrence of extreme weather events such as heat waves, cold spells, floods, droughts and storms. Recent years have seen a number of weather events cause large losses of life as well as a tremendous increase in economic losses. According to the IPCC (2007), an extreme weather event is an event that is rare at a particular place and time of year. Definitions of rare vary, but an extreme weather event would normally be as rare as or rarer than the 10th or 90th percentile of the observed probability density function. Changes in frequency or/and intensity of extreme events can affect not only human health, directly through heat and cold waves and indirectly by floods or pollution episodes, but also for example, on crops or even insurance calculations. Climate extremes associated with temperature (heatwaves) and precipitation (heavy rain, snow events, droughts) can also affect energy consumption, human comfort and tourism and are responsible for a disproportionately large part of climate-related damages (Easterling et al., 2000; Meehl et al., 2000). Extreme weather events recorded in recent years, and associated losses of both, lives and economics goods, has captured the interest of the general public, governments, stakeholders and media. The scientific community has responded to this inquiry and has raised interest in studying with more attention to detail. Our understanding of the mean behavior of climate and its normal variability has been improving significantly during the last decades. In comparison, climatic extreme events have been hard to study and even harder to predict because they are, by definition, rare and obey different statistical laws than averages. In particular, extreme value analysis usually requires estimation of the probability of events that are more extreme than any that have already been observed, and they are linked to small probabilities. Climate extremes can be placed into two broad groups: (i) those based on simple climate statistics, which include extremes such as a very low or very high daily temperature, or heavy daily or monthly rainfall amounts, that occur every year; and (ii) more complex event-driven extremes, examples of which include drought, floods, or hurricanes, which do not necessarily occur every year at a given location. Katz & Brown (1992) first suggested that the sensitivity of extremes to changes in mean climate may be greater than one would assume from simply shifting the location of the climatological distributions. Since then, observations of historical changes as well as future

Smallholder farmers in Nepal are vulnerable to climate change-related extreme weather events. Adaptation in the agriculture sector is needed to mitigate social, economic, and ecological impacts from increasing levels of hazard activity. To examine this issue, a household survey of 350 farmers in the Terai region of Nepal was carried out to assess farmers’ risk perceptions towards three common extreme weather events (floods, cold spells, and heat waves) and to explore their intended responses to cope with future impacts. The intended common adaptation strategies include changes in farm management, seeking off-farm employment, emergency management planning, purchasing crop insurance, and the raising of awareness. Threat appraisal is the strongest predictor of the number of intended adaptation strategies adopted in response to slow-onset hazards (heat waves and cold spells), while coping appraisal is the major predictor of the number of intended adaptation strategies adopted to mitigate flood risk, a rapid onset hazard. Crop insurance and off-farm employment are farmers’ most preferred flood adaptation strategies, while crop insurance is the most preferred adaptation strategy for heat waves and cold spells. Other variables such as the number of past implemented strategies, experience with extreme events, community organisation membership, and access to credit and extension services were also significantly associated with farmers’ choices for adaptation strategies in response to the three extreme events. This information can be used to tailor community-centred communication about potential threats from different extreme weather events and government technical and financial support, which will be crucial for farmers to adapt effectively to climate change-related weather extremes.

In order to overcome the problems of poor pollutant concentration correlation and poor simulation effect in the traditional simulation results of air pollution concentration temporal and spatial distribution characteristics, a new simulation method of air pollution concentration temporal and spatial distribution characteristics in residential areas based on random forest is proposed. First, divide the indicators of air pollutants in residential areas, and setup the data series of the temporal and spatial distribution characteristics of air pollutant concentration. Then, build the feature judgement matrix and complete feature extraction. The simulation model of temporal and spatial distribution characteristics of pollutant concentration is constructed by using random forest, and the model is solved to realise the simulation of temporal and spatial distribution characteristics of pollutant concentration. The experimental results show that the proposed method has good correlation and high simulation accuracy.

ObjectiveOver the last five decades, extreme weather events (EWEs) have made a substantial contribution to the overall climate change impacts in India. Intergovernmental Panel on Climate Change (IPCC) has predicted that India will experience an increase in extreme weather events in the future. The primary aim of the study was to gain insights into India’s overall occurrence of EWEs between 1970 and 2019 across different states.MethodsIn the present study, data from the Indian Meteorological Department (IMD) spanning the last five decades (1970–2019) was examined to understand how specific EWEs have changed in India over varying regions and time spans. The analysis involved descriptive statistics using heatmaps, and trend analysis using the Mann- Kendall test.FindingsIn the past 50 years (1970–2019), around 11,158 EWEs occurred in India. EM-DAT data shows a rise from 4 + events in the 1950s to 20 + in 2018, while IMD data indicates an increase from 50 + events in the 1970s to 400 + in 2019. The event-wise trend analysis of 50 years of data on EWEs in India revealed a consistent increase in the incidence of each EWE. The Mann–Kendall test, conducted to detect trends in EWEs over 50 years revealed a significant upward trend at 1% level for total EWEs, including heat waves, floods, heavy rains, and thunderstorms. Heat map and spatial analysis revealed that significant regions for heat waves include Maharashtra, Odisha, West Bengal, Uttar Pradesh, Rajasthan, and Uttarakhand. Cold waves have increased in Uttar Pradesh, Uttarakhand, Rajasthan, Bihar, and Jharkhand. Floods, heavy rains, thunderstorms, and lightning are common in Maharashtra, West Bengal, Kerala, Assam, and Karnataka.ConclusionThe findings of the study have critical implications for climate resilience strategies and disaster management in India. The increasing frequency and geographical concentration of EWEs call for region-specific preparedness and mitigation plans. By knowing the trends of EWEs and hotspot states through retrospective data records, the Government can proactively plan for future adverse events to prioritize high-risk areas, implementing targeted preparedness and mitigation strategies to prevent significant mortality and morbidity.

Temporal and spatial distribution characteristics of water resources in Guangdong Province based on a cloud model

Understanding the temporal and spatial distribution characteristics of the cultural heritage of the Yellow River Basin can effectively improve the scientific understanding of the historical changes, environmental evolution, and cultural and economic development of the Yellow River Basin and thus provide a scientific and reasonable decision-making basis for the protection and development of its cultural heritage. The research object of this paper are the national cultural relic protection units. These are examined using the GIS spatial analysis method to explore the spatial and temporal distribution characteristics and spatial structure of 2,102 national material cultural heritage sites in the Yellow River basin. The results show that the spatial distribution of cultural heritage has a significant spatial agglomeration effect. The whole basin is concentrated in stable high- and low-value areas, and the difference between the high- and low-value areas is clear. Some aspects of the spatial structure heterogeneity are strong, showing a low value dispersion distribution trend. In different periods, the distribution direction and scope of cultural heritage have low ranges of rotation, a clear direction, and a high degree of centripetal distribution. The spatial and temporal distribution of cultural heritage is the result of the combined action of natural geographical environment such as climate change, topography, river hydrology, and human environment such as administrative institutional changes, ideological evolution, and social and economic development.

Understanding the temporal and spatial distribution characteristics of the cultural heritage of the Yellow River Basin can effectively improve the scientific understanding of the historical changes, environmental evolution, and cultural and economic development of the Yellow River Basin and thus provide a scientific and reasonable decision-making basis for the protection and development of its cultural heritage. The research object of this paper are the national cultural relic protection units. These are examined using the GIS spatial analysis method to explore the spatial and temporal distribution characteristics and spatial structure of 2,102 national material cultural heritage sites in the Yellow River basin. The results show that the spatial distribution of cultural heritage has a significant spatial agglomeration effect. The whole basin is concentrated in stable high- and low-value areas, and the difference between the high- and low-value areas is clear. Some aspects of the spatial structure heterogeneity are strong, showing a low value dispersion distribution trend. In different periods, the distribution direction and scope of cultural heritage have low ranges of rotation, a clear direction, and a high degree of centripetal distribution. The spatial and temporal distribution of cultural heritage is the result of the combined action of natural geographical environment such as climate change, topography, river hydrology, and human environment such as administrative institutional changes, ideological evolution, and social and economic development.

Air and water quality are impacted by extreme weather and climate events on time scales ranging from minutes to many months. This review paper discusses the state of knowledge of how and why extreme events are changing and are projected to change in the future. These events include heat waves, cold waves, floods, droughts, hurricanes, strong extratropical cyclones such as nor'easters, heavy rain, and major snowfalls. Some of these events, such as heat waves, are projected to increase, while others, with cold waves being a good example, will decrease in intensity in our warming world. Each extreme's impact on air or water quality can be complex and can even vary over the course of the event. Implications: Because extreme weather and climate events impact air and water quality, understanding how the various extremes are changing and are projected to change in the future has ramifications on air and water quality management.

The increasing intensity and frequency of extreme weather events resulting from climate change have led to grid outages and other negative consequences. To ensure the resilience of buildings which serve as primary shelters for occupants, resilient strategies are being developed to improve their ability to withstand these extreme events (e.g., building upgrades and renewable energy generators and storage). However, a crucial step towards creating a resilient built environment is accurately estimating building performance during such conditions using historical extreme climate change-induced weather events. To conduct Building Performance Simulation (BPS) in extreme conditions, such as weather events induced by climate change, it is essential to utilize Actual Meteorological Year (AMY) weather files instead of Typical Meteorological Year (TMY) files. AMY files capture the precise climatic conditions during extreme weather events, enabling accurate simulation of such scenarios. These weather files provide valuable data that can be used to assess the vulnerabilities and resilience of buildings to extreme weather events. By analyzing past events and their impacts using BPS tools, we can gain insights into the specific weaknesses and areas that require improvement. This approach applies to both existing buildings needing climate change-resilient retrofits and new building designs that must be compatible with future climatic conditions. Moreover, the intensification and frequency increase of these extreme weather events makes developing adaptation and resilient-building measures imperative. This involves understanding the potential losses that households may experience due to the intensification of extreme events and developing farsighted coping strategies and climate-proof resilient-building initiatives. However, addressing the knowledge gap caused by the absence of an AMY weather file dataset of extreme events is essential. This will allow for accurate BPS during past extreme climate change-induced weather events. To fill this gap, this article introduces a comprehensive .epw format weather file dataset focusing on historical extreme weather events in Canada. This collection encompasses a diverse array of past extreme climate change occurrences in various locations, with potential for future expansion to include additional locations and countries. This dataset enables energy simulations for different types of buildings and considers a diverse range of historical weather conditions, allowing for better estimation of thermal performance.

It is a perilous time to be a farmer. Across the world, 2015 broke records for unseasonal, unprecedented, and unexpected weather. The combination of El Nino and climate change produced conditions with devastating effects for the agriculture sector around the globe. This article examines the impacts of unseasonal weather on farmers around the world, in losses to yield quality and quantity but also in economic, physical and psychological effects for farmers coping with the “new normal” in weather. It considers regional differences in farmers’ susceptibility to unseasonal weather, and presents the implications of the lack of resiliency of the major crop producers for the future of food security, and by extension, political stability. Finally, it looks at how the international community is addressing this situation, concluding with practical and achievable means for farmers and cooperatives to start to build resiliency to climate change today.

The Asia Pacific region is regarded as the most disaster-prone area of the world. Since 2000, 1.2 billion people have been exposed to hydrometeorological hazards alone through 1215 disaster events. The impacts of climate change on meteorological phenomena and environmental consequences are well documented. However, the impacts on health are more elusive. Nevertheless, climate change is believed to alter weather patterns on the regional scale, giving rise to extreme weather events. The impacts from extreme weather events are definitely more acute and traumatic in nature, leading to deaths and injuries, as well as debilitating and fatal communicable diseases. Extreme weather events include heat waves, cold waves, floods, droughts, hurricanes, tropical cyclones, heavy rain, and snowfalls. Globally, within the 20-year period from 1993 to 2012, more than 530 000 people died as a direct result of almost 15 000 extreme weather events, with losses of more than US$2.5 trillion in purchasing power parity.

In the last decade, the WHO European Region has been struck by various extreme weather events. The dramatic political, social, environmental and health consequences have stimulated debate on whether appropriate action can prevent the health effects of such extreme weather events. Based on our knowledge of climate change, more extreme weather and climate events will occur in the coming years, and they are likely to be more severe. International collaboration is needed to evaluate and target actions better. Many lessons have been learned from early warning and information systems. In preparation for the Fourth Ministerial Conference on Environment and Health in Budapest in 2004, the WHO European Centre for Environment and Health of the WHO Regional Office for Europe and the European Environment Agency (EEA) organized a meeting entitled “Extreme weather events and public health responses” in Bratislava, Slovakia, on 9–10 February 2004 to exchange information regarding the 2002 floodings and the 2003 heat waves as well as to develop recommendations on public health and environmental responses to climate extremes. This paper reviews the contributions from the Bratislava meeting and summarizes the policy recommendations that were developed in a working document for the Fourth Ministerial Conference. Climate variability and extremes are discussed, as are country case studies and experience with floods, heat and cold waves in various European countries; some of the lessons learned are summarized in response to extreme events.

In response to the intensification of global warming, extreme weather events, such as tropical cyclones (TCs) and cold waves (CWs) have become increasingly frequent near the eastern Guangdong coast, significantly affecting the structure and material transport of coastal waters. Based on nearshore-measured and remote sensing reanalysis data in the winter of 2011 and summer of 2012 on the eastern Guangdong coast, this study analyzed the nearshore hydrodynamic evolution process, influencing mechanism, and marine environmental effects under the influence of TCs and CWs, and further compared the similarities and differences between the two events. The results revealed significant seasonal variations in the hydrological and meteorological elements of the coastal waters, which were disrupted by the passage of TCs and CWs. The primary influencing factors were TC track and CW intensity. The current structure changed significantly during the TCs and CWs, with the TC destroying the original upwelling current and the CW affecting the prevailing northeastward current. Wind is one of the major forces driving nearshore hydrodynamic processes. According to the synchronous analysis of research data, the TC-induced water level rise is primarily attributed to the combined effects of wind stress curl and the Ekman effect, whereas the water level rise associated with CW is primarily linked to the Ekman effect. The water transport patterns during the TC and CW differed, with transport concentrated on the right side of the TC track and within the coastal strong-wind zones, respectively. Additionally, the temporal frequency domain of wavelet analysis highlighted the distinct nature of TC and CW signals, with 1–3 d and 4–8 d, respectively, and with TC signals being short-lived and rapid compared to the more sustained CW signals. This study enhances our understanding of the response of coastal hydrodynamics to extreme weather events on the eastern Guangdong coast, and the results can provide references for disaster management and protection of nearshore ocean engineering under extreme events.

Assessment and planning for emerging impacts of climate change on species