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The sub-tropical, flat, peninsular region of Florida is subject to a unique climate with extreme weather events that impact agriculture, public health, and management of natural resources. Meteorological data at high temporal resolutions especially in tropical latitudes are essential to understand diurnal and semi-diurnal variations of climate, which are considered as the fundamental modes of climate variations of our Earth system. However, many meteorological datasets contain gaps that limit their use for validation of models and further detailed observational analysis. The objective of this paper is to apply a set of data gap filling strategies to develop a gap-free dataset with 15-minute observations for the sub-tropical region of Florida. Using data from the Florida Automated Weather Network (FAWN), methods of linear interpolation, trend continuation, reference to external sources, and nearest station substitution were applied to fill the data gaps depending on the extent of the gap. The outcome of this study provides continuous, publicly accessible surface meteorological observations for 30 FAWN stations at 15-minute intervals for years 2005–2020. [ABSTRACT FROM AUTHOR]

With global warming, the frequency, intensity, and period of extreme climates in more areas will probably increase in the twenty first century. However, the impact of climate extremes on forest vulnerability and the mechanisms by which forests adapt to climate extremes are not clear. The eastern Tianshan Mountains, set within the arid and dry region of Central Asia, is very sensitive to climate change. In this paper, the response of Picea schrenkiana and Larix sibirica to climate fluctuations and their stability were analyzed by Pearson's correlation based on the observation of interannual change rates of climate indexes in different periods. Additionally, their ecological adaptability to future climate change was explored by regression analysis of climate factors and a selection of master control factors using the Lasso model. We found that the climate has undergone significant changes, especially the temperature, from 1958 to 2012. Around 1985, various extreme climate indexes had obvious abrupt changes. The research results suggested that: (1) the responses of the two tree species to extreme climate changed significantly after the change in temperature; (2) Schrenk spruce was more sensitive than Siberian larch to extreme climate change; and (3) the resistance of Siberian larch was higher than that of Schrenk spruce when faced with climate disturbance events. These results indicate that extreme climate changes will significantly interfere with the trees radial growth. At the same time, scientific management and maintenance measures are taken for different extreme weather events and different tree species. [ABSTRACT FROM AUTHOR]

Weather and climate extremes such as heat waves, droughts and floods are projected to become more frequent and intense in several regions. There is compelling evidence indicating that changes in climate and its extremes over time influence the living conditions of society and the surrounding environment across the globe. This study applies max-stable models to capture the spatio–temporal extremes with dependence. The objective was to analyse the risk of drought caused by extremely high temperatures and deficient rainfall. Hopkin's statistic was used to assess the clustering tendency before using the agglomerative method of hierarchical clustering to cluster the study area into n = 3 temperature clusters and n = 3 precipitation clusters. For the precipitation and temperature data, the values of Hopkin's statistic were 0.7317 and 0.8446, respectively, which shows that both are significantly clusterable. Various max-stable process models were then fitted to each cluster of each variable, and the Schlather model with several covariance functions was found to be a good fit on both datasets compared to the Smith model with the Gaussian covariance function. The modelling approach presented in this paper could be useful to hydrologists, meteorologists and climatologists, including decision-makers in the agricultural sector, in enhancing their understanding of the behaviour of drought caused by extremely high temperatures and low rainfall. The modelling of these compound extremes could also assist in assessing the impact of climate change. It can be seen from this study that the size, including the topography of the location (cluster/region), provides important information about the strength of the extremal dependence. [ABSTRACT FROM AUTHOR]

Current climate projections for Southern Africa indicate an increase in the incidence of extreme weather events in the future. Even though South Africa does not rank among the highest on the world multi-hazard index list, the country is prone to multiple climate-related extreme events which pose substantial human and ecological impacts. Consequently, such climate extremes have serious negative effects on regional water resources, public health, biodiversity, food security, natural systems, and infrastructure. The main aim of this study is to review the literature on climate-change-induced weather events and the implications for urban water resource management in South Africa particularly focusing on QwaQwa. The study reviewed 122 documents which include books, peer-reviewed articles, conference papers, newspaper articles, institutional and government reports, and one news broadcast video. Findings revealed that QwaQwa experiences increasing water challenges as demand for water increases and both quantity and quality decrease to critical levels. This study, therefore, provides preliminary suggestions of strategies to build resilience in this climate change context, such as investment in climate-resilient water infrastructure, effective and transparent management of public resources with accountability, strengthening resilience through addressing poverty and marginalisation, nature-based solutions, and education and awareness. Furthermore, conducting hazard, exposure, and resilience analyses is necessary in order to inform the development of relevant disaster risk reduction strategies. The findings contribute to the literature on climate change impacts on water resource planning in South Africa and similar climate change contexts. The findings could; therefore, be valuable to researchers and applied practitioners such as policymakers, water resource management professionals, and urban planners. [ABSTRACT FROM AUTHOR]

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Among several devastating natural hazards, flooding is a common and serious threat to society causing huge loss of lives, properties, and infrastructure throughout the world. The intensity and frequency of this extreme weather event are expected to increase due to significant changes in the present‐day climate and land use and land cover (LULC) pattern. India has a very systematic and organized structural program and policies but lacks proper implementations, and adverse effect of climate change and the extreme event goes on in society. This paper is an analysis of floods in India and hazards due to climate change and LULC change patterns. Three models, namely "Eco‐biogeography‐based optimization (EBO), Random forest (RF), and Support vector machine (SVM)" were used to obtain the final output to prepare a "Flood susceptibility map". The result was validated through the "Receiver operating characteristics (ROC)" with "Area under curve (AUC)" values. The future rainfall scenario has been estimated by considering the "General circulation models" through different "shared socioeconomic pathways (SSPs)". The values of AUC are 0.915 (EBO), 0.887 (RF), and 0.869 (SVM), respectively. After consideration of different SSPs, the result shows that there is an increasing tendency of flood hazards in the projected period. Among all the employed modelling approaches, the EBO model has notable potential in delineating the possible flood‐prone regions for effective flood planning and management. Decision‐makers can benefit from country‐specific information and regional planner to implement sustainable and long‐term measures to overcome this type of hazardous situation. [ABSTRACT FROM AUTHOR]

Understanding climate extremes and indices is crucial for addressing climate change impacts, including the increased variability in local weather patterns and extreme events. Previous studies on the Arabian Peninsula (AP) have been limited by sparse station data and restricted spatial coverage. To overcome this limitation, this paper aims to assess the spatial distribution and temporal trends of temperature and precipitation indices suggested by the Expert Team on Climate Change Detection and Indices (ETCCDI) using ERA5 reanalysis data from 1951 to 2020 for the AP. Additionally, this study investigated the changes relative to the reference period (1951–1980). The modified Mann-Kendall test and Sen's Slope estimator are utilized to detect significant trends and estimate their magnitude. Results revealed that ERA5 was consistent with previous studies that utilized in-situ station data, which offers a more detailed picture of the affected areas. The findings indicated a significant warming trend in temperature indices, with an increase of over 1 °C per decade observed across several areas, including the northern AP, and certain regions experiencing a discrepant change of 3 °C increase compared to the reference period. Changes in rainfall indices indicate a shift in rainfall patterns from the AP's fertile southwest regions towards more intense patterns in specific eastern regions, including Oman, Kuwait, Saudi Arabia, and Yemen. However, the precipitation temporal trends are weak in magnitude and variable spatially, with dominant decreases in both intensity (-10 mm per decade) and frequency indices (-5 days per decade). Some locations are subject to the combined effects of most heatwave indicators simultaneously, while flood indicators and yet others by drought indicators influence others. All these locations have been accurately identified in this study. The findings provide valuable information regarding the region's climate change vulnerability and adaptation needs. [Display omitted] • Prior studies relied on limited station data, short period, and MK trend test. • Extremes are assessed using ERA5, ETCCDI, Modified-MK, and Sen's Slope. • Affected areas are identified, and valuable insights for policymakers are set. • Significant warming trend: >1 °C/decade and > 2 °C change from reference period. • Spatiotemporal trends of precipitation are weak in magnitude and variable spatially. [ABSTRACT FROM AUTHOR]

This study analyzes daily temperature and precipitation data collected from 44 weather stations throughout New York, New Jersey, and Connecticut to assess and quantify the historical climatic changes within these states. The study conducts a detailed examination of spatial and temporal trends, focusing on specific stations that best represent the climatic diversity of each area. A critical analysis aspect involves comparing temperature trends in urban and suburban areas, mainly focusing on New York City. The findings reveal a significant upward increasing trend in average temperatures across all seasons, with urban areas, especially NYC, exhibiting the most marked increases. This trend is notably sharp in the spring, reflecting climate change's escalating influence. The study also observes an increase in the annual average temperatures and a concurrent decrease in the variability of temperature ranges, suggesting a stabilization of temperature fluctuations over time. Also, we identified a notable increase in heat wave frequency, more so in urban locales than in their suburban counterparts. Analysis of precipitation patterns, particularly in NYC, reveals a decline in snowfall days, consistent with the general warming trend. The results demonstrate significant trends in seasonal average temperatures, a decrease in the variability of temperatures, and a rise in heat wave occurrences, with urban areas typically experiencing warmer conditions. This comprehensive study highlights the need for a more in-depth analysis of spatial precipitation trends. It underscores the importance of continued research in understanding the multifaceted impacts of climate change, particularly in differentiating urban and rural experiences. [ABSTRACT FROM AUTHOR]

Climate change and rising temperatures have led to an increase in extreme weather and climate reports at regional, hemispheric and international scales, especially in terms of heat. The worrying increase in the number of global climate-related disasters, such as widespread fires in Australia in 2019-2020, those in Greece in 2021, volcanic eruptions in 2021, earthquakes, landslides and floods, the three main greenhouse gases greenhouse gases - carbon dioxide, methane and nitrogen oxides - which reached a record level in 2020 and 2021, despite the reduction of human activities due to the COVID-19 pandemic, draws attention to the effects that may influence the development of the planet. The paper aims to highlight how climate change affects sustainable development, adaptation and vulnerability of people, ecosystems, agriculture and cities in relation to environmental issues. The article presents economic impact considerations and possible ways to mitigate climate change. [ABSTRACT FROM AUTHOR]

The air temperature in Bosnia and Herzegovina is increasing (0.3 - 0.6 °C per decade), while rainfall events are more extreme. Additionally, there is an increased variability in weather conditions across all seasons, marked by rapid shifts from extremely cold to warm weather, as well as transitions from periods of exceptionally high rainfall to exceedingly dry periods. Droughts and floods pose the most significant risks. However, Bosnia and Herzegovina faces a lack of adequate information and analyses of extreme climate events, especially regarding their timing, intensity, magnitude, duration, and spatial extent. Therefore, this study aims to address these questions using the precise drought index SPEI. The identified wet years were: 1969, 1970, 1976, 1978, 1999, 2001, 2010, 2013, and 2014, while the dry years were 1961, 1971, 1983, 1990, 2000, 2003, 2007, 2011, 2012, and 2020. In the northern and western regions of BiH, the longest wet period in terms of duration and spatial extent occurred from May 2014 to July 2015. In the central and southern parts of BiH, the longest wet period extended over 19 months from February 1969 to August 1970. The longest drought with the largest spatial extent was the drought from August 2011 to July 2013. The obtained data shows a significant shift towards drier weather, as dry months have increased by 15% compared to wet months. At the same time, there has been a decrease in near-normal conditions and an increase in extremely wet months. [ABSTRACT FROM AUTHOR]

Within the past decade, the attribution of extreme weather events and their impacts has enabled scientists, the public, and policymakers alike to connect real-world experiences of extreme weather events with scientific understanding of anthropogenic climate change. Attribution studies of recent extreme weather events have formed a new and important line of evidence in the most recent Intergovernmental Panel on Climate Change (IPCC) assessment report understanding present-day impacts of climate change. IPCC studies using different methods of event attribution have been assessed together, highlighting that these differences are smaller than the academic discourse on the methods suggests. This development raised two important research questions the science needs to answer: First, how do we formally combine attribution statements using highly conditional methods with probabilistic assessments of how climate change alters the likelihood and intensity of extreme weather events? Second, under what circumstances are individual attribution studies still necessary and to what extent do existing attribution studies provide enough information to answer societal questions? Furthermore, the scientific development still leaves important gaps, particularly in countries of the Global South, leading to ethical questions around the need and requirement of attribution of extreme events in policy contexts, informing adaptation and loss and damage and the role of vulnerability. [ABSTRACT FROM AUTHOR]

Climate change and global urbanization have often been anticipated to increase future population exposure (frequency and intensity) to extreme weather over the coming decades. Here we examine how changes in urban land extent, population, and climate will respectively and collectively affect spatial patterns of future population exposures to climate extremes (including hot days, cold days, heavy rainfalls, and severe thunderstorm environments) across the continental U.S. at the end of the 21st century. Different from common impressions, we find that urban land patterns can sometimes reduce rather than increase population exposures to climate extremes, even heat extremes, and that spatial patterns instead of total quantities of urban land are more influential to population exposures. Our findings lead to preliminary suggestions for embedding long-term climate resilience in urban and regional land-use system designs, and strongly motivate searches for optimal spatial urban land patterns that can robustly moderate population exposures to climate extremes throughout the 21st century. Considering changes in urban land extent, population, and climate over the 21st century, the authors find spatial urban land patterns can reduce rather than increase population exposures to climate extremes, even heat extremes, at regional scales. [ABSTRACT FROM AUTHOR]

Climate change has severe and sweeping impacts on mental health. Although research is burgeoning on mental health impacts following climate and weather extremes, less is known about how common these impacts are outside of extreme events. Existing research exploring the prevalence of psychosocial responses to climate change primarily examines university students and uses non-random sampling methods. Herein, our protocol outlines an approach to data collection, processing, and analysis to estimate the population prevalence, magnitude, and distribution of mental health responses to climate change in Canada. A cross-sectional survey of youth and adults aged 13 years and older in Canada will be administered over the course of one year. The questionnaire will take approximately 10 minutes to complete orally and will be administered in English, French, and Inuktitut. The survey will consist of six sections: (1) self-reported past experiences of climate change; (2) self-reported climate-related emotions; (3) self-reported past and current impacts, anticipatory impacts, and vicarious experiences; (4) self-reported subclinical outcomes; (5) self-reported behavioural responses; and (6) demographics. A multi-stage, multi-stratified random probability sampling method will be used to obtain a sample representative of the Canadian population. We will use two different modes of recruitment: an addressed letter sent by postal mail or a telephone call (landlines and cellular). Population-weighted descriptive statistics, principal component analysis, and weighted multivariable regression will be used to analyse the data. The results of this survey will provide the first national prevalence estimates of subclinical mental health responses to climate change outcomes of people living in Canada. [ABSTRACT FROM AUTHOR]

Involuntary displacement from conflict and other causes leads to clustering of refugees and internally displaced people, often in long-term settlements. Within refugee-hosting countries, refugee settlements are frequently located in isolated and remote areas, characterized by poor-quality land and harsh climatic conditions. Yet, the exposure of refugee settlements to climatic events is underresearched. In this article, we study the exposure of the 20 largest refugee settlements worldwide to extreme variations in climatic conditions. The analysis integrates exposure of camp locations compared to the national trends for both slow- and rapid-onset events and includes descriptive statistics, signal-to-noise analyses, and trend analyses. Our findings show that most refugee settlements included face relatively high exposure to slow-onset events, including high temperatures (for settlements in Kenya, Ethiopia, Rwanda, Sudan, and Uganda), low temperatures (in the case of Jordan and Pakistan), and low levels of rainfall (in Ethiopia, Rwanda, Kenya, and Uganda) compared to national averages. Our findings for rapid-onset events--heatwaves, coldwaves, and extreme rainfall--are less conclusive compared to country trends, although we find relatively high exposure to extreme rainfall in Cox's Bazar, Bangladesh. Our analyses confirm that refugee populations are exposed to extreme weather conditions postdisplacement, which, in combination with their sociopolitical exclusion, poses a threat to well-being and increased marginalization. Our findings call for an inclusive and integrated approach, including refugees and their host communities, in designing climate adaptation and sustainable development policies, in order to promote equitable sustainable development pathways in refugee-hosting countries. [ABSTRACT FROM AUTHOR]

Increasing extreme weather and climate events have led to recurrent disasters that cause significant harm to human populations. The aim of this present study is to complement Costa Rica's National Meteorological Institute 2017 risk assessment methodology for extreme weather and climate events. This methodology uses different socio-spatial indicators related to vulnerability and hazards to extreme hydrometeorological events. However, in the methodology applied and presented in this document, an exposure component was added to the model to obtain a more detailed representation of climate-related risks. The presented methodology was implemented in the municipalities of Cartago and Turrialba, where the frequency and severity of weather events have been a major issue in the last few decades. The results showed in fact, there were considerable differences between both, whereby factoring in the exposure component it is possible to visualize more specific risk zones, which evidences the need to include exposure components in this type of model, as this may allow for more timely responses and disaster risk prevention according to the specific vulnerability conditions in these zones. The outcomes at the minimal geostatistical unit level can aid local decision makers in developing more effective disaster risk management and adaptation strategies to minimize the loss of life and property resulting from extreme weather and climate events in Costa Rica. [ABSTRACT FROM AUTHOR]

As a consequence of global warming, extreme weather events have become much more common in many countries. Extreme weather events negatively impact on mortal social and environmental issues, and recognizing the dynamical aspects of extreme weather is absolutely essential for forecasting and mitigating the implications of extreme weather occurrences on people and the planet. This research looked at the variations in space and time of 11 extreme precipitation indices and 16 extreme temperature indices in the Liaohe River Basin within Jilin Province and their associations with normalized-difference vegetation index (NDVI) and atmospheric circulation indices were evaluated. The results showed that: (1) The extreme warmth index showed a growing pattern and the extreme coldness index showed a declining tendency. The average consecutive dry days and consecutive wet days (CWD) indices showed a slow decreasing trend, and all other extreme precipitation indices showed a slowly intensifying trend. (2) There was a favorable connection between the NDVI and the extreme climate index, and most of the NDVI showed a significant correlation with the extreme temperature index, which shows that the dominant factor causing changes in the NDVI is extreme temperature. (3) The Arctic Oscillation index has a significant effect on extreme low temperatures. The Pacific Decadal Oscillation (PDO) has a large influence on extremely high temperatures. The CWD index in the extreme precipitation index had significant negative and positive correlations with the Southern Oscillation index and the PDO index, respectively. The results of the study contribute to further understanding and forecasting of extreme weather events in the Liaohe River Basin of Jilin Province and provide insights for appropriate measures to reduce the social and environmental impacts associated with extreme weather events in the study area. [ABSTRACT FROM AUTHOR]

Rise in mean temperature put a great deal of uncertainty about how weather and climate extremes may play out, particularly in India's varied climatic zones. Consequently, it is important to understand the possible changes in both magnitude and direction of weather and climate extremes like rainfall for different warming levels of 1.5 and 2°C scenarios concerning preindustrial and present levels. Hence in the present study, the precipitation behavior of seven North Indian states that is, Haryana, Himachal Pradesh, J&K, Punjab, Rajasthan, Uttar Pradesh, and Uttarakhand carefully studied using CMIP5 models. Future projections of precipitation has been done for the Paris Agreement global warming level of 1.5 and 2°C scenarios. Along with model validation and future projections of precipitation, the return period of extreme rainfall is also discussed to understand the behavior of the occurrence of extreme precipitation. Statistical analysis shows that the ensemble means have the least error as compared to the other six CMIP5 models. Therefore, future analysis has been done with the ensemble mean. Our findings show that the precipitation is likely to decrease in the 1.5°C scenarios, while it is likely to increase in the 2°C scenarios. The occurrence and intensity of extreme rainfall events are likely to be more frequent in all the models. The return period of the extreme rainfall events is likely to increase in all the states in both the warming scenarios. A three‐fold rise is likely to increase extreme rainfall events in the 2°C scenario. Key Points: Study performs a detailed analysis of rainfall behavior of the northern states India during preindustrial, present, 1.5 and 2° scenariosSix climate models were selected out of 26 CMIP5 climate models based on the capability of representing the monsoon rainfall over IndiaIn the 2°C scenario, the recurrence period for intense rainfall events will likely to increase by a factor of 3 [ABSTRACT FROM AUTHOR]

Central Oklahoma is undergoing investment in new intermodal transportation and rehabilitation of its infrastructure. Despite a highly variable historical climate, future changes resulting from anthropogenic climate change may be outside of the range for which infrastructure was designed. We examined 21st century trends, focusing on weather and climate extremes of demonstrated importance to transportation professionals as identified through expert input. We assessed trends from a suite of 15 global climate models (GCMs) using two emissions scenarios and two high-resolution statistically downscaled datasets. This ensemble provided a quantitative range for potential future climate conditions whilst revealing uncertainties associated with different models and downscaling methods. Our results support the general consensus of a reduction in the frequency of cold temperatures, freeze–thaw cycles, and winter weather; however, for the latter, there is not necessarily a reduction in intensity. Extreme heat days (e.g., days ≥100 °F) increased by factors of 3–6, with this upper range associated with high greenhouse gas emissions, while the seasonal duration of extreme heat extended by 4–10 weeks. Projected return intervals for heavy rainfall increased in frequency and magnitude in the mid and late 21st century. Although the contribution of the emissions pathway to these changes is evident, different extreme value distributions and the varying simulations of precipitation from the GCMs have a large effect on magnitudes, leading to a range of possible futures to consider in infrastructure design. Precipitation metrics, particularly at the extremes, were more sensitive to the selection of downscaled data, as compared with temperature metrics. Our approach represents a resource for transportation professionals seeking to identify changing risk probabilities at regional to local scales, as a precursor to planning and adaptation. [ABSTRACT FROM AUTHOR]

Climate change is increasing the intensity, duration, and frequency of extreme climate events (ECEs). These ECEs can have major ecological consequences, e.g., changing nutrient flows, causing extirpation, and altering organismal development. Many ECEs are discrete events that occur at distinctive times during the biological processes they impact. Because of this, ECEs are likely to have differing ecological impacts depending on when they happen, yet we lack on studies that explore how the ecological consequences of ECEs vary with when they occur. Drawing upon evidence from physiological, population, and community ecology, and previous work on ecological disturbances, we suggest that the consequences of ECEs will be sensitive to when they occur. We illustrate the importance of timing by showing how the effects of an ECE could vary depending on when it occurs through the course of (1) organismal ontogeny, (2) population dynamics, and (3) community assembly. An enhanced focus on the timing of extreme weather in climate change research will reveal how and when ECEs are altering ecosystems, possible mechanisms behind these impacts, and what ecosystems or species are most vulnerable to ECEs, helping us to make more informed predictions about the ecological consequences of climate change. [ABSTRACT FROM AUTHOR]

Climate change is one of the biggest health threats facing humanity and can directly affect human health through heat waves. This study aims to evaluate excess deaths during heat waves between the summer months of 2004 and 2017 in Istanbul and to determine a definition of heat waves that can be used in the development of an early warning system, a part of prospective urban heat-health action plans. In this study, heat waves were determined using the Excess Heat Factor, an index based on a three-day-averaged daily mean temperature. The death rates during heat waves and non-heat wave days of the summer months were compared with a Z test of the difference of natural logarithms. Thirty heat waves were recorded in Istanbul during the summer months of 2004–2017. In 67% of the heat waves, the death rate was significantly higher than the reference period and 4281 excess deaths were recorded. The mortality risk was especially higher during heat waves of higher intensity. The study showed an excess risk of mortality during heat waves in Istanbul, and the findings suggest that the Excess Heat Factor could be an appropriate tool for an early warning system in Istanbul. [ABSTRACT FROM AUTHOR]

The El Niño Southern Oscillation (ENSO) impacts climate variability globally and can influence extreme climate and weather events. We quantify the uncertainty in ENSO's atmospheric teleconnections with extremes using the Twentieth Century Reanalysis, showing that uncertainty estimates vary regionally over the historical period. Uncertainty is found to be greater in regions of lower socioeconomic development. This can be linked to the limited availability of observational data in these regions as well as difficulties constraining tropical climate dynamics in global gridded atmospheric data sets. Poorer locations face greater challenges due to lack of understanding of past variability limiting confidence in regional projections. Plain Language Summary: Extreme weather events, such as droughts and floods, can be influenced by climate phenomena such as the El Niño Southern Oscillation. El Niño and La Niña events are the biggest drivers of climate variability globally and so it is important to understand their influence on climate extremes. We demonstrate that understanding of how El Niño and La Niña influence extremes is not consistent across the globe. There is the least understanding in the poorest regions of the world. As many of these regions are especially vulnerable to climate change, this has important implications for adapting to the impacts of extremes. Key Points: Uncertainty in historical El Niño Southern Oscillation teleconnections is examined using an ensemble reanalysis productRegional climate responses to El Niño and La Niña are more uncertain in poorer regionsThis inequality in climate information must be addressed to increase resilience to extremes [ABSTRACT FROM AUTHOR]

Developing the engineering design standard of wind speed is a key aspect of the climate research in the Yangtze River Inland Waterway (YRIW), which is highly sensitive to extreme weather and climate processes. An engineering design wind speed projection model was established to evaluate the distribution of extreme wind speeds in the YRIW region at spatiotemporal scales from 1979 to 2100, integrating the Weibull distribution and generalized extreme value (GEV) distribution characteristics. We also used high-precision climate model products and integrated analysis methods to predict the evolution of engineering design wind speeds in the study area in the future. The results show that: (1) The maximum wind speed in the study area shows a decline—recovery trend in the historical period in general and a weak increase in Wuhan and Shanghai. (2) The maximum wind speed does not follow the Weibull distribution, and the extracted extreme wind speed types include type I, II, and III GEV distributions. (3) The updated inland port project design wind speed can meet the climatic and topographic characteristics of the YRIW. (4) The model of CNRM-CM6-1-HR product accurately captures the spatial and temporal characteristics of the maximum wind speed. (5) In the future, the design wind speed shows a slight decrease in Shanghai, Jiujiang and Yueyang. These findings provide a scientific theoretical reference and engineering reference for the development of design wind speeds for inland port projects at various cross-sections in the YRIW. [ABSTRACT FROM AUTHOR]

Climate change-induced extreme weather events have been at their worst increase in the past decade (2010–2020) across Africa and globally. This has proved disruptive to global socio-economic activities. One of the challenges that has been faced in this regard is the increased coastal flooding of cities. This study examined the trends and impacts of coastal flooding in the Western Cape province of South Africa. Making use of archival climate data and primary data from key informants and field observations, it emerged that there is a statistically significant increase in the frequency of flooding and consequent human and economic losses from such in the coastal cities of the province. Flooding in urban areas of the Western Cape is a factor of human and natural factors ranging from extreme rainfall, usually caused by persistent cut off-lows, midlatitude cyclones, cold fronts and intense storms. Such floods become compounded by poor drainage caused by vegetative overgrowth on waterways and land pollution that can be traced to poor drainage maintenance. Clogging of waterways and drainage systems enhances the risk of flooding. Increased urbanisation, overpopulation in some areas and non-adherence to environmental laws results in both the affluent and poor settling on vulnerable ecosystems. These include coastal areas, estuaries, and waterways, and this worsens the risk of flooding. The study recommends a comprehensive approach to deal with factors that increase the risk of flooding as informed by the provisions of both the Sustainable Development Goals framework and the Sendai Framework for Disaster Risk Reduction 2015–2030 in a bid to de-risking human settlement in South Africa. [ABSTRACT FROM AUTHOR]

An anomalous strengthening in western Pacific subtropical high (WPSH) increases moisture transport from the tropics to East Asia, inducing anomalous boreal summer monsoonal rainfall, causing extreme weather events in the densely populated region. Such positive WPSH anomalies can be induced by central Pacific (CP) cold sea-surface temperature (SST) anomalies of an incipient La Niña and warm anomalies in the Indian and/or the tropical Atlantic Ocean, both promoting anticyclonic anomalies over the northwestern Pacific region. How variability of the WPSH, its extremity, and the associated mechanisms might respond to greenhouse warming remains elusive. Using outputs from 32 of the latest climate models, here we show an increase in WPSH variability translating into a 73% increase in frequency of strong WPSH events under a business-as-usual emission scenario, supported by a strong intermodel consensus. Under greenhouse warming, response of tropical atmosphere convection to CP SST anomalies increases, as does the response of the northwestern Pacific anticyclonic circulation. Thus, climate extremes such as floods in the Yangtze River Valley of East China associated with WPSH variability are likely to be more frequent and more severe. [ABSTRACT FROM AUTHOR]

Climate change continues to increase the intensity, frequency and impacts of weather and climate extremes. This work uses bias-adjusted Coupled Model Intercomparison Project Phase six (CMIP6) model datasets to investigate the future changes in temperature extremes over Mediterranean (MED) and Sahara (SAH) regions. The mid- (2041–2070) and far-future (2071–2100) are studied under two Shared Socioeconomic Pathways: SSP2-4.5 and SSP5-8.5 scenarios. Quantile mapping function greatly improved the performance of CMIP6 by reducing the notable biases to match the distribution of observation data, the Climate Prediction Center (CPC). Results show persistent significant warming throughout the 21st century, increasing with the increase in radiative forcing. The MED will record a higher increase in temperature extremes as compared to SAH. The warming is supported by the projected reduction in cold days (TX10p) and cold nights (TN10p), with the reduction in the number of cold nights exceeding cold days. Notably, warm spell duration index (WSDI) and summer days (SU) have a positive trend in both timelines over the entire study area. There is a need to simulate how climate sensitive sectors, such as water and agriculture, are likely to be affected by projected changes under different scenarios for informed decision making in the choice and implementation of adaptation and mitigation effective measures. [ABSTRACT FROM AUTHOR]

Understanding the evolution of heatwaves is important for their prediction, mitigation, and adaptation. While most studies focused on either their temporal variability at individual station (or grid point) or the spatial variation over fixed durations, their daily joint evolution over space and time remains largely unexplored. Here, we investigate multi‐dimensional characteristics of spatiotemporally contiguous heatwaves across China during 1961–2018 using observational data from a 3D perspective (i.e., latitude × longitude × time). Results obtained by the 3D identification show that large contiguous heatwaves in China exhibit distinct characteristics in different geographical locations and time periods. Heatwaves in northern areas prefer to move from west to east at a faster speed, persist longer, and have greater extent and intensity than southern heatwaves, which are generally originated from the east and move westward. It is also found that contiguous heatwaves are growing in frequency, magnitude, areal extent, duration, and traveling distance across China. Plain Language Summary: Known as episodes with temperature exceeding a certain threshold, heatwaves exert severe detrimental impacts on human health. Understanding their joint evolution at both temporal and spatial dimensions is beneficial for us to mitigate the adverse effects and adapt ourselves to future heatwave increases under global warming. However, previous studies mainly focused on either the temporal or spatial changes of heatwaves rather than their co‐variability over both time and space. Here we introduce a new method, the 3D connected component algorithm, to track the 3D evolution of spatiotemporally contiguous heatwaves over China during 1961–2018 using observational data. We find that contiguous heatwaves over northern China prefer to move eastward at a faster speed, persist longer, and have greater extent and intensity than southern heatwaves, which are generally originated from the east and move westward. Contiguous heatwaves show significant increases in frequency, magnitude, coverage, duration, and traveling distance. Key Points: True 3D structure and spatiotemporal evolution of large contiguous heatwave over China are tracked by the 3D connected component labeling algorithmContiguous heatwaves in China exhibit distinct characteristics and evolution patterns in different geographical locations and time periodsSubstantial increases are observed in the frequency, area, magnitude, duration, and moving distance of contiguous heatwaves since the 1960s [ABSTRACT FROM AUTHOR]

Orphan crops are indigenous and invariably grown by small and marginal farmers under subsistence farming systems. These crops, which are common and widely accepted by local farmers, are highly rich in nutritional profile, good for medicinal purposes, and well adapted to suboptimal growing conditions. However, these crops have suffered neglect and abandonment from the scientific community because of very low or no investments in research and genetic improvement. A plausible reason for this is that these crops are not traded internationally at a rate comparable to that of the major food crops such as wheat, rice, and maize. Furthermore, marginal environments have poor soils and are characterized by extreme weather conditions such as heat, erratic rainfall, water deficit, and soil and water salinity, among others. With more frequent extreme climatic events and continued land degradation, orphan crops are beginning to receive renewed attention as alternative crops for dietary diversification in marginal environments and, by extension, across the globe. Increased awareness of good health is also a major contributor to the revived attention accorded to orphan crops. Thus, the introduction, evaluation, and adaptation of outstanding varieties of orphan crops for dietary diversification will contribute not only to sustained food production but also to improved nutrition in marginal environments. In this review article, the concept of orphan crops vis-à-vis marginality and food and nutritional security is defined for a few orphan crops. We also examined recent advances in research involving orphan crops and the potential of these crops for dietary diversification within the context of harsh marginal environments. Recent advances in genomics coupled with molecular breeding will play a pivotal role in improving the genetic potential of orphan crops and help in developing sustainable food systems. We concluded by presenting a potential roadmap to future research engagement and a policy framework with recommendations aimed at facilitating and enhancing the adoption and sustainable production of orphan crops under agriculturally marginal conditions. [ABSTRACT FROM AUTHOR]

The whole world's economy lies in the heavy industry, which is not very saving to the living environment or the people. European Union wants to become an ecologic continent that demands concrete measurements for the single states. In this connection also, climate change is widespread, rapid, and intensifying, and some trends are now irreversible, at least during the present time frame, according to the latest Intergovernmental Panel on Climate Change (IPCC) report. Human-induced climate change is already affecting many weather and climate extremes in every region across the globe. So that, people of the European Union and the world are facing a challenge because there must be a change in each and every one of us. One of the most important measures is to reduce emissions and the amount of waste we produce as humankind, to protect biodiversity and to allow a wide variety of organisms to develop and thrive. The main goal is to find out what the European Union's goals have been in relation to climate change, and at the same time to find out what goals the European Union has set itself in the coming years and how it wants to meet those goals. The main approach of the research was the analysis of the statistical data of greenhouse gas emissions, increasing renewable energy use and better energy efficiency. The analysis of individual Member States is another important part of the work because, thanks to the analysis, we can find out how these countries have met their set goals or, conversely, have not. We can also see how countries are moving closer to achieving long-term goals. According to the results, we concluded that the EU as a whole was able to meet the plan much earlier. We also found which country of the Visegrád Group, for now on V4 fulfilled the plan and which did not. The contribution results could thus contribute to the energy strategy in the EU and chosen states. The results could contribute to the "Earth sanation" from the view of energetic industry sanation, through agriculture, to individual industries. [ABSTRACT FROM AUTHOR]

Evidence for intensifying rainfall extremes has not translated into "actionable" information needed by engineers and risk analysts, who are often concerned with very rare events such as "100‐year storms." Low signal‐to‐noise associated with such events makes trend detection nearly impossible using conventional methods. We use a regional aggregation approach to boost this signal‐to‐noise, showing that such storms have increased in frequency over much of the conterminous United States since 1950, a period characterized by widespread hydrologic infrastructure development. Most of these increases can be attributed to secular climate change rather than climate variability, and we demonstrate potentially serious implications for the reliability of existing and planned hydrologic infrastructure and analyses. Though trends in rainfall extremes have not yet translated into observable increases in flood risks, these results nonetheless point to the need for prompt updating of hydrologic design standards, taking into consideration recent changes in extreme rainfall properties. Plain Language Summary: Numerous studies have shown that heavy rainfall in the United States and elsewhere is becoming more common and more severe in a warming climate. These studies have not shown, however, how the most extreme rainfall events are changing, since these storms are so rare that they are difficult to assess using conventional techniques, which generally focus on changes at individual geographic locations. We instead use a simple aggregation technique to "pool" multiple observations within a region. This "pooling" allows us to show that rainfall events that exceed common engineering design criteria, including 100‐year storms, have increased in frequency in most parts of the United States since 1950—a period of widespread infrastructure construction. We show that in most locations, these increases are likely due to climate warming. We also show that much of the existing and planned hydrologic infrastructure in the United States based on published rainfall design standards is and will continue to underperform its intended reliability due to these rainfall changes. Key Points: Conventional analyses neglect trends in extreme rainfall events such as the 100‐year storm, which are critical for engineering designA regional aggregation approach reveals significant trends in very extreme rainfall in the United States, mainly due to climate warmingExisting hydrologic infrastructure and analyses in much of the United States may be underperforming due to increases in storm activity [ABSTRACT FROM AUTHOR]

Human adaptation to climate change is the outcome of long-term decisions continuously made and revised by local communities. Adaptation choices can be represented by economic investment models in which the often large upfront cost of adaptation is offset by the future benefits of avoiding losses due to future natural hazards. In this context, we investigate the role that expectations of future natural hazards have on adaptation in the Colorado River basin of the USA. We apply an innovative approach that quantifies the impacts of changes in concurrent climate extremes, with a focus on flooding events. By including the expectation of future natural hazards in adaptation models, we examine how public policies can focus on this component to support local community adaptation efforts. Findings indicate that considering the concurrent distribution of several variables makes quantification and prediction of extremes easier, more realistic, and consequently improves our capability to model human systems adaptation. Hazard expectation is a leading force in adaptation. Even without assuming increases in exposure, the Colorado River basin is expected to face harsh increases in damage from flooding events unless local communities are able to incorporate climate change and expected increases in extremes in their adaptation planning and decision making. [ABSTRACT FROM AUTHOR]