Hydrological drought, characterized by prolonged deficiencies in river discharge, presents significant challenges globally, exacerbated by climate change-induced alterations in precipitation patterns. Notably, studies have revealed evolving minimum discharge trends across Europe, yet a research gap persists regarding Bosnia and Herzegovina’s (BH) low-flow phenomena. Here, we investigate minimum discharges in the Una [Van Loon, AF (2015). Hydrological drought explained. Wiley Interdisciplinary Reviews: Water, 2(4): 359–392, https://doi.org/10.1002/WAT2.1085] and Sana Rivers, filling a crucial void in regional low-flow research. Through comprehensive sensitivity analysis and novel trend analysis methods, we identify significant temporal variations and trends in minimum discharges, particularly during winter and summer seasons. Our results indicate distinct patterns in occurrence rates, with the Sana River experiencing notable increases in extreme events during winter. For example, the Sana River witnessed an increase from 15 documented M1 events in the period 1961–1970 to 28 events in the period 2011–2020. Conversely, while the Una River demonstrates stable trends, the Sana River exhibits a significant decrease in severe events. For instance, the occurrence rate of severe events (M2) on the Sana River decreased from six documented events in the period 1961–1970 to four events in the period 2011–2020. Climate change emerges as a key driver, influencing temperature, precipitation patterns, and snowmelt timing, thereby impacting river discharge dynamics. These findings underscore the urgency of adaptive water management strategies to mitigate the potential impacts of changing hydrological conditions on water resources and communities in BH.
Groundwater is an important freshwater resource around the world which supports drinking water supply, agriculture, and industry. Many communities, particularly in low- and middle-income countries, rely on groundwater because it is more stable than surface water. This study investigated the elemental composition of groundwater in Badagry Division, Lagos, Nigeria, to assess water quality and potential health risks. Twelve groundwater samples were randomly collected from major settlements, covering both coastal and inland areas. Twenty elemental components were analyzed, including essential minerals and potentially toxic elements, using Atomic Absorption Spectrophotometry (AAS). Findings revealed that groundwater in Badagry Division has varied quantities of elements, some of which exceed safe levels. Out of the 20 elements examined, 65% met World Health Organization (WHO) and Standard Organization of Nigeria (SON) criteria, while 35% exceeded the allowable levels. Lead, arsenic, cadmium, manganese, sodium, and gallium were all discovered above permissible levels, indicating possible health hazards. Calcium, magnesium, and potassium were all within permissible levels. These exceedances raise serious public health concerns, particularly regarding long-term exposure to heavy metals. The findings underscore the urgent need for groundwater treatment, regular monitoring, and awareness campaigns in Badagry Division. The study provides baseline data, which is important for public health and water policy interventions in the region.
The past 30 years have witnessed a surge in the number of statistical downscaling techniques and applications. However, an absence of standardized approaches across studies has resulted in a bewildering array of methods that likely obstruct the effective use of downscaling in climate risk management. We address these challenges by demonstrating a transparent workflow for benchmarking downscaling methods. This incorporates a protocol for outlining the reference model, calibration criteria, skill diagnostics, and assessment metrics. When downscaling daily rainfall series and extremes in northern Serbia, we find that an automated calibration of our chosen benchmark model (SDSM) generally outperforms manual calibration for skill diagnostics encompassing rainfall occurrence, variability, and extremes. Additionally, we assess the added value of machine learning (ML) methods relative to the same benchmark. Our findings reveal superior performance of these advanced techniques when downscaling extreme rainfall, but less for rainfall occurrence when compared to the benchmark. Overall, the ML downscaling “won” 42% of our diagnostic tests, the automated SDSM 33% tests, and manually calibrated SDSM ranked first for 25% of the tests. This means that the ML methods do add value relative to the benchmark model (here, SDSM). These findings underscore the utility of our workflow, which also enabled us to identify specific avenues for enhancing the tested ML models.
The characterization of extreme events (XE) from time series has witnessed an increase of interest due to the great observational occurrence found in several fields, such as space and environmental physics. Motivated by this challenge, we propose a new parameter space (namely, [Formula: see text]-space) composed of two attributes that identify different classes of extreme fluctuations in a time series. Based on reformulated measures for statistical quantiles and singularity spectra, the distance from the origin in the [Formula: see text]-space characterizes the escape from Gaussianity and monofractality that occurs when extreme fluctuations are present in a time series. To generate time series with different patterns of extreme fluctuations, two canonical systems were carefully chosen as illustrative examples: the so-called p-model for multifractal extreme dissipation and the driven Lorenz chaotic model within an appropriate parameterization scheme. The results show that the investigated attributes can compose a two-dimensional space in which the patterns of extreme endogenous and exogenous fluctuations are distinguished with great precision. The characterization of some observed fluctuation patterns from space and environmental physics is presented as a case of practical application.
Since 2010, several major extreme storm events have struck the Northeastern United States. Most significant of these in terms of extent and damage have been Tropical Storms Irene and Lee in 2011 and Hurricane Sandy in 2012. In addition to their individual impact, the fact that they occurred within a 15-month period (August 2011–October 2012) added extra significance and alerted stakeholders in the region to the increased likelihood of these types of events under the conditions of climate change. The objective of this study is to explore the policy legacies of these extreme events by examining the windows of opportunity they created for institutional learning, governance transformation, and climate adaptation. Using a mixed-method approach, including surveys and policy document analysis, we assess how policy responses varied across regions with different levels of storm impact and how these responses have evolved over time. The findings reveal that while the most heavily impacted areas, like New Jersey and New York, pursued comprehensive and transformative policy changes, even less affected regions perceived a window of opportunity for policy innovation. This extension of policy change beyond the immediate zones of impact highlights the role of collective awareness and inter-regional dependencies in driving adaptation strategies. The study further identifies significant variations in policy legacies across regions, influenced by factors such as perceived risk, resource availability, and political will. Higher-impact areas exhibited a sustained focus on infrastructure resilience and community adaptation, while lower-impact areas showed more limited changes, often centered on enhancing existing capacities. This research underscores the importance of fostering organizational learning and institutional memory to maintain the momentum for policy change and build resilient, adaptive communities in the face of escalating climate risks.
Rising global heatwaves disproportionately endanger elderly populations, demanding targeted interventions. This study explored the strategies of older people living in Tokyo for dealing with heat waves and the efforts and programs of the government to deal with the threat of heat waves using field research (interviews) and document review methods. The study identified policy gaps in information dissemination and age-specific adaptations, examined Tokyo’s healthcare initiatives, which reveal infrastructure potential yet highlight critical failures in grassroots awareness and facility utilization. The study suggests that effective solutions require community-engaged platforms, improved risk communication, and adaptive urban planning. The study contributes actionable recommendations for policymakers to develop age-inclusive climate adaptation strategies, emphasizing the urgent need for improved risk communication and feedback mechanisms to protect aging populations in warming cities nationally and globally.
A common theme across the globe is off-the-mark extreme weather warnings that lead to significant social, economic, physical, and environmental damages and, more broadly, the loss of public trust. The question is, how can the weather warning system be improved? The study is based on recent extreme weather-related warnings in Canada, including the 2021 tornado warning in Barrie, Ontario [CBC News (2021). Barrie, Ont., devastated by tornado that left 5-kilometre-long path of destruction, CBC News, Retrieved from https://www.cbc.ca/news/canada/toronto/barrie-tornado-ef-2-clean-up-1.6105258 .], the 2021 severe flooding due to atmospheric river phenomenon in British Columbia [Vancouver S (2021). Significant atmospheric river causing rainfall warnings across southern BC. Retrieved from https://vancouversun.com/news/local-news/significant-atmospheric-river-causing-rainfall-warnings-across-southern-b-c .], the 2023 tornado warning in Ottawa, ON [CBC News (2023). Tornado in Barrhaven damages about 125 homes, CBC News, Retrieved from https://www.cbc.ca/news/canada/ottawa/tornado-ottawa-barrhaven-july-13-1.6905782 .], and in 2023, flood alerts were found to be confusing and distracting in response efforts in Nova Scotia. Environment and Climate Change Canada (ECCC), a federal agency, monitors weather through instruments, radar, and satellite coverage. News outlets, media platforms, emergency management professionals and other stakeholders use this information in their work, functions and services. This research attempts to identify root causes for inefficiencies and areas for improvement in the Canadian system of extreme weather forecasting and warnings and their communication to the public. The approach to achieve this objective includes examining the current warning system, reviewing the fundamentals of risk communication, and in-depth interviews with broadcast meteorologists who routinely deliver the weather to the public across Canada.
As coasts are increasingly affected by the impacts of climate change, such as flooding associated with sea level rise, extreme precipitation events, and storm surges, many coastal communities are facing damages to infrastructure and property. Within the United States, at the federal and state scales, there are various programs dedicated to funding and facilitating sea level rise resilience and adaptation measures as well as public outreach. However, at the local scale, coastal adaptation is done primarily via development restrictions and individual projects that construct green, gray, or hybrid infrastructure. This analysis assessed the coastal hazard efforts that local governments in New Jersey are communicating to the public on their websites to assess the preparedness of coastal municipalities in confronting climate change and look at the relationships between specific factors. Data were collected directly from the websites of 24 local governments located in coastal New Jersey in the first half of 2019. Websites mentioned a wide variety of flood risk management programs with participation in the United States National Flood Insurance Program, applications for grants, development restrictions, and funding for housing retrofit and adaptation measures being mentioned significantly more frequently in locations with higher flood risk. No websites mentioned managed retreat or buyout programs. The projects most frequently mentioned as being planned, in progress, or completed were stormwater management (62% of communities) and road improvements (50% of communities). A climate adaptation index based on cumulative project planning and completion had a bimodal distribution with roughly half of communities being fairly active in terms of reported adaptations to climate change, while the other half reported fewer actions. Coastal flood risk appears to be a main determinant of local action, with political lean and population not observed to have significant effects.
This paper investigates the spatio-temporal trends for different return periods of extremely significant wave height (SWH) in the Bay of Bengal (BOB), Indian Ocean based on a 40-yr (1979–2018) wave hindcast. High-resolution reanalysis of wind field datasets is used to force a spectral wave model WAVEWATCH III (WW3). The wave hindcast information is validated using satellite data gathered from the European Centre for Medium-Range Weather Forecast (ECMWF) Era-Interim. The model performance is adequate. Findings showed that trends for the 5–100-yr return periods of the 99th percentile wave height are significantly strong and range between 0.1[Formula: see text]m yr[Formula: see text] and 1.4[Formula: see text]m yr[Formula: see text] in the northeastern islands of the sea. Weaker trends (0.06–0.6[Formula: see text]m yr[Formula: see text]) exist in the western region of the sea while insignificant and negative trends dominate the rest waters. For the 2-yr return period, negative trends were distributed all over the sea. Temporal trend analysis for each of the return periods revealed insignificant and negative trends in all cases.
Rain is the lifeblood of the Sudanese economy; therefore, rain studies are of concern to many researchers. This study is a continuation of previous studies. This study was conducted to determine the changes in extreme rainfall indices in Sudan from 1981 to 2020, as well as to determine the relationship between extreme rainfall indices and rainfall drivers, such as El Niño Southern Oscillation and Indian Ocean Dipole (ENSO/IOD). We used satellite daily rainfall data (CHIRPS). The study found that June to September (JJAS) had the highest rainfall rate. According to the rainfall rate data, we chose Consecutive Wet Days (CWD), Maximum 5-day precipitation (RX5day), and Severe precipitation days (R20mm) to represent the indices that have been calculated. To evaluate the index results, we divided the targeted stations into four categories for discussion (Type 1, Type 2, Type 3, and Type 4). For the stations included in each class, we calculated the average of the three indices to obtain the average precipitation index of these classes. This study aimed to investigate the relationship between extreme rainfall indices and rainfall drivers like ENSO/IOD. The study found variability in extreme rainfall indices during the study period, and this variability was distributed from south to north according to the climatic zones. In addition, there is a strong relationship between extreme rainfall indices and drivers, particularly during winter.
This study examines how prior experience with tornados and predicted warning lead times of severe weather may influence one’s willingness to take protective action when a potential tornadic event is imminent. Using theoretical constructs from the Protective Action Decision Model and Risk Information Seeking and Processing model, the project examines how individuals make decisions about taking protective action and what factors motivate them during severe weather. The overall focus of the study is the impact of prior experience with tornados, geographic location and amount of warning lead time on an individual’s likelihood to prepare for potential severe weather. A survey of 679 mid-south residents provided insight into their perceptions of warning language and events. Results indicated that individuals who live in rural areas and those who have more prior experience with tornadic events are more likely to engage in protective behavior. Further, an interaction was noted, indicating those with more prior experience with tornados reporting that they needed less warning lead time to prepare when compared to those with less prior experience, who reported they wished for more lead warning time. Finally, definitions of “tornado warning” noted that more than half of participants did correctly identify its meaning.
Warning systems enable timely communication of risk during disasters. This study examines the relationship between planning and warning, as well as their effect on capacity in island communities. The study establishes planning as a form of warning and uses empirical evidence from a natural experiment, Hurricane Maria in Puerto Rico (2017), to describe how planning functions as a warning process before, during, and after a disaster. Qualitative interview and participant observation data were gathered before and after the storm event. The study finds that planning, like warning, translates knowledge of risks into appropriate courses of protective action to reduce human suffering. Island communities, which tend to be under-resourced before, during, and after disasters, can benefit from operationalizing planning as a form of warning to build capacity and resilience.
Journal of Extreme EventsOnline Ready Open AccessEDITORIAL: CASCADE-NET — Increasing Civil Society's Capacity to Deal with Changing Extreme Weather Risk: Negotiating Dichotomies in Theory and PracticeLindsey McEwen, Robin Leichenko, Joanne Garde-Hansen, and Tom BallLindsey McEwenUniversity of the West of England, Bristol, UKCorresponding author., Robin LeichenkoRutgers University, USA, Joanne Garde-HansenUniversity of Leeds, UK, and Tom BallUniversity of Winchester, UKhttps://doi.org/10.1142/S2345737623020013Cited by:0 (Source: Crossref) Next AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail FiguresReferencesRelatedDetails Recommended Online Ready Metrics History Published: 19 December 2023 Information© The Author(s)This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC BY) License which permits use, distribution and reproduction in any medium, provided the original work is properly cited.PDF download
This paper proposes a critical reflection on the use of language to address the challenge of promoting and supporting civic agencies in adaptation to increasing extreme weather risk. Such reflection needs to focus on the opportunities and limitations of language, and the navigation amongst multiple or contested meanings within interdisciplinary and inter-sectorial collaborations. This commentary was inspired by the authors’ conversations on their journey in writing the paper — Liguori et al. (2023) “Exploring the uses of arts-led community spaces to build resilience: Applied storytelling for successful co-creative work” and the impact it had on their understanding of various language systems. Here writing was conceived as a form of networking, undertaking a sequence of intimate, in-depth discussions in a safe space. ‘Playing’ with words, moving out from our disciplinary homes, provided a fertile way of thinking within multi/inter-sectorial/disciplinary conversations to expand the language system for meaningful community engagement around local climate adaptation. Three key terms were at the core of these diverse — and sometimes divergent — ways of looking at social preparedness for extreme weather events: disruption, empowerment, and creative ecosystem. The meta-reflections, based on iterative conversations around these three key terms, highlight the importance of explorations of language as a generative meaning-making process that can be boundary-spanning. There is significant value in understanding the implications of language used in public engagement — its different interpretations, their loading and potential for transformed thinking when conceived creatively. Such insight can contribute to more effective approaches for participatory research and practice working with communities when addressing issues related to climate adaptation. This commentary argues that the socially engaged or participatory arts are particularly well placed to be active in such processes.
The North American Multi-Model Ensemble (NMME) has grown into a fully developed scientific database for seasonal and sub-seasonal climate forecasts, progressing prediction from global to regional scales. The NMME has continuously developed, with new models replacing old ones; it is hypothesized that this development will generate more accurate forecasts over time. However, to date, this hypothesis has not been verified in Central Africa (CA). This study investigates the hypothesis that the skill of NMME models will increase as the forecasting system advances, focusing on rainfall in CA. The study is conducted for the four configuration (phases) of NMME models, from the oldest to the most recent. The analyses are performed with Short Lead (SL) time and Long Lead (LL) time hindcasts very coherent with the perspectives of the CA. The results show from configuration 1 (phase 1) to configurations 4 (phase 4), the NMME models reasonably replicate the spatial structures in the seasonal rainfall climatology of the observations with a remarkable bias at LL. The mean absolute error and root mean square difference reveal small but incremental improvements in the prediction skills of NMME models from phase 1 to phase 4. The Pearson coefficient (r) increased in SL by about 1%, i.e., from 0.94 to 0.95 during June–August (JJA) season and about 4% during the September–November (SON), i.e., from [Formula: see text] in phase 1 to [Formula: see text] in phase 4, about 3% from phase 1 to phase 4 during the March–May (MAM). The categorical scores show that the Probability of Detection (POD) and False Alarm (FAR) increased very slightly from phase 1 to phase 4, but is it noted that the different combinations of the NMME forecasting system present difficulties in predicting rainy and dry events. It should be added that by introducing newer models into a multi-model ensemble as they are developed, and by eliminating older models, small skill gains are observed in the NMME forecasting system in CA.
This research delves into the factors contributing to tornado formation in South Africa, with a specific focus on the Klerksdorp tornado that occurred on March 4, 2007, in Northwest Province. Despite their recurrent occurrence and significant potential for damage, tornadoes have received relatively little attention. Between 1990 and 2014, these weather phenomena incurred estimated costs exceeding half a billion American dollars in addition to other weather-related disasters. In this study, data from multiple observation systems, including the National Oceanic and Atmospheric Administration (NOAA), the National Centers for Environmental Prediction (NCEP), the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) in Germany, and the South African Weather Service (SAWS), were thoroughly analyzed. The findings reveal that the Klerksdorp tornado was linked to a cold front and a cut-off low, which were the dominant weather systems on the day of the tornado. This case study enhances our comprehension of tornado dynamics in South Africa, aiding in improving short-term forecasts and potentially early warning systems. Future research should concentrate on the recurring nature of tornadoes in association with tropical weather systems and locally-driven factors.
In this study, the wind shear vector variability likely to mitigate the flights activities at the Cameroon Airport and in particular Garoua has been analyzed. This research is based on a statistical method R of pilot probe and observation synoptic station data, April–July 2021 period. The results show that Garoua Airport has recorded more than 55 percent of the intensities of the wind shear vector greater than 10 kt/100 ft with dominant directions in the North-South sector. The intensities of the headwind/tailwind shear vector are at 60 percent moderate; the probability density distribution shows 40 percent strong to very strong shear with moderate to strong probability. This fact may represent a problem for lighter aircrafts, whose crosswind rates are lower. In this context, the forecast of high wind speed values and directions becomes very important. The schedule distribution of the various wind during this period displays that the most sheared month is the month of May, the sounding that presents the strongest to very strong shears is that of 5 p.m. and the most sheared slice is the ground surface layer where the frictional force has a very large impact on the wind. In addition, the convective system’s formation and the geographical discontinuities effects contributed to the recording of shear types during the period not only at ground level but also at the superior levels.
Within the themes of CASCADE NET, this paper focusses on less heard voices and the need to develop new social spaces. Disaster vulnerability identifies diversity in society through a lens of constraints to solutions, on such bases as demography, socio-economic status, cultural, ethnic and gendered minorities within society, and marginalized groups as well as physical proximity to a hazard. The focus of disaster risk reduction is on building resilience through the strengths and capacities in society, but it has a tendency to homogenize characteristics of resilience to the community level, thereby flattening and hiding diversity. LGBTQ people are largely ignored as minority groups with specific information needs. Specific response and recovery processes and actors exacerbate the vulnerability of the LGBTQ minority, especially in evacuation, support, counselling, and rehousing. The role of faith-based organizations (FBO) in providing these services during disaster relief and recovery is examined in this paper. This paper identifies and critiques the attitudes and practices of some FBO towards LGBTQ groups in their provision of disaster relief services.
Climate change-related extreme weather events are becoming more frequent and severe, requiring urgent action to effectively plan for them. While disabled women are one group likely to be disproportionately and negatively affected by disasters, they are often not included in disaster planning. This commentary paper utilizes McRuer’s Crip Theory as a lens to explore this topic, where the strength of disabled women’s capacity to positively contribute to effective disaster planning becomes evident. Their lived understandings of negotiating often unacknowledged barriers can act as useful tools to assuage the impacts of disasters. Their experiences are recognized under the rubric of crip theory as neither deviant nor “other”, but as capabilities worthy of mainstreaming. Disaster situations that may be seen as chaotic to those accustomed to services and environments that closely match their requirements, could be perceived as both familiar and resolvable to a disabled woman. In this way, disabled women can utilize their everyday problem-solving skills to help tackle these impacts, viewing them as circumstances to be methodically navigated and overcome. Enabling disabled women room at the planning table is neither luxury nor bonus, but essential. Participatory inclusion and successful planning for disabled individuals benefits a much larger swathe of society than initially anticipated, as illustrated in this paper by international examples of best practice. We all profit from more inclusive planning to create more accessible and inclusive communities.
Wildfires can be devastating for social and ecological systems, but the recovery period after wildfire presents opportunities to reduce future risk through adaptation. We use a collective case study approach to systematically compare social and ecological recovery following four major fire events in Australia and the United States: the 1998 wildfires in northeastern Florida; the 2003 Cedar fire in southern California; the 2009 Black Saturday bushfires in Victoria, southeastern Australia; and the 2011 Bastrop fires in Texas. Fires spurred similar policy changes, with an emphasis on education, land use planning, suppression/emergency response, and vegetation management. However, there was little information available in peer-reviewed literature about social recovery, ecological recovery was mostly studied short term, and feedbacks between social and ecological outcomes went largely unconsidered. Strategic and holistic approaches to wildfire recovery that consider linkages within and between social–ecological systems will be increasingly critical to determine if recovery leads to adaptation or recreates vulnerability.
