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We present an application of quantile generalized additive models (QGAMs) to study spatially compounding climate extremes, namely extremes that occur (near-) simultaneously in geographically remote regions. We take as an example wintertime cold spells in North America and co-occurring wet or windy extremes in Western Europe, which we collectively term Pan-Atlantic compound extremes. QGAMS are largely novel in climate science applications and present a number of key advantages over conventional statistical models of weather extremes. Specifically, they remove the need for a direct identification and parametrization of the extremes themselves, since they model all quantiles of the distributions of interest. They thus make use of all information available, and not only of a small number of extreme values. Moreover, they do not require any a priori knowledge of the functional relationship between the predictors and the dependent variable. Here, we use QGAMs to both characterize the co-occurrence statistics and investigate the role of possible dynamical drivers of the Pan-Atlantic compound extremes. We find that cold spells in North America are a useful predictor of subsequent wet or windy extremes in Western Europe, and that QGAMs can predict those extremes more accurately than conventional peak-over-threshold models. In this paper we propose a new data-driven method to study climate extremes occurring simultaneously in multiple, possibly remote, locations. Such extremes can pose a greater threat to human societies than single, isolated extremes, as their effects may exacerbate each other and lead to correlated losses. The method we suggest requires fewer assumptions than conventional extreme value statistical techniques, and can help us to identify previously unknown relationships between the extremes themselves and their possible drivers. We exemplify its use by studying the co-occurrence of periods of unusually cold weather in North America and subsequent uncommonly

Extreme weather events linked to climate change are becoming more frequent. The online public discourse on and during these events, especially on social media, attracts misinformation that can undermine short-term emergency responses, but can also be aimed at influencing long-term public perceptions of climate change. This contribution reviews existing research on online misinformation with the aim to understand the types, origins, and potential impacts of misinformation during extreme weather events like storms, floods, and wildfires. The screening of 289 publications reveals that there is scarce body of only 13 studies addressing this question. Relevant studies exploring online misinformation during extreme weather events rarely document misinformation immediately relevant for emergency responses and only recently link this to the discussion about climate change. The reviewed research provides however insights to derive a framework that can guide future research into this topic. Specifically, that misinformation in social media during environmental emergencies 1) cuts across domains and merges different areas of public interest, 2) cuts across temporal and geographical scales, and 3) needs to be studied as part of an interconnected online media landscape. Misinformation differs between emergency event types, can undermine the debate about climate change in diverse ways, appeal to completely different audiences and thus will likely require different responses and countermeasures. Structured research with comparable methodologies is urgently needed.

The existing body of research into the environmental and socio-economic benefits of green infrastructure supports the case for it to be positioned as a form of critical infrastructure, particularly in urban settings. It is broadly recognized that extreme weather and climate change pose significant risks to critical infrastructure systems linked to the provision of services, including electricity, water, communications, and transport, and consequently risk assessments and associated adaptation strategies are common practice. However, although green infrastructure is also at risk from extreme weather and climate change, threatening the realization of benefits that it can deliver in urban settings, associated risks to green infrastructure are not widely understood or assessed in practice. This paper discusses the status of existing research on this topic and uses this as a foundation for a Greater Manchester (UK) case study that assesses the risk of low water availability to grassed areas, which represent a key element of the city-region’s green infrastructure. In doing so, the paper demonstrates how risks linked to extreme weather and climate change can be assessed spatially to inform green infrastructure planning. In summary, this paper aims to raise awareness of extreme weather and climate change risk to urban green infrastructure, present an empirical case study and associated methodological approach on this topic, and ultimately support efforts to enhance the resilience of urban green infrastructure to extreme weather and climate change.

Climate change and climate instability driven by anthropogenic fossil fuel emissions areincreasing the frequency and severity of extreme weather events. One such event, heat waves, are becoming more frequent, intense and prolonged (Meehl and Tebaldi 2004; Stillman 2019; Thiery et al. 2021). Extreme heat associated with these heat waves may be particularly damaging to critical species life-history events such as reproduction and mating, and also interactions between organisms (Vasseur et al. 2014; Harvey et al. 2023). Heat may especially impact plant- pollinator interactions and the mating of flowering plants, as heat may disrupt the process of pollination and alter the stable dynamics of mating (Hedhly et al. 2009; Walters et al. 2022; Hemberger et al. 2023). Importantly, heat may disrupt plant-pollinator interactions and successful mating directly through heat’s effects on flower gamete production and performance (Hedhly et al. 2009), but also indirectly through heat’s effects on foraging pollinators (Walters et al. 2022; Hemberger et al. 2023). My dissertation is divided into three chapters with the aim of understanding methodically how heat impacts the ecology of pollination and floral reproduction. Chapter 1 used experimental pollination treatments explicitly focusing on the perspective of the plant to understand how heat affects the dynamics of pollen limitation-the reduction in potential seed production through insufficient receipt of or pollen that is incapable of fertilizing ovules. It evaluates how heat may simultaneously influence the quantity of pollen grains produced and the quality of those pollen grains in addition to pollen quality effects inherent to pollen origin (self versus outcross). I found that heat dramatically limited pollen production, and the quality of pollen grains measured as its viability and performance to grow pollen tubes and fertilize ovules. Although outcross pollen was of higher quality than self pollen under control conditions, h

Extreme weather has a direct and significant impact on buildings and infrastructure, resulting in billions of dollars of damage each year. This problem continues to grow as climate patterns change and buildings are exposed to new and different hazards than what they were designed to withstand. In order to better plan for the long-range sustainment, restoration, modernization, and eventual recapitalization of these buildings, organizations with large building portfolios, such as the U.S. Department of Defense (DoD), must have an awareness of the risks that these extreme weather events present. This research aimed to develop an approach to estimate condition loss and reduction in service life for the components of a building due to extreme weather hazards, to understand the risks that may be present in certain buildings and building systems. To achieve this objective, a damage association matrix was developed that categorizes climate hazards, the damage modes that they produce, and the individual component types impacted. This damage matrix formally links state-of-the-art climate model output, which provides projections of the probability of various climate hazards with a damage effects model that quantifies the consequence on component-level condition and service life. This method is applied to an actual portfolio of buildings in a particular geographic location and with a pre-defined component inventory that comprises the building. This approach can be aggregated to the system-, facility-, and site-level thus helping support billions of dollars in recapitalization decisions related to restoration/modernization of facilities.

The immense attention to climate change risk has stimulated increasing interest in carbon markets and their linkages to other markets. This study investigates the dynamic volatility spillover relationships between the Chinese carbon and international energy markets, and the impact of extreme weather events on the relationships. Empirical results show that the risk is transferred from the international gas (GAS) and crude oil (OIL) markets to the Chinese carbon market (GDC). The total volatility spillover among markets and the net spillover of GDC with other markets both have obvious periodicity. The shocks from extreme weather events and extremely high temperatures can amplify the trading volume of GDC, and strengthen the fluctuations of GDC, ultimately turning GDC from a risk receiver to a risk transmitter. The portfolio strategies based on the reversal phenomenon can achieve higher average returns compared to the Chinese and EU carbon markets. In addition, the shocks of the Sino-US trade war, the Covid-19 outbreak, the COP 26 and the Russo-Ukrainian war have different effects on the volatility spillovers among markets. Economic and policy implications for investors and regulators are also provided along with these findings. © 2024 Elsevier Inc.

In several parts of Sweden, difficulties arise regarding access to water. In this article, I explore the biopoliticsthat take shape when low groundwater levels are turned into an object of government. Firstly, I examinethe formation of a so-called anatomical politics which refers to a disciplining form of power in which theresponsibilities and actions of the population are at the center. Secondly, I explore the priorities that are madein the political work where human life, health, and well-being are to be protected and other life forms that arenot vital for human living are instead deprioritized or allowed to die. The problems have clear consequencesbut do not pose a threat to human survival. Political efforts aim to bring about changes in people’s everydaylives and affect the use and decoration of households and public spaces. Empirically, I attach particularsignificance to the irrigation bans that Swedish municipalities can introduce to reduce water consumption., QC 20240503

Den ökande växthuseffekten påverkar klimatet såväl som vädret. I framtiden väntasextremväder bli fler och kraftigare och stora nederbördsmängder som skyfall väntas öka.Konsekvenserna av detta är bland annat att risken för översvämningar till följd av nederbördökar, något som riskerar att skada både materiel och hälsa. I Sverige är kommunernaansvariga för att leda bort bland annat dagvatten från områden med samlad bebyggelse.Denna rapport syftar därför till att undersöka hur ett urval av Sveriges kommuner arbetar medskyfalls - och dagvattenhantering i ett förändrat klimat. De kommuner som undersöks har givetvis olika förutsättningar och prioriteringar, mensamtliga arbetar förebyggande för att förhindra översvämningar orsakade av skyfall och att detar höjd för väntade ökade nederbördsmängder i sina beräkningar. Strategierna och åtgärdernade vidtar i sitt förebyggande arbete skiljer sig något åt, men liknande arbetsmetoder kan ivissa fall urskönjas. Svenska kommuner står inför flera utmaningar kopplade till skyfallsfrågan där den mestframträdande är den befintliga lagstiftningen som är bristande och otydlig, främst gällandeansvarsfördelning. Vidare förekommer andra utmaningar som att få in skyfallsfrågan ipolitiken och kommunalarbetet jämte andra befintliga problem. Ytterligare utmaningar somkommunerna står inför är kopplade till ekonomi och samverkan med andra aktörer., The increasing greenhouse effect affects both the climate as well as the weather. In the future,extreme weather is expected to become more frequent and intense. Furthermore, the amountof precipitation associated with heavy rainfall is expected to increase as well. Theconsequences of this include an elevated risk of flooding due to heavy rain, which poses athreat to both property and health. The Swedish municipalities are responsible for managingstormwater runoff in densely populated areas. This report aims to investigate how a selectionof Sweden’s municipalities work with stormwater and flood management in a changingclimate and what challenges they face. The municipalities being studied naturally have different prerequisites and priorities, but allof them take preventive measures to mitigate flood risks caused by heavy rainfall and accountfor expected increases in precipitation in their calculations. The strategies and actions theytake in their preventive work may vary slightly, but similar approaches can be observed insome cases. Swedish municipalities face several challenges related to stormwater issues and heavyrainfall. The most prominent one is the existing legislation which is unclear, particularlyregarding the allocation of responsibility between the municipalities, the government andprivate actors. Other challenges include integration of the stormwater concerns into politicsand already existing municipality work. Additionally, municipalities face challenges relatedto finances and collaboration with other actors to adapt cities to a changing climate and moreextreme weathers.

This work aimed to understand active mobility's role in urban mobility resilience. It analysed existing attempts to connect the concept of resilience with transport and mobility, focusing specifically on work that underlines the role of active mobility for resilient transport systems. It started with an extensive overview of various definitions of resilience and resilience in transportation. By selecting and comparing the most relevant definitions, this thesis proposed two measurable indicators for analysing resilience in urban mobility. The quantification of these two indicators was improved based on earlier formulations focusing on providing measurement with sensitivity analysis. The two indicators were then applied in a case study where the transport infrastructure was disrupted rapidly and severely by a flood that occurred in 2023 in New York City to assess the role of bike sharing in contributing to urban mobility resilience. Using the metro and the bike-sharing ridership data from the New York City Metropolitan Transport Authority, survivability and robustness indicators were calculated and compared for different intervals of time aggregation. It was found that the Citi Bike sharing system (BSS) appeared to be more robust than the metro infrastructure, recovering faster. On the contrary, the BSS survived less than the metro, sustaining a larger decrease in relative ridership compared to the metro. By varying the aggregation of time interval from one hour to a day, the numerical values for survivability and robustness indicators change, but the outcomes hold. These results suggest that the BSS users are more vulnerable since they rely on the surface transport infrastructure and are directly exposed to weather events. Despite this, active mobility could play a positive role in the resilience of urban mobility by returning to functioning in shorter times compared to the metro system, which can take longer to return fully operational. Although the hypothesis that

In this thesis I aim to determine the importance of extreme weather experience in Swedish farmers crop mix decisions. In this way, I add to the evolving field of climate change impacts on farmer livelihoods with a specific focus on perception of risk and locational vulnerabilities. I develop a simplified measure for locationally specific vulnerabilities and position these against the actual crop mixes that Swedish farmers have chosen, to test the influence of extreme rainfall exposure on decision making. My data builds off the Land Parcel Identification System (LPIS) Database of farm and crop extents for 99% of Swedish agricultural land between 2015 and 2023, and climate data from a large-scale meteorological assessment across Europe. I also account for environmental characteristics that may affect vulnerability and the perception of risk via soil characteristics. I use these data to map functional diversity changes at the farm level over the period, and also for estimating mixed models with two way interaction terms. Based on an adapted Protection Motivation Theory (Rogers, 1975), I expect that farms that are more exposed to an increased frequency of extreme weather events (rainfall over the 95th and 99th percentile) year on year, would diversify their crop mix as a risk mitigation practice. However, I find that on average, previous exposure to extreme weather has essentially no effect on the level of diversity a farmer chooses to pursue. When decomposing these findings into different farmer types and environmental conditions there is a moderate level of heterogeneity such that farmers that are more able to take adaptive measures, do. Also, farmers that have planted more diverse farms in the past tend to continue doing so. While those that trend toward less diverse crop mixes tend to respond to exposure by further specializing their crop mixes. These findings suggest that there is a weak underlying preference for higher levels of diversity among Swedish farmers, ho

The urgency of addressing housing challenges in low-income areas is increasing due to widening socio-economic inequalities and the worsening impact of natural disasters. Saint Martin, a small Caribbean island, is struggling to provide affordable housing amidst hurricanes, floods, and heat waves. As a result, there has been a rise in self-organized housing units, which are built incrementally and are susceptible to risks. The main challenge is to balance durability, functionality, and esthetic appeal over time. Inspired by St. Martin’s self-organized units, this article explores housing considerations in low-income, hazard-prone contexts by emphasizing their temporalities. Integrating insights from a formative study, including a literature review and ethnographic research, the paper draws on Stewart Brand’s “Layers of Change” and the concept of “Flow”. The study identifies layers within self-organized units corresponding to durability, functionality, and esthetic appeal. It delves into their connection with building activities over time, unveiling the temporalities of housing considerations. This exploration leads to the proposition of “Designing for a Flow” as a novel design approach. Offering practical insights within a concise framework, the study provides nuanced perspectives on mitigating housing challenges in low-income and hazard-prone contexts., Architectural Technology, Space & Type, Management in the Built Environment

In Sweden, municipalities and municipal planning are central to the government’s preparedness for climate-related risks, as municipalities are the organizations that will largely have to adapt to and prepare for climate change. However, there is little government guidance in the form of clearly formulated policies, policy objectives, and detailed regulations to support municipalities in this work. In practice, municipal officials are tasked with developing climate preparedness, including facilitating citizen awareness of the need to prepare for climate-related risks. By exploring the local level of Swedish public administration, which in practice has to deal with different and sometimes divergent understandings of a situation and who should manage it, the paper explores the implications of officials’ meaning-making about local risk governance. An exploratory approach to risk governance and meaning-making rationality is used to examine Swedish municipal officials’ views of citizens’ climate crisis preparedness and the motives and barriers they perceive the citizens to have in developing this preparedness. An interview study is conducted with 23 officials in 5 municipalities. Based on the results, the paper discusses the implications of the perception that citizens have no constructive role to play in the work to better prepare municipalities for climate change. The paper concludes by discussing how officials’ meaning-making rationality needs to be addressed in the development of robust climate preparedness., Digital urban risk communication

Since the 1960's, Portugal has been affected by profound land use/land cover changes, which have boosted fuel continuity and fire-proneness nationwide. Within this context, the assets of pulp paper companies are exposed to large wildfires, which may cause severe economic losses. Wildfire simulations can help to scenarize and anticipate fire spread, contributing to efficiently allocate resources to protect values at risk. To test this framework, we assessed wildfire hazard in a 115,000 ha landscape, including 3,720 ha owned by two companies, with the aim of identifying the management units most exposed to large wildfires and the ones most at risk. We used Minimum Travel Time algorithm to estimate Burn Probability (BP), Fire Size (FS) and Conditional Flame Length (CFL). Wildfire hazard and exposure were assessed at the landscape-level; risk was estimated in production eucalypt plantations, by combining the annual BP with potential economic losses, based on management costs, loss of revenue and salvage wood. Our results showed that eucalypt plantations not managed by the companies represent a major threat to their patrimony. Industrial plantations with ages between 6 and 9 years have proven the most exposed. Very large wildfires (≥5,000 ha) can potentially spread in 53 % of the landscape, affecting 75 % of young eucalypt (<5 years) area. The 90 percentile of the risk ranges from 213 to 429 €ha year (9.6 % of production eucalypt area). This work resulted in a flexible methodology, replicable in Mediterranean regions with similar landcover. The information produced can provide additional guidance for wildfire prevention and risk management.

Understanding the impact of climate change on cities is fundamental to address the increasing occurrence of extreme weather events. This research aims to raise awareness and emphasise the need and potential of proactive measures to mitigate the adverse effects of climate change. To do so, this article conducts a case study for a huge snowfall that occurred in the city of Madrid (Spain) in January 2021, blocking the city for several days. The analysis is based on geolocated big data sourced from Google Popular Times (GPT), which captures the occupancy of establishments throughout the city over the entire study period. An exploratory spatial-temporal analysis has been conducted to examine the impact of the snowfall on the daily activities of the city, taking into consideration the demographic characteristics. The findings reveal a distinction in the impact of the snowfall on activities. Essential activities experience less impact compared to leisure activities. Furthermore, at the socio-economic level, the impact on low-income neighbourhoods is observed to be less affected than on high-income neighbourhoods. The implications of this research contribute to the body of knowledge on climate change resilience and adaptation, providing valuable insights for urban management strategies and informing future research in this field., Agencia Estatal de Investigación, JST SICORP, Depto. de Geografía, Fac. de Geografía e Historia, TRUE, pub

Global gridded data sets of observed extremes indices underpin assessments of changes in climate extremes. However, similar efforts to enable the assessment of indices relevant to different sectors of society have been missing. Here we present a data set of sector-specific indices, based on daily station data, that extends the HadEX3 data set of climate extremes indices. These additional indices, which can be used singly or in combinations, have been recommended by the World Meteorological Organization and are intended to empower decision makers in different sectors with accurate historical information about how sector-relevant measures of the climate are changing, especially in regions where in situ daily temperature and rainfall data are hard to come by. The annual and/or monthly indices have been interpolated on to a 1.875° × 1.25° longitude-latitude grid for 1901–2018. We show changes in globally-averaged time series of these indices in comparison with reanalysis products. Changes in temperature-based indices are consistent with global scale warming, with days with Tmax > 30°C (TXge30) increasing virtually everywhere with potential impacts on crop fertility. At the other end of the scale, the number of days with Tmin < −2°C (TNltm2) are reducing, decreasing potential damage from frosts. Changes in heat wave characteristics show increases in the number, duration and intensity of these extreme events in most places. The gridded netCDF files and, where possible, the underlying station indices are available from, All software, with the exception of Climpact2 which is in R (Ihaka & Gentleman, 1996; R Core Team, 2013), have been written in Python 3 (Python Software Foundation, 2013). The dependencies and interplay between them have been controlled using a Rose (Shin et al., 2019)/Cylc suite (Oliver et al., 2018). RJHD was supported by the Met Office Hadley Centre Climate Programme funded by DSIT and by the UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China under the International Science Partnerships Fund (ISPF), and thanks Kate Willett, Lizzie Good and Nick Rayner for useful discussions and comments. LVA was supported by Australian Research Council Grant CE170100023. MGD is grateful for funding by the Horizon 2020 LANDMARC project (grant agreement no. 869367). JM was supported by the RED-CLIMA (Red Española e Iberoamericana sobre Variabilidad Climática y Servicios Climáticos en Ecosistemas Terrestres y Marinos: RED-CLIMA) Project, under Grant INCCLO0023 from the Consejo Superior de Investigaciones Científicas LINCGLOBAL CSIC from Spain. Additional funding comes from National Institute of Science and Technology for Climate Change Phase 2 under CNPq Grant 465501/2014-1; FAPESP Grant 2014/50848-9; and the National Coordination for Higher Education and Training (CAPES) Grants 88887.136402–00INCT. Data from Southeast Asia (excl. Indonesia) was supported by work on using ClimPACT2 during the Second Workshop on ASEAN Regional Climate Data, Analysis and Projections (ARCDAP-2), 25–29 March 2019, Singapore, jointly funded by Meteorological Service Singapore and WMO through the Canada-Climate Risk and Early Warning Systems (CREWS) initiative. Daily data for Mexico were provided by the Servicio Meteorológico Nacional (SMN) of Comisión Nacional del Agua (CONAGUA). The Pacific data is associated with an ET-SCI workshop in Fiji over 7–11 December 2015 funded by Environment Canada. Additional detail available via https, Peer Reviewed, "Article signat per 29 autors/es: Robert J. H. Dunn, Nicholas Herold, Lisa V. Alexander, Markus G. Donat, Rob Allan, Margot Bador, Manola Brunet, Vincent Cheng, Wan Maisarah Wan Ibadullah, Muhammad Khairul Izzat Bin Ibrahim, Andries Kruger, Hisayuki Kubota, Tanya J. R. Lippmann, Jose Marengo, Sifiso Mbatha, Simon McGree, Sandile Ngwenya, Jose Daniel Pabon Caicedo, Andrea Ramos, Jim Salinger, Gerard van der Schrier, Arvind Srivastava, Blair Trewin, Ricardo Vásquez Yáñez, Jorge Vazquez-Aguirre, Claudia Villaroel Jiménez, Russ Vose, Mohd Noor’Arifin Bin Hj Yussof, Xuebin Zhang", Postprint (published version)

The electrification of societies and the decarbonisation of electricity production are changing energy systems worldwide. A fast transition towards the replacement of fossil fuels by intermittent renewable energy sources is expected in the next decades to combat climate change. A significant share of the produced electricity is likely to be generated from offshore wind farms, due to the abundant wind resources in the offshore regions and the lack of available onshore sites. However, increased electricity dependence in combination with expanded offshore wind power generation introduce new vulnerabilities to the society. Specifically, the effects of high impact low probability (HILP) events are considered as potential threats to the power system, not least because of the increasing number of extreme weather events. Therefore, research on power grid vulnerability and power system resilience to HILP events are of significant interest. This thesis presents results of studies investigating power grid vulnerability from a topological perspective, and resilience to storm conditions of power systems with varying dependencies on offshore wind. To achieve this, methods based on complex network theory and AC power flow analysis have been developed, tested, and evaluated. Further, geospatial wind data from historical extreme storm events have been used to generate realistic power production profiles from hypothetical offshore wind farms. The results strengthen that complex network concepts can be used successfully in the context of power grid vulnerability analysis. Further, the results show that the resilience of power systems with large dependencies on offshore wind differ vastly depending on the grid properties and control strategies, which are further discussed in this thesis.

Insurance companies are grappling with the rising frequency and severity of extreme weather-related flooding events, which currently pose the highest financial burden both in total and per individual case. The existing insurance model isn't economically sustainable if such events continue to increase. To assess future needs and challenges in flooding insurances, research on changing weather patterns and interviews with employees at major firms were conducted. The research indicates that climate change has and will further worsen extreme rain events in Sweden, leading to more frequent and intense flooding events. Interviews revealed that firms are aware of impending changes in the insurance industry due to climate change but lack proactive measures to address them. Responsibility is fragmented, and communication between stakeholders is suboptimal. To address these challenges, I look at recent research regarding flood risk assessment and if these are applicable for the insurance industry in Sweden to ensure future profitability.

Understanding the impact of climate change on cities is fundamental to address the increasing occurrence of extreme weather events. This research aims to raise awareness and emphasise the need and potential of proactive measures to mitigate the adverse effects of climate change. To do so, this article conducts a case study for a huge snowfall that occurred in the city of Madrid (Spain) in January 2021, blocking the city for several days. The analysis is based on geolocated big data sourced from Google Popular Times (GPT), which captures the occupancy of establish ments throughout the city over the entire study period. An exploratory spatial-temporal analysis has been conducted to examine the impact of the snowfall on the daily activities of the city, taking into consideration the demographic characteristics. The findings reveal a distinction in the impact of the snowfall on activities. Essential activities experience less impact compared to leisure ac tivities. Furthermore, at the socio-economic level, the impact on low-income neighbourhoods is observed to be less affected than on high-income neighbourhoods. The implications of this research contribute to the body of knowledge on climate change resilience and adaptation, providing valuable insights for urban management strategies and informing future research in this field., Depto. de Geografía, Fac. de Geografía e Historia, TRUE, pub

With climate change leading to more frequent, more intense, and longer durations of extreme weather events such as heat waves and cold snaps, it is essential to maintain safe indoor environmental conditions for occupants during such events, which may coincide with, or even cause, power outages that expose residents to health risks. Analyzing the impacts of extreme weather events on the thermal resilience of buildings can help stakeholders (including occupants) understand the risk and inform them about mitigation and adaptation actions. Moreover, analyzing the technological, social and policy dimensions of thermal resilience is critical for climate-proofing buildings. This paper presents 10 questions that highlight the most important issues regarding the thermal resilience of buildings for occupants in the face of climate change. The proposed questions and answers aim to provide insights into current and future building thermal resilience research and applications, and more importantly to inspire new significant questions in the field.

Understanding the impact of climate change on cities is fundamental to address the increasing occurrence of extreme weather events. This research aims to raise awareness and emphasise the need and potential of proactive measures to mitigate the adverse effects of climate change. To do so, this article conducts a case study for a huge snowfall that occurred in the city of Madrid (Spain) in January 2021, blocking the city for several days. The analysis is based on geolocated big data sourced from Google Popular Times (GPT), which captures the occupancy of establishments throughout the city over the entire study period. An exploratory spatial-temporal analysis has been conducted to examine the impact of the snowfall on the daily activities of the city, taking into consideration the demographic characteristics. The findings reveal a distinction in the impact of the snowfall on activities. Essential activities experience less impact compared to leisure activities. Furthermore, at the socio-economic level, the impact on low-income neighbourhoods is observed to be less affected than on high-income neighbourhoods. The implications of this research contribute to the body of knowledge on climate change resilience and adaptation, providing valuable insights for urban management strategies and informing future research in this field.

Fashion is technological, since the first clothing worn by early humans, the garments have been developed radically to become efficient and comfortable (quick dry, highly warm, extremely light) to match weatherability. Up until the last decade, fiber technology and materials science was limited to specialists. Since then, textile and clothing brands decided to invest in research and development. The lower costs of cutting-edge technology made it possible for independent designers as well as medium and larger companies to create concepts using innovative products. Additionally, there is a new consumer profile opting for environmentally responsible products that reflect their digital lifestyle. The Try It Out contribution - sited in the Andermatt, a village in the Swiss Alps - proposes a facility for the development of prototyping and testing of the textile performance. Material research becomes increasingly paramount, as material innovation is one of the main drivers for the fashion industry to tackle environmental challenges. Improving the lifespan of fabrics (duration), creating better-performing garments (higher value), and revolutionizing production processes (production), will change how fashion is consumed (consumption). This contribution is part of Fashion House, a collective project on the spatial implications of a decentralized and more tightly regulated fashion industry across Europe that reimagines the function and design for a fashion house., https://thesisinprogress-theberlage.nl/Fashion-House-Introword This contribution is part of Fashion House, a collective project on the spatial implications of a decentralized and more tightly regulated fashion industry across Europe that reimagines the function and design for a fashion house. Try It Out is a research center for prototyping and testing of products that perform under extreme conditions. It combines cutting-edge equipment with the rapid growth of influencers reviewing products. It is sited in Andermatt, Swiss Alps, Switzerland., Collective Project: Fashion House, Individual Contribution: Try Ir Out Research Center, The Berlage Post-MSc in Architecture and Urban Design

This report performs a gap analysis on microgrid models with respect to climate change risks at Naval installations. Six climate change risks are identified for the model analysis including drought, flooding, heat, cold, wildfires, and weather extremes. Each climate change risk is decomposed into ordered effects that inform the impacts that the climate risks may have on microgrids. The climate change risks, ordered effects, and the impacts on microgrids are used to analyze three microgrid models to determine if they adequately incorporate the six climate risks. A model analysis framework is developed to identify gaps in the approach of the models, the input parameters of the models, and the assumptions made in the models. The analysis demonstrates that gaps exist in each model when considering the climate change risks, the ordered effects, and the impacts to the microgrid. These gaps exist in all three models analyzed using the model analysis framework. The identified gaps are used to develop recommendations for ways to improve the incorporation of the climate change risks into microgrid models and the necessary research required to inform that data used in microgrid models., Naval Facilities Engineering Command, Civilian, Department of the Navy, Civilian, Department of the Navy, Civilian, Department of the Navy, Civilian, Department of the Navy, Approved for public release. Distribution is unlimited.

We are facing a climate crisis, and need to promptly reduce anthropogenic greenhouse gas emissions; for this reason, it is essential for the general public to engage in collective mit- igation behaviors. One of the psychological barriers to engaging in such behaviors is the unawareness that antropogenic global warming (AGW) is affecting people directly where they are, for example by increasing catastrophic extreme weather events. Climate scientists have developed tools such as Extreme Event Attribution (EEA), to understand the regional impacts of AGW at present, and to make projections of future developments. EEA identifies area-specific extreme weather events, and looks for evidence that the frequency, intensity and dynamics of these events have increased due to AGW. Such assessments can enhance the public’s perception of the vicinity and immediacy of the climate crisis, encouraging engage- ment in emission reduction behaviors. In this thesis a statistical and dynamic attribution study was carried out, to understand how AGW is affecting extreme precipitation events over Trentino (northern Italy), such as the 2018 Vaia storm. The results suggest that AGW increased the frequency of events as intense as Vaia by x3.4 CI[0.8, 12.0] from 1960-1985 to 1995-2021. Additionally, AGW increased the predictability (i.e. how predictable the temporal evolution of a Vaia-like atmospheric state is) and persistence of Vaia-like events, and induced thermodynamic changes that are likely responsible for the greater instensity of extreme precipitation like Vaia in Trentino. In response to the urgent need to inform local stakeholders, a communication study was planned, to convey this evidence to the residents of Trentino. In the study, participants will attend an educational video intervention on AGW- induced extreme weather in Trentino. Personal risk perception of AGW and behavioral engagement are hypothesized to increase from before to after the educational intervention., Masterarbeit Universität Innsbruck 2023

This master thesis investigates planning initiatives to address extreme weather events' impacts, specifically focusing on floods in Namibia. The study highlights the significance of such events in the context of global climate change, emphasising their adverse effects on livelihoods, particularly in rural communities and informal settlements. The research aims to evaluate existing strategic plans and policies in Namibia concerning extreme weather events and to examine the extent to which such events are considered when planning initiatives are implemented. Based on the theoretical framework of implementation theory, the study adopts a mixed-method research approach. Document analysis is employed to examine policies and plans related to planning in Namibia, while semi-structured interviews with key informants provide insights into the stakeholders' perspectives. A comprehensive understanding of the subject is achieved by comparing and validating findings from both methods. The results of the study reveal several approaches in current strategic plans and policies regarding the consideration of floods in Namibia. While several documents acknowledge the threat of floods and outline responsibilities and measures, there is a lack of comprehensive and coordinated approaches. The study highlights the need for a more integrated approach and increased alignment among different levels of planning documents. Furthermore, the research shows that the implementation of planning initiatives in Namibia is a centralised process overseen by the Ministry of Urban and Regional Development, with a limited focus on flooding beyond urban areas. The study identifies key challenges in implementing climate change adaptation strategies and projects in Namibia, including limited communication and coordination between actors, difficulties in accessing planning laws, plans and policies, and the centralisation of planning at the national level. However, opportunities for improvement are also recog

Flight delays are one of the most discussed, yet not fully understood, topics in the aviation industry. In this paper, we shed more light into propagation of flight delays by providing a spatio-temporal analysis of flight departure delays of the US domestic air network for the year 2017. The analysis focuses on four US air carriers (full-service and low-cost) and two time events characterized by extreme weather conditions, in addition to a baseline case free of extreme weather conditions. We constructed a Delay Propagation Network (DPN) for each (time event, airline) pair detecting patterns of causality between hourly delays in airports using a Granger Causality approach. In addition, we identified four (time event, airline) pairs with a volume of cancellations large enough to construct a Cancellation Propagation Network (CPN), analogously to DPNs. For the baseline case, we observed that central nodes of the airport network (i.e., hubs) usually act as absorbers or intermediary nodes in the DPN. DPNs were more homogeneously distributed in space for point-to-point than for hub-and-spoke networks. For extreme weather events, we observed that the size of a DPN increases with the percentage of canceled flights as long as this stays below 10\%. Conversely, it suddenly decreases when the percentage exceeds such tipping point because most causal relationships among delays are lost due to the volume of cancellations. We also observed that some airports located in the region of the extreme weather event were among the central nodes of the DPN. Those airports, together with the hub airports, acted as the top generators, absorbers, or intermediary nodes of the DPN. On the other hand, CPNs monotonously increased in size with the proportion of canceled flights. CPNs are less noisy and therefore easier to interpret than DPNs, as cancellations stem primarily from the extreme weather event only. In CPNs, hubs act as cancellation absorbers, due to the larger volume of resources that, Peer Reviewed, Postprint (published version)

Primary production, particularly in the agriculture industry, has been and will be affected by climate change. Extreme weather conditions and their effects on the agriculture supply chain and agricultural field soil are highly evident and attract considerable media attention. Although the agriculture supply chain is scrutinized carefully, there is not enough focus on first-mile logistics. The first mile also affects the downstream stages of the supply chain. These project deliverables aim to enhance the understanding of the challenges of first-mile logistics in poor-bearing soils and vulnerable environments. It seeks to identify and elaborate on different challenges and proposes how agricultural machine and equipment providers might be able to provide solutions. This research applies both qualitative and quantitative methods. The scientific and gray literature and other sources are scanned to compile the challenges. The fault-tree type of analysis is carried out to categorize and structure the challenges. Next, the information value of the identified challenges is assessed by an evidence-scoring and ranking system. Industrial partners and other field experts are interviewed to ensure the validity of the findings. The quality function deployment (QFD) framework is proposed to link the identified challenges with industrial partners’ product features. Lastly, some arguments are provided in order to define the prerequisites of simulation and testing of soil–machine interaction on sensitive soils. Based on the interviews with company representatives, the report also re-examines the first-mile concept, redefines the sequential supply chain, and proposes a hybrid supply chain topology with circular transportation (between pre-harvest and post-harvest phases). Altogether, 93 challenges are identified and categorized into six different clusters, with subgroups. Through additional expert interviews, it is also found that the majority of the identified challenges are

BackgroundThe effects of climate change are seen with a rise of extreme weather and climate events (EWCEs) which lead to the closures of many healthcare facilities, such as community pharmacies. Pharmacists in community pharmacies are seen as the most accessible healthcare professional to the public and are responsible for the continued delivery of care to patients. However, amid closures due to EWCEs and the emergence of pharmacy deserts, there is decreased access to pharmacies and a disruption of care.ObjectiveIt is important to address the preparedness and accessibility of pharmacies post-EWCEs to guide future research and policy. Additionally, to tackle health disparities that arise due to pharmacy deserts, the populations most affected by a decreased access to pharmacies should be identified. We conducted a scoping review to assess the preparedness and accessibility of pharmacies post-EWCEs and to identify populations most affected by pharmacy deserts.MethodsWe searched PubMed, Embase, and Web of Science from January 1, 2012 to September 30, 2022 and included all English-language, peer-reviewed primary literature that examined the preparedness and accessibility of community pharmacies in the United States post-EWCEs and addressed disparities within pharmacy deserts. Studies meeting these criteria were screened of their titles and abstracts by the first author and discrepancies were resolved with co-authors. We used Covidence for data extraction.ResultsA total of 472 studies were identified (196 duplicates removed) and after screening, 53 studies were assessed for eligibility. The results of included publications (N = 26) showed that pharmacists and pharmacies are not equipped with the necessary emergency protocols which could lead to decreased access of pharmacies in the wake of EWCEs. Pharmacy deserts disproportionately affect residents living in rural, lower income, and Black/African American and Hispanic/Latino neighborhoods. The lack of preparedness of phar

BackgroundPeople with HIV (PWH) are disproportionately vulnerable to the impacts of wildfires, given the need for frequent access to healthcare systems, higher burden of comorbidities, higher food insecurity, mental and behavioral health challenges, and challenges of living with HIV in a rural area. In this study, we aim to better understand the pathways through which wildfires impact health outcomes among PWH.MethodsFrom October 2021 through February 2022, we conducted individual semi-structured qualitative interviews with PWH impacted by the Northern California wildfires and clinicians of PWH who were impacted by wildfires. The study aims were to explore the influence of wildfires on the health of PWH and to discuss measures at the individual, clinic, and system levels that helped to mitigate these impacts.ResultsWe interviewed 15 PWH and 7 clinicians. While some PWH felt that surviving the HIV epidemic added to their resilience against wildfires, many felt that the wildfires compounded the HIV-related traumas that they have experienced. Participants outlined five main routes by which wildfires negatively impacted their health: (1) access to healthcare (medications, clinics, clinic staff), (2) mental health (trauma; anxiety, depression, or stress; sleep disturbances; coping strategies), (3) physical health (cardiopulmonary, other co-morbidities), (4) social/economic impacts (housing, finances, community), and (5) nutrition and exercise. The recommendations for future wildfire preparedness were at the (1) individual-level (what to have during evacuation), (2) pharmacy-level (procedural, staffing), and (3) clinic- or county-level (funds and vouchers; case management; mental health services; emergency response planning; other services such as telehealth, home visits, home laboratory testing).ConclusionsBased on our data and prior research, we devised a conceptual framework that acknowledges the impact of wildfires at the community-, household-, and individual-level w

Different means of yield forecasting have been investigated in many publications, although very few with a focus on pre-season forecasting. Climate change and the increasing risk of extreme weather events is a threat to food production, and early yield predictions could therefore be beneficial for farmer’s planning and management as a way towards more resilient food production. This thesis aims to explore if yield forecasting of malting barley in Southern Sweden can be done using climate markers of weather occurring during the 60 days before the beginning of the cropping season. Data from field trials, conducted between 1999 and 2018 and acquired from NTFS and SLU Fältforsk, were used as experimental data to calibrate and evaluate the CERES-Barley crop model. Three cultivars were used: Astoria, Irina and Propino. The model input additionally consisted of weather data from AgERA5 and soil profiles from ISRIC that were connected to the field trial sites. The climate markers and the simulated mean yields were tested with a linear mixed model analysis and a Pearson chi-square test in RStudio. The crop model was successfully calibrated, with Astoria being the best cultivar to mirror observed yields from different years and locations in Sweden. The results indicated, however, that none of the analysed climate markers during the 60 days prior to the beginning of the cropping season was able to explain malting barley yields, highlighting the difficulty in making early yield forecasts. One hypothesis for this lack of explanatory power from the climate markers on the yield of spring malting barley is that the effect of precipitation in the 60 days before the beginning of the cropping season is buffered by winter and early spring, when soils are usually at or close to field capacity.

The aim of this paper is to make a detailed study on climate change's impacts on physical activity and organized competitive sports with further attention paid to their adaptation efforts and evaluating the future impacts with special reference to Arunachal Pradesh, India. Linkages between climate and human activity cannot be ignored and it is a universal phenomenon and is certainly possible due to adaptations. These adaptations have direct linkage with physical, mental, emotional, social and overall wellbeing of human beings. Ignoring the degree of adaptation could impact the health upto severe consequences due to climate change. The relationship between sport and environment has to be examined to understand how environment and climatic parameters impacts sport in terms of training, performance and sports injuries. Arunachal Pradesh is a hub of youth potentials especially in sports. Looking at the present climatic crisis, the study aims to assess the impacts of climate change, and measures to be taken by organized competitive sport entities to adapt to the impacts. The study adopts a descriptive analysis including both qualitative and quantitative assessment by exploring secondary information. The findings of the study states that most of the outdoor sport activities especially endurance sports are strongly influenced by meteorological parameters. The effects of weather on sports are varied, performances can get reduced or improved, becomes very severe during extreme weather conditions leading to threat for life. If climate change progresses in scope and severity as predicted, no doubt physical activity and outdoor organized competitive sports is under threat. The valence of this paper lies in its conceptualization of the climate vulnerability on sport activities and its potential to inspire future research and interest in this domain. However, it is important for government, agencies, sports organizations, coaches, athletes, environmentalists, and health experts t

The built environment of the future should move with the changes the weather brings as well as evolve with slower and larger trends in our society like climate change, demographic changes, and technical advancements. By planning for the future now we can reduce obstacles for future generations of planners, designers, and governing bodies. The built environment should be able to function well whether water is in high or low flux. Water is fluid. It is shaped by and shapes its surroundings. Cities can learn a lot from this fluidity. By increasing the flexibility of urban design, we can anticipate and move with the changes the future brings instead of being in a continuous cycle of trying to catch up. The built environment should follow the current of the future and adapt to the changes in our climate and weather. Creating a city that adapts to new circumstances and moves with water., Architecture, Urbanism and Building Sciences

Hot, cold and dry meteorological extremes are often linked with severe impacts on the public health, agricultural, energy and environmental sectors. Skillful predictions of such extremes could therefore enable stakeholders to better plan and adapt to future impacts of these events. The intensity, duration and frequency of such extremes are affected by anthropogenic climate change and modulated by different modes of climate variability. Here we use a large multi-model ensemble from the Coupled Model Intercomparison Project Phase 6 and constrain these simulations by sub-selecting those members whose global SST anomaly patterns are most similar to observations at a given point in time, thereby phasing in the decadal climate variability with observations. Hot and cold extremes are skillfully predicted over most of the globe, with also a widespread added value from using the constrained ensemble compared to the unconstrained full CMIP6 ensemble. On the other hand, dry extremes show skill only in some regions with results sensitive to the index used. Still, we find skillful predictions and added skill for dry extremes in some regions such as western north America, southern central and eastern Europe, southeastern Australia, southern Africa and the Arabian peninsula. We also find that the added skill in the constrained ensemble is due to a combination of improved multi-decadal variations in phase with observed climate extremes and improved representation of long-term changes. Our results demonstrate that constraining decadal variability in climate projections can provide improved estimates of temperature extremes and drought in the next twenty years, which can inform targeted adaptation strategies to near-term climate change., This research has been partly supported by the Horizon2020 LANDMARC project (grant agreement No. 869367) and the Horizon Europe ASPECT project (grant number 101081460). PDL has received funding from the European Union’s Horizon Europe Research and Innovation Programme under grant agreement No 101059659. CDT acknowledges financial support from the Spanish Ministry for Science and Innovation (FPI PRE2019-509 08864 financed by MCIN/AEI/10.13039/501100011033 and by FSE invierte en tu futuro). MGD is grateful for support by the AXA Research Fund. The authors are further grateful for the support by the Department of Research and Universities of the Government of Catalonia to the Climate Variability and Change Research Group (Code: 2021 SGR 00786)., Peer Reviewed, Postprint (author's final draft)

Flight delays are one of the most discussed, yet not fully understood, topics in the aviation industry. In this paper, we shed more light into propagation of flight delays by providing a spatio-temporal analysis of flight departure delays of the US domestic air network for the year 2017. The analysis focuses on four US air carriers (full-service and low-cost) and two time events characterized by extreme weather conditions, in addition to a baseline case free of extreme weather conditions. We constructed a Delay Propagation Network (DPN) for each (time event, airline) pair detecting patterns of causality between hourly delays in airports using a Granger Causality approach. In addition, we identified four (time event, airline) pairs with a volume of cancellations large enough to construct a Cancellation Propagation Network (CPN), analogously to DPNs. For the baseline case, we observed that central nodes of the airport network (i.e., hubs) usually act as absorbers or intermediary nodes in the DPN. DPNs were more homogeneously distributed in space for point-to-point than for hub-and-spoke networks. For extreme weather events, we observed that the size of a DPN increases with the percentage of canceled flights as long as this stays below 10%. Conversely, it suddenly decreases when the percentage exceeds such tipping point because most causal relationships among delays are lost due to the volume of cancellations. We also observed that some airports located in the region of the extreme weather event were among the central nodes of the DPN. Those airports, together with the hub airports, acted as the top generators, absorbers, or intermediary nodes of the DPN. On the other hand, CPNs monotonously increased in size with the proportion of canceled flights. CPNs are less noisy and therefore easier to interpret than DPNs, as cancellations stem primarily from the extreme weather event only. In CPNs, hubs act as cancellation absorbers, due to the larger volume of resources that a, Air Transport & Operations

This study aims to unravel and quantify the impact of sea surface temperature (SST) on the formation, intensity, structure and track of the Mediterranean tropical-like cyclone (medicane) Ianos occurred on 15–20 September 2020 at the central Mediterranean. This study, thus, demonstrates how Ianos would be in past and future climate conditions, assuming that SST changes over the years, but preserving the same atmospheric conditions. To investigate the SST impact, the medicane was simulated using the Advanced Weather and Research Forecasting (WRF-ARW) model. The numerical experiments were initialized either with SST analysis data (control experiment) or applying a uniform decrease and increase to SST analysis by 1 °C and 2 °C (four sensitivity experiments). In this way, the past and future climatic SSTs were concisely approximated. Analysis of various thermodynamic parameters in combination with phase space diagrams, revealing the thermal symmetry and the warm core structure of the cyclone, indicated that Ianos was very sensitive on SST. Thus, SST changes especially by ±2 °C had significant impact on its intensity, changing the period of tropical features while also determining the track and the landfall location. Overall, the average enthalpy flux (i.e., the sum of sensible and latent heat fluxes) in Ianos changed by approximately −39% and + 50% when SST changed by −2 °C and + 2 °C, respectively. This, in turn, affected the characteristics of Ianos causing changes for example in the average wind speed (approximately −15% and + 15%) and the average precipitation (approximately −56% and + 44%). This study quantifies the impacts of SST on Ianos medicane that have important research and socioeconomic implications with a view to a changing future. Therefore, it could support scientists, decision-makers and civil protection in the adaptation to extreme weather phenomena by building climate resilience and sustainability.

Self-sustaining green roofs can considerably reduce the building cooling demand in summer. In recent decades, extreme weather events including heatwaves and drought have increased, while there is a lack of knowledge of the dynamic thermal performance of green roofs during a severe drought. The present study is based on in-situ measurements of a room with a self-sustaining green roof and a reference room with a bare roof. The temporal evolution of the thermal performance of the green roof during a severe drought is investigated. Long-term observations for several years showed that Sedum lineare on the green roof survived in summers, except for a period during the severe drought. Although extreme drought weather led to extensive mortality, plants revived in the next year. The status of the green roof during the drought period could be divided into three phases: (I) normal, (II) substrates dried, and (III) plants withered and substrate dried. The respective contributions of live plants and substrates are quantified based on the results from these phases. In phase I, the average heat transfer into the indoor space through the green roof was 81% less than that of the reference bare roof. In phase II, the plants and the substrate dried out gradually, and the average heat transfer through the green roof was 69% less. In phase III, the dry substrate without live plants acts as a normal thermal insulation layer, and the average heat transfer through the green roof was still 40% less than that of the reference bare roof. In those three phases, the equivalent overall heat transfer coefficient of the green roof was 0.26, 0.49, and 0.88 W/(m2K), respectively. It suggests that the use of drought-tolerant plant species and substrate with a low thermal conductivity could improve the thermal performance of green roofs during a severe drought. © 2022 Elsevier B.V.

Context Both climatic extremes and land-use change constitute severe threats to biodiversity, but their interactive effects remain poorly understood. In forest ecosystems, the effects of climatic extremes can be exacerbated at forest edges. Objectives We explored the hypothesis that an extreme summer drought reduced the richness and coverage of old-growth forest species, particularly in forest patches with high edge exposure. Methods Using a high-resolution spatially explicit precipitation dataset, we could detect variability in drought intensity during the summer drought of 2018. We selected 60 old-growth boreal forest patches in central Sweden that differed in their level of drought intensity and amount of edge exposure. The year after the drought, we surveyed red-listed and old-growth forest indicator species of vascular plants, lichens and bryophytes. We assessed if species richness, composition, and coverage were related to drought intensity, edge exposure, and their interaction. Results Species richness was negatively related to drought intensity in forest patches with a high edge exposure, but not in patches with less edge exposure. Patterns differed among organism groups and were strongest for cyanolichens, epiphytes associated with high-pH bark, and species occurring on convex substrates such as trees and logs. Conclusions Our results show that the effects of an extreme climatic event on forest species can vary strongly across a landscape. Edge exposed old-growth forest patches are more at risk under extreme climatic events than those in continuous forests. This suggest that maintaining buffer zones around forest patches with high conservation values should be an important conservation measure.

The accurate prediction of extreme weather events is an important and challenging task, and has typically relied on numerical simulations of the atmosphere. Here, we combine insights from numerical forecasts with recent developments in dynamical systems theory, which describe atmospheric states in terms of their persistence (theta(-1)) and local dimension (d), and inform on how the atmosphere evolves to and from a given state of interest. These metrics are intuitively linked to the intrinsic predictability of the atmosphere: a highly persistent, low-dimensional state will be more predictable than a low-persistence, high-dimensional one. We argue that theta(-1)andd,derived from reanalysis sea level pressure (SLP) and geopotential height (Z500) fields, can provide complementary predictive information for mid-latitude extreme weather events. Specifically, signatures of regional extreme weather events might be reflected in the dynamical systems metrics, even when the actual extreme is not well-simulated in numerical forecasting systems. We focus on cold spells in the Eastern Mediterranean, and particularly those associated with snow cover in Jerusalem. These rare events are systematically associated with Cyprus Lows, which are the dominant rain-bearing weather system in the region. In our analysis, we compare the 'cold spell Cyprus Lows' to other 'regular' Cyprus Low days. Significant differences are found between cold spells and 'regular' Cyprus Lows from a dynamical systems perspective. When considering SLP, the intrinsic predictability of cold spells is lowest hours before the onset of snow. We find that the cyclone's location, depth and magnitude of air-sea fluxes play an important role in determining its intrinsic predictability. The dynamical systems metrics computed on Z500 display a different temporal evolution to their SLP counterparts, highlighting the different characteristics of the atmospheric flow at the different levels. We conclude that the dynamical sys

Precipitation is a vital component of the water-energy-food nexus and a deadly force of nature responsible for natural hazards like flooding and debris flows. Because of its profound impact to society at large, it is an extremely important variable to measure and predict. Fittingly, the highly variable and chaotic nature of the precipitation field makes quantifying and forecasting arduous. One tool useful for precipitation measurements are satellites, which are capable of measuring precipitation quasi-globally over land and oceans. Given the rapid advancement of remotely sensed observational techniques over the past few decades and the satellite record’s recent emergence into climate time scales, new kilometer-scale, sub-daily records of precipitation have been produced capable of high-spatiotemporal insights into some of the most extreme hydroclimate events. With climate change’s influence becoming more profound through the passage of time, this dissertation seeks to examine how atmospheric rivers (ARs) and tropical cyclones (TCs) have evolved since the beginning of the satellite age using high resolution climate data records of precipitation (HRPCDRs) and testing for the influence of anthropogenic warming. In the first half of the dissertation, we adapt the CONNected-objECT (CONNECT) algorithm for the tracking of global mid-latitude AR lifecycles and associated precipitation by implementing a seeded region growing segmentation algorithm, creating the AR-CONNECT algorithm. One of AR-CONNECT’s goals is to track atmospheric water vapor anomalies before evolving into AR geometries, effectively tracking AR genesis farther back than other studies. To accomplish this, AR-CONNECT is without hard-coded geometric criteria yet is still proven to extract synoptic-scale elongated objects >99.99% of the time. With the aid of sub-daily satellite-derived rain data, we investigate the climatology, trends, and patterns of AR lifecycles from 1983-2016 and compare with other AR tr

The significant impacts of climate change on extreme weather events have been widely demonstrated in past decades. As the most expensive climate disaster, the drought and its risks under the warming climate always attract people's attention. However, huge uncertainties exist in climate projections, mainly consisting of scenario uncertainty, model uncertainty, and internal variability. Moreover, drought is more difficult to assess in climate datasets, due to its long duration per event, relative to the length of a typical simulation. Meanwhile, since the infamous extreme drought of the 1960s, the climate of the Northeastern United States (NEUS) has generally trended towards warmer and wetter conditions. Nonetheless, there is mounting evidence that short-term droughts will continue to pose a significant risk for this region. Therefore, there is a growing need for a comprehensive framework with the most advanced climate techniques and datasets to investigate the impacts of climate change on drought over NEUS.In this thesis, firstly, a comprehensive drought feature-based evaluation system, equipped with statistical hypothesis testing and Principal Feature Analysis, is put forward and is designed to be easily used for any climate datasets. With its help, people can choose climate models with fewer model uncertainties and biases in capturing droughts in the regions of interest. This system is applied to three characteristically distinct regions in the conterminous US and across several commonly employed climate datasets (CMIP5/6, LOCA, and CORDEX). As a result, insights emerge into the underlying drivers of model bias in global climate models, regional climate models, and statistically downscaled models.Then to reduce the impacts of internal variability on drought projections, 7 large ensemble (LE) models and a novel drought index are employed to examine the changing trends of drought at different temporal scales. We find most LE models indicate the NEUS will experience a

Socio-ekologisk resiliens är ett begrepp som bör integreras i en större omfattning i dagens stadsplanering då extremväder till följd av klimatförändringar, samt Covid-19 pandemin har förändrat behoven i stadens offentliga rum. Ett sätt att bemöta de nya behoven är att öka andelen grönområden. Denna studie fokuserar på Stockholms mest centrala delar, Vasastan, Norrmalm och Östermalm som har ett väldigt begränsat utbud av grönområden, sett till hur många som bor där. Stockholms stads rekommendation är att boende ska ha maximalt 200 meter till närmsta grönområde, vilket studiens fokusområden inte uppfyller idag. Dessutom är dessa områden utsatta för värmeöar och översvämningsrisker, vilket var ytterligare en orsak till varför studieområdet valdes. Att få loss mark och implementera nya grönområden i ett redan högt exploaterat område är en utmaning. Denna studie syftar därför till att undersöka var urbana grönområden såsom mikroparker kan införas i syfte att öka den socio-ekologiska resiliensen, men även att undersöka hur Stockholms stad arbetar med resiliensstrategier idag samt hur dessa kan förbättras. Vidare undersöktes vilka faktorer som ett urbant grönområde ska ha för att bidra till resiliens. Med resultatet av intervjuer och spatiala analyser som underlag, kan denna studie konstatera att Stockholms stads arbete med socio-ekologisk resiliens har förbättringsmöjligheter, och att det finns flertalet spillytor att anlägga mikroparker på. Dessutom har de viktigaste framgångsfaktorerna när det kommer till grönområden, ur ett socio- ekologiskt perspektiv, presenterats vilket framför allt handlar om mångfunktionalitet. Dock visar studien på att man behöver ta vissa bilvägar i anspråk för att säkerställa ekologisk resiliens., Socio-ecological resilience is a concept that should be integrated to a greater extent in today's urban planning since extreme weather as a result of climate change, and the Covid-19 pandemic have changed the needs of the city's public spaces. One way to meet the new needs is to increase the proportion of green areas. This study focuses on Stockholm's most central parts, ON, Norrmalm and Östermalm, which have a very limited range of green areas, in comparison to how many people live there. The City of Stockholm's recommendation is that residents should have a maximum of 200 meters to the nearest green area, which the study's focus areas do not meet today. In addition, these areas are exposed to heat islands and flood risks, which was another reason why the study area was chosen. To implement new green areas in an already highly developed area is a challenge. Therefore, this study aims to investigate where urban green areas, such as micro parks, can be introduced to increase social-ecological resilience. It also aims to investigate how the City of Stockholm works with resilience strategies today and how these can be improved. Furthermore, it was investigated what factors an urban green area should have to contribute to resilience. With the results of interviews and spatial analysis as a basis, this study can point out that the City of Stockholm's work with socio-ecological resilience has room for improvement, and that there are several available areas to build micro parks on. In addition, the most important success factors when it comes to green areas, from a socio-ecological perspective, have been presented, which is primarily about multifunctionality. However, the study shows that it is necessary to develop some car roads into greener areas, to ensure socio-ecological resilience.

Extreme weather events are becoming more frequent due to climate change. We therefore need to understand how species respond to these events. In 2018, the worst drought ever recorded hit the island of Gotland in the Baltic Sea, which led to a major decline of the threatened marsh fritillary (Euphydryas aurinia) the succeeding summer. We compared yearly occupancy among 256 habitat patches between 2018 and 2020 and analysed the colonisation-extinction dynamics between 2019 and 2020 in relation to patch area, connectivity, and habitat quality. Moreover, using capture-mark-release data in two patch clusters differing in connectivity, we also compared population sizes before and after the drought and analysed 'population growth rates'. We also compared yearly abundance of host plants (Succisa pratensis) over time. Results show a remarkable recovery of the marsh fritillary. Both patch occupancy in 2020 and the number of individuals in the well-connected patch cluster were higher than before the drought. In contrast, host plants were fewer and smaller, which taken together suggest that the amount of food resources was roughly half in 2020 compared to the pre-drought conditions. Moreover, the butterfly population in the less connected patch cluster was eight times smaller compared to the population size before the drought. Local colonisations, extinctions, and population growth rates were explained by connectivity. The ability to quickly recover after extreme droughts is promising in times of climate change. The significance of connectivity for the population dynamics during recovery highlights the importance of maintaining well-connected patch networks.

Extreme weather events have devastating impacts on human health, economic activities, ecosystems, and infrastructure. It is therefore crucial to anticipate extremes and their impacts to allow for preparedness and emergency measures. There is indeed potential for probabilistic subseasonal prediction on time scales of several weeks for many extreme events. Here we provide an overview of subseasonal predictability for case studies of some of the most prominent extreme events across the globe using the ECMWF S2S prediction system: heatwaves, cold spells, heavy precipitation events, and tropical and extratropical cyclones. The considered heatwaves exhibit predictability on time scales of 3–4 weeks, while this time scale is 2–3 weeks for cold spells. Precipitation extremes are the least predictable among the considered case studies. ­Tropical cyclones, on the other hand, can exhibit probabilistic predictability on time scales of up to 3 weeks, which in the presented cases was aided by remote precursors such as the Madden–Julian oscillation. For extratropical cyclones, lead times are found to be shorter. These case studies clearly illustrate the potential for event-dependent advance warnings for a wide range of extreme events. The subseasonal predictability of extreme events demonstrated here allows for an extension of warning horizons, provides advance information to impact modelers, and informs communities and stakeholders affected by the impacts of extreme weather events., Peer Reviewed, "Article signat per 40 autors/es: Daniela I. V. Domeisen, Christopher J. White, Hilla Afargan-Gerstman, Ángel G. Muñoz, Matthew A. Janiga, Frédéric Vitart, C. Ole Wulff, Salomé Antoine, Constantin Ardilouze, Lauriane Batté, Hannah C. Bloomfield, David J. Brayshaw, Suzana J. Camargo, Andrew Charlton-Pérez, Dan Collins, Tim Cowan, Maria del Mar Chaves, Laura Ferranti, Rosario Gómez, Paula L. M. González, Carmen González Romero, Johnna M. Infanti, Stelios Karozis, Hera Kim, Erik W. Kolstad, Emerson LaJoie, Llorenç Lledó, Linus Magnusson, Piero Malguzzi, Andrea Manrique-Suñén, Daniele Mastrangelo, Stefano Materia, Hanoi Medina, Lluís Palma, Luis E. Pineda, Athanasios Sfetsos, Seok-Woo Son, Albert Soret, Sarah Strazzo, and Di Tian", Postprint (published version)

This perspectives piece examines efforts to enact a new approach to risk communication (referred to as the relational model of risk communication) in the field. The model involves empowering community residents to translate and spread knowledge concerning risks from extreme weather events. The process of implementing and evaluating the model by the Cyclone Preparedness Programme of Bangladesh is described. Of particular interest is the task of analyzing the program's effects in practice, which involved an ad hoc exercise in data collection and analysis. The study found that the enhanced mode of risk communication was indeed practiced in the field. Secondly, there was a marked improvement in evacuation behavior, which may partly be due to the risk communication program. The inquiry underscores both the potential and challenges of conducting field evaluation (whether after or during an event). The capacities for evaluation of field agents need to be fostered, as well as the construction of systematic data collection instruments for use in real-time. © 2022 The Author(s)

Urban environments lie at the confluence of social, cultural, and economic activities and have unique biophysical characteristics due to continued infrastructure development that generally replaces natural landscapes with built-up structures. The vast majority of studies on urban perturbation of local weather and climate have been centered on the urban heat island (UHI) effect, referring to the higher temperature in cities compared to their natural surroundings. Besides the UHI effect and heat waves, urbanization also impacts atmospheric moisture, wind, boundary layer structure, cloud formation, dispersion of air pollutants, precipitation, and storms. In this review article, we first introduce the datasets and methods used in studying urban areas and their impacts through both observation and modeling and then summarize the scientific insights on the impact of urbanization on various aspects of regional climate and extreme weather based on more than 500 studies. We also highlight the major research gaps and challenges in our understanding of the impacts of urbanization and provide our perspective and recommendations for future research priorities and directions. © 2022, The Author(s).

This paper summarizes the current challenges in climate and weather research and provides suggestions for future research directions in global observing systems, in modelling and prediction, and in academic environment and education systems.