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Reconciliation of Trends in Global and Regional Economic Losses from Weather Events: 1980–2008
Abstract
In recent years, claims have been made in venues including the authoritative reports of the Intergovernmental Panel on Climate Change (IPCC) and in testimony before the U.S. Congress that economic losses from weather events have been increasing beyond that which can be explained by societal change, based on loss data from the reinsurance industry and aggregated since 1980 at the global level. Such claims imply a contradiction with a large set of peer-reviewed studies focused on regional losses, typically over a much longer time period, which concludes that loss trends are explained entirely by societal change. To address this implied mismatch, this study disaggregates global losses from a widely utilized reinsurance data set into regional components and compares this disaggregation directly to the findings from the literature at the regional scale, most of which reach back much further in time. The study finds that global losses increased at a rate of $3.1 billion/year (2008 USD) from 1980-2008 and losses from North American, Asian, European, and Australian storms and floods account for 97% of the increase. In particular, North American storms, of which U.S. hurricane losses compose the bulk, account for 57% of global economic losses. Longer-term loss trends in these regions can be explained entirely by socioeconomic factors in each region such as increasing wealth, population growth, and increasing development in vulnerable areas. The remaining 3% of the global increase 1980 to 2008 is the result of losses for which regionally based studies have not yet been completed. On climate timescales, societal change is sufficient to explain the increasing costs of disasters at the global level and claims to the contrary are not supported by aggregate loss data from the reinsurance industry. (C) 2014 American Society of Civil Engineers.
... These relative differences in the size of the companies and the countries that are affected could influence not only the negotiation process but also the impact that pollution could have on production and 1 [2] They estimate average losses of around 17,000 million dollars per year due to tornados, hurricanes and floods over the period, solely in the United States, which, in some years has surpassed the 100,000 million dollar mark. Similarly, according to Mohleji and Pielke [3], global losses under this rubric increased to an average of more than 3,000 million dollars between 1980 and 2008. They also state how 97% of these costs correspond to damages centered on North America, Europe, Asia and Australia, with losses in North America representing 57% of global losses. ...
... Although there are many studies on environmental regulations, 3 not enough studies have been conducted on the rubric for environmental controls and commercial competition. Thus, this study approaches the subject of the establishment of strategic environmental policies through, specifically, the implementation of an environmental control instrument, a pollution tax, and its effects on the trade relationships between different-sized countries, in both of which there is a heterogeneous company trading a homogeneous good. ...
... 4 This bidirectional exchange of similar, if not identical, merchandise is also known in international economic literature as crosshauling. It has been widely analyzed in the specialized bibliography dealing with price- 3 For example, the meticulous study by Cropper and Oates [4]. 4 Among the classic studies on intra-industrial trade, the following can be cited [5,6,7]. setting in perfect competition, although some studies have been conducted in the context of imperfect markets, particularly under Cournot's framework of oligopoly. ...
The present study develops a partial equilibrium model, under reciprocal dumping conditions for bilateral trade in a homogeneous good between two different-sized countries under Cournot competition conditions. In order to control the emission of pollutants, the governments of both countries use pollution taxes, which consist in levying an amount against the companies per unit of pollution emitted. While this does mean that those companies that pollute more pay more, the companies have the adequate technology for reducing the emissions caused by their production processes.http://www.journaljemt.com/index.php/JEMT/article/view/29359/55213
... A number of risk assessment studies have looked at disaster losses on a global scale [29][30][31][32]. However, because the global scale losses seem to be dominated by the losses induced in wealthy regions [33,34], more studies have concentrated on the specific regions of the world. Considering wind-related disasters only, extratropical storms were investigated in Switzerland [35] and Europe [36], while tropical cyclones were studied over China [37][38][39], India [40], and Latin America and the Caribbean [41]. ...
... Based on the detailed literature review conducted by Ref. [21]; none of the previous studies considered Canada in terms of normalized damage losses caused by windstorms. While severe wind hazards are most frequent in the US [33], they have also been causing significant damage in highly populated areas in Canada [52]. Hence, by addressing this research gap, the present study aims at a systematic analysis of insured losses imposed by different types of windstorms in two provinces of Canada-Ontario (ON) and Quebec (QC). ...
Severe windstorms pose threats to people, human-made structures, and the environment. An investigation of insured losses caused by windstorms is a multipurpose study that serves to advance the resilience and sustainability of modern communities. The present study proposes a systematic analysis of insured losses imposed by different types of windstorms in two Canadian provinces, Ontario (ON) and Quebec (QC), during the period 2008–2021. Actual wind damage data from the Canadian insurance market were considered in this study. Our calculations show that ON and QC received half of all wind catastrophes across Canada, and nearly three-quarters of all types of catastrophes in ON and QC were wind-related ones. The total windstorm loss of over CA$5.2 billion was not evenly distributed between QC and ON, but rather had a QC:ON ratio of 1:3.1. We attributed this discrepancy in the inflicted damage between two provinces to the predominantly eastward and northeastward storm trajectories and the higher density of wealth and population in ON. Convective storms were the most devastating wind type comprising nearly 65% and 67% of the total number of events and associated damage, respectively. Finally, tornadoes had the highest average loss per event in two provinces combined. Future prospects and the implication of this research are also discussed.
... They caused more than 18% of all weather-related damage on average (China Meteorological Administration, 2015;Fischer et al., 2015;Wang et al., 2016). With a clear temporal increase in absolute TC losses globally, there is an ongoing debate whether this rise is caused by increasing wealth or due to changes in climatic conditions (Nordhaus, 2010;Mohleji and Pielke Jr., 2014;Estrada et al., 2015), and whether the trend will continue in future (Knutson et al., 2010). Agreement is emerging that TCs are shifting towards stronger intensities and that economic losses from TCs might increase severely by the end of the century based on today's socio-economic conditions and looming climate change (Mendelsohn, 2010;Gemmer et al., 2011;Peduzzi et al., 2012;Geiger et al., 2016). ...
... The majority of existed studies pay close attention to the analysis of the historical period (Pielke Jr. et al., 2008;Nordhaus, 2010;Gemmer et al., 2011;Fischer et al., 2015;Wang et al., 2016), and little research has been performed in regard to future TC losses. Although different opinions exist in the detection and attribution of TC losses, the development of socio-economic conditions plays a similar if not greater role in determining TC losses than climate change itself (Miller et al., 2008;Pielke Jr. et al., 2008;Changnon, 2009;Nordhaus, 2010;Schmidt et al., 2010;Bouwer, 2011;Mohleji and Pielke Jr., 2014;Estrada et al., 2015). While existing studies assess future impacts of a changing climate based on the assumption of fixed populations and/or historical economic states (Hirabayashi et al., 2013), ignoring the rapid changes in economy and exposed population, which could contain substantial inaccuracies. ...
Adverse impacts and increasing economic losses from tropical cyclones (TCs) are a major focus in respect to the potential global warming of 1.5 °C or even 2.0 °C. Based on observed meteorological data and county‐scale loss records, loss‐inducing rainfall and wind speed thresholds are identified using the regional climate model CCLM to project future TC events in China. An established damage function is combined with future gross domestic product predictions under five shared socio‐economic pathways. At the 1.5 °C warming level, normalized TC losses will be four times higher than in the reference period (1986–2005). At the 2.0 °C warming level, a sevenfold increase is projected. Relative to the 1.5 °C warming level, TCs will become more frequent under the 2.0 °C scenario, especially along the southeast coast of China. Nearly 0.2–0.5% of the increase in gross domestic product might be offset by TC losses between the 1.5 °C and 2.0 °C warming levels, and the single highest TC loss at 2.0 °C may double that at 1.5 °C, with a larger affected area and more severe rainstorms and wind speeds. Rainfall is attributed more often to TC losses than wind speed. Limiting global warming at 1.5 °C would avoid an estimated increase in TC losses of more than 120 billion CNY annually.
... In the context of significant contemporary climate change, extreme weather events have become a prominent focus in climatology, largely due to their substantial economic and social risks. The observed increase in air temperatures, which has accelerated particularly in the early twenty-first century (NOAA 2023;IPCC 2021), has led to a rise in the frequency of heat waves (HWs), considered among the most lethal natural hazards (e.g., Kovats and Kristie 2006;Mohleji and Pielke 2014). Heatwave events have been shown to increase mortality and morbidity rates, posing a higher risk to specific groups, including all age groups, particularly the elderly and children, as well as low-income individuals and those with specific medical conditions, especially cardiovascular and respiratory diseases (e.g., Arsad et al. 2022;Graczyk et al. 2022;Syah et al. 2022;Yadav et al. 2023). ...
The spatiotemporal variability and trends of atmospheric blockings over the Euro-Atlantic region and their influence on the occurrence of the persisting extreme temperature conditions in Poland namely heat waves (HWs) and cold spells (CSs) during the period 1979–2023 were analyzed. Blockings were identified at 500 hPa geopotential level, using the meridional geopotential gradient method, supplemented with the quantile filter and persistence filter, using reanalysis data from the National Oceanic and Atmospheric Administration Physical Science Laboratory (NCEP-DOE AMIP-II R-2). HWs and CSs were defined as sequences of at least 3 days with the maximum air temperature above 30 °C or below -10 °C, respectively based on data obtained from the Institute of Meteorology and Water Management – National Research Institute (IMGW – PIB) for the period 1979–2022 across 37 stations in Poland. The climatology of Euro-Atlantic blocking occurrence in the zonal belt between 45 and 75 degrees in the northern hemisphere exhibits high spatiotemporal variability. Blocking structures are most frequent in the spring, particularly in May. A secondary peak of frequency is observed in July when the Ural blocking exhibits 15% frequency. Patterns of trends in blocking occurrence are variable and the strongest signals of changes are observed in spring. The occurrence of HWs in Poland is constantly accompanied by blocking situations, most often located northeast of Poland, while the winter CSs are associated with the blockings located over the North Atlantic and northern Scandinavia.
... In the context of signi cant contemporary climate change, extreme weather events have become a prominent focus in climatology, largely due to their substantial economic and social risks. The observed increase in air temperatures, which has accelerated particularly in the early 21st century (NOAA 2023; IPCC 2021), has led to a rise in the frequency of heat waves (HWs), considered among the most lethal natural hazards (e.g., Kovats and Kristie 2006;Mohleji and Pielke 2014). Additionally, HWs are frequently linked with droughts that exacerbate the risk of forest res and cause substantial damage to agriculture, thus amplifying the associated hazards (e.g., Christian et al. 2020). ...
The spatiotemporal variability and trends of atmospheric blockings over the Euro-Atlantic region and their influence on the occurrence of the persisting extreme temperature conditions in Poland namely heat waves (HWs) and cold spells (CSs) during the period 1978–2023 were analyzed. Blockings were identified at 500 hPa geopotential level, using the meridional geopotential gradient method, supplemented with the quantile filter and persistence filter, using reanalysis data from the National Oceanic and Atmospheric Administration Physical Science Laboratory (NCEP-DOE AMIP-II R-2). HWs and CSs were defined as sequences of at least 3 days with the maximum air temperature above 30°C or below − 10°C, respectively based on data obtained from the Institute of Meteorology and Water Management – National Research Institute (IMGW – PIB) for the period 1978–2022 across 37 stations in Poland. The climatology of Euro-Atlantic blocking occurrence in the zonal belt between 45 and 75 degrees in the northern hemisphere exhibits high spatiotemporal variability. Blocking structures are most frequent in the spring, particularly in May. A secondary peak of frequency is observed in July when the Ural blocking exhibits 15% frequency. Patterns of trends in blocking occurrence are variable and the strongest signals of changes are observed in spring. The occurrence of HWs in Poland is constantly accompanied by blocking situations, most often located northeast of Poland, while the winter CSs are associated with the blockings located over the North Atlantic and northern Scandinavia.
... Damages caused by extremely large floods might be huge and even irreparable. Moreover, over several decades, economic and environmental losses due to floods have significantly increased (Mohleji and Pielke Jr 2014). This can be explained for at least two reasons. ...
There have been many destructive pluvial and fluvial floods in Poland and the projection of increasing flood hazards in the future is a reason of considerable concern. The maps of river hazard zones are changing over time, and understanding these changes is of primary importance for flood risk reduction and climate change adaptation. This article aims to assess the impact of climate change on the spatial extent and depth classes of flood hazard zones for a selected reach of the River Warta in the western part of Poland. To this end, we integrated the Soil & Water Assessment Tool (SWAT) hydrological model of the Warta River Basin with the 1D hydraulic model HEC-RAS of the selected reach. The climate change effect was quantified based on the coupled model simulations forced with bias-corrected projections from the EURO-CORDEX project. Flood hazard maps were developed for two townships along the River Warta (Oborniki and Wronki), three greenhouse gas concentration scenarios (one for the baseline scenario in the reference period, 1971–2000; one for RCP 4.5 and one for RCP 8.5, for the time horizon 2021–2050) and for three return periods (10-, 100- and 500-year floods). Based on the ensemble mean, the increase in the flooded area projected in the future is more pronounced for RCP8.5 than for RCP4.5. This unique combination of software and data enabled the transformation of climate change impact into the land surface part of the hydrological cycle and assessment of changes in flood hazard and opens the way to assess the potential increases in the economic losses in the future.
... Floods are the natural hazard with the greatest global impact due to their frequency and the socioeconomic and environmental losses they cause, especially because they are frequently associated with other phenomena, such as landslides and severe weather events (Llasat 2021). Global flood losses have risen in recent decades, primarily due to increased exposure due to rapid population growth and economic development in flood-prone areas (IPCC 2012;Mohleji and Pielke 2014). Furthermore, as a result of climate change, the frequency and intensity of heavy precipitation events have increased since the 1950s (Kundzewicz et al. 2014;IPCC 2014), affecting many extreme weather and climate events, including floods (Milly et al. 2002;Dankers et al. 2014). ...
Flooding is the second most serious hazard in Algeria, after earthquakes. According to the Civil Protection Services census, the department of Algiers experienced 174 floods between 1946 and 2021, several devastating floods. This study examines Algiers’ vulnerability to flooding using the Hierarchical Multicriteria Analysis method, which aggregates eight criteria: altitude distribution, slopes, drainage density, topographic wetness index, land cover and land use, normalized difference vegetation index, soil types, and precipitations. With an 88% accuracy rate determined by the receiver operating characteristic method, the vulnerability map provides an essential tool for better risk and land-use management. The municipalities most vulnerable to flooding are located in the Mitidja (east of Algiers) and Algiers’ Western Sahel. These areas cover 209 km² (10% of Algiers’ urbanized area) and are primarily located in the watersheds of El Harrach, El Hamiz, and Reghaia, while 26% of urbanized areas are moderately vulnerable. However, these areas require special attention because of their high population density. In 2021, urbanization in Algiers reached 44.35%, with major wadis beds recording nearly half (~ 49.4%) of their watershed area as urbanized. These percentages underscore the urgency of addressing the impact of urban expansion on heightened flood risks. Our findings emphasize the need for a more rigorous implementation of land-use planning regulations, as well as prevention, adaptation, and mitigation measures.
... Landslides caused 242 deaths between 2008 to 2018 [40] and caused economic loss estimated as the 0.2% of the total GDP [41]. However, the assessment of the exact loss estimates (direct and indirect) is extremely challenging and the actual economic loss could be significantly bigger that what is determined [42]. Even if recurrent landslides occur, about 45% of the total population live in the landslide-prone zones. ...
Resilience of systems to natural hazards has become an interesting concept in civil engineering and it is based on the determination of the losses due to the impacts of natural hazards. In the last decades, many contributions have focused on the assessment of losses that may occur at the time of the event, as generally assumed for earthquakes. However, this assumption may be incorrect when the interval between the time of occurrence and the time when the system functionality reaches the minimum value needs to be considered. This paper aims to propose a novel method to quantify this interval, which is called disruption time, by proposing a novel formulation of the loss model based on infrastructure redundancy. The proposed method was herein applied to a case study that considers landslides in Sri Lanka. The main goal of the paper is to propose a formulation that can be implemented in a more comprehensive framework to calculate more realistically the resilience of systems to natural hazards.
... These threats have escalated from low levels in the fifth assessment to moderate levels in the sixth assessment (Ziervogel et al., 2014). According to Mohleji and Pielke (2014), the ongoing drought has caused the death of over one million people and resulted in economic losses over sixty billion US dollars since 1974. Gidey et al. (2018) asserted that the population dwelling in regions experiencing high water stress, due to repeated droughts, is expected to rise considerably from 300 million to over 5 billion by 2025. ...
... The concerning statistics and devastating impacts of hurricanes stress the critical importance of proactive measures for comprehensive preparedness, effective response strategies, and mitigation efforts to safeguard vulnerable communities 5,[8][9][10][11] . Hurricanes are powerful and destructive weather phenomena that can cause significant damage to coastal areas and beyond 12,13 . In addition to their powerful winds, these major natural events also bring heavy rainfall, contributing to flood hazards. ...
Hurricanes associated with strong winds and heavy rainfall, significantly impact lives and property globally. Traditional approaches focusing only on wind speed lack a comprehensive assessment of potential impacts. Here, we present an innovative method for generating real-time dynamic bivariate hazard assessments for hurricanes, with a specific focus on wind and rainfall, offering a holistic perspective on probable impact. Demonstrated on four hurricanes, this method computes the probabilistic wind and rainfall hazard values at different lead days. These are categorized and presented as bivariate hazard maps to facilitate straightforward interpretation and efficient communication. These maps provide insights into the combined hazard and highlight the individual contributions of wind and rainfall across different lead times, empowering stakeholders to strategize preparedness and precautionary measures. This method provides a novel generic approach for communicating forecast through dynamic bivariate hazard maps, applicable to a range of extreme events such as floods, wildfires, and droughts.
... These threats have escalated from low levels in the fifth assessment to moderate levels in the sixth assessment (Ziervogel et al., 2014). According to Mohleji and Pielke (2014), the ongoing drought has caused the death of over one million people and resulted in economic losses over sixty billion US dollars since 1974. Gidey et al. (2018) asserted that the population dwelling in regions experiencing high water stress, due to repeated droughts, is expected to rise considerably from 300 million to over 5 billion by 2025. ...
To mitigate the effects of drought in water-stressed agro-ecological zones (AEZs), it is crucial to implement efficient monitoring of drought characteristics and establish proactive water-use strategies. The Western Cape (WC) province is being confronted with an escalating threat of diminished water availability due to unsustainable human activities. The objective of this study was to assess the spatio-temporal characteristics of meteorological drought within a 12-month timescale in the WC province of South Africa spanning from 1980 to 2020. The University of East Anglia's Climate Research Unit provided precipitation datasets from fifteen stations across the six AEZs of the WC province. These datasets were processed using the Standardized Precipitation Index (SPI). The Mann–Kendall (M–K) test was used to analyze the precipitation trend and SPI values at a significance level of p < 0.05. The results indicated substantial negative trends in annual precipitation across all AEZs. An examination of seasonal precipitation patterns revealed a rise in summer precipitation in subtropical cool-arid regions and subtropical warm semi-arid regions, with increases of 0.4 and 0.2 mm/year, respectively. Conversely, the overall annual precipitation trend fell by -1.0 mm/year in both AEZs. The SPI values consistently fell within the range of -2 to 0 in the subtropical warm-arid, subtropical cool-arid, and subtropical cool-arid zones. Conversely, the SPI values were consistently positive in the subtropical warm-arid, subtropical cool-humid, and subtropical warm-humid zones. This finding suggests that there will be persistent drought conditions that will affect agricultural production, surface flows in rivers, and groundwater levels across the WC province.
... In 2019, approximately 317 significant natural disasters occurred worldwide, with floods accounting for 45% of these natural disasters. The continent of Asia has faced more flood disasters than anywhere else [3,4]. On the continent, Iran is located in hazardous flood covers approximately 10,358.9 ...
The aim of this paper is to assess the extent to which the Sad-Kalan watershed in Iran participates in floods and rank the Sad-Kalan sub-watersheds in terms of flooding potential by utilizing multi-criteria decision-making approaches. We employed the entropy of a drainage network, stream power index (SPI), slope, topographic control index (TCI), and compactness coefficient (Cc) in this investigation. After forming a decision matrix with 25 possibilities (sub-watersheds) and 5 evaluation indices, we used four MCDM approaches, including the analytic hierarchy process (AHP), best–worst method (BWM), interval rough numbers AHP (IRNAHP), picture fuzzy with AHP (PF-AHP), and picture fuzzy with linear assignment model (PF-LAM, hereafter PICALAM) algorithms, to rank the sub-watersheds. The study results demonstrated that PICALAM exhibited superior performance compared to the other methods due to its consideration of both local and global weights for each criterion. Additionally, among the methods used (AHP, BWM, and IRNAHP) that showed similar performances in ranking the sub-watersheds, the BWM method proved to be more time-efficient in the ranking process.
... Floods are one of the most frequent and disruptive natural disasters that cause widespread devastation, resulting in loss of life and severely affecting livelihood. The intensity and frequency of floods have been exacerbated over the recent decades in several parts of the world (Maskey & Samuels, 2021;Mohleji & Pielke, 2014). It is reported that 19% of the world's population faces a moderate flood risk (Rentschler & Salhab, 2020). ...
Flood management activities require development of flood maps that depict the spatial and temporal extent of floods with the help of hydrodynamic models. Two-dimensional (2-D) hydrodynamic models are frequently employed for flood inundation modeling and mapping with the help of high-end computational resources and high-resolution terrain information such as LiDAR (light detection and ranging) data. However, LiDAR data are either unavailable or not freely accessible in many parts of the world, especially in nations belonging to Global South. Hence, one-dimensional (1-D) models are still in practice owing to their lesser computational cost and data requirement. Nonetheless, the successful application of a 1-D model depends mainly on the representation of the natural river and floodplain geometry, which is the primary input in the form of discrete cross-sections. The assumed flow directions on floodplains while orienting the cross-sections in 1-D models induce some uncertainty in the model simulations. This study aims to evaluate the variability in the model simulations caused by the cross-sectional orientations. Flood simulations were performed using a 1-D hydrodynamic model for six different cross-sectional realizations for three river reaches, having distinct morphological and topographical characteristics, and were compared with the simulations of a 2-D hydrodynamic model and available reference inundation maps. The study suggests that the simulations of flood inundation extent and maximum flow depth variation are influenced by the cross-sectional orientation on flood plains in river reaches characterized by broad flood plains with complex local topographical variations. In contrast, for reaches with relatively less wide and complex terrains, 1-D models can generate robust simulations of flood inundation extent and spatial variation in maximum flood depth (R2 and NSE greater than 0.89) for high flood events.
... In recent years, both the number of people affected by floods and the damages have been rising significantly. In particular, this increase in economic losses can be explained entirely by changes in socioeconomic factors such as population growth, wealth and increasing development in hazardous areas (Barredo, 2009, IPCC, 2012, Mohleji and Pielke, 2014, GFDRR, 2016. Therefore, flood events manifest themselves as disasters when combined with the exposure and vulnerability of settlements and communities (e.g. ...
... Coastal communities in the southeastern United States have a great degree of risk from frequent hurricanes which devastate this region each year, and that is only exacerbated by rapid urbanization near the coasts. While global occurrences of natural hazards and their resulting economic losses fluctuate from year to year, Mohleji and Pielke (2014) provide comprehensive review of such losses from 1980 to 2008 and indicate that global losses are increasing at a rate of $3.1 billion per year, of which hurricane hazards in North America account for 57%. Focusing on the continental United States, where the majority of this loss has taken place, 197 hurricanes occurred between 1900 and 2017, resulting in 206 landfalls in the US and nearly $17 billion in annual damage, normalized to 2018 dollar value (Weinkle et al., 2018). ...
As coastal populations increase every year, greater numbers of people and buildings to support them are left vulnerable to severe hazards associated with hurricanes, which have shown signs of increasing strength and frequency related to climate change. Community-level decision making is essential to adequately prepare populations for the risks associated with imminent hurricanes and to adapt buildings to be more resilient. This creates a need for state-of-the-art methods such as data-driven machine learning to predict the damage that buildings will experience during hurricanes and support decisions for community stakeholders. Previous research has attempted to proactively forecast hurricane damage using numerical frameworks for individual building archetypes or by incorporating a narrow spectrum of input features. The focus of this study is a novel machine learning framework trained on building, hazard, and geospatial data to hindcast damage from Hurricanes Harvey, Irma, Michael, and Laura, with the objective of forecasting expected damage from future hurricanes. Performance of different algorithms were investigated including k-nearest neighbors, decision tree, random forest, and gradient boosting trees algorithms. In predicting qualitative damage states, random forest outperforms other algorithms with 76% accuracy in the hindcast. Parametric studies identify which features contribute the most to accurate predictions and demonstrate that prediction accuracy increases linearly for this case study with additional reconnaissance data to train the model. Finally, a comparison is drawn between this model and the ability of Federal Emergency Management Agency’s Hazus Multi-Hazard Hurricane Model to estimate building-specific damage on the same hindcast set of buildings.
... Weather extremes have a great significance for society, as they pose a threat to human life and can result in enormous economic damage and disruption. In Europe, heat waves are among the deadliest natural hazards, while storms and flooding events are among the costliest (Kovats and Kristie, 2006;Mohleji and Pielke, 2014;Raška, 2015;Forzieri et al., 2017). The heat wave in 2010, which affected eastern Europe and large parts of Russia, is a prominent example of such an event (e.g., Grumm, 2011). ...
The physical understanding and timely prediction of extreme weather events are of enormous importance to society due to their associated impacts. In this article, we highlight several types of weather extremes occurring in Europe in connection with a particular atmospheric flow pattern, known as atmospheric blocking. This flow pattern effectively blocks the prevailing westerly large-scale atmospheric flow, resulting in changing flow anomalies in the vicinity of the blocking system and persistent conditions in the immediate region of its occurrence. Blocking systems are long-lasting, quasi-stationary and self-sustaining systems that occur frequently over certain regions. Their presence and characteristics have an impact on the predictability of weather extremes and can thus be used as potential indicators. The phasing between the surface and the upper-level blocking anomalies is of major importance for the development of the extreme event. In summer, heat waves and droughts form below the blocking anticyclone primarily via large-scale subsidence that leads to cloud-free skies and, thus, persistent shortwave radiative warming of the ground. In winter, cold waves that occur during atmospheric blocking are normally observed downstream or south of these systems. Here, meridional advection of cold air masses from higher latitudes plays a decisive role. Depending on their location, blocking systems also may lead to a shift in the storm track, which influences the occurrence of wind and precipitation anomalies. Due to these multifaceted linkages, compound events are often observed in conjunction with blocking conditions. In addition to the aforementioned relations, the predictability of extreme events associated with blocking and links to climate change are assessed. Finally, current knowledge gaps and pertinent research perspectives for the future are discussed.
... Tropical cyclones (TCs), known as typhoons (Pacific regions) or hurricanes (Atlantic region), are responsible for the largest historical damages among climate-and weatherrelated events (Mohleji and Pielke, 2014). Therefore, TCs are gaining more attention recently due to their abrupt and devastating impacts worldwide (Huang and Wang, 2015; X. . ...
Risk-informed planning and management are integral to the sustainability of hazard-prone areas at all spatial scales. In connection to this, the current thesis advances the in-practice traditional risk frameworks for inclusiveness, reliability, and future vigilance in the wake of natural hazards and climate change via fostering inter-disciplinary approaches, recommends the integration of natural systems in risk assessment process for co-benefits, proposes aligning risk and sustainability frameworks for multi-objective planning and management, and explains how geospatial information models/technology could assist in risk management (profiling, decision-making, policy development, and resource allocation). The thesis consists of four main parts: (I) risk assessment perspectives, (II) influence of natural systems on risk level and its distribution, (III) aligning risk and sustainability frameworks, and (IV) integrating spatial models for effective risk management.
Each part addresses a specific objective of this study. These include risk perspectives, realizing natural habitats role in risk frameworks, aligning risk management and sustainability intentions, and integrating geospatial technology to inform risk management for effective planning (decision-making and resource allocation). Among all the natural hazards, tropical cyclones and coastal storms are chosen for this study due to their significant impacts.
Part I comprehensively details different risk assessment perspectives using hurricane flood risk along the United States Atlantic and Gulf coasts as a case study—under current and future scenarios. Most of the high-risk hotspots are found in the Gulf coast region, particularly along the west coast of Florida. While the resultant risk is sensitive to the consideration of evaluation factors (i.e., hazard, vulnerability, and resilience), two out of three risk evaluation approaches indicate New York City as a risk hotspot under the future climate. Additionally, a machine-learning algorithm-based approach to map the spatially distinct groups shows that the counties in the highest risk group (15% of total counties, including New York City) in the future lack specifically in the community capital and the social components of community resilience.
In Part II, a coupled human-nature system-based framework is used to provide evidence on the influence of coastal natural habitats (CNHs) on coastal storm-risk level and spatial distribution. To do so, a spatially relative risk index for each coastal county along the U.S. Atlantic coast is computed incorporating several bio-geo-physical variables (e.g., geomorphology, natural habitats, coastal relief, and historical data on sea level trends, wind, and wave) and data on socio-ecological systems. The index is calculated under two CNH scenarios (i.e., without- and with-habitat) and is further used for mapping the at-risk population. The without-habitat scenario is found to overestimate the population in the highest risk category by 10 % and the number of counties by as much as 40 % as compared to the with-habitat scenario—mostly in the Gulf region. Also, the without-habitat scenario miscalculates the spatial distribution of the risk. While the results highlight the role of CNHs in influencing the risk level and its distribution, the findings support the emphasis by conservationists on policies relevant to the protection and restoration of coastal natural systems owing to their multiple services.
In Part III, a risk-resilience-sustainability nexus-based approach is proposed to align risk and sustainability frameworks. In contrast to traditional approaches, the framework employs an integrative approach and simultaneously provides useful input for resilience management in parallel to achieving certain Sustainable Development Goals (SDGs). The proposed framework is applied for risk assessment (represented by a Typhoon Risk Index—TRI) of coastal counties in Mainland China. A large spatial heterogeneity in typhoon risk is found with an increase in the risk from north to south in the study area. Further, the overall performance of coastal provinces in Mainland China is higher to achieve SDGs 3 and 15 followed by 13 and 8. The study shows that while Guangdong Province in southern China is in the highest risk category, its achievement status for SDG-13 (climate actions, strengthening resilience) is the lowest relative to other provinces.
In Part IV, a geographic-information-system-based framework integrating spatial distributional models is proposed to evaluate the spatial heterogeneities of risk, its spatial patterns, and statistically significant hotspots of the highest risk. Further, the level of contribution of each risk parameter (i.e., hazard, vulnerability, and community resilience) towards overall risk is evaluated. It is found that among 70% exposed counties, ~ 30% are in the highest risk category (value ≥ 3rd quartile). The areas under the highest risk harbour > 50 million people (~43%)—more than 7 million non-adults (0–14 years, ~42%), and approximately 2.5 million elderly people (above 65 years, ~31%). The Pearl-River-Delta region of Guangdong Province in southern China is identified as the hotspot of the highest typhoon risk, followed by Fujian and Zhejiang provinces—95% confidence.
... Research modeling commercial flood risk often is restricted by data availability issues. For example, property information may not differentiate between building and use types (Mohleji and Pielke, 2014) such as when sourced from satellite imagery. Other research has been limited to only residential losses (typically for single family residential properties) or critical infrastructures as this data may be provided by government databases. ...
Environmental changes are predicted to exacerbate changes in flood events, resulting in consequences for exposed systems. While the availability and quality of flood risk analyses are generally increasing, very little attention has been paid to flood impacts related to the commercial market. This is notable given that the commercial market is often made up of the most valuable physical structures in communities, employs much of the local labor force, and generally plays a key role in the sustainability of economies. This study provides the first national spatial model of flood risk for commercial and multi-unit residential buildings at a property level resolution within the United States. This is achieved through the use of high-resolution inputs (hazard and property data), flood hazard information for the four major flood types, multi-return period hazard information, component-based depth-damage functions, GDP and economic multipliers information, and future facing projections. This study estimates that over the next 30 years, the absolute count of commercial and multi-unit buildings with risk will increase 8%, structural damage costs will increase 25.4%, downtime days will increase 29.1%, and economic impacts will increase 26.5%. Additionally, these impacts are concentrated in certain spatial locations. A high resolution model capturing flood risk as related to these commercial buildings is important for a comprehensive understanding of overall flood risk within the United States.
Classification Codes
JEL C30, E00, G17, M20, R10, R30
... Historically, around 60% of all economic damages caused by disasters worldwide is the consequence of hurricanes in the USA [12], and more than 80% of this damage comes from major hurricanes. It is therefore not surprising that hurricanes grab interest and attention. ...
This article reviews recent bibliography on time series of some extreme weather events and related response indicators in order to understand whether an increase in intensity and/or frequency is detectable. The most robust global changes in climate extremes are found in yearly values of heatwaves (number of days, maximum duration and cumulated heat), while global trends in heatwave intensity are not significant. Daily precipitation intensity and extreme precipitation frequency are stationary in the main part of the weather stations. Trend analysis of the time series of tropical cyclones show a substantial temporal invariance and the same is true for tornadoes in the USA. At the same time, the impact of warming on surface wind speed remains unclear. The analysis is then extended to some global response indicators of extreme meteorological events, namely natural disasters, floods, droughts, ecosystem productivity and yields of the four main crops (maize, rice, soybean and wheat). None of these response indicators show a clear positive trend of extreme events. In conclusion on the basis of observational data, the climate crisis that, according to many sources, we are experiencing today, is not evident yet. It would be nevertheless extremely important to define mitigation and adaptation strategies that take into account current trends.
... The new approaches, which we have presented in this study, can be used in a wider context of TC impact assessment. Many studies investigated the changes in TC-related losses on climate time scales around the world using historical data [46,[62][63][64][65][66][67]. Since the principle of our approaches is general, they can be used for an in-depth analysis on the potential global risk of TCs on the climate time scale. ...
Parametric typhoon insurances are an increasingly used financial tool to mitigate the enormous impact of tropical cyclones, as they can quickly distribute much-needed resources, e.g., for post-disaster recovery. In order to optimise the reliability and efficiency of parametric insurance, it is essential to have well-defined trigger points for any post-disaster payout. This requires a robust localised hazard assessment for a given region. However, due to the rarity of severe, landfalling tropical cyclones, it is difficult to obtain a robust hazard assessment based on historical observations. A recent approach makes use of unrealised, high impact tropical cyclones from state-of-the-art ensemble prediction systems to build a physically consistent event set, which would be equivalent to about 10,000 years of observations. In this study, we demonstrate that (1) alternative trigger points of parametric typhoon insurance can be constructed from a local perspective and the added value of such trigger points can be analysed by comparing with an experimental set-up informed by current practice; (2) the estimation of the occurrence of tropical cyclone-related losses on the provincial level can be improved. We further discuss the potential future development of a general tropical cyclone compound parametric insurance.
... Economic impact analyses of a disaster event often use a multiplier model to estimate the economic losses (Mohleji & Pielke 2014;Smith & Katz 2013). The use of a multiplier model-a SAM model in this study-is critical in the effort to "gauge individual and community vulnerability" (Rose, 2004). ...
Interests are growing in the distributional impact of natural catastrophes. Motivated by the increasing frequency and intensity of extreme weather events, the present study proposes the use of structural path analysis (SPA) to identify the paths that render certain populations more vulnerable to an economic shock. The analysis proceeds in three main stages. The first stage employs geographic information systems (GIS) maps to identify economic activities disrupted by virtue of their geo-location in directly affected areas. The direct sectoral impact is subsequently fed into a social accounting matrix (SAM) model in the second stage to estimate the ripple effects generated by the network of economic linkages. SPA is deployed in the final stage to determine the paths through which the impact ripples from the shock's origin to households. Because SAM disaggregates households into distinct categories, the multiplier decomposition procedure enables SPA to identify the specific links that transmit the shock to every household category. The approach is employed to examine the New York City case in the backdrop of Superstorm Sandy and compare it with post-Katrina New Orleans. The results suggest that while relatively well-off New Yorkers may have suffered the most from Sandy's path of destruction, the New Orleans poor appeared most vulnerable in Katrina's aftermath.
... Floods are a recurrent problem for public safety, which disrupts life and bring distress and losses in many areas of the world (Mohleji and Pielke 2014). Over the years, specialized tools have been devised to be better prepared to face such natural hazards. ...
Floods are among natural disasters that increasingly threaten society, especially with current and future climate change trends. Several tools have been developed to help planners manage the risks associated to flooding, including the mapping of flood-prone areas, but one of the major challenges is still the availability of detailed data, particularly bathymetry. This manuscript compares two modeling approaches to produce flood maps. An innovative large-scale approach that, without bathymetric data, estimates by inverse modeling the bed section for a given flow and a given roughness coefficient through 1 D/2D hydraulic modeling (LISFLOOD-FP). And a local approach, with a detailed coupled 1 D/2D hydraulic model (HEC-RAS) that uses all available information at the bed and floodplain (LiDAR and bathymetry). Both implementations revealed good performance values for flood peak levels as well as excellent fit indices in describing the areal extent of flooding. As expected, the local approach is more accurate, but the results of the large-scale approach are very promising especially for areas lacking bathymetric data and for large-scale governmental programs.
... The US focus of the studies could be attributed to its long history of hurricanes. For example, between 1980 and 2008 U.S. hurricanes alone resulted in 57% of global economic losses from extreme weather events (Mohleji & Pielke, 2014). It is also possible that the US focus is due to funding availability (i.e., the United States is a large contributor of research funding) or that one of the systematic literature review search criteria was that papers be available in English. ...
Non-technical summary
Coastal communities face environmental challenges that put food, energy, and water systems at risk. Although highly interdependent, it is unknown the extent to which coastal resilience research has considered interactions among food–energy–water systems. Twenty peer-reviewed articles were identified that focused on these systems and coastal resilience. Although a nexus approach was not employed universally, these studies most commonly addressed interactions among these systems related to acute hazards. They consistently acknowledged the influence of energy and transportation systems upon the others. As such, planners should incorporate linkages across all three systems during coastal resilience planning especially in relation to acute hazards.
Technical summary
Coastal communities strive for resilience in the face of an ever-growing suite of threats by planning and preparing for numerous uncertain futures. Food, energy, and water systems are highly interconnected and essential to the well-being of coastal communities. However, it is unknown the extent to which coastal resilience research has included food–energy–water nexus considerations. This study used a systematic literature review of peer-reviewed research articles and identified 20 studies that focused on food, energy, and water systems as related to coastal resilience. Results revealed four main findings: (1) the food–energy–water nexus approach was most commonly applied to coastal resilience in the study of US locations and in the context of acute hazards, (2) a direct food–energy–water or other nexus approach was directly employed by only half of the studies, however, all highlighted the relevance of systems interconnections in the context of coastal resilience, (3) the energy system was shown to impact every system to which it was connected, and (4) the transportation system was also shown to impact every system to which it was connected, which suggests that the food–energy–water nexus should be expanded to include transportation systems.
Social media summary
Coastal resilience and food–energy–water nexus literature synthesis finds interconnected systems considerations relevant to resilience.
... However, coastal areas are vulnerable to multiple natural hazards because such events occur at the dynamic interface between the ocean and land (Yang, Madden, Kim, & Jordan, 2012). Among all natural hazards, tropical cyclones are one of the most devastating threats to coastal tourism destinations (Gall, Borden, & Cutter, 2009;Mohleji & Pielke, 2014). The strong winds and heavy precipitation of tropical cyclones cause storm surges and flooding. ...
The increasing number of natural hazards in coastal tourism destinations has negatively affected their local lodging industries. The recent boom in shared accommodation in coastal destinations is also under threat due to increasing sea levels and extreme weather events. Thus, estimating the economic impact of natural hazards on shared accommodation is a critical prerequisite for effective tourism destination crisis management. This study aimed to estimate the economic impact of natural hazards on shared accommodation. To achieve this purpose, HAZards U.S. MultiHazard (HAZUS-MH) hurricane/flood models were employed in a case study of Hurricane Irma and 822 Airbnb properties in Collier County, Florida, for 2017. The estimated direct combined losses from wind gusts and storm surge flooding were 19,120 per day. This estimation method can help individual owners and local government managers predict problems related to natural hazards and more effectively prepare for future hazardous events in coastal tourism destinations.
... Flooding regularly causes severe casualties and great economic losses globally , CERD and UNISDR 2018, CRED 2019, as well as a variety of horrible diseases and destruction of the ecological environment (Dionisio et al 2017, Green et al 2017, Berry et al 2018. Moreover, losses due to floods have been increasing over the past several decades (Mohleji and Pielke 2014). River floods, in particular, are responsible for the largest proportion of total losses caused by floods (UNISDR 2011, Jongman et al 2012. ...
Floods that cause yearly economic losses and casualties have increased in frequency with global warming. Assessing the mortality risks of populations due to flooding is important and necessary for risk management and disaster reduction. Thus, this paper develops a method for assessing global mortality risks due to river flooding. Global historical annual death tolls are first estimated during the historical period 1986–2005 (T0) by using available mortality vulnerability functions of river flooding. Then, the best vulnerability function is selected according to lower root mean square errors (RMSE) and the differences in the multi-year mean (DMYM) values. Next, the adjustment coefficient K c for each country (region) is calculated to use in the revision of the selected vulnerability function. Finally, the mortality risks are estimated based on an adjusted vulnerability function. As a case, the paper assessed and analysed the global mortality risks due to river flooding during 2016–2035 (2030s) and 2046–2065 (2050s) for the combined scenario of the Representative Concentration Pathway 4.5 (RCP4.5) and the Shared Socioeconomic Pathway 2 (SSP2), and the RCP8.5-SSP5 scenario. The results show that the estimation errors of the death tolls in most countries (regions) decrease after adjusting the vulnerability function. Under the current defense capacity and vulnerability level, the average annual death tolls of RCP4.5-SSP2 and RCP8.5-SSP5 in the 2030s will increase by 1.05 times and 0.93 times compared with the historical period. They will increase 1.89 and 2.20 times, respectively for the two scenarios during 2050s. High-risk areas are distributed in the south-eastern Eurasia.
... That is why they are described as natural disasters that are events due to natural causes, there are more than 10 deaths, or at least 100 people declared to be affected or a call to international assistance or declaration of the state of emergency (Rasmussen, 2004;Cavallo & Noy, 2009). The main factors contributing to the increase of natural disasters are, for example, population and urban pressure Mohleji and Pielke (2014), Hoeppe (2016). ...
This paper aims to empirically analyze the relationship between natural disaster, health spending, urban population, gross fixed capital formation, and gross domestic product (GDP) per capita for lower middle-income countries. The data cover the period 2000–2019. The methodological approach used is based on Granger causality and Vector Error Correction Model (VECM) procedures. Empirical result reveals that GDP per capita and health spending are correlated positively with urban population. The results also indicate that there is a one-way relationship running from natural disaster to GDP per capita and from natural disaster to health spending in short and long run, while two-way relationship between health spending and urban population in short term. In long run, there is two-way relationship between GDP per capita and health spending.
... I n recent decades, there have been increases in damage and societal impacts relating to tropical cyclones (TCs) [1,2]. Since damages caused by TCs are highly correlated with their intensity and frequency, it is crucial to understand causes for the increase in TC activities. ...
We present a framework to quantify the radiation from tropical cyclones (TCs) in shortwave (SW, wavelength smaller than 3 micron) and longwave (LW, wavelength larger than 3 micron) portions of the electromagnetic spectrum. The framework includes two stages: segmentation of TC clouds and calculation of the radiation effects attributable to TC clouds. The segmentation task is accomplished by an algorithm which takes a time series of brightness temperature images of TCs and uses image processing techniques to acquire segmentation for each image in a semi-supervised manner. The radiation is calculated by combining the segmentation results with the Cloud and Earth's Radiant Energy System dataset via a coordinate-matching scheme due to their difference in resolution. The framework was implemented to analyse the net contribution of TCs to the upwelling radiation in 2016 and in summer months between 2015 and 2019 at regional and global scales. Results show that both the magnitude and the variability of radiation contribution by TCs are of an order of magnitude that could have a significant effect on the overall Earth's Energy Balance.
... Hurricane Sandy, may distort damage costs. In fact, Mohleji and Pielke (2014) argue that societal changes are sufficient to explain increasing disaster damages; see also Bouwer (2011). ...
Recent research in financial economics has shown that rare large disasters have the potential to disrupt financial sectors via the destruction of capital stocks and jumps in risk premia. These disruptions often entail negative feedback effects on the macroeconomy. Research on disaster risks has also actively been pursued in the macroeconomic models of climate change. Our paper uses insights from the former work to study disaster risks in the macroeconomics of climate change and to spell out policy needs. Empirically, the link between carbon dioxide emission and the frequency of climate related disaster is investigated using a panel data approach. The modeling part then uses a multi-phase dynamic macro model to explore the effects of rare large disasters resulting in capital losses and rising risk premia. Our proposed multi-phase dynamic model, incorporating climate-related disaster shocks and their aftermath as a distressed phase, is suitable for studying mitigation and adaptation policies as well as recovery policies.
... Hurricanes are believed to be major natural hazards due to their strong winds, storm surges, and rainfall in coastal areas globally. Since 1980, landfalling hurricanes in the continental U.S. have caused twothirds of the global total damages from natural hazards (Mohleji and Pielke, 2014;Weinkle et al., 2018). For example, in 2005, Hurricane Katrina-known to be the most devastating disaster in the U.S.-produced the highest flooding in the history of the U.S., resulting in more than USD100 billion in terms of damages and causing approximately 2000 mortalities. ...
We evaluate the spatial heterogeneities of hurricane flood risk along the United States (U.S.) Atlantic and Gulf coasts under two different climate scenarios (current and future). The flood hazard is presented as the hurricane surge flood level with 1% annual exceedance probability (100-year flood) under the two scenarios, where the future scenario considers the effect of hurricane climatology change and sea level rise towards late-21st-century under a high emission scenario (RCP8.5). This hazard information is combined with estimated vulnerability and disaster resilience of coastal communities to map the relative current and future risk employing different risk definitions. Several geographical techniques and spatial distributional models (e.g., spatial autocorrelation, spatial hotspot analysis, and spatial multivariate clustering analysis) are applied to systematically analyze the risk and identify statistically significant hotspots of the highest risk. Most of the high-risk hotspots are found in the Gulf coast region, particularly along the west coast of Florida. However, two out of three risk evaluation approaches also indicate New York City as a risk hotspot under the future climate—showing that the resultant risk is sensitive to the consideration of evaluation factors (i.e., hazard, vulnerability, and resilience). Additionally, we apply a machine-learning algorithm-based spatial multivariate approach to map the spatially distinct groups based on the values of risk, hazard, vulnerability, and resilience. The results show that the counties in the highest risk group (value >3rd quartile, 15% of total counties, including New York City) in the future lack specifically in the community capital and the social components of community resilience. This assessment of coastal risk to hurricane flood has important policy-relevant implications to provide a focus-for-action for risk reduction and resilience enhancement for the U.S., where 6.5 million households live in the hurricane flood-prone areas.
... Data from the reinsurance industry suggest that societal change-population and wealth-is sufficient to explain increasing disaster losses (Mohleji and Pielke 2014). An analysis of 22 disaster-loss studies suggests that if increases in population and capital were included in the disaster-loss equations, no loss trends can be attributed to human-induced climate change (Bouwer 2011). ...
Intense climate-related disasters—floods, storms, droughts, and heat waves—have been on the rise worldwide. At the same time and coupled with an increasing concentration of greenhouse gases in the atmosphere, temperatures, on average, have been rising, and are becoming more variable and more extreme. Rainfall has also been more variable and more extreme.
Is there an ominous link between the global increase of these hydrometeorological and climatological events on the one side and anthropogenic climate change on the other? This paper considers three main disaster risk factors—rising population exposure, greater population vulnerability, and increasing climate-related hazards—behind the increased frequency of intense climate-related natural disasters.
In a regression analysis within a model of disaster risk determination for 1971–2013, population exposure measured by population density and people’s vulnerability measured by socioeconomic variables are positively linked to the frequency of these intense disasters. Importantly, the results show that precipitation deviations are positively related to hydrometeorological events, while temperature and precipitation deviations have a negative association with climatological events. Moreover, global climate change indicators show positive and highly significant effects.
Along with the scientific association between greenhouse gases and the changes in the climate, the findings in this paper suggest a connection between the increasing number of natural disasters and man-made emissions of greenhouse gases in the atmosphere. The implication is that climate mitigation and climate adaptation should form part of actions for disaster risk reduction.
... Between 1998 and 2017, floods were the most frequent type of disaster, affecting more than two billion people and causing $656 billion USD in damages [2]. In particular, the increase in economic losses is almost entirely explained by changes in socioeconomic factors such as population growth, wealth and increasing development in hazardous areas [3][4][5][6][7]. Hazard events, such as floods, manifest themselves as disasters when combined with the exposure and vulnerability of human settlements and communities. ...
Disaster damages and losses have been increasing in recent decades, highlighting the need to learn from past events. Only a better understanding of the fundamental causes of disasters and their impacts on society can lead to effective prevention and reduction of disaster risk. In this context, disaster forensics focuses on the analysis and interaction of risk factors (i.e., hazard, exposure and vulnerability) and the identification of underlying causes, in order to tackle them through dedicated action. In this work, we explore the results of disaster forensics through a case study of subsequent floods in 2002 and 2013 in the city of Grimma, Saxony, in Germany. Risk factors are investigated to identify their contribution in increasing or reducing disaster damage, in conjunction with socio-economic impacts in the mostly affected inner city of Grimma. In particular, we analyze (i) what data is needed to conduct a disaster forensic analysis and (ii) how much the sequential application of disaster forensics contributes to a better understanding of risk and the identification of the causes of disasters impacts. The analysis shows that the sequential approach for disaster forensics is key for understanding cause–effect relationships regarding socio-economic impacts.
... Hurricane Sandy, may distort damage costs. In fact, Mohleji and Pielke (2014) argue that societal changes are sucient to explain increasing disaster damages (see also Bouwer, 2011). ...
Recent research in financial economics has shown that rare large disasters have the potential to disrupt financial sectors via the destruction of capital stocks and jumps in risk premia. These disruptions often entail negative feedback e?ects on the macroecon-omy. Research on disaster risks has also actively been pursued in the macroeconomic models of climate change. Our paper uses insights from the former work to study disaster risks in the macroeconomics of climate change and to spell out policy needs. Empirically the link between carbon dioxide emission and the frequency of climate re-lated disaster is investigated using cross-sectional and panel data. The modeling part then uses a multi-phase dynamic macro model to explore this causal nexus and the e?ects of rare large disasters resulting in capital losses and rising risk premia. Our proposed multi-phase dynamic model, incorporating climate-related disaster shocks and their aftermath as one phase, is suitable for studying mitigation and adaptation policies.
... For instance, the possible link between Arctic warming and an increase in extreme weather events in mid-latitude regions would affect various economic sectors in Europe, North America and Asia, including agriculture, tourism and insurance (Francis et al. 2017). To put this in a perspective, global annual weather-related losses increased from around US$ 50 billion in 1980 to around US$ 150 billion in 2012 (Munich Re 2013; The World Bank Group Experience 2013), although a significant part of this increase has been attributed to socio-economic factors alone (Bouwer 2011;Mohleji and Pielke 2014). ...
The scientific literature on physical changes in the Arctic region driven by climate change is extensive. In addition, the emerging understanding of physical feedbacks and teleconnections between the Arctic and the rest of the world suggests that the warming in the Arctic region is likely to cause impacts that extend well beyond the region itself. However, there is only limited research on how Arctic change may affect economies and individual industry sectors around the world. We argue that there is a pressing need for more research on this topic and present a conceptual framework to guide future research for assessing the regional and global economic impacts of Arctic change, including both possible benefits and costs. We stress on the importance of a transdisciplinary approach, which includes an integration of the natural sciences, economics and social sciences, as well as engagement with a wide range of stakeholders to better understand and manage the implications of Arctic change.
... Trends in global flood losses have been increasing over the past decades and have been attributed mainly to increasing exposure due to high population growth and economic development in flood-prone areas (4)(5)(6)(7)(8)(9). At the same time, rainfall patterns and intensities may shift under climate change (10,11), which could influence the flood hazard (12)(13)(14)(15). ...
The global impacts of river floods are substantial and rising. Effective adaptation to the increasing risks requires an in-depth understanding of the physical and socioeconomic drivers of risk. Whereas the modeling of flood hazard and exposure has improved greatly, compelling evidence on spatiotemporal patterns in vulnerability of societies around the world is still lacking. Due to this knowledge gap, the effects of vulnerability on global flood risk are not fully understood, and future projections of fatalities and losses available today are based on simplistic assumptions or do not include vulnerability. We show for the first time (to our knowledge) that trends and fluctuations in vulnerability to river floods around the world can be estimated by dynamic high-resolution modeling of flood hazard and exposure. We find that rising per-capita income coincided with a global decline in vulnerability between 1980 and 2010, which is reflected in decreasing mortality and losses as a share of the people and gross domestic product exposed to inundation. The results also demonstrate that vulnerability levels in low-and high-income countries have been converging, due to a relatively strong trend of vulnerability reduction in developing countries. Finally, we present projections of flood losses and fatalities under 100 individual scenario and model combinations , and three possible global vulnerability scenarios. The projections emphasize that materialized flood risk largely results from human behavior and that future risk increases can be largely contained using effective disaster risk reduction strategies. flooding | vulnerability | adaptation | climate change | development F looding is one of the most frequent and damaging natural hazards affecting societies across the globe, with average annual reported losses and fatalities between 1980 and 2012 exceeding $23 billion (bn) (in 2010 prices) and 5,900 people, respectively (1). These risks have been shown to negatively affect economic growth on a country level (2). Global trends and regional differences in flood risk result from the dynamics of hazard (i.e., the natural frequency and intensity of floods, without human interference), exposure (i.e., the population and economic assets located in flood hazard-prone areas), and vulnerability (i.e., the susceptibility of the exposed elements to the hazard) (3, 4). Each of these contributing factors can be expected to change over time. Trends in global flood losses have been increasing over the past decades and have been attributed mainly to increasing exposure due to high population growth and economic development in flood-prone areas (4-9). At the same time, rainfall patterns and intensities may shift under climate change (10, 11), which could influence the flood hazard (12-15). In addition, inter-annual variations in peak discharge, caused by climatic oscillations such as El Niño Southern Oscillation, may lead to strong spatiotemporal fluctuations in the occurrence of floods (16, 17). These hazard and exposure elements can only partly explain spatiotemporal patterns in flood risk, because of the importance of vulnerability (8, 18). There are many different and competing definitions of vulnerability in literature (see ref. 4, chap. 2, for a discussion on these). Vulnerability is considered in this study to include all man-made efforts to reduce the impact of the natural flood hazard on the exposed elements, including structural flood defenses, building quality early-warning systems, and available health care and communication facilities (19-21). Vulnerability is dynamic and varying across temporal and spatial scales, and may depend on economic, social, geographic, demographic, cultural, institutional, gover-nance, and environmental factors (ref. 4, chap. 2). The level of vulnerability is therefore affected by socioeconomic development (ref. 4, chap. 2; see also ref. 22) and can specifically be influenced by deliberate disaster risk reduction efforts (19, 23). The reduction of vulnerability over time makes countries less prone to the adverse effects of the current and future flood hazard and is therefore considered as a display of adaptation. For example, two similar tropical cyclones made landfall in eastern India, one in 2013 (Phailin) and one in 1999 (Cyclone 05B). Exposed population was greater in 2013 due to population growth and development in cyclone-prone areas. However, the vulnerability in the region had drastically decreased with the implementation of a disaster management authority; cyclone shelters and early-warning systems ensured that only a small fraction of the population was vulnerable to this event. Because of this, the total reported impacts for the similar event in 2013 were much lower; fewer than 50 lives were lost in 2013, whereas the cyclone in 1999 was responsible for more than 10,000 lives lost (24). A similar study examined the effect of mangrove forests in the 1999 event; controlling for distance from the coast and Significance Understanding the vulnerability of societies around the world is crucial for understanding historical trends in flood risk and for producing accurate projections of fatalities and losses. We reproduced historical river flood occurrence using daily climate data for the period 1980-2010 and quantified the natural and socioeconomic contributions to flood risk trends. We show that the fatalities and losses as a share of the exposed population and gross domestic product are decreasing with rising income. We also show that there is a tendency of convergence in vulnerability levels between low-and high-income countries. Projections based on a wide range of climate change and socioeconomic development scenarios demonstrate that amplified adaptation efforts have the potential to largely contain losses from future floods.
... Trends in global flood losses have been increasing over the past decades and have been attributed mainly to increasing exposure due to high population growth and economic development in flood-prone areas (4)(5)(6)(7)(8)(9). At the same time, rainfall patterns and intensities may shift under climate change (10,11), which could influence the flood hazard (12)(13)(14)(15). ...
The global impacts of river floods are substantial and rising. Effective adaptation to the increasing risks requires an in-depth understanding of the physical and socioeconomic drivers of risk. Whereas the modeling of flood hazard and exposure has improved greatly, compelling evidence on spatiotemporal patterns in vulnerability of societies around the world is still lacking. Due to this knowledge gap, the effects of vulnerability on global flood risk are not fully understood, and future projections of fatalities and losses available today are based on simplistic assumptions or do not include vulnerability. We show for the first time (to our knowledge) that trends and fluctuations in vulnerability to river floods around the world can be estimated by dynamic high-resolution modeling of flood hazard and exposure. We find that rising per-capita income coincided with a global decline in vulnerability between 1980 and 2010, which is reflected in decreasing mortality and losses as a share of the people and gross domestic product exposed to inundation. The results also demonstrate that vulnerability levels in low-and high-income countries have been converging, due to a relatively strong trend of vulnerability reduction in developing countries. Finally, we present projections of flood losses and fatalities under 100 individual scenario and model combinations , and three possible global vulnerability scenarios. The projections emphasize that materialized flood risk largely results from human behavior and that future risk increases can be largely contained using effective disaster risk reduction strategies. flooding | vulnerability | adaptation | climate change | development F looding is one of the most frequent and damaging natural hazards affecting societies across the globe, with average annual reported losses and fatalities between 1980 and 2012 exceeding $23 billion (bn) (in 2010 prices) and 5,900 people, respectively (1). These risks have been shown to negatively affect economic growth on a country level (2). Global trends and regional differences in flood risk result from the dynamics of hazard (i.e., the natural frequency and intensity of floods, without human interference), exposure (i.e., the population and economic assets located in flood hazard-prone areas), and vulnerability (i.e., the susceptibility of the exposed elements to the hazard) (3, 4). Each of these contributing factors can be expected to change over time. Trends in global flood losses have been increasing over the past decades and have been attributed mainly to increasing exposure due to high population growth and economic development in flood-prone areas (4-9). At the same time, rainfall patterns and intensities may shift under climate change (10, 11), which could influence the flood hazard (12-15). In addition, inter-annual variations in peak discharge, caused by climatic oscillations such as El Niño Southern Oscillation, may lead to strong spatiotemporal fluctuations in the occurrence of floods (16, 17). These hazard and exposure elements can only partly explain spatiotemporal patterns in flood risk, because of the importance of vulnerability (8, 18). There are many different and competing definitions of vulnerability in literature (see ref. 4, chap. 2, for a discussion on these). Vulnerability is considered in this study to include all man-made efforts to reduce the impact of the natural flood hazard on the exposed elements, including structural flood defenses, building quality early-warning systems, and available health care and communication facilities (19-21). Vulnerability is dynamic and varying across temporal and spatial scales, and may depend on economic, social, geographic, demographic, cultural, institutional, gover-nance, and environmental factors (ref. 4, chap. 2). The level of vulnerability is therefore affected by socioeconomic development (ref. 4, chap. 2; see also ref. 22) and can specifically be influenced by deliberate disaster risk reduction efforts (19, 23). The reduction of vulnerability over time makes countries less prone to the adverse effects of the current and future flood hazard and is therefore considered as a display of adaptation. For example, two similar tropical cyclones made landfall in eastern India, one in 2013 (Phailin) and one in 1999 (Cyclone 05B). Exposed population was greater in 2013 due to population growth and development in cyclone-prone areas. However, the vulnerability in the region had drastically decreased with the implementation of a disaster management authority; cyclone shelters and early-warning systems ensured that only a small fraction of the population was vulnerable to this event. Because of this, the total reported impacts for the similar event in 2013 were much lower; fewer than 50 lives were lost in 2013, whereas the cyclone in 1999 was responsible for more than 10,000 lives lost (24). A similar study examined the effect of mangrove forests in the 1999 event; controlling for distance from the coast and Significance Understanding the vulnerability of societies around the world is crucial for understanding historical trends in flood risk and for producing accurate projections of fatalities and losses. We reproduced historical river flood occurrence using daily climate data for the period 1980-2010 and quantified the natural and socioeconomic contributions to flood risk trends. We show that the fatalities and losses as a share of the exposed population and gross domestic product are decreasing with rising income. We also show that there is a tendency of convergence in vulnerability levels between low-and high-income countries. Projections based on a wide range of climate change and socioeconomic development scenarios demonstrate that amplified adaptation efforts have the potential to largely contain losses from future floods.
... L andfalling hurricanes in the continental United States (CONUS) are responsible for more than two-thirds of total global catastrophe losses since 1980, according to data from Munich Re, a global reinsurance company, which are consistent with the academic literature on disaster loss trends and the assessments of the Intergovernmental Panel on Climate Change (IPCC) 1 . The management of economic risks associated with hurricanes largely relies on 'catastrophe models' , which estimate losses from modelled storms in the context of contemporary data on exposure and vulnerability 2,3 . ...
Direct economic losses result when a hurricane encounters an exposed, vulnerable society. A normalization estimates direct economic losses from a historical extreme event if that same event was to occur under contemporary societal conditions. Under the global indicator framework of United Nations Sustainable Development Goals, the reduction of direct economic losses as a proportion of total economic activity is identified as a key indicator of progress in the mitigation of disaster impacts. Understanding loss trends in the context of development can therefore aid in assessing sustainable development. This analysis provides a major update to the leading dataset on normalized US hurricane losses in the continental United States from 1900 to 2017. Over this period, 197 hurricanes resulted in 206 landfalls with about US17 billion annually. Consistent with observed trends in the frequency and intensity of hurricane landfalls along the continental United States since 1900, the updated normalized loss estimates also show no trend. A more detailed comparison of trends in hurricanes and normalized losses over various periods in the twentieth century to 2017 demonstrates a very high degree of consistency. © 2018, The Author(s), under exclusive licence to Springer Nature Limited.
... The IPCC Assessment Report of Working Group II states with "high confidence" that economic costs of extreme weather events have increased over the period 1960-2000(Cramer et al., 2014. The question of whether anthropogenic climate change is responsible for the rise in damage is still a highly debated topic in science and politics (Bouwer, 2011;Cramer et al., 2014;Mohleji & Pielke, 2014). Bouwer (2011) analysed 22 studies, most of which demonstrated that this increase is due to an increase in the wealth and population exposed to damage from natural hazards, as no trend was detected after normalisation of nominal damage costs. ...
Switzerland is prone to many natural hazards causing high yearly damage to infrastructure and settlements. In this study questions about trends in data on damage from floods, debris flows and landslides are addressed and a potential connection to climate change is discussed. The data set of the Swiss flood and landslide damage database was normalized with three different approaches and trend tests were applied to yearly damage data from the period 1972–2016. Socio‐economic developments including those related to population and wealth were accounted for. The normalization of the nominal damage data resulted in much higher values in the earlier years of the study period, especially for high damage years. Total and mean damage were both around twice as high with normalization. Around 71–75% of the total (nominal and normalized) damage was found to occur from June through August, and spatial analysis showed the highest damage in central Switzerland and along river reaches in the main Alpine valleys. The results indicated no statistically significant increase over time in yearly nominal damage data or in data normalized with any of the three approaches. Potential effects of climate change on damage data therefore were not detected.
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... The inter-temporal evolution of global losses from catastrophes is clearly rising but mostly due to socioeconomic factors such as wealth, population, and urban pressure (cf. Mohleji and Pielke (2014) or Hoeppe (2016)). Regarding macroeconomic impact, the meta-analysis of Klomp and Valckx (2014) concludes to a negative short-run effect beyond the direct destruction losses and a negative drag on long-run growth, although this latter finding is disputed. ...
Using an exhaustive administrative database, we assess the impact of extreme weather events over French cities between 1982 and 2017. We identify numerous non-catastrophic disasters, thereby improving coverage wrt. the existing literature. Counting residents of cities stricken by a disaster, we find that in the long run, there were 22 residents affected every month per thousand population. This risk factor has been falling by 5 fewer people with every passing decade. France has thus improved its preparedness to natural disasters even though the seaboard regions fare worse than the northern region, most likely because of heightened urban pressure in hazardous areas by the seaside. Tropical territories are more at risk than the temperate European mainland, from a different mix of events. The full economic cost of natural disasters is estimated at 22 € per capita per year and represent a small fraction of property insurance premiums. Residents from safer areas currently subsidize those living in riskier areas. To be more effective, preventive investments should be directed towards the main cities.
... Floods affect millions of people [Jonkman, 2005] and cost billions of dollars annually [Mills, 2005] due to extensive socioeconomic growth [Bouwer, 2011;Mohleji & Pielke, 2014] and perhaps large spatial variation in flood protection [Scussolini et al., 2016]. Acceleration of the global hydrological cycle in a warmer world (e.g., Oki & Kanae [2006]; Lim & Roderick [2009]; Durack et al. [2012]; Roderick et al. [2014]) is projected to intensify precipitation [Allen & Ingram, 2002;Allan & Soden, 2008;O'Gorman & Schneider, 2009;Donat et al., 2016;Fischer & Knutti, 2016], causing bigger floods [Milly et al., 2002;Hirabayashi et al., 2008] with possible risk exacerbation because of socioeconomic development, land-use change (e.g., deforestation, urbanization) and/or subsidence [Hirabayashi et al., 2013;Winsemius et al., 2016;Ward et al., 2017;Dixon et al., 2006;Brown & Nicholls, 2015]. ...
A warmer climate is expected to accelerate the global hydrological cycle, causing more intense precipitation and floods. Despite recent progress in global flood risk assessment, the socioeconomic benefits of flood defenses (i.e., reduction in population/economic exposure) and the residual risk (i.e., residual population/economic exposure) are poorly understood globally and regionally. To address these knowledge gaps, we use the runoff data from a baseline and 11 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models to drive the Catchment-based Macro-scale Floodplain model incorporating the latest satellite river width information. From the simulated annual maxima, we use a Gumbel distribution to estimate the river water depth-flood return period relationship. We independently evaluate flood impacts on population and economy (i.e., gross domestic product) for a range of flood return periods. We estimate the socioeconomic benefits and the corresponding residual risk for the globe and 26 subcontinental regions. The global population (gross domestic product) exposed to flooding is ∼8% (∼7%) per year lower when implementing existing flood protection infrastructure extracted from the FLOod PROtection Standards database. If the current flood defenses were to be unchanged in the future (Representative Concentration Pathway 4.5 [RCP4.5] and RCP8.5, i.e., ∼2 to ∼4.3°C above the preindustrial levels), the globe and most of the regions (particularly where developing countries are concentrated) would experience an increase in residual risk. This increase is especially obvious when the gap of climate forcing between RCP8.5 and RCP4.5 widens by the end of the 21st century. We finally evaluate the impact of changed flood defense levels on the socioeconomic benefits and the corresponding residual risk.
Flooding is the second most serious hazard in Algeria, after earthquakes. According to the Civil Protection Services census, the department of Algiers experienced 174 floods between 1946 and 2021, several devastating floods. This study examines Algiers’ vulnerability to flooding using the Hierarchical Multicriteria Analysis (AHP) method, which aggregates eight criteria: altitude distribution, slopes, drainage density, topographic wetness index, land cover and land use, normalized difference vegetation index, soil types, and precipitations. With an accuracy of 85%, the resulting vulnerability map is an essential tool for better risk and land use management. The municipalities most vulnerable to flooding are located in the Mitidja (east of Algiers) and Algiers’ Western Sahel. These areas cover 71.29 km ² (10% of Algiers’ area) and are primarily located in the watersheds of El Harrach, El Hamiz, and Reghaia, while 25.8% of urbanized areas are moderately vulnerable. However, these areas require special attention because of their high population density. Flood risk has undeniably become more frequent and intense due to Algiers’ significant and often anarchic increase in urbanization in recent years, particularly at the edge of the major Wadis beds (nearly half of their watershed area is urbanized). This trend will worsen as extreme weather events increase, necessitating a stricter application of land use planning regulations and prevention, adaptation, and mitigation measures.
The transportation sector is critical to the emergency response during a hurricane. This research does a systematic assessment of the literature to determine how the transportation system actively engages in the aftermath of a hurricane by examining the transportation system's major function indicators- “Evacuation Routing”, “Emergency Services”, and “Search & Rescue”. To accomplish this goal, 86 academic publications were examined using the Web of Science and Scopus databases. The emergency response functions of the transportation system were evaluated using academic research methods, with various modes of transport considered. In the studies, optimization and simulation techniques were found to be common research methodologies, whereas personal cars and public transportation were used more often than other modes of transportation. The findings of the study may provide useful guidelines to researchers in the area, as well as serve as a research reference for future studies on hurricane emergency transportation system response.
The growing financial impact of natural disasters has motivated governments to rethink resiliency policy pertaining to built-infrastructure. The creation of an effective resiliency policy is a product of the interplay between informed elites (i.e., engineers, utility operators), governments, and citizen engagement. To help orientate informed elites on the prevalent trends and constraints in this policy domain, a literature review was conducted on built-infrastructure resiliency policy addressing natural disasters. Collection methodology consisted of a targeted keyword search on JSTOR, which resulted in forty relevant articles. Those articles were categorized into the following five resiliency policy approaches: mitigation, adaptation, economic, reconstruction, and policy frameworks. Additionally, a review of country-specific disaster response frameworks was also conducted. The review highlights recent trends in policy decisions. Decision-making on infrastructure resilience policy is moving from a national level to a local level. The consequences of that jurisdictional movement have caused policy decisions to favor mitigation and education tactics which prove to be more politically and fiscally feasible than adaptation tactics. The review also revealed a gap in the literature concerning the diversity of natural disasters being studied. A clear focus has been placed on earthquakes and flooding while wildfires and drought have been neglected.
Resumo Eventos extremos de precipitação são causados pelo excesso ou falta de chuva que podem provocar inundações, períodos de estiagem longos e secas que afetam a vida da população. Este trabalho visa estudar as tendências da precipitação através dos índices de extremos climáticos (CDD, R10mm, Rx1day, Rx5day e R95p) nas sub-bacias Alto Juquiá, Baixo Ribeira e Rio Ribeira de Iguape, localizadas na Bacia do Rio Ribeira de Iguape, tanto no contexto atual quanto futuro. A sub-bacia Alto Juquiá alimenta o Sistema Produtor de São Lourenço que abastece parte dos municípios da Grande São Paulo. Analisaram-se os dados de índices extremos observados e simulados por dois modelos regionais climáticos: Eta-HadGEM2-ES e Eta-MIROC5. A análise histórica dos dados observados identificou tendências de aumento nos números de dias secos consecutivos (CDD) e em anos com dias muito chuvosos (R95p) nas três sub-bacias. As projeções dos dois modelos e cenários indicam para um futuro mais próximo (2006-2040) períodos de estiagem mais longos (CDD) e uma menor intensidade da chuva diária (R95p e Rx1day) até 2099. Ainda, é possível inferir que o modelo Eta-HadGEM2-ES obteve melhor desempenho, já que os erros sistemáticos das simulações foram menores nas sub-bacias de Alto Juquiá e Rio Ribeira de Iguape.
Atlantic tropical cyclones (TCs) affect the United States every year, and depending on their intensity, can cause coastal storm surge and inland inundation, leading to substantial damages in the east coast. Accurate TC risk assessment, however, is not easily quantified given the limited spatial and temporal historical records. This paper describes the development of a model framework for TC forecasts based on large ensemble generation. We illustrate the capability of the ensemble technique to improve TC forecasts by generating probabilistic forecasts of track and intensity. We show that the using this approach can generate tracks that are statistically similar to those of the underlying historical records, even TCs with long return periods. We began with historical compilations of the NOAA National Climatic Data Center (NCDC) tropical cyclone database. TCs reaching a hurricane strength and making landfall in or passing close to the United States were identified. The geographical area influenced by these hurricanes was discretized and the parameters of Markov chains and multivariate distributions were derived for each discretized area. Synthetic tracks were generated using repetitive random draws from the spatiotemporal distribution of historical genesis and storm motion, conditioned by Markov chains for each 6-hour displacement. Kolmogorov–Smirnov (K-S) tests revealed that the ensemble members and’best track’ data are drawn from the same underlying population at the 95% significance level, with no test statistics exceeding the critical value of 0.13. The proposed algorithm is validated in both macro and micro scales. The results revealed that the general pattern of hurricane activities conforms well to the historical observations with high spatial correlations, over 90% for the Saffir-Simpson hurricane categories of 1 through 4 and near 80% for the category 5. The track generator also produces a history of potential wind and translational speeds for both of these scales.
Nowadays, following every weather disaster quickly follow estimates of economic loss. Quick blame for those losses, or some part, often is placed on claims of more frequent or intense weather events. However, understanding what role changes in climate may have played in increasing weather-related disaster losses is challenging because, in addition to changes in climate, society also undergoes dramatic change. Increasing development and wealth influence exposure and vulnerability to loss – typically increasing exposure while reducing vulnerability. In recent decades a scientific literature has emerged that seeks to adjust historical economic damage from extreme weather to remove the influences of societal change from economic loss time series to estimate what losses past extreme events would cause under present-day societal conditions. In regions with broad exposure to loss, an unbiased economic normalisation will exhibit trends consistent with corresponding climatological trends in related extreme events, providing an independent check on normalisation results. This paper reviews 54 normalisation studies published 1998–2020 and finds little evidence to support claims that any part of the overall increase in global economic losses documented on climate time scales is attributable to human-caused changes in climate, reinforcing conclusions of recent assessments of the Intergovernmental Panel on Climate Change.
El trabajo desarrolla un modelo de equilibrio parcial en condiciones de mercados integrados en el comercio bilateral de un bien homogéneo, en el cual dos empresas heterogéneas y monopólicas en sus respectivos países que generan contaminantes compiten bajo un esquema oligopólico. De esta manera los gobiernos deben aplicar políticas ambientales estratégicas que garanticen un medio ambiente saludable, pero que al mismo tiempo consideren el beneficio de las empresas y de los consumidores, además del ingreso propio a través de la recaudación de impuestos de contaminación a las empresas. Los resultados establecen que, si el costo marginal por contaminar es muy alto entonces, el gobierno debe implementar un impuesto de contaminación elevado. Por otro lado, si el costo marginal por contaminar no es muy significativo, el gobierno aplicará un impuesto nulo a la emisión de contaminantes.
The Sustainable Development Goals indicator framework identifies as an indicator of progress the objective of reducing disaster losses as a proportion of global gross domestic product. This short analysis presents data on this indicator from 1990. In constant 2017 US dollars, both weather-related and non-weather related catastrophe losses have increased, with a 74% increase in the former and 182% increase in the latter since 1990. However, since 1990 both overall and weather/climate losses have decreased as proportion of global GDP, indicating progress with respect to the SDG indicator. Extending this trend into the future will require vigilance to exposure, vulnerability and resilience in the face of uncertainty about the future frequency and magnitude of extreme events.
This study reevaluates the history of building damage and loss of life due to bushfire (wildfire) in Australia since 1925 in light of the 2009 Black Saturday fires in Victoria in which 173 people lost their lives and 2298 homes were destroyed along with many other structures. Historical records are normalized to estimate building damage and fatalities had events occurred under the societal conditions of 2008/09. There are relationships between normalized building damage and the El Niño-Southern Oscillation and Indian Ocean dipole phenomena, but there is no discernable evidence that the normalized data are being influenced by climatic change due to the emission of greenhouse gases. The 2009 Black Saturday fires rank second in terms of normalized fatalities and fourth in terms of normalized building damage. The public safety concern is that, of the 10 years with the highest normalized building damage, the 2008/09 bushfire season ranks third, behind the 1925/26 and 1938/39 seasons, in terms of the ratio of normalized fatalities to building damage. Afeature of the building damage in the 2009 Black Saturday fires in some of the most affected towns-Marysville and Kinglake-is the large proportion of buildings destroyed either within bushland or at very small distances from it (<10 m). Land use planning policies in bushfire-prone parts of this country that allow such development increase the risk that bushfires pose to the public and the built environment.
Climate change is real, and has a significant human component related to greenhouse gases, as summarized by the IPCC's Working Group I. Nothing in this white paper contradicts this work. • Global disaster losses have increased. • The increase in disaster losses is primarily due to floods and storms. • Scientists have not yet attributed changes in floods and storms to human causes. However, there is evidence for the detection of trends in some phenomena, especially tropical cyclones. • Some long-term disaster loss records are of suitable quality for research purposes. • Long-term records of disaster losses indicate that the overwhelming factors responsible for increasing disaster losses are a result of societal change and development. • Looking to the future, societal change will continue to be the dominant factor in increasing disaster losses. This conclusion is robust to a wide range of climate change scenarios. Identifying the signal of human-caused climate change in disaster loss trends will remain difficult for decades to come. Global disaster losses have increased.
In 2011, thunderstorms in the United States resulted in 550 deaths from tornadoes and more than $28 billion in property damage, according to data from the US National Oceanic and Atmospheric Administration, with the vast majority of economic losses resulting from tornadoes. This article normalizes U.S. tornado damage from 1950 to 2011, using several methods. A normalization provides an estimate of the damage that would occur if past events occurred under a common base year's societal conditions. We normalize for changes in inflation and wealth at the national level and changes in population, income and housing units at the county level. Under several methods, there has been a sharp decline in tornado damage. This decline corresponds with a decline in the reported frequency of the most intense (and thus most damaging) tornadoes since 1950. However, quantification of trends in tornado incidence is made difficult due to discontinuities in the reporting of events over time. The normalized damage results are suggestive that some part of this decline may reflect actual changes in tornado incidence, beyond changes in reporting practices. In historical context, 2011 stands out as one of the most damaging years of the past 61 years and provides an indication that maximum damage levels have the potential to increase should societal change lead to increasing exposure of wealth and property.
In recent decades, economic damage from tropical cyclones (TCs) around the world has increased dramatically. Scientific literature published to date finds that the increase in losses can be explained entirely by societal changes (such as increasing wealth, structures, population, etc.) in locations prone to tropical cyclone landfalls, rather than by changes in annual storm frequency or intensity. However, no homogenized dataset of global tropical cyclone landfalls has been created that might serve as a consistency check for such economic normalization studies. Using currently available historicalTC best-track records, a global database focused on hurricane-force strength landfalls was constructed. The analysis does not indicate significant long-period global or individual basin trends in the frequency or intensity of landfalling TCs of minor or major hurricane strength. The evidence in this study provides strong support for the conclusion that increasing damage around the world during the past several decades can be explained entirely by increasing wealth in locations prone to TC landfalls, which adds confidence to the fidelity of economic normalization analyses.
Historical records of damage from major tornadoes in the United States are taken and adjusted for inflation and wealth. Such adjustments provide a more reliable method to compare losses over time in the context of significant societal change. From 1890 to 1999, the costliest tornado on the record, adjusted for inflation, is the 3 May 1999 Oklahoma City tornado, with an adjusted 2.2 billion. A more realistic adjustment yields a figure of $2.9 billion. A comparison of the ratio of deaths to wealth-adjusted damage shows a clear break in 1953, at the beginning of the watch/warning/awareness program of the National Weather Service.
After more than two decades of relatively little Atlantic hurricane activity, the past decade saw heightened hurricane activity and more than 10 billion under both methods. The most damaging single storm is the 1926 Great Miami storm, with $140-157 billion of normalized damage: the most damaging years are 1926 and 2005. Of the total damage, about 85% is accounted for by the intense hurricanes Saffir-Simpson Categories 3, 4, and 5, yet these have comprised only 24% of the U.S. landfalling tropical cyclones. Unless action is taken to address the growing concentration of people and properties in coastal areas where hurricanes strike, damage will increase, and by a great deal, as more and wealthier people increasingly inhabit these coastal locations.
HAVE DISASTER LOSSES INCREASED BECAUSE OF ANTHROPOGENIC CLIMATE CHANGE? The increasing impact of natural disasters over recent decades has been well documented, especially the direct economic losses and losses that were insured. Claims are made by some that climate change has caused more losses, but others assert that increasing exposure due to population and economic growth has been a much more important driver. Ambiguity exists today, because the causal link between climate change and disaster losses has not been addressed in a systematic manner by major scientific assessments. Here, the author presents a review and analysis of recent quantitative studies on past increases in weather disaster losses and the role of anthropogenic climate change. Analyses show that, although economic losses from weather-related hazards have increased, anthropogenic climate change so far did not have a significant impact on losses from natural disasters. The observed loss increase is caused primarily by increasing exposure and value of capital at risk. This finding is of direct importance for studies on impacts from extreme weather and for disaster policy. Studies that project future losses may give a better indication of the potential impact of climate change on disaster losses and needs for adaptation than the analysis of historical losses. (Page 39)
Hurricanes are the costliest natural disasters in the United States. Understanding how both hurricane frequencies and intensities vary from year to year as well as how this is manifested in changes in damages that occur is a topic of great interest to meteorologists, public and private decision makers, and the general public alike. Previous research into long-term trends in hurricane-caused damage along the U.S. coast has suggested that damage has been quickly increasing within the last two decades, even after considering inflation. However, to best capture the year-to-year variability in tropical cyclone damage, consideration must also be given toward two additional factors: coastal population changes and changes in wealth. Both population and wealth have increased dramatically over the last several decades and act to enhance the recent hurricane damages preferentially over those occurring previously. More appropriate trends in the United States hurricane damages can be calculated when a normalization of the damages are done to take into account inflation and changes in coastal population and wealth. With this normalization, the trend of increasing damage amounts in recent decades disappears. Instead, substantial multidecadal variations in normalized damages are observed: the 1970s and 1980s actually incurred less damages than in the preceding few decades. Only during the early 1990s does damage approach the high level of impact seen back in the 1940s through the 1960s, showing that what has been observed recently is not unprecedented. Over the long term, the average annual impact of damages in the continental United States is about ), substantially more than previous estimates. Of these damages, over 83% are accounted for by the intense hurricanes (Saffir-Simpson categories 3, 4, and 5), yet these make up only 21% of the U.S.-landfalling tropical cyclones.
In late October 1998, the remnants of Hurricane Mitch stalled over Honduras and Nicaragua, killing more than 10,000 people and causing as much as $8.5 billion in damage. While Central America and the Caribbean have a history of natural disasters, the fatalities and destruction caused by Mitch were the greatest in at least several decades, prompting many questions including: What accounts for the extent of these losses? Is Mitch a harbinger of future disasters in the region? and What might be done in response? This paper seeks to shed light on these questions by examining the historical and geographic context of hurricane vulnerability in Latin America and the Caribbean. The paper examines trends in economic and other societal factors that increase vulnerability to hurricanes in Central America and the Caribbean and includes a case study of normalized hurricane losses in Cuba made possible by newly collected damage data published herein. The paper places its findings into the context of policies related to climate change and natural hazards.
The United States is becoming more vulnerable to natural hazards mostly
because of changes in population and national wealth density—more
people and more societal infrastructure have become concentrated in
disaster-prone areas. For most of the 20th century, the United States
has been largely spared the expense of a catastrophic natural disaster.
A great earthquake (magnitude 8 or larger) has not struck a major
metropolitan area since the 1906 San Francisco earthquake. An extreme or
catastrophic hurricane (Class 4 or 5) has not struck directly a major
urban area since the one that hit Miami, Florida, in 1926. Yet even
without such disasters, which might create losses well over 54 billion per year for the
past 5 years, or approximately $1 billion per week [National Science and
Technology Council, 1997].
Statistical relationships between annual floods at 200 long-term (85–127 years of record) streamgauges in the coterminous United States and the global mean carbon dioxide concentration (GMCO2) record are explored. The streamgauge locations are limited to those with little or no regulation or urban development. The coterminous US is divided into four large regions and stationary bootstrapping is used to evaluate if the patterns of these statistical associations are significantly different from what would be expected under the null hypothesis that flood magnitudes are independent of GMCO2. In none of the four regions defined in this study is there strong statistical evidence for flood magnitudes increasing with increasing GMCO2. One region, the southwest, showed a statistically significant negative relationship between GMCO2 and flood magnitudes. The statistical methods applied compensate both for the inter-site correlation of flood magnitudes and the shorter-term (up to a few decades) serial correlation of floods.Citation Hirsch, R.M. and Ryberg, K.R., 2012. Has the magnitude of floods across the USA changed with global CO2 levels? Hydrolological Sciences Journal, doi: 10.1080/02626667.2011.621895.
Recent reviews have concluded that efforts to date have yet to detect or attribute an anthropogenic climate change influence on Atlantic tropical cyclone (of at least tropical storm strength) behaviour and concomitant damage. However, the possibility of identifying such influence in the future cannot be ruled out. Using projections of future tropical cyclone activity from a recent prominent study we estimate the time that it would take for anthropogenic signals to emerge in a time series of normalized US tropical cyclone losses. Depending on the global climate model(s) underpinning the projection, emergence timescales range between 120 and 550 years, reflecting a large uncertainty. It takes 260 years for an 18-model ensemble-based signal to emerge. Consequently, under the projections examined here, the detection or attribution of an anthropogenic signal in tropical cyclone loss data is extremely unlikely to occur over periods of several decades (and even longer). This caution extends more generally to global weather-related natural disaster losses.
To understand the nature of increasing flood damage in the United States, accurate data are needed on costs and vulnerability associated with flooding. The National Weather Service (NWS) is the only organization that has maintained a long-term historical record of flood damage throughout the country. The NWS estimates are obtained from diverse sources, compiled soon after each flood event, and not verified by comparison with actual expenditures. This paper presents results of a comprehensive reanalysis of the scope, accuracy, and consistency of NWS damage estimates from 1926 to 2000 and recommends appropriate methods for data use and interpretation. Estimates for individual flood events are often quite inaccurate, but when estimates from many events are aggregated the errors become propor-tionately smaller. With the precautions described in this paper, the reanalyzed NWS damage estimates can be a valuable tool to aid researchers and decision makers in understanding the changing character of damaging floods in the United States.
As the world becomes wealthier over time, inflation-adjusted insured damages from natural disasters go up as well. This article analyzes whether there is still a significant upward trend once insured natural disaster loss has been normalized. By scaling up loss from past disasters, normalization adjusts for the fact that a hazard event of equal strength will typically cause more damage nowadays than in past years because of wealth accumulation over time. A trend analysis of normalized insured damage from natural disasters is not only of interest to the insurance industry, but can potentially be useful for attempts at detecting whether there has been an increase in the frequency and/or intensity of natural hazards, whether caused by natural climate variability or anthropogenic climate change. We analyze trends at the global level over the period 1990 to 2008, over the period 1980 to 2008 for West Germany and 1973 to 2008 for the United States. We find no significant trends at the global level, but we detect statistically significant upward trends in normalized insured losses from all non-geophysical disasters as well as from certain specific disaster types in the United States and West Germany.
We examined the anthropogenic and natural causes of flood risks in six representative cities in the Gangwon Province of Korea.
Flood damage per capita is mostly explained by cumulative upper 5% summer precipitation amount and the year. The increasing
flood damage is also associated with deforestation in upstream areas and intensive land use in lowlands. Human encroachment
on floodplains made these urban communities more vulnerable to floods. Without changes in the current flood management systems
of these cities, their vulnerability to flood risks will remain and may even increase under changing climate conditions.
Climate change is likely to lead to an increase in the frequency and/or intensity of certain types of natural hazards, if not globally, then at least in certain regions. All other things equal, this should lead to an increase in the economic toll from natural disasters over time. Yet, all other things are not equal since affected areas become wealthier over time and rational individuals and governments undertake defensive mitigation measures, which requires normalizing economic losses if one wishes to analyze trends in economic loss from natural disasters for detecting a potential climate change signal. In this article, we argue that the conventional methodology for normalizing economic loss is problematic since it normalizes for changes in wealth over time, but fails to normalize for differences in wealth across space at any given point of time. We introduce an alternative methodology that overcomes this problem in theory, but facesmanymore problems in its empirical application. Applying, therefore, bothmethods to the most comprehensive existing global dataset of natural disaster loss, in general we find no significant upward trends in normalized disaster damage over the period 1980–2009 globally, regionally, for specific disasters or for specific disasters in specific regions. Due to our inability to control for defensive mitigation measures, one cannot infer from our analysis that there have definitely not been more frequent and/or more intensive weather-related natural hazards over the study period already. Moreover, it may still be far too early to detect a trend if human-induced climate change has only just started and will gain momentum over time.
Whether the characteristics of tropical cyclones have changed or will change in a warming climate - and if so, how - has been the subject of considerable investigation, often with conflicting results. Large amplitude fluctuations in the frequency and intensity of tropical cyclones greatly complicate both the detection of long-term trends and their attribution to rising levels of atmospheric greenhouse gases. Trend detection is further impeded by substantial limitations in the availability and quality of global historical records of tropical cyclones. Therefore, it remains uncertain whether past changes in tropical cyclone activity have exceeded the variability expected from natural causes. However, future projections based on theory and high-resolution dynamical models consistently indicate that greenhouse warming will cause the globally averaged intensity of tropical cyclones to shift towards stronger storms, with intensity increases of 2-11% by 2100. Existing modelling studies also consistently project decreases in the globally averaged frequency of tropical cyclones, by 6-34%. Balanced against this, higher resolution modelling studies typically project substantial increases in the frequency of the most intense cyclones, and increases of the order of 20% in the precipitation rate within 100 km of the storm centre. For all cyclone parameters, projected changes for individual basins show large variations between different modelling studies.
On 18 January 2007, windstorm Kyrill battered Europe with hurricane-force winds killing 47 people and causing 10 billion US$ in damage. Kyrill poses several questions: is Kyrill an isolated or exceptional case? Have there been events costing as much in the past? This paper attempts to put Kyrill into an historical context by examining large historical windstorm event losses in Europe for the period 1970–2008 across 29 European countries. It asks the question what economic losses would these historical events cause if they were to recur under 2008 societal conditions? Loss data were sourced from reinsurance firms and augmented with historical reports, peer-reviewed articles and other ancillary sources. Following the same conceptual approach outlined in previous studies, the data were then adjusted for changes in population, wealth, and inflation at the country level and for inter-country price differences using purchasing power parity. The analyses reveal no trend in the normalised windstorm losses and confirm increasing disaster losses are driven by societal factors and increasing exposure.
International experts agree that the emission of greenhouse gases by mankind is rising further and further, and causing climate change. This can clearly be seen in the rise in the average global temperature and sea level. It is also evident in the increase in extreme weather events and natural catastrophes, which are causing enormous economic damage. If the global temperature changes by 1 degree Celsius economic damage of up to 2 trillion US dollars is possible in 2050. If greenhouse gas emissions are not reduced enough to prevent such a rise in temperature, altogether damage from natural catastrophes amounting to 137 billion euros could be caused in Germany by the year 2050. With optimal cooperation from the main emitters - Europe, Russia and the United States - the costs of reducing greenhouse gas emissions could be minimised. By offering emission rights for sale Russia would gain from climate policy, its participation could bring a revenue of up to 20 billion US dollars over a period of four years (2008 to 2012). So Russia is well advised to ratify the Kyoto Protocol.
Since the record impact of Hurricane Katrina, attention has focused on understanding trends in hurricanes and their destructive potential. Emanuel reports a marked increase in the potential destructiveness of hurricanes based on identification of a trend in an accumulated annual index of power dissipation in the North Atlantic and western North Pacific since the 1970s. If hurricanes are indeed becoming more destructive over time, then this trend should manifest itself in more destruction. However, my analysis of a long-term data set of hurricane losses in the United States shows no upward trend once the data are normalized to remove the effects of societal changes.
Action on disaster risk reduction can support sustainable development under climate change.
Condensed summary: This chapter focuses on the types of extreme weather and climate events that are important to property insurers, and it considers evidence on how those risks have been changing and how they might change in the future with climate change. Some evidence is drawn from the United Kingdom, which has wide insurance coverage for weather perils and much familiarity with international catastrophe insurance. The author believes there is good ground to argue that climate change is already affecting the risks, although it is not the only factor that has caused change. Further, the risks of extremes may be changing very rapidly. Introduction: The insurance industry is affected by climate change in a number of ways, although the effects may vary greatly between jurisdictions, owing to industry structure and practice as well as to climatic and geographical differences. Insurers are already encountering aggravated claims for insured property damage in extreme events, particularly floods, storms, and droughts. As yet, the main causes of the trend of rising property claims in recent decades are socioeconomic rather than climatic; however, the contribution of climatic change could rise quickly, owing to the strongly nonlinear relationship between climatic variables and damage, and the fact that a small shift in mean conditions can create a large change in extremes. The pace of change regarding weather extremes is fast. © Cambridge University Press 2008 and Cambridge University Press, 2009.
Condensed summary: In order to evaluate potential trends in global natural catastrophe losses, it is important to compensate for changes in asset values and exposures over time. We create a Global Normalized Catastrophe Catalogue covering weather-related catastrophe losses in the principal developed (Australia, Canada, Europe, Japan, South Korea, United States) and developing (Caribbean, Central America, China, India, the Philippines) regions of the world. We survey losses from 1950 through 2005, although data availability means that for many regions the record is incomplete for the period before the 1970s even for the largest events. After 1970, when the global record becomes more comprehensive, we find evidence of an annual upward trend for normalized losses of 2% per year. Conclusions are heavily weighted by US losses, and their removal eliminates any statistically significant trend. Large events, such as Hurricane Katrina and China flood losses in the 1990s, also exert a strong impact on trend results. In addition, once national losses are further normalized relative to per capita wealth, the significance of the post-1970 global trend disappears. We find insufficient evidence to claim a statistical relationship between global temperature increase and normalized catastrophe losses. Introduction: Economic losses attributed to natural disasters have increased from US659.9 billion in the 1990s (United Nations Development Programme [UNDP], 2004), for an annual growth rate of approximately 8%. Private sector data also show rising insured losses over a similar period (Munich Re, 2001; Swiss Re, 2005). © Cambridge University Press 2008 and Cambridge University Press, 2009.
Thunderstorm-caused property losses resulted in 892 property insurance catastrophic events during 1949-98 and amounted to 1 million, and the loss values over the 50-yr period were adjusted for temporal changes in inflation, shifts in insurance coverage, and population. Thunderstorm catastrophes were most common in the south and central climatic regions and infrequent in the west and northwest regions. The eastern two-thirds of the nation experienced 87% of all losses. The number of catastrophes causing losses of 19 billion in losses during 1949-53, 5 billion during the 5-yr periods from 1959 to 1988, and then increasing to $15 billion in 1994-98. The loss distributions were also U-shaped on the east coast and Midwest, but losses elsewhere in the nation increased continually from 1949 to 1998. The median loss of catastrophes in each 5-yr period, a measure of storm intensity, exhibited a slight U-shaped distribution nationally, but in the western half of the nation the intensity values decreased from high early values to minimums in the 1970s and then increased thereafter. Certain findings reveal that societal shifts were major factors in the time distributions of losses and catastrophe frequencies. Areas with rapid population growth and wealth including California, Florida, Colorado, and the southwest, all experienced rapid increases in storm losses that began during the 1960s and 1970s. In many areas temporal fluctuations in the catastrophe frequencies and losses also agreed with time shifts in the number of thunderstorm days reported by observing stations, the only independent measure of storm activity. Increases in thunderstorm activity since the 1950s in the western half of the nation and along the Gulf Coast relate well to the upward shifts in catastrophe frequencies and losses in these areas. However, thunder-day incidences decreased with time over most of the Midwest and northeast where catastrophe losses increased, further reflecting the influence of societal factors on the temporal distribution of catastrophe losses.
This paper reviews recent work on trends during this century in societal impacts (direct economic losses and fatalities) in the United States from extreme weather conditions and compares those with trends of associated atmospheric phenomena. Most measures of the economic impacts of weather and climate extremes over the past several decades reveal increasing losses. But trends in most related weather and climate extremes do not show comparable increases with time. This suggests that increasing losses are primarily due to increasing vulnerability arising from a variety of societal changes, including a growing population in higher risk coastal areas and large cities, more property subject to damage, and lifestyle and demographic changes subjecting lives and property to greater exposure. Flood damages and fatalities have generally increased in the last 25 years. While some have speculated that this may be due in part to a corresponding increase in the frequency of heavy rain events, the climate contribution to the observed impacts trends remains to be quantified. There has been a steady increase in hurricane losses. However, when changes in population, inflation, and wealth are considered, there is instead a downward trend. This is consistent with observations of trends in hurricane frequency and intensity. Increasing property losses due to thunderstorm-related phenomena (winds, hail, tornadoes) are explained entirely by changes in societal factors, consistent with the observed trends in the thunderstorm phenomena. Winter storm damages have increased in the last 10-15 years and this appears to be partially due to increases in the frequency of intense nor'easters. There is no evidence of changes in drought-related losses (although data are poor) and no apparent trend in climatic drought frequency. There is also no evidence of changes in the frequency of intense heat or cold waves.
The poor relationship between what climatologists, hydrologists, and other physical scientists call floods, and those floods that actually cause damage to life or property, has limited what can be reliably said about the causes of observed trends in damaging floods. It further limits what can be said about future impacts of floods on society based on predicted changes in the global hydrological cycle. This paper presents a conceptual framework for the systematic assessment of the factors that condition observed trends in flood damage. Using the framework, it assesses the role that variability in precipitation has in damaging flooding in the United States at national and regional levels. Three different measures of flood damage—absolute, per capita, and per unit wealth—each lead to different conclusions about the nature of the flood problem. At a national level, of the 10 precipitation measures examined in this study, the ones most closely related to flood damage are the number of 2-day heavy rainfall events and the number of wet days. Heavy rainfall events are defined relative to a measure of average rainfall in each area, not as absolute thresholds. The study indicates that the growth in recent decades in total damage is related to both climate factors and societal factors: increased damage is associated with increased precipitation and with increasing population and wealth. At the regional level, this study reports a stronger relationship between precipitation measures and flood damage, and indicates that different measures of precip- itation are most closely related to damage in different regions. This study suggests that climate plays an important, but by no means determining, role in the growth in damaging floods in the United States in recent decades.
One strand of research relates the magnitude of severe weather disasters to climatic and human development factors; another highlights dramatic growth in catastrophe losses. However, there have been few attempts to put the two strands together. Here we use an explicit modeling framework to determine the contribution of climate variability relative to human factors in reported catastrophe losses. We then examine how future climate change can be expected to affect losses from natural disasters. Simultaneous regression models are constructed from three equations in which the dependent variables are U.S. flood loss, U.S. hurricane loss and U.S. catastrophe loss. Then two kinds of simulation under two climate change scenarios explore how climate change would affect losses. The climate change scenarios respectively project 13.5% and 21.5% increases in annual precipitation. The first simulation increases only the mean value of annual precipitation; the second simulation assumes that the mean and standard deviation of annual precipitation change in the same proportion. Results show that the growth in reported losses from weather-related natural disasters is due mainly to three socioeconomic factors: inflation, population growth and growth in per capita real wealth. However, weather variables such as precipitation and the number of hurricanes per period also clearly affect losses. The three stage least squares (3SLS) simultaneous equation model shows that a 1% increase in annual precipitation would enlarge catastrophe loss by as much as 2.8%. These findings are suggestive as planning signals to decision makers.
Based on damage records released by the Department of Civil Affairs of China, direct economic losses and casualties associated with tropical cyclones that made landfall over China during 1983-2006 are examined. In an average year, landfalling tropical cyclones cause 472 deaths and 28.7 billion yuans (2006 RMB) in direct economic losses, accounting for 0.38% of the annual total gross domestic product (GDP) of China. As the deadliest landfalling tropical cyclone, Super Typhoon Fred killed 1,126 people in 1994, making it the deadliest year (1,815 deaths). The costliest landfalling tropical cyclone was Super Typhoon Herb, which caused 73.3 billion yuans (2006 RMB) in direct economic losses in 1996, making it the costliest year (107.9 billion yuans). The direct economic losses and casualties of a landfalling tropical cyclone tend to increase with the northward shift in landfall track. Over the past 24 yr the direct economic losses have had a significant upward trend, but no trend can be found if the losses are scaled with the annual total GDP of China and the annual GDP per capita, suggesting that the upward trend in direct economic losses is primarily a result of Chinese economic development. This is consistent with changes in tropical cyclone casualties, which show no significant trend over the past 24 years.
Contrary to the common perception that tropical cyclones are on the
increase, due perhaps to global warming, studies all over the world show
that, although there are decadal variations, there is no definite
long-term trend in the frequency or intensity of tropical cyclones over
the period of about a century for which data are available. There is,
nevertheless, a sharp increase in the socio-economic impact of tropical
cyclones in the form of increasing property damage. An analysis of
cyclones affecting the state of Andhra Pradesh, India, in the last
quarter century by normalizing cyclone damage for economic and
demographic factors shows that here, as elsewhere, the greater
vulnerability is attributable mainly to these factors and not to any
increase in frequency or intensity of cyclones. The decrease of
alertness in disaster management that often occurs after a few years'
lull in occurrence of cyclones, known as the "fading memory syndrome,"
also contributes to increases in loss of lives and property damage. This
distinction between meteorological and socio-economic causes for the
increased impact is important to avoid a tendency for political and
administrative decision makers to blame natural causes. They have to
take these realities into account, not just in developing a vigilant
disaster management system, but in land-use planning, development of
coastal districts, and insurance measures.
This study examines the economic impacts of US hurricanes. The major conclusions are the following: First, there are substantial vulnerabilities to intense hurricanes in the Atlantic coastal United States. Damages appear to rise with the ninth power of maximum wind speed. Second, greenhouse warming is likely to lead to stronger hurricanes, but the evidence on hurricane frequency is unclear. We estimate that the average annual US hurricane damages will increase by $10 billion at 2005 incomes (0.08 percent of GDP) due to global warming. However, this number may be underestimated by current storm models. Third, 2005 appears to have been a quadruple hurricane outlier, involving a record number of North Atlantic tropical cyclones, a large fraction of intense storms, a large fraction of the intense storms making landfall in the United States, and an intense storm hitting the most vulnerable high-value region in the country.
There is a need for comprehensive, standardised and georeferenced information on floods for political and economic decision-making. Relevant, accurate and up-to-date data is an important aspect for resource distribution, mitigation programmes, disaster monitoring and assessment. Despite this, there is a lack of spatial and thematic accurate global data for floods. In Europe, historic data on flood losses and casualties are neither comprehensive nor standardised, thus making long-term analyses at continental level difficult. In this article, we present a map and catalogue of the major flood events of the last 56 years in the European Union (EU), Bulgaria and Romania. This study is an effort to alleviate the lack of homogeneous and georeferenced information on flood disasters for large periods in Europe. The objectives of this paper are to identify and classify the major flood disasters of the last 56 years in the EU; to map the major flood disasters at pan-European scale with the support of a potential flood hazard map and ancillary GIS datasets; and to give a picture of the current situation for major floods in the EU on the basis of past events and current trends.
The Emergency Events Database (EM-DAT) of the Centre of Research on Epidemiology of Disasters in Brussels (CRED) and United States Office for Foreign Disaster Assistance (OFDA) and NATHAN of Munich Re are two of the main public global databases for natural disasters. Information from EM-DAT and NATHAN on flood disasters producing more than 70 casualties and/or more than 0.005% of EU GDP in damage has been assessed for the production of the map and catalogue of major flood disasters in Europe.
High wind caused catastrophes, storms causing property losses >1 million, during 1952–2006 averaged 3.1 events per year in
the U.S. The average loss per event was 90 million, and the annual average loss was 354 million. High wind catastrophes
were most frequent in the Northeast, Central, and West Coast areas. Storm losses on the West Coast were the nation’s highest,
averaging 115 million per event. High wind losses are the nation’s only form of severe weather that maximizes on the West
Coast. High wind catastrophes were most frequent in winter, and were infrequent in the late spring and early fall seasons.
Loss areas were frequently confined to one state. Losses in the western U.S. and nationally have increased during the 1952–2006
period, both with statistically significant upward trends.
Since 1967, the Insurance Council of Australia has maintained a database of significant insured losses. Apart from five geological events, all others (156) are the result of meteorological hazards—tropical cyclones, floods, thunderstorms, hailstorms and bushfires. In this study, we normalise the weather-related losses to estimate the insured loss that would be sustained if these events were to recur under year 2006 societal conditions. Conceptually equivalent to the population, inflation and wealth adjustments used in previous studies, we use two surrogate factors to normalise losses—changes in both the number and average nominal value of dwellings over time, where nominal dwelling values exclude land value. An additional factor is included for tropical cyclone losses: this factor adjusts for the influence of enhanced building standards in tropical cyclone-prone areas that have markedly reduced the vulnerability of construction since the early 1980s.Once the weather-related insured losses are normalised, they exhibit no obvious trend over time that might be attributed to other factors, including human-induced climate change. Given this result, we echo previous studies in suggesting that practical steps taken to reduce the vulnerability of communities to today's weather would alleviate the impact under any future climate; the success of improved building standards in reducing tropical cyclone wind-induced losses is evidence that important gains can be made through disaster risk reduction.
Economic losses caused by tropical cyclones have increased dramatically. Historical changes in losses are a result of meteorological factors (changes in the incidence of severe cyclones, whether due to natural climate variability or as a result of human activity) and socio-economic factors (increased prosperity and a greater tendency for people to settle in exposed areas). This paper aims to isolate the socio-economic effects and ascertain the potential impact of climate change on this trend. Storm losses for the period 1950–2005 have been adjusted to the value of capital stock in 2005 so that any remaining trend cannot be ascribed to socio-economic developments. For this, we introduce a new approach to adjusting losses based on the change in capital stock at risk. Storm losses are mainly determined by the intensity of the storm and the material assets, such as property and infrastructure, located in the region affected. We therefore adjust the losses to exclude increases in the capital stock of the affected region. No trend is found for the period 1950–2005 as a whole. In the period 1971–2005, since the beginning of a trend towards increased intense cyclone activity, losses excluding socio-economic effects show an annual increase of 4% per annum. This increase must therefore be at least due to the impact of natural climate variability but, more likely than not, also due to anthropogenic forcings.