Gridded population projections for the coastal zone under the Shared Socioeconomic Pathways

Merkens, Jan-Ludolf; Reimann, Lena; Hinkel, Jochen; Vafeidis, Athanasios T.

doi:10.1016/j.gloplacha.2016.08.009

Cited by 212 publications

(147 citation statements)

References 26 publications

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“…Coastal populations and associated economic assets have increased steadily in recent decades (Neumann et al, 2015); by 2100, the population within 10-m elevation of mean sea level could exceed 830 million (Merkens et al, 2016). As coastal populations expand, the risks associated with sea-level rise (SLR) are also continuing to grow (P. U.…”

Section: Introductionmentioning

confidence: 99%

Evolution of 21st Century Sea Level Rise Projections

et al. 2018

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The modern era of scientific global-mean sea level rise (SLR) projections began in the early 1980s. In subsequent decades, understanding of driving processes has improved, and new methodologies have been developed. Nonetheless, despite more than 70 studies, future SLR remains deeply uncertain. To facilitate understanding of the historical development of SLR projections and contextualize current projections, we have compiled a comprehensive database of 21st century global SLR projections. Although central estimates of 21st century global-mean SLR have been relatively consistent, the range of projected SLR has varied greatly over time. Among studies providing multiple estimates, the range of upper projections shrank from 1.3-1.8 m during the 1980s to 0.6-0.9 m in 2007, before expanding again to 0.5-2.5 m since 2013. Upper projections of SLR from individual studies are generally higher than upper projections from the Intergovernmental Panel on Climate Change, potentially due to differing percentile bounds or a predisposition of consensus-based approaches toward relatively conservative outcomes.Plain Language Summary In spite of more than 35 years of research, and over 70 individual studies, the upper bound of future global-mean sea level rise (SLR) remains deeply uncertain. In an effort to improve understanding of the history of the science behind projected SLR, we present and analyze the first comprehensive database of 21st century global-mean SLR projections. Results show a reduction in the range of SLR projections from the first studies through the mid-2000s that has since reversed. In addition, results from this work indicate a tendency for Intergovernmental Panel on Climate Change reports to err on the side of least drama-a conservative bias that could potentially impede risk management.

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Section: Introductionmentioning

confidence: 99%

Evolution of 21st Century Sea Level Rise Projections

et al. 2018

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“…As TCs move over land, they decay due to the absence of a substantial surface enthalpy source [13,23]. Factors related to coastal development, e.g., shipping, coastal tourism, and coastal settlement, that promote a more densely populated coastal area than heretofore [34,38], will lead to higher exposure to TC-induced hazards. Apart from being affected by extreme winds, coastal areas such as Can Tho are also vulnerable to storm surges induced by intense TCs [24,39].…”

Section: Discussionmentioning

confidence: 99%

Rising future tropical cyclone-induced extreme winds in the Mekong River Basin

et al. 2020

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a b s t r a c tThe societal impact of extreme winds induced by tropical cyclones (TCs) is a major concern in the Mekong River Basin (MRB). Though no clear trend of landfalling TC intensity along the Vietnam coastline has been observed since the 1970s, climate models project an increasing TC intensity in the 21st century over the Western North Pacific, which is the primary TC source region influencing the MRB. Yet, how future TC activities will affect extreme winds quantitatively in the MRB remains unclear. By employing a novel dynamical downscaling technique using a specialized, coupled ocean-atmospheric model, shorter return periods of maximum wind speed in the MRB for 2081-2100 compared with 1981-2000 are projected based on five global climate models under the RCP8.5 scenario, suggesting increases in the future tropical cyclone intensity. The results point to consistently elevated future TC-related risks that may jeopardize sustainable development, disrupt food supply, and exacerbate conflicts in the region and beyond.

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“…Currently, an estimated 310 million people and US$11 trillion of assets are exposed to a 100‐year coastal flood event globally (Hinkel et al, ). This is expected to increase throughout the 21st century due to a combination of several factors, including an increased frequency of ESL events as a result of rising mean sea levels (Church et al, ; Dangendorf et al, ; Haigh et al, ), along with population growth, urbanization, and socioeconomic development (Hanson et al, ; Jongman et al, ; Merkens et al, ; Neumann et al, ). Under no adaptation, losses due to coastal flooding may reach 10% of global gross domestic product by 2100 (Hallegatte et al, ).…”

Section: Introductionmentioning

confidence: 99%

A Stochastic Extreme Sea Level Model for the German Baltic Sea Coast

et al. 2019

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This paper describes a framework in which artificial extreme sea levels (ESLs) can be generated for use in flood risk analyses. Such analyses require large numbers of events to accurately assess the risk associated with certain return water levels and quantify uncertainties surrounding the temporal variability of ESL events. Stochastic models satisfy this requirement as they are computationally inexpensive, and thus, many thousands of events may be generated over a very short period of time. As a case study, we have developed a stochastic model for the German Baltic Sea coast capable of simulating the temporal behavior of ESLs. To do this, high‐resolution water level data from 45 tide‐gauges have been used as model input. At each location, observed ESLs are identified and parameterized. Artificial ESLs are generated using Monte Carlo simulations based on the parametric distribution functions fitted to the parameterized observed ESLs. We show that the method outlined here provides an accurate representation of ESLs at all tide‐gauges tested. However, the model is limited by the availability, length, and quality of high‐resolution water level data. Due to the rarity of ESLs in the German Baltic Sea, including historical measurements into the stochastic procedure allows for the generation of artificial ESLs more in‐line with past extremes.

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Gridded population projections for the coastal zone under the Shared Socioeconomic Pathways

Cited by 212 publications

References 26 publications

Evolution of 21st Century Sea Level Rise Projections

Evolution of 21st Century Sea Level Rise Projections

Rising future tropical cyclone-induced extreme winds in the Mekong River Basin

A Stochastic Extreme Sea Level Model for the German Baltic Sea Coast

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