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      New elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding

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      Nature Communications
      Nature Publishing Group UK
      Climate-change impacts, Projection and prediction

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          Abstract

          Most estimates of global mean sea-level rise this century fall below 2 m. This quantity is comparable to the positive vertical bias of the principle digital elevation model (DEM) used to assess global and national population exposures to extreme coastal water levels, NASA’s SRTM. CoastalDEM is a new DEM utilizing neural networks to reduce SRTM error. Here we show – employing CoastalDEM—that 190 M people (150–250 M, 90% CI) currently occupy global land below projected high tide lines for 2100 under low carbon emissions, up from 110 M today, for a median increase of 80 M. These figures triple SRTM-based values. Under high emissions, CoastalDEM indicates up to 630 M people live on land below projected annual flood levels for 2100, and up to 340 M for mid-century, versus roughly 250 M at present. We estimate one billion people now occupy land less than 10 m above current high tide lines, including 250 M below 1 m.

          Abstract

          Accurate estimates of global mean sea-level rise are important. Here the authors employ a new digital elevation model (DEM) utilizing neural networks and show that the new DEM more than triples the NASA SRTM-based estimates of current global population occupying land below projected sea levels in 2100, with more than 200 million people could be affected based on RCP4.5 and 2 degC of warming.

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          Most cited references40

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          Future flood losses in major coastal cities

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            The rising tide: assessing the risks of climate change and human settlements in low elevation coastal zones

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              Coastal flood damage and adaptation costs under 21st century sea-level rise.

              Coastal flood damage and adaptation costs under 21st century sea-level rise are assessed on a global scale taking into account a wide range of uncertainties in continental topography data, population data, protection strategies, socioeconomic development and sea-level rise. Uncertainty in global mean and regional sea level was derived from four different climate models from the Coupled Model Intercomparison Project Phase 5, each combined with three land-ice scenarios based on the published range of contributions from ice sheets and glaciers. Without adaptation, 0.2-4.6% of global population is expected to be flooded annually in 2100 under 25-123 cm of global mean sea-level rise, with expected annual losses of 0.3-9.3% of global gross domestic product. Damages of this magnitude are very unlikely to be tolerated by society and adaptation will be widespread. The global costs of protecting the coast with dikes are significant with annual investment and maintenance costs of US$ 12-71 billion in 2100, but much smaller than the global cost of avoided damages even without accounting for indirect costs of damage to regional production supply. Flood damages by the end of this century are much more sensitive to the applied protection strategy than to variations in climate and socioeconomic scenarios as well as in physical data sources (topography and climate model). Our results emphasize the central role of long-term coastal adaptation strategies. These should also take into account that protecting large parts of the developed coast increases the risk of catastrophic consequences in the case of defense failure.
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                Author and article information

                Contributors
                skulp@climatecentral.org
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                29 October 2019
                29 October 2019
                2019
                : 10
                : 4844
                Affiliations
                ISNI 0000 0004 0580 1886, GRID grid.426747.4, Climate Central, Palmer Square #402, ; Princeton, NJ 08542 USA
                Author information
                http://orcid.org/0000-0002-6856-6575
                Article
                12808
                10.1038/s41467-019-12808-z
                6820795
                31664024
                ea106185-b2e7-4477-a6b7-73e412fe8f5d
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 5 March 2019
                : 1 October 2019
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                © The Author(s) 2019

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                climate-change impacts,projection and prediction
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                climate-change impacts, projection and prediction

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