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Coastal land can be lost at rapid rates due to relative sea-level rise (RSLR) resulting from local land subsidence. However, the comparative severity of local land subsidence is unknown due to high spatial variabilities and difficulties reconciling observations across localities. Here we provide self-consistent, high spatial resolution relative local land subsidence (RLLS) velocities derived from Interferometric Synthetic Aperture Radar for the 48 largest coastal cities, which represent 20% of the global urban population. We show that cities experiencing the fastest RLLS are concentrated in Asia. RLLS is also more variable across the 48 cities (−16.2 to 1.1 mm per year) than the Intergovernmental Panel on Climate Change estimations of vertical land motion (−5.2 to 4.9 mm per year). With our standardized method, the identification of relative vulnerabilities to RLLS and comparisons of RSLR effects accounting for RLLS are now possible across cities worldwide. These will better inform sustainable urban planning and future adaptation strategies in coastal cities. Ministry of Education (MOE) Nanyang Technological University National Environmental Agency (NEA) National Research Foundation (NRF) This research is supported by the Earth Observatory of Singapore (EOS), the National Research Foundation (NRF), Singapore, and the Ministry of Education (MOE), Singapore, under the Research Centres of Excellence initiative, by a Singapore NRF Investigatorship (Award ID NRF-NRFI05-2019-0009) and a Singapore MOE Tier 3 grant (Award ID MOE2019-T3-1-004) awarded to E.M.H. This research is also supported by the NRF, Singapore, and National Environment Agency, Singapore, under the National Sea Level Programme Initiative as part of the Urban Solutions & Sustainability – Integration Fund (Award No. USS-IF-2020-5) by a grant (Award ID NSLP-2021-3R-05) awarded to E.M.H. The research was carried out, in part, at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. T.L. and B.P.H. are supported by the Singapore MOE Academic Research Fund (MOE-T2EP50120-0007). |
