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In 2012, Hurricane Sandy hit the East Coast of the United States, creating widespread coastal flooding and over $60 billion in reported economic damage. The potential influence of climate change on the storm itself has been debated, but sea level rise driven by anthropogenic climate change more clearly contributed to damages. To quantify this effect, here we simulate water levels and damage both as they occurred and as they would have occurred across a range of lower sea levels corresponding to different estimates of attributable sea level rise. We find that approximately $8.1B ($4.7B–$14.0B, 5th–95th percentiles) of Sandy’s damages are attributable to climate-mediated anthropogenic sea level rise, as is extension of the flood area to affect 71 (40–131) thousand additional people. The same general approach demonstrated here may be applied to impact assessments for other past and future coastal storms., Sea level rise amplifies coastal storm impacts, but the role of anthropogenic climate change is poorly resolved. Here the authors reassess Hurricane Sandy, using a dynamic flood model to show that anthropogenic sea level rise added a central estimate of $8 billion in damages.

Significance River discharge exerts an important influence on coastal ocean circulation but has been overlooked as a driver of historical coastal sea-level change and future coastal flood risk. We explore the relation between observed river discharge and sea level on the United States Atlantic and Gulf coasts over interannual and longer periods. We formulate a theory that predicts the observed correspondence between river discharge and sea level, demonstrating a causal relation between the two variables. Our results highlight a significant but overlooked driver of coastal sea level, indicating the need for (1) improved resolution in remote sensing and modeling of the coastal zone and (2) inclusion of realistic river runoff variability in climate models., Identifying physical processes responsible for historical coastal sea-level changes is important for anticipating future impacts. Recent studies sought to understand the drivers of interannual to multidecadal sea-level changes on the United States Atlantic and Gulf coasts. Ocean dynamics, terrestrial water storage, vertical land motion, and melting of land ice were highlighted as important mechanisms of sea-level change along this densely populated coast on these time scales. While known to exert an important control on coastal ocean circulation, variable river discharge has been absent from recent discussions of drivers of sea-level change. We update calculations from the 1970s, comparing annual river-discharge and coastal sea-level data along the Gulf of Maine, Mid-Atlantic Bight, South Atlantic Bight, and Gulf of Mexico during 1910–2017. We show that river-discharge and sea-level changes are significantly correlated (p

We assess the relationship between temperature and global sea-level (GSL) variability over the Common Era through a statistical metaanalysis of proxy relative sea-level reconstructions and tide-gauge data. GSL rose at 0.1 ± 0.1 mm/y (2σ) over 0-700 CE. A GSL fall of 0.2 ± 0.2 mm/y over 1000-1400 CE is associated with ∼ 0.2 °C global mean cooling. A significant GSL acceleration began in the 19th century and yielded a 20th century rise that is extremely likely (probability [Formula: see text]) faster than during any of the previous 27 centuries. A semiempirical model calibrated against the GSL reconstruction indicates that, in the absence of anthropogenic climate change, it is extremely likely ([Formula: see text]) that 20th century GSL would have risen by less than 51% of the observed [Formula: see text] cm. The new semiempirical model largely reconciles previous differences between semiempirical 21st century GSL projections and the process model-based projections summarized in the Intergovernmental Panel on Climate Change's Fifth Assessment Report.

The prediction of global sea-level rise is one of the major challenges of climate science. While process-based models are still being improved to capture the complexity of the processes involved, semi-empirical models, exploiting the observed connection between global-mean sea level and global temperature and calibrated with data, have been developed as a complementary approach. Here we investigate whether twentieth century sea-level rise could have been predicted with such models given a knowledge of twentieth century global temperature increase. We find that either proxy or early tide gauge data do not hold enough information to constrain the model parameters well. However, in combination, the use of proxy and tide gauge sea-level data up to 1900 AD allows a good prediction of twentieth century sea-level rise, despite this rise being well outside the rates experienced in previous centuries during the calibration period of the model. The 90% confidence range for the linear twentieth century rise predicted bythe semi-empirical model is 13–30 cm, whereas the observed interval (using two tide gauge data sets) is 14–26 cm.