Coastal locations around the United States, particularly along the Atlantic coast, are experiencing recurrent flooding at high tide. Continued sea-level rise (SLR) will exacerbate the issue where present, and many more locations will begin to experience recurrent high-tide flooding (HTF) in the coming decades. Here we use established SLR scenarios and flooding thresholds to demonstrate how the combined effects of SLR and nodal cycle modulations of tidal amplitude lead to acute inflections in projections of future HTF. The mid-2030s, in particular, may see the onset of rapid increases in the frequency of HTF in multiple US coastal regions. We also show how annual cycles and sea-level anomalies lead to extreme seasons or months during which many days of HTF cluster together. Clustering can lead to critical frequencies of HTF occurring during monthly or seasonal periods one to two decades prior to being expected on an annual basis.
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Scientific Reports Open Access 06 April 2022
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The tide-gauge sea-level data used in this analysis are publicly accessible and were obtained from the NOAA CO-OPS Data Retrieval API (https://api.tidesandcurrents.noaa.gov/api/prod/). The NOAA SLR scenarios are publicly available and were obtained from the NOAA CO-COPS website (https://tidesandcurrents.noaa.gov/publications/techrpt083.csv).
All code generated for the data analysis and figure creation is archived in a public repository47 under the GNU Affero General Public License v.3.0. The repository includes the Python environment, which provides the versions of all third-party libraries and packages used in this work.
Moftakhari, H. R., AghaKouchak, A., Sanders, B. F. & Matthew, R. A. Cumulative hazard: the case of nuisance flooding. Earth’s Future 5, 214–223 (2017).
Moftakhari, H. R., AghaKouchak, A., Sanders, B. F., Allaire, M. & Matthew, R. A. What is nuisance flooding? Defining and monitoring an emerging challenge. Water Resour. Res. 54, 4218–4227 (2018).
Ghanbari, M., Arabi, M. & Obeysekera, J. Chronic and acute coastal flood risks to assets and communities in southeast Florida. J. Water Resour. Plan. Manage. 146, 04020049 (2020).
Hino, M., Belanger, S. T., Field, C. B., Davies, A. R. & Mach, K. J. High-tide flooding disrupts local economic activity. Sci. Adv. https://doi.org/10.1126/sciadv.aau2736 (2019).
Sweet, W. V. & Park, J. From the extreme to the mean: acceleration and tipping points of coastal inundation from sea level rise. Earth’s Future 2, 579–600 (2014).
Wdowinski, S., Bray, R., Kirtman, B. P. & Wu, Z. Increasing flooding hazard in coastal communities due to rising sea level: case study of Miami Beach, Florida. Ocean Coast. Manage. 126, 1–8 (2016).
Ray, R. D. & Foster, G. Future nuisance flooding at Boston caused by astronomical tides alone. Earth’s Future 4, 578–587 (2016).
Burgos, A. G., Hamlington, B. D., Thompson, P. R. & Ray, R. D. Future nuisance flooding in Norfolk, VA from astronomical tides and annual to decadal internal climate variability. Geophys. Res. Lett. 45, 12432–12439 (2018).
Dahl, K. A., Fitzpatrick, M. F. & Spanger-Siegfried, E. Sea level rise drives increased tidal flooding frequency at tide gauges along the U.S. East and Gulf Coasts: projections for 2030 and 2045. PLoS ONE 12, e0170949 (2017).
Sweet, W. V., Dusek, G., Obeysekera, J. & Marra, J. J. Patterns and Projections of High Tide Flooding along the U.S. Coastline Using a Common Impact Threshold NOAA Technical Report NOS CO-OPS 086 (US Department of Commerce, National Oceanic and Atmospheric Administration, National Ocean Service Center for Operational Oceanographic Products and Services, 2018).
Sweet, W. et al. 2019 State of U.S. High Tide Flooding with a 2020 Outlook NOAA Technical Report NOS CO-OPS 092 2019 (US Department of Commerce, National Oceanic and Atmospheric Administration, National Ocean Service Center for Operational Oceanographic Products and Services, 2020).
Kwadijk, J. C. J. et al. Using adaptation tipping points to prepare for climate change and sea level rise: a case study in the Netherlands. WIREs Clim. Change 1, 729–740 (2010).
Barnett, J. et al. A local coastal adaptation pathway. Nat. Clim. Change 4, 1103–1108 (2014).
Stephens, S. A., Bell, R. G. & Lawrence, J. Developing signals to trigger adaptation to sea-level rise. Environ. Res. Lett. 13, 104004 (2018).
Pugh, D. & Woodworth, P. Sea-Level Science (Cambridge Univ. Press, 2014).
Haigh, I. D., Eliot, M. & Pattiaratchi, C. Global influences of the 18.61 year nodal cycle and 8.85 year cycle of lunar perigee on high tidal levels. J. Geophys. Res. Oceans 116, C06025 (2011).
Li, S. et al. Evolving tides aggravate nuisance flooding along the U.S. coastline. Sci. Adv. 7, eabe2412 (2021).
Taherkhani, M. et al. Sea-level rise exponentially increases coastal flood frequency. Sci. Rep. 10, 6466 (2020).
Thompson, P. R., Widlansky, M. J., Merrifield, M. A., Becker, J. M. & Marra, J. J. A statistical model for frequency of coastal flooding in Honolulu, Hawaii, during the 21st century. J. Geophys. Res. Oceans 124, 2787–2802 (2019).
Tebaldi, C., Strauss, B. H. & Zervas, C. E. Modelling sea level rise impacts on storm surges along US coasts. Environ. Res. Lett. 7, 014032 (2012).
Marcos, M., Calafat, F. M., Berihuete, Á. & Dangendorf, S. Long-term variations in global sea level extremes. J. Geophys. Res. Oceans 120, 8115–8134 (2015).
Buchanan, M. K., Oppenheimer, M. & Kopp, R. E. Amplification of flood frequencies with local sea level rise and emerging flood regimes. Environ. Res. Lett. 12, 064009 (2017).
Wahl, T. et al. Understanding extreme sea levels for broad-scale coastal impact and adaptation analysis. Nat. Commun. 8, 16075 (2017).
Sweet, W. V. et al. Global and Regional Sea Level Rise Scenarios for the United States NOAA Technical Report NOS CO-OPS 083 (US Department of Commerce, National Oceanic and Atmospheric Administration, National Ocean Service Center for Operational Oceanographic Products and Services, 2017); https://doi.org/10.7289/V5/TR-NOS-COOPS-083
Hamlington, B. D., Leben, R. R., Strassburg, M. W., Nerem, R. S. & Kim, K. Contribution of the Pacific Decadal Oscillation to global mean sea level trends. Geophys. Res. Lett. 40, 5171–5175 (2013).
Nerem, R. S. et al. Climate-change-driven accelerated sea-level rise detected in the altimeter era. Proc. Natl Acad. Sci. USA 115, 2022–2025 (2018).
Han, W. et al. Impacts of basin-scale climate modes on coastal sea level: a review. Surv. Geophys. 40, 1493–1541 (2019).
Kopp, R. E. et al. Probabilistic 21st and 22nd century sea-level projections at a global network of tide-gauge sites. Earth’s Future 2, 383–406 (2014).
IPCC Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).
Peng, D., Hill, E. M., Meltzner, A. J. & Switzer, A. D. Tide gauge records show that the 18.61-year nodal tidal cycle can change high water levels by up to 30 cm. J. Geophys. Res. Oceans 124, 736–749 (2019).
Peltier, W. R. & Tushingham, A. M. Influence of glacial isostatic adjustment on tide gauge measurements of secular sea level change. J. Geophys. Res. Solid Earth 96, 6779–6796 (1991).
Ray, R. D. & Merrifield, M. A. The semiannual and 4.4-year modulations of extreme high tides. J. Geophys. Res. Oceans 124, 5907–5922 (2019).
Yoon, H., Widlansky, M. J. & Thompson, P. R. Nu‘a Kai: flooding in Hawaii caused by a ‘stack’ of oceanographic processes [in ‘State of the Climate in 2017’]. Bull. Am. Meteorol. Soc. 99, S88–S89 (2018).
Hague, B. S., McGregor, S., Murphy, B. F., Reef, R. & Jones, D. A. Sea level rise driving increasingly predictable coastal inundation in Sydney, Australia. Earth’s Future 8, e2020EF001607 (2020).
Rueda, A. et al. A global classification of coastal flood hazard climates associated with large-scale oceanographic forcing. Sci. Rep. 7, 5038 (2017).
Widlansky, M. J. et al. Multimodel ensemble sea level forecasts for tropical Pacific islands. J. Appl. Meteorol. Climatol. 56, 849–862 (2017).
Jacox, M. G. et al. Seasonal-to-interannual prediction of North American coastal marine ecosystems: forecast methods, mechanisms of predictability, and priority developments. Prog. Oceanogr. 183, 102307 (2020).
Widlansky, M. J., Long, X. & Schloesser, F. Increase in sea level variability with ocean warming associated with the nonlinear thermal expansion of seawater. Commun. Earth Environ. 1, 9 (2020).
Thompson, P. R. Flooding Days Projection Tool. https://sealevel.nasa.gov/flooding-days-projection/ (2019).
Skellam, J. G. A probability distribution derived from the binomial distribution by regarding the probability of success as variable between the sets of trials. J. R. Stat. Soc. B 10, 257–261 (1948).
Salvatier, J., Wiecki, T. V. & Fonnesbeck, C. Probabilistic programming in Python using PyMC3. PeerJ Comput. Sci. https://doi.org/10.7717/peerj-cs.55 (2016).
Vandenberg-Rodes, A. et al. Projecting nuisance flooding in a warming climate using generalized linear models and Gaussian processes. J. Geophys. Res. Oceans 121, 8008–8020 (2016).
Devlin, A. T. et al. Coupling of sea level and tidal range changes, with implications for future water levels. Sci. Rep. 7, 17021 (2017).
Familkhalili, R. & Talke, S. A. The effect of channel deepening on tides and storm surge: a case study of Wilmington, NC. Geophys. Res. Lett. 43, 9138–9147 (2016).
Codiga, D. L. Unified Tidal Analysis and Prediction Using the UTide Matlab Functions Technical Report No. 2011-01 (Graduate School of Oceanography, University of Rhode Island, 2011); https://doi.org/10.13140/RG.2.1.3761.2008
Haigh, I. D. et al. The tides they are a-changin’: a comprehensive review of past and future nonastronomical changes in tides, their driving mechanisms, and future implications. Rev. Geophys. 58, e2018RG000636 (2020).
Thompson, P. R. Code repository for ‘Rapid increases and extreme months in projections of United States high-tide flooding’. Zenodo https://doi.org/10.5281/zenodo.4723019 (2021).
P.R.T. acknowledges support from NASA grant no. 80NSSC17K0564 and NOAA grant no. NA16NMF4320058. M.J.W. acknowledges support from NOAA grant nos NA17OAR4310110 and NA19OAR4310292. B.D.H. acknowledges support from the NASA Sea-Level Change Team (N-SLCT, WBS no. 105393).
The authors declare no competing interests.
Peer review information Nature Climate Change thanks Kristina Dahl, Ben Hague and Hamed Moftakhari for their contribution to the peer review of this work.
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Extended Data Fig. 1 Projections of annual counts of high-tide-flooding (HTF) days compared to expectations from SLR and tides alone.
The four ensemble projections (blue) are identical to Fig. 1. The simple projection of HTF frequency based only on the SLR scenario and predictions of astronomical tides (gray) underestimates the frequency of HTF due to the exclusion of local mean sea level variability across a variety of time scales from high-frequency surge to decadal climate variability.
The upper and lower panels correspond to the NOAA Minor and Moderate flooding thresholds, respectively. Position along the horizontal axis corresponds to the timing of the YOI. The vertical axis is projected ten-year increases in annual counts of HTF days following YOIs. Marker size corresponds to ten-year multipliers following the YOIs. Color denotes geographic region.
Projections correspond to the YOI (blue) and 10 years later (orange) for the four US locations in Fig. 1 assuming the NOAA Intermediate SLR scenario. Shading shows the 10th–90th percentile intervals for each year and month.
Extended Data Fig. 4 Years for which U.S. coastal locations will experience HTF on a majority of days during annual and monthly windows.
Calculations assume the Intermediate Low SLR scenario. Years for which HTF is expected to occur on a majority of days on average during annual and monthly periods (top two rows) are compared to years for which flooding will first occur on a majority of days during a single month (bottom two rows). Marker colors denote station region. The vertical position of each marker within the rows is an arbitrary vertical offset to allow visual distinction between regions and individual locations.
Examples correspond to the observed (gray and black) and fitted (orange and red) relationships for the month of January in (a) Honolulu and (b) Boston.
Station metadata, NOAA derived flooding thresholds and YOIs for 89 US stations. The columns labelled 10A and 10M list the absolute changes and relative changes (that is, ten-year multipliers) in annual counts of HTF days during decades following the YOIs.
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Thompson, P.R., Widlansky, M.J., Hamlington, B.D. et al. Rapid increases and extreme months in projections of United States high-tide flooding. Nat. Clim. Chang. 11, 584–590 (2021). https://doi.org/10.1038/s41558-021-01077-8
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