Abstract
The rate of future global sea-level rise will likely increase due to elevated ocean temperatures and land-ice loss. Coastal properties are expected to become more prone to coastal flooding in coming decades due to relative sea-level rise caused by both global and local factors. Translating sea-level rise projections into lost physical and economic value is critical for companies, governments, and regulators. We use probability distributions of local sea-level rise projections, National Oceanic and Atmospheric Administration (NOAA) coastal digital elevation models, and CoreLogic housing data to estimate the timing of future sea-level rise inundation and a range of housing market impairments in four U.S. coastal metros (Atlantic City, NJ; Miami, FL; Galveston, TX; and Newport-San Pedro, CA) for a series of climate scenarios. We implement a novel methodology, refining estimates for the timing for future inundation, considering both housing properties’ elevation above the tidal datum (Mean Higher High Water-MHHW), and hydrologic connectivity to the ocean—a critical consideration where natural or human-built features alter the relationship between sea levels and inundation. The unique risk factors in our four metros (housing market, topography, and local sea level) illustrate how our methods are applicable across geographies and scales of observation. Our results provide an important perspective on the timing of future losses, the associated uncertainty, and highlight positive (high-skewed) asymmetry of risk from sea-level rise inundation. This information can aid planners, policy makers, and investors in cost-benefit decision making related to mitigation, adaptation, and remediation at the local and national levels.
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Notes
Under current carbon emission policies and energy transitions, empirical evidence would suggest that RCP8.5 is less likely, and we are currently closer to a medium GHG concentration scenario (RCP4.5) (Hausfather and Peters 2020).
We convert all DEMs from the original vertical datum of the North American Vertical Datum of 1988 (NAVD88) and vertical units of meters to the same vertical datum (MHHW) and vertical units (feet) as the Sea-Level Rise Viewer inundation shapefiles using NOAA’s VDatum conversion tool (NOAAd 2019).
With the climate risk field advancing quickly, other groups have started to produce proprietary national level flood risk models (First Street Foundation 2020). However, the granular private label flood data from these providers are only available at cost and use models not available in the public domain. Our SLR risk-matching methods use publicly available spatial and climate risk datasets, which are freely available to risk practitioners. Thus, each component of our risk methodology is transparent and easy to replicate: (1) Refined measure of property inundation elevation; (2) Estimated timing of SLR inundation; (3) SLR risk accounting for climate uncertainty.
We focus our discussion of results on the medium GHG scenario (RCP 4.5) for both K14 and DP16 as recent scientific evidence would suggest that we are closest to the medium scenario (Hausfather and Peters 2020). For detailed results across all metros and climate scenarios, see supplemental material section 2.
Recent survey evidence indicates that coastal homeowners that are most at risk are reluctant to acknowledge the risks they face from SLR and coastal inundation (Palm and Bolsen 2020).
References
Amante CJ (2018) Estimating coastal digital elevation model uncertainty. J Coast Res 34–1397:1382–1397. https://doi.org/10.2112/JCOASTRES-D-17-00211.1
Amante CJ (2019) Uncertain seas: probabilistic modeling of future coastal ood zones. Int J Geogr Inf Sci 33:1–30. https://doi.org/10.1080/13658816.2019.1635253
Amante CJ, Eakins BW (2016) Accuracy of interpolated bathymetry in digital elevation models. J Coast Res 76:123–133. https://doi.org/10.2112/SI76-011
Arrow KJ, Cropper ML, Gollier C, Groom B, Heal GM, Newell RG, Weitzman ML (2013) Determining benefits and costs for future generations. Science 341:349–350
Barnston AG, Livezey RE (1987) Classification, seasonality and persistence of low-frequency atmospheric circulation patterns. Mon Weather Rev 115(6):1083–1126
Bauer M, Rudebusch G (2020) The rising cost of climate change: Evidence from the bond market. Federal Reserve Bank of San Francisco, Working Paper Series. https://doi.org/10.24148/wp2020-25
Benson E, Hansen J, Schwartz A Jr, Smersh G (1998) Pricing residential amenities: the value of a view. J Real Estate Finance Econ 16:55–73. https://doi.org/10.1023/A:1007785315925
Bernstein A, Gustafson M, Lewis R (2019) Disaster on the horizon: the price effect of sea level rise. J Finan Econ 134(2):253–272. https://doi.org/10.1016/j.jfineco.2019.03.013
Black Rock (2019) Getting physical: assessing climate risks. https://www.blackrock.com/us/individual/insights/blackrock-investment-institute/physical-climate-risks
Brunetti C, Dennis B, Gates D, Hancock D, Ignell D, Kiser EK,Tabor NK (2021) Climate change and financial stability. FEDS Notes. https://doi.org/10.17016/2380-7172.2893
Campiglio E, Dafermos Y, Monnin P, Ryancollins J, Schotten G, Tanaka M (2018) Climate change challenges for central banks and financial regulators. Nat Climate Change 8:1. https://doi.org/10.1038/s41558-018-0175-0
Carney M (2015) Breaking the tragedy of the horizon—climate change and financial stability. Retrieved from (Remarks by Mark Carney, Governor of the Bank of England and Chairman of the Financial Stability Board, at Lloyd’s of London. September) https://www.bis.org/review/r151009a.pdf
Cazenave A, Nerem RS (2004) Present-day sea level change: observations and causes. Rev Geophys 42:3. https://doi.org/10.1029/2003RG000139
Census (2017) Historical census of housing tables:units in structure. United States Census Bureau. www.census.gov/data/tables/time series/dec/coh-units.html)
Census (2020) Quick facts united states. United States Census Bureau. https://www.census.gov/quickfacts/)
Church J (2013) Sea level change. In: Stocker TF, et al (ed) Climate Change 2013—The Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. pp 1137–1216. https://doi.org/10.1017/CBO9781107415324.026
CoBank (2019) Rural industries and climate change. CoBank. https://www.cobank.com/knowledge-exchange/general/rural-industries-and-climate-change accessed 31 Dec 2019
Deconto RM, Pollard D (2016) Contribution of Antarctica to past and future sea-level rise. Nature 531:591–597
Department of the Treasury US (2021) Report on climate related financial risk. Financial Stability Oversight Council. October. https://home.treasury.gov/system/files/261/FSOC-Climate-Report.pdf
Drupp MA, Freeman MC, Groom B, Nesje F (2018) Discounting disentangled. Am Econ J 10(4):109–134
Federal Reserve Board of Governors (2020) Financial stability report-November 2020. https://www.federalreserve.gov/publications/2020-november-financial-stability-report- purpose.htm accessed 12 Apr 2021
First Street Foundation (2020) First street foundation ood model 2020 methodol- ogy overview. https://firststreet.org/research-lab/published-research/flood-model-methodology overview/ (Intergovernmental Panel on Climate Change) accessed 21 Oct 2021
FSB-TCFD (2017) Recommendations of the task force on climate related financial disclosures. Financial Stability Board. https://www.fsb-tcfd.org/publications/final-recommendations-report/ accessed 31 Dec 2021
Gesch DB (2009) Analysis of lidar elevation data for improved identification and delineation of lands vulnerable to sea-level rise. J Coast Res 10053:49–58. https://doi.org/10.2112/SI53-006.1
Gesch DB (2018) Best practices for elevation-based assessments of sea-level rise and coastal ooding exposure. Front Earth Sci 6:230
Giglio S, Maggiori M, Rao K, Stroebel J, Webe A (2021) Climate change and long-run discount rates: evidence from real estate. The Review of Financial Studies 34(8):3527–3571. https://doi.org/10.1093/rfs/hhab032
Gillies S, et al (2013) Rasterio: geospatial raster i/o for Python programmers. https://github.com/mapbox/rasterio
Goldman Sachs (2019) Taking the heat: making cities resilient to climate change. (Goldman Sachs. September. https://www.goldmansachs.com/insights/pages/taking-the-heat.html) accessed 31 Dec 2019
Guthrie G (2020) Adapting to rising sea levels: how short-term responses complement long-term investment. https://ssrn.com/abstract=3571033
Han W, Meehl GA, Stammer D, Hu A, Hamlington B, Kenigson J, Thompson P (2017) Spatial patterns of sea level variability associated with natural internal climate modes. Surv Geophys 38:217–250. https://doi.org/10.1007/s10712-016-9386-y
Hauer M, Evans J, Mishra D (2016) Millions projected to be at risk from sea-level rise in the continental United States. Nat Climate Change 6:03. https://doi.org/10.1038/nclimate2961
Hausfather Z, Peters GP (2020) Emissions—the ‘business as usual’ story is misleading. Nature 577:618–620
Hawkins E, Sutton R (2009) The potential to narrow uncertainty in regional climate predictions. Bull Am Meteorol Soc 90:1095. https://doi.org/10.1175/2009BAMS2607.1
Heal G, Millner A (2014) Reactions: uncertainty and decision making in climate change economics. Rev Environ Econ Policy 8:120–137
Horton R, Little C, Gornitz V, Bader D, Oppenheimer M (2015) New York city panel on climate change 2015 report chapter 2: sea level rise and coastal storms. Ann N Y Acad Sci 1336(1):36–44. https://doi.org/10.1111/nyas.12593
Hunter JD (2007) Matplotlib: a 2D graphics environment. Comput Sci Eng 9(3):90–95. https://doi.org/10.1109/MCSE.2007.55
Hurrell JW (1995) Decadal trends in the North Atlantic oscillation: regional temperatures and precipitation. Science 269(5224):676–679. https://doi.org/10.1126/science.269.5224.676
IPCC (2021) AR6 Synthesis Report: Climate Change 2021. https://www.ipcc.ch/assessment-report/ar6/ (Intergovernmental Panel on Climate Change)
Jordahl K, den Bossche JV, Wasserman J, McBride J, Fleischmann M, Gerard J, maxalbert (2020) geopandas/geopandas: v0.7.0. Zenodo. https://doi.org/10.5281/zenodo.3669853
Keenan JM, Bradt JT (2020) Underwaterwriting: from theory to empiricism in regional mortgage markets in the U.S. Climatic Change 162(4):2043–2067
Keys BJ, Mulder P (2020) Neglected no more: housing markets, mortgage lending, and sea level rise [Working Paper]. (27930). http://www.nber.org/papers/w27930https://doi.org/10.3386/w27930
Kirezci E, Young I, Ranasinghe R, Muis S, Nicholls R, Lincke D, Hinkel J (2020) Projections of global-scale extreme sea levels and resulting episodic coastal ooding over the 21st century. Sci Rep 10:11629. https://doi.org/10.1038/s41598-020-67736-6
Kopp RE, DeConto RM, Bader DA, Hay CC, Horton RM, Kulp S, Strauss BH (2017) Evolving understanding of Antarctic ice-sheet physics and ambiguity in probabilistic sea-level projections. Earth’s Future 5(12):1217–1233. https://doi.org/10.1002/2017EF000663
Kopp RE, Horton RM, Little CM, Mitrovica JX, Oppenheimer M, Rasmussen DJ, Tebaldi C (2014) Probabilistic 21st and 22nd century sea-level projections at a global network of tide-gauge sites. Earth’s Future 2(8):383–406
Li X, Rowley RJ, Kostelnick JC, Braaten D, Meisel J, Hulbutta K (2009) Gis analysis of global impacts from sea level rise. Photogramm Eng Remote Sens 75(7):807–818
Lombard A, Cazenave A, Traon P-Y, Ishii M (2005) Contribution of thermal expansion to present-day sea-level change revisited. Glob Planetary Change 47:1–16. https://doi.org/10.1016/j.gloplacha.2004.11.016
Mcalpine S, Porter J (2018) Estimating recent local impacts of sea-level rise on current real-estate losses: A housing market case study in Miami-Dade, Florida. Popul Res Policy Rev 37:1. https://doi.org/10.1007/s11113-018-9473-5
Milne G, Gehrels W, Hughes C, Tamisiea M (2009) Identifying the causes of sea-level change. Nature Geosci 2:471–478. https://doi.org/10.1038/ngeo544
Moftakhari H, AghaKouchak A, Sanders B, Feldman D, Sweet W, Matthew R, Luke A (2015) Increased nuisance flooding along the coasts of the united states due to sea level rise: past and future. Geophys Res Lett 42(22):9846–9852
Moss R, Edmonds J, Hibbard K, Manning M, Rose S, Vuuren D, Wilbanks T (2010) The next generation of scenarios for climate change research and assessment. Nature 463:747–56. https://doi.org/10.1038/nature08823
Nerem R, Mitchum G (2001) Satellite altimetry and earth sciences: a handbook of techniques and applications. Academic Press, Boca Raton
NOAA (2019a) United states billion-dollar weather and climate disasters. NOAA National Centers for Environmental Information (NCEI). https://www.ncdc.noaa.gov/billions/
NOAA (2019b) Office of coast management: economics and demographics. NOAA Office of Coast Management. https://coast.noaa.gov/states/fast-facts/economics-and-demographics.html)
NOAA (2019c) NOAA sea level rise viewer. NOAA Office of Coast Management. https://coast.noaa.gov/digitalcoast/tools/slr.html
NOAA (2019d) NOAA vertical datum tranformation (vdatum). version v4.0.1. National Ocean Service. https://vdatum.noaa.gov/
Nordhaus W (2013) The climate casino: risk, uncertainty, and economics for a warming world. Yale University Press, London
Ortega F, Taspinar S (2018) Rising sea levels and sinking property values: hurricane Sandy and New York’s housing market. J Urban Econ 106:81–100. https://doi.org/10.1016/j.jue.2018.06.005
Palm R, Bolsen TW (2020) Even looking at ood maps can’t convince coastal residents their homes will be underwater. Retrieved 2020-02-08, from (Fast Company. https://www.fastcompany.com/90461819/even-looking-at-ood-maps-cant-convince-coastal-residents-their-homes-will-be-underwater)
Pandas Development Team T (2020) pandas-dev/pandas: Pandas. Zenodo. https://doi.org/10.5281/zenodo.3509134
Poppenga S, Worstell B (2015) Evaluation of airborne lidar elevation surfaces for propagation of coastal inundation: the importance of hydrologic connectivity. Remote Sensing 7(9):11695–11711. https://doi.org/10.3390/rs70911695
Poulter B, Halpin P (2008) Raster modelling of coastal flooding from sea-level rise. Int J Geogr Inf Sci 22(2):167–182
Rao K (2017) Climate change and housing: will a rising tide sink all homes? https://www.zillow.com/research/climate-change-underwater-homes-12890/
Rogelj J, Meinshausen M, Knutti R (2012) Global warming under old and new scenarios using IPCC climate sensitivity range estimates. Nature Climate Change 2:248–253. https://doi.org/10.1038/nclimate1385
Sweet WV, Kopp RE, Weaver CP, Obeysekera J, Horton RM, Thieler ER, Zervas C (2017) Global and regional sea level rise scenarios for the united states. (Technical Report NOS CO-OPS 083. National Oceanic and Atmospheric Administration)
Trenberth KE, Shea DJ (2006) Atlantic hurricanes and natural variability in 2005. Geophys Res Lett 33(12):15. https://doi.org/10.1029/2006GL026894
USGCRP (2018) Impacts, risks, and adaptation in the united states: Fourth national climate assessment. (U.S. Global Change Research Program) https://doi.org/10.7930/NCA4.2018
USPS (2020) City state product. (United States Postal Service. November. https://postalpro.usps.com/address-quality/city-state-product)
Wang C, Zhang L (2013) Multidecadal ocean temperature and salinity variability in the tropical North Atlantic: linking with the amo, amoc, and subtropical cell. J Climate 26:6137–6162. https://doi.org/10.1175/JCLI-D-12-00721.1
Wrathall D, Mueller V, Clark P, Bell A, Oppenheimer M, Hauer M, Warner K (2019) Meeting the looming policy challenge of sea-level change and human migration. Nature Climate Change 9(12):898–901. https://doi.org/10.1038/s41558-019-0640-4 (11,26)
Zhang K, Li Y, Liu H, Xu H, Shen J (2013) Comparison of three methods for estimating the sea level rise effect on storm surge ooding. Climatic Change 118(2):487–500
Zillow (2013) 20.6 million U.S. homeowners own homes free and clear of mortgage debt. (Zillow Research. http://zillow.mediaroom.com/2013-01-10-20-6-Million-U-S-Homeowners-Own-Homes-Free-And-Clear-Of-Mortgage-Debt)
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The views expressed here are those of the authors and are not attributable to the Federal Reserve Bank of Kansas City, the Federal Reserve System, or the National Oceanic and Atmospheric Administration. Rodziewicz: Federal Reserve Bank of Kansas City; Amante: Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder at the National Oceanic and Atmospheric Administration (NOAA), National Centers for Environmental Information (NCEI); Dice: Federal Reserve Bank of Kansas City; Wahl: National Oceanic and Atmospheric Administration (NOAA), National Centers for Environmental Information (NCEI) (retired).
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Rodziewicz, D., Amante, C.J., Dice, J. et al. Housing market impairment from future sea-level rise inundation. Environ Syst Decis 42, 637–656 (2022). https://doi.org/10.1007/s10669-022-09842-6
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DOI: https://doi.org/10.1007/s10669-022-09842-6