Modeling and analysis

The statistical/deterministic hurricane model19 generates synthetic TCs for a given large-scale atmospheric and oceanic environment estimated from observations or a climate model (see “Methods” section). We run the model to generate 5018 synthetic TCs for the observed climate of the historical period between 1980 and 2005, based on the National Centers for Environmental Prediction (NCEP) reanalysis26. To study the TC climatology change, we run the model to generate synthetic TCs for the projected climate of the future period between 2070 and 2095, under the RCP 8.5 greenhouse gas concentration scenario. Given data availability and following previous studies7,18, we consider projections from six CMIP5 GCMs27 including CCSM4 (Community Climate System Model, the University Corporation for Atmospheric Research); GFDL5 (Geophysical Fluid Dynamics Laboratory Climate Model, USA); HadGEM5 (Hadley Centre Global Environment Model, U.K. Meteorological Office); MIROC (Model for Interdisciplinary Research on Climate, University of Tokyo, National Institute for Environmental Studies, Japan, and Japan Agency for Marine-Earth Science and Technology Frontier Research Center for Global Change); MPI5 (Max Planck Institute for Meteorology, Germany); and MRI5 (Meteorological Research Institute, Japan). We simulate 5018 synthetic TCs for each model for the future period. We also generate another 5018 TCs for each model for the historical period.

The storm tide induced by each generated synthetic storm is simulated using the advanced circulation model (ADCIRC)23,24 with a basin scale mesh25 (see “Methods” section). For each coastal county, we extract the storm tide associated with each synthetic TC as the largest peak storm tide generated by the TC along the county’s coastlines. The probabilistic SLR projection is obtained from ref. 2 (see “Methods” section). For each coastal county, we use the projection under RCP 8.5 of the end-of-21st century SLR from the closest station to that county. Combining the probabilistic projections of storm tide and SLR, we perform statistical analysis to estimate the return periods of flood heights (see “Methods” section). Considering that climate model projections may be biased, we bias correct the climate model-projected storm tides based on a comparison of the model estimates for the historical period with the NCEP-based estimates (see “Methods” section). We also obtain a weighted average projection of storm tides with the weight on each climate model depending on its accuracy in the historical estimations relative to the NCEP estimations (see “Methods” section). The flood return level estimations are performed for each coastal county along the US Atlantic and Gulf Coasts (Fig. 1 shows the list of the counties; the basin is divided into four regions: Gulf of Mexico, southeast Atlantic, mid-Atlantic, and New England).

Fig. 1 Coastal counties along the US Atlantic and Gulf Coasts (numbers represent the county ID). The study area is divided into four regions: New England (green), mid-Atlantic (orange), southeast Atlantic (blue), and Gulf of Mexico (red). Source data are provided as a Source data file Full size image

The hydrodynamic model was previously evaluated against historical storm tides and the model showed a satisfactory performance25. The hurricane model was also previously evaluated and was shown to generate synthetic storms that statistically agree with observations28 and compare well with storms generated by other methods5,29. Here we evaluate the integrated climatology–hydrodynamic modeling system by comparing the flood return period estimates derived from the NCEP-based synthetic TCs for the historical period of 1980–2005 to those based on the observed water levels at tide gauge stations for the same period. Comparisons show a good agreement between the modeled and observation-based flood level estimates for relatively short return periods that can be resolved based on the observations during the relatively short historical period, although larger return levels cannot be well resolved from the observations and wide uncertainty bounds exist (Supplementary Fig. 1). To assist the spatial comparison of flood hazards, the flood heights are determined relative to the local mean higher high water.

Spatial and temporal variation of flood hazards

As examples, Fig. 2 shows the return period curves for representative coastal counties in each region. The future return period curves take into account the impacts of SLR and TC climatology change, which is the weighted average over the six climate models (with weighting factors shown in Supplementary Fig. 2). Results indicate that the flood level for a given return period substantially increases by the end of 21st century, due to SLR as well as TC climatology change. The very likely estimates (5th–95th percentiles; i.e., 90% statistical confidence interval) of flood levels with a long return period cover a wide range, indicating a large statistical uncertainty in such events. The uncertainties are smaller for flood levels with a higher probability of occurrence, e.g., the 100-year flood return level. We retain the focus of the remainder of this paper on the 100-year flood level.

Fig. 2 Flood return period curves for the historical period of 1980–2005 (black) and future period of 2070–2095 (blue: only effects of TC changes, red: compound effects of SLR and TCs) at selected coastal counties. a–c Representative counties in New England; d–f representative counties in mid Atlantic; g–i representative counties in southeast Atlantic; j–l representative counties in Gulf of Mexico. Empirical data points for the historical period are shown as black circles. Solid lines represent the best estimates of flood return periods. Shaded areas cover the very likely range estimates (i.e., 90% statistical confidence interval). Future projections are weighted average over the six climate models. Flood levels are relative to mean higher high water (MHHW, obtained from https://vdatum.noaa.gov). Source data are provided as a Source data file Full size image

Figure 3 displays the spatial distribution of the estimated 100-year flood level along the US Atlantic and Gulf Coasts. The NCEP-based best estimate of 100-year flood level (η 100–yr ) for the historical period varies greatly along the coast (Fig. 3a): it is between 1.53 and 4.30 m (with the average over all counties of 3.03 m) in the Gulf of Mexico, 0.52 and 2.82 m (1.46 m) in the southeast Atlantic, 0.27 and 1.67 m (0.84 m) in the mid-Atlantic, and 0.48 and 1.20 m (0.66 m) in the New England regions. Figure 3b shows the spatial distribution of the total changes in η 100 year for the future period, hereinafter ∆η 100 year (changes are weighted average over six climate models; ∆η 100 year projected by each climate model is shown in Supplementary Fig. 3).

Fig. 3 Projected flood hazards along the US Atlantic and Gulf Coasts. a NCEP-based best estimate of 100-year flood level η 100 year for the historical period of 1980–2005. b Projected weighted average changes in η 100 year for the future period of 2070–2095 under the compound effects of SLR and TC climatology change. c Future return period of historical 100-year flood level. Flood levels are relative to MHHW. Source data are provided as a Source data file Full size image

Along coastal counties in the Gulf of Mexico region, the best estimate of ∆η 100 year is between 1.5 and 2.80 m, with an average value of 2 m (66% increase in the average η 100 year ). The largest ∆η 100 year is projected to be between 2 and 2.8 m along the northern coast of the Gulf of Mexico (Alabama, Mississippi, Louisiana, and East Texas). The average very likely (5th–95th percentile) range of η 100 year changes from 2.38–4.16 m in the historical period to 4.19–6.62 m in the future period for the Gulf of Mexico region. The best estimate of ∆η 100 year is between 1.34 and 1.85 m (average change of 1.52 m; 104% increase) in the southeast Atlantic region and between 1.43 and 1.92 m (average change of 1.67 m; 200% increase) in the mid-Atlantic region. The average very likely estimate of η 100 year changes from 1.03–2.32 m to 2.6–3.87 m in the southeast Atlantic region and from 0.65–1.21 m to 2.24–3.10 m in the mid-Atlantic region. The best estimate of ∆η 100 year for the New England region is between 1.55 and 1.82 m (average change of 1.68 m; 255%). The average very likely estimate of η 100 year in this region changes from 0.56–0.89 m to 2.23–2.62 m.

A previous study has shown that the TC climatology change and a 1-m SLR by the end of 21st century substantially increase flood levels at New York City21. Four different climate models (based on CMIP3 A1B scenario) in this previous study21 projected an increase of between 0.8 and 1.75 m in η 100 year . Our projections from six climate models (based on CMIP5 RCP 8.5 scenario) for the New York county show an increase of between 1.36 and 1.90 m with a weighted average increase of 1.53 m. The subtle difference between the range of projections is mainly because the previous study was based on a different synthetic TC dataset, its projections were not bias corrected, and a different computational mesh was used in the hydrodynamic model. The previous study was also based on a deterministic SLR of 1 m, whereas the present study is based on a probabilistic projection of SLR.

Figure 3c shows the future return periods of the historical NCEP-based 100-year flood level, which are estimated to be between 5 and 30 years (16.4 years, averaged over all counties) for the coastal counties in the Gulf of Mexico and between 1 and 29 years (average 8.3 years) in the southeast Atlantic. In the New England and mid-Atlantic regions, the historical η 100 year is estimated to occur annually by the end of 21st century. In these high latitude regions, the historical 100-year flood levels are relatively small and thus significant changes in the future climate lead to substantial reductions of the return periods of such flood levels.

Relative impact of SLR and TC climatology change

Figure 4 shows the contribution of SLR and TC climatology change (respectively, ∆η 100 year, SLR and ∆η 100 year, TC ) to ∆η 100 year . The effect of SLR is largest in the mid-Atlantic and New England regions, and the northern coast of the Gulf of Mexico, consistent with the projected SLR patterns2. We find that SLR results in an increase in η 100 year of 1.07 m (35% increase in the average η 100 year ) in the Gulf of Mexico (averaged over all counties in this region), 1.08 m (74%) in the southwest Atlantic, 1.38 m (165%) in the mid-Atlantic, and 1.58 m (239%) in New England. The effect of TC climatology change varies along the coastlines in a contrary way. The TC climatology change alone increases η 100 year by about 0.93 m (31% increase in the average η 100 year ) in the Gulf of Mexico, 0.44 m (30%) in the southeast Atlantic, 0.29 m (35%) in the mid-Atlantic, and only 0.1 m (15%) in New England. The largest-projected TC induced change in the 100-year flood level is about 1.5 m for several coastal counties in Mississippi and Louisiana. Our projections show a ∆η 100 year, TC of about 0.16 m for the New York county, NY, which is consistent with a previous study21, where results from four climate models showed that the influence of TC climatology change on New York City’s η 100 year is between −0.2m and 0.75 m.

Fig. 4 Projected contributions of SLR and TC climatology change to changes in the 100-year flood level. a Changes in η 100 year for the future period of 2070–2095 due to SLR (Δη 100 year, SLR ). b Changes in η 100 year for the future period of 2070–2095 due to TC climatology change (Δη 100 year, TC ). c Relative contributions of SLR and TC climatology change to the projected changes in η 100 year . Source data are provided as a Source data file Full size image

Our projections show that TC climatology change has a minimal impact on ∆η 100 year at high latitudes whereas its impact on ∆η 100 year at lower latitudes is as significant as SLR. In the New England region, SLR is projected to contribute between 82.2 and 99.7% to ∆η 100 year , whereas TC climatology change contributes only between 0.3 and 17.8% (for counties bordering the Gulf of Maine, ∆η 100 year, TC < 3%). The contribution of SLR to ∆η 100 year is between 67.1 and 96.1% in mid-Atlantic and between 44.6 and 89.8% in southeast Atlantic. It is reduced to 35–80.1% for the Gulf of Mexico region. In 41% of coastal counties in the Gulf of Mexico, the TC climatology change is projected to be the main cause of increase in the future 100-year flood level (i.e., contribution of TC climatology change >50%). This spatial trend of relative effects of SLR and TC climatology change on the flood level also exists for other return periods, as shown in Fig. 2 for representative counties.

Increasing flood levels induced by TC climatology change, especially in lower-latitude regions, suggest that the frequency, intensity, and/or size of TCs could increase by the end of 21st century. Figure 5 shows that the frequency, intensity, and size of NCEP-based historical TCs off the US Atlantic and Gulf Coasts greatly varies as a function of latitude. While the TC frequency and intensity (represented by maximum wind speed V max ) are higher in the Gulf of Mexico and southeast Atlantic regions, the TC size (represented by radius of maximum wind speed R max ) is larger in the mid-Atlantic and New England regions. Figure 5 shows that both the intensity and size of TCs off the entire US Atlantic and Gulf Coasts increase from the historical period to the future period (up to a 21% increase). In particular, the index V max 2R max , which we use here as a consolidated measure of TC intensity and size, increases in the entire basin with the largest increase in the Gulf of Mexico, resulting in the large values of ∆η 100 year, TC projected for the Gulf of Mexico compared with other regions (see Fig. 4). Changes in the TC frequency, shown in Fig. 5, reveal a larger increase for the northern coast of the Gulf of Mexico than the Gulf ’s eastern and western coasts, explaining the larger ∆η 100 year, TC along the coastal counties of Alabama, Mississippi, Louisiana, and East Texas than other counties in the Gulf. In addition, our analysis of TC translation speed, not shown here, reveals an increase in the number of slow-moving TCs and a decrease in the number of fast-moving TCs. Slower TCs allow winds to blow onshore for longer periods of time, resulting in possibly larger and longer coastal flooding.

Fig. 5 Projected changes in TC characteristics from the historical period of 1980–2005 to the future period of 2070–2095. a–d NCEP-based TC annual frequency (Fr), maximum wind speed (V max ), radius of maximum wind speed (R max ), and the intensity size index V max 2R max for the historical period. e–h Projected changes (weighted average over climate models) in Fr, V max , R max , and V max 2R max for the future period. A basin wide weighting factor (which is the average of weighting factors for storm tides over all coastal counties) is used for each climate model. Values represent 90th percentile of TCs (with V max > 40 knot) passing through 2 × 2 degrees boxes. Source data are provided as a Source data file Full size image

Projections based on all six climate models agree that the largest impact of TC climatology change on the 100-year flood level takes place in the Gulf of Mexico (Supplementary Fig. 4). Projections from five models (out of six) suggest that ∆η 100 year, TC along the northern coast of Gulf of Mexico is larger than that along the Gulf ’s eastern and western coasts. Only MRI5 projects a larger ∆η 100 year, TC along the eastern Gulf Coast. The GFDL5 model shows profoundly larger ∆η 100 year, TC in the Gulf of Mexico region. This model projects an average increase of 2.19 m (73% of the average η 100 year ) in this region whereas projections from other models are between 0.49 (16%) and 1.0 m (33%). In the Southeast Atlantic region, HadGEM5 projects the largest ∆η 100 year, TC with an average increase of 1.2 m (86%). In this region, MRI5 shows that the impact of TC climatology change on η 100 year is between −0.36 (23% decrease) and 0.68 m (57% increase), with an average increase of 0.08 m (8%). The projections from other models are between 0.5 (11%) and 0.79 m (60%). In the mid-Atlantic region, HadGEM5 shows the largest ∆η 100 year, TC with an average increase of 0.75 m (90%). For this region, MRI5 shows an average decrease of 0.05 m (4%). Projections from other models indicate an average increase between 0.14 (17%) and 0.53 m (60%). In the New England region, HadGEM5 shows the largest ∆η 100 year, TC with an average increase of 0.41 m (57%) whereas MRI5 shows an average decrease of 0.16 m (21%). Other models project an average increase between 0.06 (8%) and 0.13 m (18%).