Global and Regional Sea Level Rise Scenarios for the United States | 74

Section A1: Tables and Figures

Figure A1.1: Region definitions for observation-based extrapolations and scenarios in Section 2. These regions are used both to 

group tide gauges and also to generate regional averages for the gridded scenarios. A bathymetry mask is used to define the 

regions for the gridded scenarios.
Global and Regional Sea Level Rise Scenarios for the United States | 75

Figure A1.2. Shown for each tide gauge record with at least 30 years of record length between 1970 and 2020 are a) range, in 

meters, between median projection of Low and High Scenarios in 2050, and b) difference, in meters, between median observation-based extrapolation and Intermediate scenario in 2050.
Global and Regional Sea Level Rise Scenarios for the United States | 76

Table A1.1: Projections methods employed.

Driver of GMSL or 

RSL change

Kopp et al. (2014) projection method 

(used in Sweet et al., 2017)

AR6 (Fox-Kemper et al., 2021) projection methods 

(used here)

Thermal expansion CMIP5 ensemble drift-corrected zostoga

Two-layer model with climate sensitivity calibrated to the 

IPCC assessment and expansion coefficients calibrated to 

emulate CMIP6 models

Greenland ice sheet 

Likely range from IPCC AR5, with shape of 

tails based on structured expert judgment 

(Bamber and Aspinall, 2013)

1. Emulated ISMIP6 simulations through 2100 (Edwards et al., 

2021), extended after 2100 based on constant post-2100 

rates

2. Structured expert judgment (Bamber et al., 2019)

Antarctic ice sheet 

Likely range from IPCC AR5, with shape of 

tails based on structured expert judgment 

(Bamber and Aspinall, 2013)

1. Emulated ISMIP6 simulations through 2100 (Edwards et al., 

2021), extended after 2100 with constant rates based on the 

IPCC AR5 parametric Antarctic Ice Sheet model (Church et 

al., 2013)

2. LARMIP-2 simulations (Levermann et al., 2020) augmented 

by AR5 surface mass balance model (Church et al., 2013), 

extended past 2100 based on constant rates 

3. Single ice-sheet model incorporated marine ice cliff instability (DeConto et al., 2021)

4. Structured expert judgment (Bamber et al., 2019)

Glaciers Distribution based on Marzeion et al. (2012) 

surface mass balance model

Emulated GlacierMIP (Marzeion et al., 2020; Edwards et al., 

2021) extended after 2100 with IPCC AR5 parametric model 

refit to GlacierMIP (Marzeion et al., 2020)

Land water storage 

Groundwater depletion: Population/

groundwater depletion relationship 

calibrated based on Konikow (2011) and 

Wada et al. (2012)

Water impoundment: Population/dam 

impoundment relationship calibrated 

based on Chao et al. (2008)

Groundwater depletion: Updated population/groundwater 

depletion relationship calibrated based on Konikow (2011) 

and Wada et al. (2012, 2016)

Water impoundment: Population/dam impoundment 

relationship calibrated based on Chao et al. (2008), adjusted 

for new construction, following Hawley et al. (2020) for 2020 

to 2040

Ocean dynamic sea 

level

Distribution derived from CMIP5 ensemble 

zos field

Distribution derived from CMIP6 ensemble zos field after 

linear drift removal

Gravitational, 

rotational, and 

deformational 

effects

Sea-level equation solver (Mitrovica et al., 

2011) driven by projections of ice-sheet and 

glacier changes

Sea-level equation solver (Slangen et al., 2014) driven by 

projections of ice-sheet, glacier, and land water storage 

changes

GIA and other 

drivers of VLM

Spatiotemporal statistical model of tidegauge dataSpatiotemporal statistical model of tide-gauge data 

(updated from Kopp et al., 2014)

Table A1.2: Offsets, in meters, for different time periods and for each region considered in 

Section 2. These offsets are assessed using the trajectory determined from the available 

tide-gauge data in each region.

1992–2000 2000–2005 2005–2020

Contiguous U.S. 0.02 0.03 0.08

Northeast 0.03 0.02 0.09

Southeast 0.03 0.02 0.09

Eastern Gulf 0.03 0.02 0.1

Western Gulf 0.05 0.04 0.14

Southwest 0.01 0.01 0.05

Northwest 0.01 0.01 0.04

Hawaiian Islands 0.02 0.02 0.06

Caribbean 0.02 0.01 0.06
Global and Regional Sea Level Rise Scenarios for the United States | 77

US 

Region

EWL 

Grid 

No.

NOAA ID Location Latitude Longitude

Tide 

Range 

(m)

Flood 

Index 

u (m, 

MHHW)

u Trend 

(mm/yr)

Epoch 

of u

Minor 

Flood (m, 

MHHW)

Moderate 

Flood (m)

Major 

Flood 

(m)

Pacific 39509 1611400 Nawiliwili, HI 21.95 −159.36 0.558 0.244 1.7 1983–

2001 0.522 0.817 1.192

39511 1612340 Honolulu, HI 21.31 −157.87 0.580 0.248 1.3 1983–

2001 0.523 0.817 1.193

39511 1612480 Mokuoloe, HI 21.43 −157.79 0.646 0.265 2.0 1983–

2001 0.526 0.819 1.196

39153 1615680 Kahului, HI 20.90 −156.48 0.686 0.252 2.1 1983–

2001 0.527 0.821 1.197

39154 1617433 Kawaihae, HI 20.04 −155.83 0.659 0.237 7.9 1983–

2001 0.526 0.820 1.196

38795 1617760 Hilo, HI 19.73 −155.06 0.731 0.272 3.1 1983–

2001 0.529 0.822 1.199

37704 1619000 Johnston Atoll 16.74 −169.53 0.674 0.295 2.2 1983–

2001 0.527 0.820 1.197

42004 1619910 Midway Islands 28.21 −177.36 0.381 0.303 1.9 1983–

2001 0.515 0.811 1.185

36941 1630000 Apra Harbor, 

Guam 13.44 144.65 0.715 0.249 4.2 1983–2001 0.529 0.821 1.199

36941 1631428 Pago Bay, 

Guam 13.43 144.80 0.525 0.287 4.2 1983–2001 0.521 0.816 1.191

26574 1770000 American 

Samoa −14.28 189.32 0.848 0.338 3.8 1983–2001 0.497 0.788 1.167

35169 1820000 Kwajalein 8.73 167.74 1.194 0.446 3.1 1983–

2001 0.548 0.836 1.218

39117 1890000 Wake Island 19.29 166.62 0.718 0.295 2.1 1983–

2001 0.529 0.822 1.199

NE 47859 8410140 Eastport, ME 44.90 −66.98 5.874 0.930 2.1 1983–

2001 0.735 0.976 1.405

47858 8411250 Cutler Naval 

Base, ME 44.64 −67.30 4.133 0.716 2.4 1983–2001 0.665 0.924 1.335

47857 8413320 Bar Harbor, ME 44.39 −68.21 3.465 0.657 2.1 1983–

2001 0.639 0.904 1.309

47496 8418150 Portland, ME 43.66 −70.25 3.019 0.605 1.9 1983–

2001 0.621 0.891 1.291

47496 8419317 Wells, ME 43.32 −70.56 2.914 0.667 3.5 1983–

2001 0.617 0.887 1.287

47496 8423898 Fort Point, NH 43.07 −70.71 2.864 0.662 3.5 1983–

2001 0.615 0.886 1.285

47136 8443970 Boston, MA 42.35 −71.05 3.131 0.634 2.8 1983–

2001 0.625 0.894 1.295

46777 8447386 Fall River, MA 41.70 −71.16 1.456 0.566 3.5 1983–

2001 0.558 0.844 1.228

46778 8447930 Woods Hole, 

MA 41.52 −70.67 0.672 0.446 3.2 1983–2001 0.527 0.820 1.197

46778 8449130 Nantucket 

Island, MA 41.29 −70.10 1.089 0.418 3.8 1983–2001 0.544 0.833 1.214

46777 8452660 Newport, RI 41.51 −71.33 1.174 0.478 2.8 1983–

2001 0.547 0.835 1.217

Table A1.3: Regional designation, tide gauge information, extreme water level metadata, and high tide flood heights.
Global and Regional Sea Level Rise Scenarios for the United States | 78

Table A1.3 (cont.): Regional designation, tide gauge information, extreme water level metadata, and high tide flood heights.

US 

Region

EWL 

Grid 

No.

NOAA ID Location Latitude Longitude

Tide 

Range 

(m)

Flood 

Index 

u (m, 

MHHW)

u Trend 

(mm/yr)

Epoch 

of u

Minor 

Flood (m, 

MHHW)

Moderate 

Flood (m)

Major 

Flood 

(m)

NE

(cont.) 46777 8452944 Conimicut Light, RI 41.72 −71.34 1.398 0.560 3.5 1983–2001 0.556 0.842 1.226

46777 8454000 Providence, RI 41.81 −71.40 1.476 0.549 2.3 1983–

2001 0.559 0.844 1.229

46777 8454049 Quonset Point, 

RI 41.59 −71.41 1.249 0.547 3.5 1983–2001 0.550 0.837 1.220

46776 8461490 New London, 

CT 41.36 −72.09 0.930 0.468 2.6 1983–2001 0.537 0.828 1.207

46776 8465705 New Haven, CT 41.28 −72.91 2.045 0.603 3.5 1983–

2001 0.582 0.861 1.252

46775 8467150 Bridgeport, CT 41.17 −73.18 2.231 0.555 3.0 1983–

2001 0.589 0.867 1.259

46777 8510560 Montauk, NY 41.05 −71.96 0.771 0.487 3.4 1983–

2001 0.531 0.823 1.201

46416 8514560 Port Jefferson, 

NY 40.95 −73.08 2.181 0.527 2.5 1983–2001 0.587 0.865 1.257

46416 8516945 Kings Point, NY 40.81 −73.76 2.378 0.638 2.5 1983–

2001 0.597 0.873 1.267

46415 8518750 The Battery, NY 40.70 −74.01 1.542 0.546 3.1 1983–

2001 0.562 0.846 1.232

46415 8519483 Bergen Point, 

NY 40.64 −74.14 1.681 0.549 4.4 1983–2001 0.567 0.850 1.237

46415 8531680 Sandy Hook, NJ 40.47 −74.01 1.593 0.552 2.7 1983–

2001 0.564 0.848 1.234

46056 8534720 Atlantic City, NJ 39.36 −74.42 1.403 0.534 4.1 1983–

2001 0.556 0.842 1.226

45697 8536110 Cape May, NJ 38.97 −74.96 1.659 0.486 4.7 1983–

2001 0.566 0.850 1.236

46055 8537121 Ship John 

Shoal, NJ 39.31 −75.38 1.894 0.578 3.5 1983–2001 0.576 0.857 1.246

46055 8540433 Marcus Hook, 

PA 39.81 −75.41 1.871 0.563 3.5 1983–2001 0.575 0.856 1.245

46055 8545240 Philadelphia, 

PA 39.93 −75.14 2.039 0.462 3.1 1983–2001 0.582 0.861 1.252

46055 8551762 Delaware City, 

DE 39.58 −75.59 1.830 0.540 3.5 1983–2001 0.573 0.855 1.243

46055 8551910 Reedy Point, DE 39.56 −75.57 1.779 0.423 4.1 1983–

2001 0.571 0.853 1.241

45696 8555889 Brandywine 

Shoal, DE 38.99 −75.11 1.676 0.616 3.5 1983–2001 0.567 0.850 1.237

45696 8557380 Lewes, DE 38.78 −75.12 1.418 0.530 3.5 1983–

2001 0.557 0.843 1.227

45696 8570280 Ocean City, MD 38.33 −75.08 1.187 0.413 3.5 1983–

2001 0.547 0.836 1.217

45696 8570283 Ocean City 

Inlet, MD 38.33 −75.09 0.751 0.360 3.5 1983–2001 0.530 0.823 1.200

45695 8571421 Bishops Head, 

MD 38.22 −76.04 0.624 0.503 3.5 1983–2001 0.525 0.819 1.195
Global and Regional Sea Level Rise Scenarios for the United States | 79

Table A1.3 (cont.): Regional designation, tide gauge information, extreme water level metadata, and high tide flood heights.

US 

Region

EWL 

Grid 

No.

NOAA ID Location Latitude Longitude

Tide 

Range 

(m)

Flood 

Index 

u (m, 

MHHW)

u Trend 

(mm/yr)

Epoch 

of u

Minor 

Flood (m, 

MHHW)

Moderate 

Flood (m)

Major 

Flood 

(m)

NE

(cont.) 45695 8571892 Cambridge, MD 38.57 −76.07 0.622 0.414 4.9 1983–2001 0.525 0.819 1.195

46054 8573364 Tolchester 

Beach, MD 39.21 −76.25 0.527 0.484 2.5 1983–2001 0.519 0.814 1.189

46055 8573927 Chesapeake 

City, MD 39.53 −75.81 0.980 0.470 3.8 1983–2001 0.539 0.829 1.209

46054 8574070 Havre De 

Grace, MD 39.54 −76.09 0.746 0.482 3.5 1983–2001 0.530 0.822 1.200

46054 8574680 Baltimore, MD 39.27 −76.58 0.506 0.443 3.2 1983–

2001 0.520 0.815 1.190

45695 8575512 Annapolis, MD 38.98 −76.48 0.438 0.430 3.7 1983–

2001 0.518 0.813 1.188

45695 8577330 Solomons 

Island, MD 38.32 −76.45 0.449 0.398 6.0 1983–2001 0.518 0.813 1.188

45694 8594900 Washington, DC 38.87 −77.02 0.965 0.461 3.3 1983–

2001 0.539 0.829 1.209

45337 8631044 Wachapreague, 

VA 37.61 −75.69 1.376 0.508 5.4 1983–2001 0.564 0.850 1.234

45337 8632200 Kiptopeke, VA 37.17 −75.99 0.896 0.435 4.7 1983–

2001 0.536 0.827 1.206

45695 8635150 Colonial Beach, 

VA 38.25 −76.96 0.591 0.406 4.7 1983–2001 0.524 0.818 1.194

45336 8635750 Lewisetta, VA 38.00 −76.46 0.458 0.420 5.6 1983–

2001 0.518 0.814 1.188

45336 8636580 Windmill Point, 

VA 37.62 −76.29 0.424 0.419 5.2 1983–2001 0.532 0.828 1.202

45336 8637689 Yorktown, VA 37.23 −76.48 0.786 0.567 3.5 1983–

2001 0.531 0.824 1.201

44977 8638610 Sewells Point, 

VA 36.95 −76.33 0.841 0.502 4.6 1983–2001 0.534 0.825 1.204

44977 8638863 CBBT, VA 36.97 −76.11 0.885 0.503 6.0 1983–

2001 0.535 0.827 1.205

44977 8639348 Money Point, 

VA 36.78 −76.30 0.977 0.528 5.6 1983–2001 0.539 0.829 1.209
Global and Regional Sea Level Rise Scenarios for the United States | 80

Table A1.3 (cont.): Regional designation, tide gauge information, extreme water level metadata, and high tide flood heights.

US 

Region

EWL 

Grid 

No.

NOAA ID Location Latitude Longitude

Tide 

Range 

(m)

Flood 

Index 

u (m, 

MHHW)

u Trend 

(mm/yr)

Epoch 

of u

Minor 

Flood (m, 

MHHW)

Moderate 

Flood (m)

Major 

Flood 

(m)

SE 44978 8651370 Duck, NC 36.18 −75.75 1.124 0.494 4.6 1983–

2001 0.545 0.834 1.215

44619 8652587 Oregon Inlet, 

NC 35.80 −75.55 0.360 0.384 4.6 1983–2001 0.514 0.811 1.184

44619 8654400 Cape Hatteras, 

NC 35.22 −75.64 1.056 0.412 3.2 1983–2001 0.542 0.832 1.212

44619 8654467 USCG Hatteras, 

NC 35.21 −75.70 0.186 0.598 3.2 1983–2001 0.507 0.806 1.177

44259 8656483 Beaufort, NC 34.72 −76.67 1.079 0.362 3.8 1983–

2001 0.543 0.832 1.213

44258 8658120 Wilmington, NC 34.23 −77.95 1.427 0.327 2.3 1983–

2001 0.557 0.843 1.227

44258 8658163 Wrightsville 

Beach, NC 34.21 −77.79 1.366 0.564 3.2 1983–2001 0.555 0.841 1.225

43898 8661070 Springmaid 

Pier, SC 33.66 −78.92 1.707 0.493 2.9 1983–2001 0.568 0.851 1.238

43897 8662245 Oyster Landing, 

SC 33.35 −79.19 1.561 0.496 3.2 1983–2001 0.562 0.847 1.232

43538 8665530 Charleston, SC 32.78 −79.93 1.757 0.453 3.3 1983–

2001 0.570 0.853 1.240

43537 8670870 Fort Pulaski, GA 32.03 −80.90 2.287 0.500 3.3 1983–

2001 0.591 0.869 1.261

42818 8720030 Fernandina 

Beach, FL 30.67 −81.47 1.999 0.473 2.3 1983–2001 0.580 0.860 1.250

42818 8720218 Mayport, FL 30.40 −81.43 1.508 0.378 2.6 1983–

2001 0.557 0.842 1.227

42818 8720357 St Johns River, 

FL 30.19 −81.69 0.312 0.333 3.2 1983–2001 0.512 0.809 1.182

42459 8720587 St. Augustine 

Beach, FL 29.86 −81.26 1.569 0.531 3.2 1983–2001 0.563 0.847 1.233

42101 8721604 Trident Pier, FL 28.42 −80.59 1.193 0.407 5.1 1983–

2001 0.537 0.825 1.207

41024 8723214 Virginia Key, FL 25.73 −80.16 0.667 0.317 5.1 1983–

2001 0.518 0.811 1.188

40664 8723970 Vaca Key, FL 24.71 −81.11 0.297 0.249 4.2 1983–

2001 0.512 0.809 1.182

40664 8724580 Key West, FL 24.56 −81.81 0.551 0.262 2.5 1983–

2001 0.522 0.817 1.192
Global and Regional Sea Level Rise Scenarios for the United States | 81

Table A1.3 (cont.): Regional designation, tide gauge information, extreme water level metadata, and high tide flood heights.

US 

Region

EWL 

Grid 

No.

NOAA ID Location Latitude Longitude

Tide 

Range 

(m)

Flood 

Index 

u (m, 

MHHW)

u Trend 

(mm/yr)

Epoch 

of u

Minor 

Flood (m, 

MHHW)

Moderate 

Flood (m)

Major 

Flood 

(m)

E. Gulf 41382 8725110 Naples, FL 26.13 −81.81 0.875 0.323 2.9 1983–

2001 0.535 0.826 1.205

41382 8725520 Fort Myers, FL 26.65 −81.87 0.401 0.325 3.1 1983–

2001 0.516 0.812 1.186

41740 8726384 Port Manatee, 

FL 27.64 −82.56 0.669 0.260 6.6 1983–2001 0.527 0.820 1.197

41740 8726520 St Petersburg, 

FL 27.76 −82.63 0.688 0.337 2.8 1983–2001 0.528 0.821 1.198

41740 8726607 Old Port 

Tampa, FL 27.86 −82.55 0.749 0.304 3.2 1983–2001 0.530 0.822 1.200

41740 8726667 Mckay Bay 

Entrance, FL 27.91 −82.43 0.814 0.320 3.2 1983–2001 0.533 0.824 1.203

41740 8726724 Clearwater 

Beach, FL 27.98 −82.83 0.841 0.294 7.1 1983–2001 0.540 0.831 1.210

42457 8727520 Cedar Key, FL 29.14 −83.03 1.157 0.415 2.2 1983–

2001 0.546 0.835 1.216

42456 8728690 Apalachicola, 

FL 29.73 −84.98 0.492 0.390 3.0 1983–2001 0.520 0.815 1.190

42814 8729108 Panama City, 

FL 30.15 −85.67 0.409 0.368 2.5 1983–2001 0.516 0.812 1.186

42814 8729210 Panama City 

Beach, FL 30.21 −85.88 0.420 0.348 4.3 1983–2001 0.517 0.813 1.187

42812 8729840 Pensacola, FL 30.40 −87.21 0.383 0.345 2.4 1983–

2001 0.515 0.811 1.185

42812 8732828 Mobile Bay, AL 30.42 −87.83 0.490 0.519 4.3 1983–

2001 0.520 0.815 1.190

42811 8735180 Dauphin Island, 

AL 30.25 −88.08 0.367 0.354 4.3 1983–2001 0.512 0.808 1.182

42811 8736897 Mobile, AL 30.65 −88.06 0.517 0.535 4.3 1983–

2001 0.521 0.816 1.191

42811 8737048 Mobile State 

Docks, AL 30.71 −88.04 0.501 0.439 4.3 1983–2001 0.520 0.815 1.190

42811 8741533 Pascagoula 

NOAA Lab, MS 30.37 −88.56 0.466 0.494 4.3 1983–2001 0.519 0.814 1.189

42810 8747437 Bay Waveland 

Yacht Club, MS 30.33 −89.33 0.529 0.498 4.6 1983–2001 0.522 0.816 1.192
Global and Regional Sea Level Rise Scenarios for the United States | 82

Table A1.3 (cont.): Regional designation, tide gauge information, extreme water level metadata, and high tide flood heights.

US 

Region

EWL 

Grid 

No.

NOAA ID Location Latitude Longitude

Tide 

Range 

(m)

Flood 

Index 

u (m, 

MHHW)

u Trend 

(mm/yr)

Epoch 

of u

Minor 

Flood (m, 

MHHW)

Moderate 

Flood (m)

Major 

Flood 

(m)

W. Gulf

42092 8760922

Pilots Station 

East, SW Pass, 

LA

28.93 −89.41 0.356 0.399 4.3 2012–

2016 0.514 0.811 1.184

42451 8761724 Grand Isle, LA 29.26 −89.96 0.323 0.309 7.8 2012–

2016 0.428 0.725 1.098

42809 8761927 New Canal 

Station, LA 30.03 −90.11 0.164 0.485 5.6 1983–2001 0.507 0.805 1.177

42450 8762075 Port Fourchon, 

LA 29.11 −90.20 0.368 0.298 4.3 2012–2016 0.515 0.811 1.185

42449 8764227 Amerada Pass, 

LA 29.45 −91.34 0.487 0.535 4.3 1983–2001 0.519 0.815 1.189

42449 8765251 Cypremort 

Point, LA 29.71 −91.88 0.518 0.458 4.3 1983–2001 0.521 0.816 1.191

42448 8766072 Freshwater 

Canal Locks, LA 29.56 −92.31 0.657 0.696 4.3 1983–2001 0.526 0.820 1.196

42806 8767816 Lake Charles, 

LA 30.22 −93.22 0.427 0.494 4.3 1983–2001 0.517 0.813 1.187

42447 8768094 Calcasieu Pass, 

LA 29.77 −93.34 0.589 0.465 6.1 1983–2001 0.524 0.818 1.194

42447 8770570 Sabine Pass 

North, TX 29.73 −93.87 0.488 0.368 6.1 1983–2001 0.520 0.815 1.190

42446 8770613 Morgans Point, 

TX 29.68 −94.99 0.398 0.488 3.1 1983–2001 0.535 0.831 1.205

42446 8771013 Eagle Point, TX 29.48 −94.92 0.338 0.331 13.8 1983–

2001 0.494 0.790 1.164

42446 8771341 Galveston Bay 

Entrance, TX 29.36 −94.72 0.510 0.499 6.1 1983–2001 0.520 0.815 1.190

42446 8771450 Galveston Pier 

21, TX 29.31 −94.79 0.429 0.366 6.5 1983–2001 0.517 0.813 1.187

42446 8771510

Galveston 

Pleasure Pier, 

TX

29.29 −94.79 0.622 0.425 6.5 1983–

2001 0.525 0.819 1.195

42086 8772440 Freeport, TX 28.95 −95.31 0.536 0.391 9.0 1983–

2001 0.521 0.816 1.191

42086 8772447 USCG Freeport, 

TX 28.94 −95.30 0.549 0.460 6.1 1983–2001 0.522 0.816 1.192

42084 8774770 Rockport, TX 28.02 −97.05 0.111 0.336 5.7 2002–

2006 0.504 0.803 1.174

41725 8775870 Corpus Christi, 

TX 27.58 −97.22 0.497 0.391 4.8 1983–2001 0.529 0.824 1.199

41366 8779770 Port Isabel, TX 26.06 −97.22 0.418 0.337 4.0 1983–

2001 0.517 0.813 1.187
Global and Regional Sea Level Rise Scenarios for the United States | 83

Table A1.3 (cont.): Regional designation, tide gauge information, extreme water level metadata, and high tide flood heights.

US 

Region

EWL 

Grid 

No.

NOAA ID Location Latitude Longitude

Tide 

Range 

(m)

Flood 

Index 

u (m, 

MHHW)

u Trend 

(mm/yr)

Epoch 

of u

Minor 

Flood (m, 

MHHW)

Moderate 

Flood (m)

Major 

Flood 

(m)

SW 43500 9410170 San Diego, CA 32.71 −117.17 1.745 0.490 2.2 1983–

2001 0.570 0.852 1.240

43500 9410230 La Jolla, CA 32.87 −117.26 1.624 0.468 2.1 1983–

2001 0.565 0.849 1.235

43858 9410660 Los Angeles, 

CA 33.72 −118.27 1.674 0.472 1.0 1983–2001 0.567 0.850 1.237

44217 9410840 Santa Monica, 

CA 34.01 −118.50 1.654 0.489 1.8 1983–2001 0.566 0.850 1.236

44216 9411340 Santa Barbara, 

CA 34.41 −119.69 1.645 0.485 0.6 1983–2001 0.566 0.849 1.236

44574 9412110 Port San Luis, 

CA 35.18 −120.76 1.623 0.449 1.0 1983–2001 0.565 0.849 1.235

44932 9413450 Monterey, CA 36.61 −121.89 1.627 0.431 1.6 1983–

2001 0.565 0.849 1.235

45290 9414290 San Francisco, 

CA 37.81 −122.47 1.780 0.375 1.9 1983–2001 0.571 0.853 1.241

45290 9414523 Redwood City, 

CA 37.51 −122.21 2.501 0.400 2.7 1983–2001 0.600 0.875 1.270

45290 9414750 Alameda, CA 37.77 −122.30 2.010 0.411 0.4 1983–

2001 0.580 0.860 1.250

45290 9414863 Richmond, CA 37.93 −122.40 1.846 0.359 3.1 1983–

2001 0.574 0.855 1.244

45290 9415020 Point Reyes, CA 38.00 −122.98 1.758 0.447 2.1 1983–

2001 0.570 0.853 1.240

45649 9415144 Port Chicago, 

CA 38.06 −122.04 1.498 0.388 1.4 1983–2001 0.560 0.845 1.230

45648 9416841 Arena Cove, CA 38.91 −123.71 1.787 0.500 0.6 1983–

2001 0.573 0.856 1.243

46365 9418767 North Spit, CA 40.77 −124.22 2.090 0.491 4.8 1983–

2001 0.584 0.863 1.254

46724 9419750 Crescent City, 

CA 41.75 −124.18 2.095 0.548 -0.8 1983–2001 0.584 0.863 1.254

47083 9431647 Port Orford, OR 42.74 −124.50 2.220 0.594 0.2 1983–

2001 0.572 0.850 1.242

47442 9432780 Charleston, OR 43.35 −124.32 2.323 0.586 1.1 1983–

2001 0.593 0.870 1.263

47801 9435380 South Beach, 

OR 44.63 −124.04 2.543 0.579 1.7 1983–2001 0.602 0.876 1.272

48161 9437540 Garibaldi, OR 45.55 −123.92 2.536 0.597 2.4 1983–

2001 0.601 0.876 1.271

48520 9439040 Astoria, OR 46.21 −123.77 2.624 0.629 −0.2 1983–

2001 0.605 0.879 1.275
Global and Regional Sea Level Rise Scenarios for the United States | 84

Table A1.3 (cont.): Regional designation, tide gauge information, extreme water level metadata, and high tide flood heights.

US 

Region

EWL 

Grid 

No.

NOAA ID Location Latitude Longitude

Tide 

Range 

(m)

Flood 

Index 

u (m, 

MHHW)

u Trend 

(mm/yr)

Epoch 

of u

Minor 

Flood (m, 

MHHW)

Moderate 

Flood (m)

Major 

Flood 

(m)

NW 48520 9440910 Toke Point, WA 46.71 −123.97 2.720 0.807 0.6 1983–

2001 0.609 0.882 1.279

48519 9441102 Westport, WA 46.90 −124.11 2.786 0.670 1.9 1983–

2001 0.611 0.884 1.281

48878 9442396 La Push, WA 47.91 −124.64 2.577 0.766 1.9 1983–

2001 0.603 0.877 1.273

49237 9443090 Neah Bay, WA 48.37 −124.61 2.425 0.688 −1.7 1983–

2001 0.597 0.873 1.267

49238 9444090 Port Angeles, 

WA 48.13 −123.44 2.153 0.562 0.2 1983–2001 0.586 0.865 1.256

49239 9444900 Port Townsend, 

WA 48.11 −122.76 2.597 0.538 1.7 1983–2001 0.604 0.878 1.274

48880 9446484 Tacoma, WA 47.27 −122.41 3.595 0.517 3.4 1983–

2001 0.644 0.908 1.314

48880 9447130 Seattle, WA 47.60 −122.34 3.462 0.541 2.1 1983–

2001 0.639 0.904 1.309

49239 9449424 Cherry Point, 

WA 48.86 −122.76 2.788 0.585 0.4 1983–2001 0.612 0.884 1.282

49238 9449880 Friday Harbor, 

WA 48.55 −123.01 2.364 0.554 1.2 1983–2001 0.595 0.871 1.265

Alaska 51743 9450460 Ketchikan, AK 55.33 −131.63 4.708 1.086 −0.4 1983–

2001 2.059 2.359 2.759

52099 9451054 Port Alexander, 

AK 56.25 −134.65 3.329 0.738 −5.8 1983–2001 1.031 1.331 1.731

52457 9451600 Sitka, AK 57.05 −135.34 3.029 0.768 −2.4 1983–

2001 0.883 1.183 1.583

52817 9452210 Juneau, AK 58.30 −134.41 4.970 1.152 −15.1 2012–

2016 2.319 2.619 3.019

53175 9452400 Skagway, AK 59.45 −135.33 5.100 1.218 −19.9 2012–

2016 2.456 2.756 3.156

52815 9452634 Elfin Cove, AK 58.19 −136.35 3.360 1.149 −5.8 1983–

2001 1.048 1.348 1.748

53171 9453220 Yakutat, 

Yakutat Bay, AK 59.55 −139.73 3.070 0.891 −10.7 2012–2016 0.902 1.202 1.602

53524 9454050 Cordova, AK 60.56 −145.75 3.838 0.937 0.8 1983–

2001 1.344 1.644 2.044

53882 9454240 Valdez, AK 61.13 −146.36 3.702 0.878 −5.8 1983–

2001 1.253 1.553 1.953

53520 9455090 Seward, AK 60.12 −149.43 3.238 0.884 −4.0 1983–

2001 0.983 1.283 1.683

53159 9455500 Seldovia, AK 59.44 −151.72 5.499 1.350 −9.8 2012–

2016 2.906 3.206 3.606

53518 9455760 Nikiski, AK 60.68 −151.40 6.262 1.254 −9.9 2012–

2016 NaN NaN NaN

53879 9455920 Anchorage, AK 61.24 −149.89 8.889 1.269 −2.7 1983–

2001 NaN NaN NaN

52440 9457292 Kodiak Island, 

AK 57.73 −152.51 2.675 0.715 −9.2 2012–2016 0.743 1.043 1.443
Global and Regional Sea Level Rise Scenarios for the United States | 85

Table A1.3 (cont.): Regional designation, tide gauge information, extreme water level metadata, and high tide flood heights.

US 

Region

EWL 

Grid 

No.

NOAA ID Location Latitude Longitude

Tide 

Range 

(m)

Flood 

Index 

u (m, 

MHHW)

u Trend 

(mm/yr)

Epoch 

of u

Minor 

Flood (m, 

MHHW)

Moderate 

Flood (m)

Major 

Flood 

(m)

Alaska 

(cont.) 52079 9457804 Alitak, AK 56.90 −154.25 3.578 0.908 −5.8 2012–2016 1.174 1.474 1.874

51714 9459450 Sand Point, AK 55.34 −160.50 2.204 0.737 1.4 1983–

2001 0.615 0.915 1.315

51712 9459881 King Cove, AK 55.06 −162.33 2.082 0.753 −5.8 1983–

2001 0.592 0.892 1.292

50262 9461380 Adak Island, AK 51.86 −176.63 1.131 NaN NaN NaN 0.572 0.872 1.272

50623 9461710 Atka, AK 52.23 −174.17 1.041 0.424 −5.8 1983–

2001 0.584 0.884 1.284

50629 9462450 Nikolski, AK 52.94 −168.87 1.213 0.537 −5.8 1983–

2001 0.563 0.863 1.263

50990 9462620 Unalaska, AK 53.88 −166.54 1.098 NaN NaN NaN 0.576 0.876 1.276

51714 9463502 Port Moller, AK 55.99 −160.57 3.175 0.697 −5.8 1983–

2001 0.952 1.252 1.652

52422 9464212 Village Cove, 

AK 57.13 −170.29 1.005 NaN NaN NaN 0.589 0.889 1.289

54940 9468756 Nome, AK 64.50 −165.43 0.464 NaN NaN NaN 0.719 1.019 1.419

56018 9491094 Red Dog Dock, 

AK 67.58 −164.07 0.269 NaN NaN NaN 0.787 1.087 1.487

57111 9497645 Prudhoe Bay, 

AK 70.40 −148.53 0.214 NaN NaN NaN 0.808 1.108 1.508

Carib 38168 9751364 St. Croix, VI 17.75 −64.71 0.226 0.205 2.4 1983–

2001 0.509 0.807 1.179

38527 9751381 St. John, VI 18.32 −64.72 0.252 0.210 2.4 1983–

2001 0.510 0.808 1.180

38168 9751401 Lime Tree Bay, 

VI 17.69 −64.75 0.216 0.154 3.0 1983–2001 0.509 0.806 1.179

38527 9751639 Charlotte 

Amalie, VI 18.34 −64.92 0.240 0.172 2.3 1983–2001 0.510 0.807 1.180

38526 9752695 Vieques Island, 

PR 18.09 −65.47 0.225 0.190 2.4 1983–2001 0.509 0.807 1.179

38525 9755371 San Juan, PR 18.46 −66.12 0.481 0.191 2.4 1983–

2001 0.519 0.814 1.189

38165 9759110 Magueyes 

Island, PR 17.97 −67.05 0.204 0.157 1.9 1983–2001 0.508 0.806 1.178

38524 9759938 Mona Island, 

PR 18.09 −67.94 0.247 0.257 2.4 1983–2001 0.510 0.807 1.180
Global and Regional Sea Level Rise Scenarios for the United States | 86

Section A2: Methods Appendix: Extreme Water Levels and Alaska Coastal 

Flood Height 

A2.1: Data and Regional Frequency Analysis 

A regional frequency analysis (RFA) of NOAA tide gauges is used to estimate extreme water levels (EWLs) 

along U.S. coastlines at and away from tide gauges. The RFA method (Hosking and Wallis, 1997) is based 

on the assumption that similar physical forcing across a region will produce a similar frequency of events 

and a probability density up to a local index (u), which is a local scaling factor that captures response peculiarities (Dalrymple, 1960). An RFA uses regional sets of data that have been locally normalized by their 

respective local index with a statistical heterogeneity test (H value) to assess the extent that the data are 

sufficiently similar. Using statistical L-moments, heterogeneity is a measure of the variation between sites 

of a location’s summary distribution statistics and the amount of dispersion expected if the locations were 

indeed a homogeneous region (Hosking and Wallis, 1997). If H < 1, the region is considered acceptably 

homogeneous. If 1 ≤ H < 2, the region is considered possibly heterogeneous but acceptable for our study. If 

H ≥ 2, then the tide-gauge group is definitely heterogeneous and not suitable for analysis. Once the regional bounds are established whose data are acceptably homogeneous, the aggregated data are fit with an 

extreme value distribution.

This study uses hourly and “top ten” data from all NOAA tide gauges46 with at least 10 years of record (Figure A2.1). Water levels are put onto the mean higher high water (MHHW) tidal datum and detrended (the 

trend value is retained and shown in Table A1.3) relative to the midpoint of the current national datum tidal epoch (1983–2001), which is similar for NOAA EWL procedures using a single-gauge analysis (Zervas, 

2013; Extreme Water Levels47). From the datasets, daily highest water levels are picked and declustered at 

each tide gauge using a 4-day storm window to ensure event independence. The 98th percentile of the 

46 https://tidesandcurrents.noaa.gov/ 47 https://tidesandcurrents.noaa.gov/est/

Figure A2.1: NOAA tide gauges used in the regional frequency analysis to generate extreme water level probabilities for 

U.S. coastlines.
Global and Regional Sea Level Rise Scenarios for the United States | 87

declustered daily highest levels at each tide gauge is used as the local index (u) to normalize the data for the 

RFA process. 

To form regions, the tide-gauge data is aggregated across a 400 km radius, similar to methods of Hall et al. 

(2016) but from the midpoint of a continuous set of coastline-intersecting 1-degree grids instead of site-specific installations. A maximum of 10 and a minimum of 3 tide gauges are included for each grid. Next, the 

regional data are spatially declustered with an additional 4-day event (i.e., storm) window to ensure that only 

the maximum water level within a region is retained (keep only the highest peak water levels for a particular event). Then, the statistical heterogeneity measure is estimated to ensure that the grouped tide-gauge 

data are sufficiently homogeneous (H < 2). In some instances, when a region surrounding a grid centroid 

Figure A2.2: Example of data from grid number 46415 showing exceedances above each local index (u) relative to the 

1983–2001 mean higher high water (MHHW) tidal datum at a) Kings Point, New York; b) The Battery, New York; c) Bergen Point, 

New York; and d) Sandy Hook, New Jersey, which are e) aggregated into a single dataset and f) fit by a Generalized Pareto 

Distribution to form a return level interval curve for the grid.
Global and Regional Sea Level Rise Scenarios for the United States | 88

has H ≥ 2, tide gauges farthest away are sequentially dropped until homogeneity is achieved. In the end, 

all 1-degree grids along the contiguous United States (CONUS) had H < 2 (considered acceptably homogeneous) except a grid (number 48519) along the Northwest Pacific coastline, which, along with the Hawaiian 

and other U.S. Pacific Islands, uses the much larger physical-process regions identified and quantified in 

Sweet et al. (2020b). Grids along the Alaska coastline are fairly well resolved by the RFA except along the 

western and northern coasts.

An example is shown for grid number 46415, which is where the NOAA tide gauge at The Battery in New 

York City (NYC) is located (Figure A2.2). Four tide gauges are included in this grid (Kings Point, New York; 

The Battery, New York; Bergen Point, New York; and Sandy Hook, New Jersey [Figure A2.2a–d]), and their 

data are considered homogeneous (H value of 0.32). After the 4-day spatial filtering for events, each of the 

tide-gauge datasets is normalized by (divided by) its respective local index (u) value and aggregated as 

shown in Figure A2e.

A2.2: Gridded (Regional) Extreme Water Level Probabilities

With the tide gauges identified for each 1-degree grid, the aggregated and normalized datasets are fit with a 

Generalized Pareto Distribution (GPD; Coles, 2001). Using the penalized maximum likelihood method (Coles 

and Dixon, 1999; Frau et al., 2018; Sweet et al., 2020b), expected and 95% confidence interval (2.5th% and 

97.5th% levels) values are estimated for the gridded EWL probabilities and defined as:

1)

where G is the exceedance probability (P[Z > z]), λ is the probability of an individual (normalized) observation 

exceeding the local index (u), α is the scale parameter, and ξ is the shape parameter. It is assumed that the 

distribution of the number of exceedances per year follows a Poisson distribution and that the return level for 

an EWL of height (Z) is given by:

2)

where N is the average recurrence interval (referred to in this study as the average event frequency, which is 

the reciprocal value), ny is number of days per year (365.25), and λ is the average number of event exceedances per year (about 3 on average across all tide gauges in the study). To estimate EWLs with return levels 

with a 10 events/year frequency, we extrapolate the gridded GPD model with a logarithmic fit for return levels 

between the 0.5–3 events/year frequencies. A return level interval curve fit to the aggregated data (Figure 

A2.2e) for the grid where NYC is located is shown in Figure A2.2f.

A2.3: Localized Extreme Water Level Probabilities

When fitting a GPD to the RFA of aggregated tide-gauge data, the local EWL (EWLlocal) probabilities including 

the model of expected values and their 95% confidence interval at a particular location are given as

3)

where EWLgridded is the gridded return level for a particular coastal 1-degree grid and ulocal is the local index 

used in both the RFA and GPD processes. The value of u is a height (98th percentile of 4-day event filtered 

daily highest water level) above the local MHHW tidal datum for the current (1983–2001) national tidal datum epoch (NTDE) or for a modified 5-year epoch. The associated uncertainty of the EWLgridded estimated 

during the RFA is expressed as σgridded. When localized at a tide gauge used in the formulation of the grids 

(see Figure A1), u is assumed to have no uncertainty. However, just as the location parameters in generalized 

extreme value (GEV) have time-dependent characteristics (Menéndez and Woodworth, 2010), it is recognized 

that u would experience similar behavior, but that is not quantified in this study.
Global and Regional Sea Level Rise Scenarios for the United States | 89

In this RFA framework, it is possible to estimate EWLlocal from the EWLgridded probabilities (expected values and 

95% confidence interval) through the use of other sources of data. Specifically, the local indices needed to 

localize the EWLgridded values can either be 1) obtained from short-term tide-gauge data (or by targeted deployments) within a particular grid that is not included in the RFA formulation (<10 years; Figure A2.3) or 2) 

based on an underlying relationship between regional sets of local index (u) values and tide range available 

from, for example, NOAA VDatum.48 In both cases, we establish large U.S. coastal regions (note: these are 

slightly different than the regions discussed in Sections 2 and 3 of the report and shown in Figure A1.1) that 

encompass several 1-degree grids to quantify information needed to obtain local indices and/or estimate 

variance/uncertainties (e.g., RMSE). These alternative methods, which are discussed below, may be of interest to coastal communities that are not co-located to a tide gauge used in this study but have predictions 

of tide range or have access to or are planning temporary tide-gauge installations to establish tidal datums 

and/or EWLs.

A2.3.1: Local Index Estimates from Short-Term Installations

When other sets of tide/water level data are available, a local index can be directly estimated to obtain 

EWLlocal probabilities from the EWLgridded probabilities. The first step for using data that are not from NOAA 

would be to estimate a local MHHW tidal datum using, for example, NOAA’s online datum tool.49 Following 

Equation 3 above, there will be some uncertainty in the local index value that is dependent on record length 

(e.g., 1–10 years). To account for short-record uncertainty in the local indices (u), RMSE (1 standard error) is estimated for regional estimates of u for the tide gauges used in the RFA (see Figure A2.1). Root mean square 

error is estimated using a logarithmic fit over a 19-year record length (Figure A4). To compute the RMSE, the 

maximum absolute differences are computed between u derived over the entire record and for progressively longer consecutive record lengths between 2001 and 2019 at each tide gauge (e.g., 19 discrete 1-year 

48 https://vdatum.noaa.gov/ 49 https://access.co-ops.nos.noaa.gov/datumcalc/

Figure A2.3: Additional tide-gauge data available from NOAA that can be used to localize the 1-degree gridded set of regional 

frequency analysis-based extreme water level probabilities. See https://tidesandcurrents.noaa.gov/. 
Global and Regional Sea Level Rise Scenarios for the United States | 90

records; 18 consecutive 2-year records). The maximum (absolute) difference is used to account for interannual variability that can be significant (e.g., during phases of El Niño–Southern Oscillation [ENSO]). This difference is considered the error in estimating u for shorter records, and the average of the absolute differences 

across the regional set of tide gauges is considered the bias. The standard deviation of the absolute differences is also computed across all tide gauges, and an estimate of the RMSE is then computed as the square 

Figure A2.4: Root mean square error for regional estimates of flood indices (u) based on 1–19 years of consecutive data over 

the 2001–2019 period, based on regional sets of tide gauges used in this study. Note: these regions are not the same as those 

shown in Figure A1.1 and used to describe results in Sections 2 and 3 of the report.
Global and Regional Sea Level Rise Scenarios for the United States | 91

root of the sum of the square of the bias and the standard deviation (variance). The estimates for Hawaiian 

and U.S. Pacific Islands follow estimates of Sweet et al. (2020b). 

A2.3.2: Obtaining a Local Index from Tide Range Information

Another method to obtain an estimate of a local index (u) and its uncertainty is based on a dependency 

(correlation) that exists with tide range (great diurnal [GT]) along most coastal regions similar to findings of 

Merrifield et al. (2013). In essence, tide range (GT), which represents the spread between MHHW and mean 

lower low water (MLLW), partially quantifies the variance of the daily highest water level distribution and the 

height of the local index u. Figure A2.5 illustrates the regression-based relationships between tide range and 

u along U.S. coastal regions (these are the same regions used in Figure A2.4). All regressions are significant 

above the 90% significance level (p values < 0.1) and applicable for the 1983–2001 tidal epoch. For the Hawaiian and U.S. Pacific Islands, the Pacific-wide regression of Sweet et al. (2020b) is used.
Global and Regional Sea Level Rise Scenarios for the United States | 92

Figure A2.5: Tide range to local index (u) regressions with equations, goodness of fit (R2), and root mean squared error (RMSE) 

shown by regions. Note: all local indices (u) are relative to the 1983–2001 tidal datum epoch. In the equations, y represents the 

local index (u) and x represents tide range.
Global and Regional Sea Level Rise Scenarios for the United States | 93

A2.3.3: Uncertainties Using Alternative Methods to Estimate EWLlocalProbabilities 

When using either alternative method (tide range or short-record estimates) to obtain a local index (u), the 

uncertainty estimates of EWLlocal probabilities will include additional uncertainty in u (σu). Following methods 

of Sweet et al. (2020b), it can be shown that

4)

where μEWLgridded and μu are the expected values of the gridded return levels and the expected value of u, for 

example, estimated by the tide-range and u dependency (see Figure A2.5), respectively, σu

2 is the uncertainty inherent to any u-prediction relationship (e.g., RMSE). Thus, there is an additive uncertainty in u as estimated from this relationship, which would introduce additional uncertainty in estimates of EWLlocal.

A2.3.4: Adjusting Local Extreme Water Level Probabilities to Time Periods

To adjust the EWLlocal probabilities to a different sea level other than the current tidal epoch (e.g., from 1992 

to 2000 or 2005 so as to apply the sea level rise scenarios), RSL estimates using the trends inherent to the 

hourly data used to compute the local index (u) should be applied (Table A1.3) to the epoch-specific EWLlocal

probabilities themselves. For tide gauges used in the RFA analysis and with more than 20 years of data, 

the local u trend can be used; otherwise, a median regional trend as defined in Figures A2.4 and A2.5 can 

be used. Alternatively, the RSL offsets derived from the regional observational RSL data (Table A1.2) could 

be used with differences between methods considered insignificant. For example, to estimate probabilities 

for the year 2000, the EWLlocal probabilities values would be increased by an amount equal to the trend in 

u (or the median u trend value for the region) multiplied by 8 years (since 1992, which is the midpoint of the 

1983–2001 epoch). The same procedure should be followed to adjust EWLlocal probabilities for a given location estimated via the tide range regression (see Figure A5). In the case of a short-term estimate of u, similar 

procedures should be followed if local tidal datums have been computed and adjusted to the national tidal 

datum epoch (e.g., using the CO-OPS Tidal Analysis Datum Calculator50); in the case where no epoch can be 

established (see the CO-OPS Tidal Analysis Datum Calculator for guidance), then the measurements will be 

assumed to be referenced to the period of collection, and trend adjustment may be less straightforward.

A2.4: Alaska Coastal Flood Heights

To assess flood exposure, the coastal high tide flooding (HTF) heights of Sweet et al. (2018) are used for 

all U.S. coastlines outside of Alaska. Used in NOAA annual outlooks (e.g., Sweet et al., 2021; The State of 

High Tide Flooding and Annual Outlook51), these heights are a best-fit solution (regression) to the dozens of 

National Weather Service (NWS) emergency response warning thresholds established at many (but not all) 

NOAA tide gauges along the country’s coastline. The NWS thresholds are used to communicate expected 

or ongoing coastal flood hazards to the public (NOAA, 2020), but often their depth-severity thresholds vary 

according to specific features near the tide gauge that affect both the associated flood frequency and the 

degree of broader vulnerabilities. Along the Alaska coastline, we follow the methodologies of Sweet et al. 

(2020b), who used a slight modification to assess “damaging flood heights” for the Pacific Basin coastlines. 

Here, the Alaska flood heights are based on a quadratic regression model using only Pacific Coast NWS 

minor flood heights and considered for only tide ranges below 6 meters (Figure A2.6a). To obtain moderate 

and major flood heights for Alaska, 0.3 m and 0.7 m are added to the regression, which is approximately the 

median difference between these heights and those for minor flooding along CONUS (Sweet et al., 2018). 

With flood heights defined nationally, minor, moderate, and major HTF are defined as occurring when water 

levels reach or exceed heights of about (median values) 0.55 m, 0.85 m, and 1.2 m above MHHW, respectively, and linearly vary with tide range (Figures A2.6b–d).

50 https://access.co-ops.nos.noaa.gov/datumcalc/index.jsp 51 https://tidesandcurrents.noaa.gov/HighTideFlooding_AnnualOutlook.html
Global and Regional Sea Level Rise Scenarios for the United States | 94

Figure A2.6: a) Quadratic regression of U.S. West Coast minor flood heights of NOAA’s National Weather Service, following 

methods of Sweet et al. (2020b), to obtain a minor HTF definition for Alaska’s coastline. The NOAA flood heights for b) minor, c) 

moderate, and d) major HTF are shown relative to mean higher high water.