noaa National Oceanic and Atmospheric Administration

U.S. DEPARTMENT OF COMMERCE

National Ocean Service

Center for Operational Oceanographic Products and Services

NOAA Technical Report NOS CO-OPS 073

Sea Level Rise and Nuisance Flood Frequency 

Changes around the United States

City Dock in Annapolis, Maryland. Photo Credit: Amy McGovern. 

Silver Spring, Maryland

June 2014
Center for Operational Oceanographic Products and Services

National Ocean Service

National Oceanic and Atmospheric Administration

U.S. Department of Commerce

The National Ocean Service (NOS) Center for Operational Oceanographic Products and Services 

(CO-OPS) provides the National infrastructure, science, and technical expertise to collect and 

distribute observations and predictions of water levels and currents to ensure safe, efficient and 

environmentally sound maritime commerce. The Center provides the set of water level and tidal 

current products required to support NOS’ Strategic Plan mission requirements, and to assist in 

providing operational oceanographic data/products required by NOAA’s other Strategic Plan 

themes. For example, CO-OPS provides data and products required by the National Weather 

Service to meet its flood and tsunami warning responsibilities. The Center manages the National 

Water Level Observation Network (NWLON), a national network of Physical Oceanographic 

Real-Time Systems (PORTS®) in major U. S. harbors, and the National Current Observation 

Program consisting of current surveys in near shore and coastal areas utilizing bottom mounted 

platforms, subsurface buoys, horizontal sensors and quick response real time buoys. The Center 

establishes standards for the collection and processing of water level and current data; collects 

and documents user requirements which serve as the foundation for all resulting program 

activities; designs new and/or improved oceanographic observing systems; designs software to 

improve CO-OPS’ data processing capabilities; maintains and operates oceanographic observing 

systems; performs operational data analysis/quality control; and produces/disseminates 

oceanographic products.
U.S. DEPARTMENT OF COMMERCE

Penny Pritzker, Secretary

National Oceanic and Atmospheric Administration 

Dr. Kathryn Sullivan, NOAA Administrator and Under Secretary of 

Commerce for Oceans and Atmosphere

National Ocean Service

Dr. Holly Bamford, Assistant Administrator

Center for Operational Oceanographic Products and Services 

Richard Edwing, Director

NOAA Technical Report NOS CO-OPS 073

Sea Level Rise and Nuisance Flood 

Frequency Changes around the 

United States

William Sweet

Joseph Park

John Marra

Chris Zervas

Stephen Gill

June 2014
ii

NOTICE

Mention of a commercial company or product does not constitute an 

endorsement by NOAA. Use of information from this publication for 

publicity or advertising purposes concerning proprietary products 

or the tests of such products is not authorized. 
iii

TABLE OF CONTENTS

NOTICE......................................................................................................................................... ii

TABLE OF CONTENTS ............................................................................................................iii

LIST OF FIGURES ..................................................................................................................... iv

LIST OF TABLES ........................................................................................................................ v

EXECUTIVE SUMMARY ......................................................................................................... vi

INTRODUCTION......................................................................................................................... 1

DATA AND METHODS .............................................................................................................. 3

Cumulative Hours and Days with Nuisance Flooding ........................................................... 4

Current and 1950 Average Recurrence Interval of Daily Nuisance Flood Events ............. 6

Monthly Distribution of Nuisance Floods and Related Physical Forcing Processes................ 7

FINDINGS..................................................................................................................................... 9

Historical SLRrel and Changing Frequencies of Nuisance Flood Events............................. 9

U.S. Northeast (NE) Coast. ................................................................................................. 10

U.S. Southeast (SE) Atlantic Coast. ................................................................................... 12

U.S. Gulf Coast. ................................................................................................................... 13

U.S. West Coast.................................................................................................................... 14

Historical SLRrel and Changing Nuisance Flood Event Probabilities................................ 15

Patterns Associated with Year-to-Year Differences in Nuisance Flood Frequency.......... 16

Seasonal Pattern of Nuisance Flood Events and Underlying Processes............................. 18

CONCLUDING REMARKS ..................................................................................................... 23

RECOMMENDATIONS............................................................................................................ 27

ACKNOWLEDGEMENTS ....................................................................................................... 27

REFERENCES............................................................................................................................ 29

APPENDIX 1............................................................................................................................... 33

APPENDIX 2............................................................................................................................... 35

ACRONYMS............................................................................................................................... 58
iv

LIST OF FIGURES

Figure 1. NOAA water level gauges used in this study and corresponding nuisance flood level...................3

Figure 2. (a) Average number of nuisance flood days between years 2007-2009 (meteorological years) that 

are correlated in (b) with the nuisance flood level elevation threshold by linear regression for 

the U.S. East Coast (NE and SE regions) gauges..........................................................................9

Figure 3. Hourly water level observations at the NOAA gauge at Sewells Point (Norfolk), Virginia for (a) 

1950 and (b) 2012 and their (c) yearly water level distribution plotted with the nuisance flood 

level elevation threshold. All figures are plotted relative to 1980-2001 MSL datum and reveal in 

(a) and (b) a monthly spring-tide influence and a few discrete storm events. Readily apparent in 

c) is the increase in MSL (change of distribution center relative to “0,” which is the 1983-2001 

epoch MSL datum elevation) between 1950 and 2012. .............................................................. 10

Figure 4. (a) Northeast U.S. coastal topography at or below nuisance flood level elevations (image from 

“Flood Frequency” tab of NOAA Sea Level Viewer with NOAA gauges (green) used in this 

study). Shown in (b) are days per year (color bar not the same scale as “Days per Year” axis) 

with nuisance flooding at 23 gauges from Massachusetts to Virginia and (c) specifically at 

Atlantic City, New Jersey (gauge 10) plotted with annual average MSL. In (d) is a scatter plot 

of nuisance flood days at Atlantic City, New Jersey fitted with a quadratic curve starting in year 

1950............................................................................................................................................. 11

Figure 5. As in Figure 4, but for the Southeast U.S. coastline that includes 7 NOAA gauges (24-31) 

between North Carolina and the Atlantic coast of Florida. Nuisance flood events are shown for 

Charleston, South Carolina (gauge 28) in (c) and (d). ................................................................ 13

Figure 6. As in Figure 4, but for Gulf Coast that includes 8 NOAA gauges (32-39) between Florida and 

Texas. Nuisance flood events are shown for Naples, Florida (gauge 33) in (c) and (d). Note, 

Louisiana has not yet been mapped by the Sea Level Viewer and shown with cross-hashes..... 14

Figure 7. As in Figure 4, but for U.S. Pacific coastline that includes 5 NOAA gauges (40-44) between 

California and Washington and gauge 45 at Honolulu, Hawaii (not shown in (a)). Nuisance 

flood events are shown for La Jolla, California (gauge 40) in (c) where the number of days per 

year with nuisance flooding is best fit by linear regression. ....................................................... 15

Figure 8. Return Periods of nuisance level flood events in (a) 1950 and (b) 2012 at NOAA gauges........... 16

Figure 9. The Oceanic Niño Index (ONI) plotted with (a) monthly MSL (black line) from San Francisco, 

California that has been smoothed by a 5-month running filter and (b) annual counts of daily 

average nontidal residual (NTR; green bars) > 0.3 m at Sewells Point, Virginia. ...................... 18

Figure 10. Season with highest frequency of nuisance flood days over the 1980-2009 period as shown for 

each NOAA gauge in Appendix 2............................................................................................... 19

Figure 11. Maximum observed water levels per calendar day over the 1980-2009 period decomposed into a 

low-frequency MSL cycle, predicted tide (without the annual and semi-annual harmonic fits) 

and remaining nontidal residual (NTR) all smoothed by a 30-day running filter shown for (a) 

the Battery, New York, (b) Mayport, Florida, (c) San Francisco, California and (d) Port Isabel, 

Texas. All series are relative to their station MSL datum and plotted with the nuisance flood 
v

level (yellow-magenta line) and MHHW datum elevation (black dot-dash). In the bottom plots, 

the number of nuisance flood hours and days (shared y-axis) are averaged by calendar month 

between 1980 and 2009............................................................................................................... 20

Figure 12. (a) Monthly mean volume transport of the Florida and Yucatan Currents over the 2000-2009 

with their means in parenthesis that reveal a geostrophic-related inverse relationship to MSL 

cycle at Mayport, Florida and Port Isabel, Texas, respectively. In (b) are hourly astronomic tide 

predictions for San Francisco, California showing semi-annual spring tide strengthening during 

the winter and summer solstice time frames, which reach the nuisance flood level. ................. 21

Figure 13. Calendar-day maxima over 1980-2009 (i.e., as shown in top plots of Figure 11a-d) are averaged 

to estimate (a) a ratio between the average of the NTR during (divided by) maximum water 

level and (b) the distance between the NOAA gauge’s nuisance flood level and the average 

tidal contribution during maximum water level. ........................................................................ 22

Figure 14. Bubble plot of nuisance flood level (x-axis) versus quadratic constant (b2; y-axis) from fit of 

annual number of nuisance flood days listed in Appendix 1 for East Coast (NE region in red 

and SE region in blue) gauges. Bubble size represents the goodness-of-fit (R2) of each quadratic 

model fit. Only gauges with significant quadratic fits and hourly data starting prior to 1960 

(Appendix 1) are included to minimize quadratic curve-fitting discrepancies due to gauge 

record length............................................................................................................................... 24

LIST OF TABLES

Table 1. NOAA water level gauges, location, start of analysis, MSL trend, and nuisance flood level (m)...........5
vi 

EXECUTIVE SUMMARY

The National Oceanic and Atmospheric Administration (NOAA) water level (tide) gauges have 

been measuring water levels around the U.S. for over a century, providing clear evidence of sea 

level rise relative to land (SLRrel) around most of the continental United States and Hawaii. As 

SLRrel increases mean sea level (MSL), there is naturally an increase in tidal datum elevations, 

which are typically used to delineate inundation thresholds. Direct consequences of rising sea 

level against fixed elevations such as today’s built infrastructure also include increased 

inundation during extreme events both spatially and temporally. Not only are extreme flooding 

events reaching higher grounds and covering larger areas due to SLRrel, the frequency and 

duration of these extreme flood events are increasing. 

Another consequence of SLRrel is the increase in lesser extremes such as occasional minor 

coastal flooding experienced during high tide. These events are becoming more noticeable and 

widespread along many U.S. coastal regions and are today becoming more of a nuisance. As sea 

levels continue to rise and with an anticipated acceleration in the rate of rise from ocean warming 

and land-ice melt, concern exists as to when more substantive impacts from tidal flooding of 

greater frequency and duration will regularly occur. Information quantifying these occurrences to 

inform mitigation and adaptation efforts and decision makers is not widely available. 

In this report, we show that water level exceedances above the elevation threshold for “minor” 

coastal flooding (nuisance level) impacts established locally by the National Weather Service 

(NWS) have been increasing in time. More importantly, we document that event frequencies are 

accelerating at many U.S. East and Gulf Coast gauges, and many other locations will soon follow 

regardless of whether there is an acceleration of SLRrel. Lastly, we show a regional pattern of 

increasingly greater event-rate acceleration as the height between MSL and a location’s nuisance 

flood threshold elevation decreases. 

Impacts from recurrent coastal flooding include overwhelmed stormwater drainage capacity, 

frequent road closures, and general deterioration and corrosion of infrastructure not designed to 

withstand frequent inundation or salt-water exposure. From this, we conclude that there is a time 

horizon, largely dependent upon the local rate of SLRrel, when critical elevation thresholds for 

various public/private/commercial serving systems will become increasingly compromised by 

tidal flooding. This concept of a non-linear impact trajectory needs to recognized, as it is critical 

for coastal planning to prevent degradation to society-serving systems at risk from SLRrel. The 

goal of this report is to heighten awareness of a growing problem of more frequent nuisance 

coastal flooding respective to a community’s living memory and to encourage resiliency efforts 

in response to impacts from SLRrel. 
1

INTRODUCTION

Thermal expansion of the world’s oceans and melting of glaciers and ice sheets from climate 

warming has contributed to global sea level rise (SLR) of approximately 1.7 mm/yr over the last 

century (Church and White, 2011) and even higher rates (3.2 mm/yr; Merrifield et al., 2013) over 

the last several decades. Superimposed upon this trend are ocean-atmosphere circulation 

dynamics producing significant regional interannual mean sea level (MSL) variability. This 

variability can be expressed as low-frequency multi-month MSL anomalies, as well as higherfrequency storminess changes in storm surge event frequency along the coast (Sweet and Zervas, 

2011; Thompson et al., 2013) from altered seasonal storm track tendencies (Hirsch et al., 2001). 

Regional variability is often coherent with climate forcings such as El Niño Southern Oscillation 

(ENSO) and the multi-decadal Pacific Decadal Oscillation (PDO) that, dependent upon their 

state, can also exacerbate (Merrifield et al., 2012) or suppress (Bromirski et al., 2011) long-term 

regional SLR rates. Vertical land motion also contributes to regional-to-local relative changes in 

long-term SLRrel rates respective to land (Zervas et al., 2013). The net effect for most of the 

United States is a SLRrel readily tracked by the U.S. National Oceanic and Atmospheric 

Administration (NOAA) National Water Level Observation Network (NWLON). NWLON is a 

nationwide monitoring program whose water level gauges have supported essential commercerelated activities for over a century, such as providing tide predictions and chart datums for safe 

navigation as well as boundary delineations for private property and federal and state economic 

zones. NWLON also provides potentially life-saving information in near real-time about extreme 

tropical and extratropical storm surges, tsunami warnings, and enhances coastal intelligence by 

establishing coastal-flood probabilities.

One consequence of SLRrel (http://tidesandcurrents.noaa.gov/sltrends) is an increase in tidal 

datum elevations (CO-OPS, 2001), such as Mean Higher High Water (MHHW), that define 

perennial inundation levels. A more societal-important consequence of SLRrel is the exacerbation 

of extreme flood event magnitudes and their frequencies from a perspective of fixed elevations 

(Hunter, 2010; Park et al., 2011; Tebaldi et al., 2012), such as those associated with private 

property and critical public-serving infrastructure and systems (e.g., transportation, energy 

generation and transmission, wastewater treatment, etc.). The increased probability occurs as a 

result of a lowered “freeboard” or gap between MSL and specific threshold flood elevations from 

SLRrel. This results in smaller storm surge magnitudes increasingly impacting similar levels as 

time progresses. This reality was recently highlighted by Superstorm Sandy’s impacts in October 

2012 along the U.S. Mid-Atlantic (Sweet et al., 2013). However, neither changes in tidal datum 

elevations nor rare-event probabilities are readily apparent to the casual observer. The former is 

generally too gradual for noticeable impacts, or incurs successional changes over generational 

time scales (CO-OPS, 2001), whereas the latter is obscured by the infrequency of the extremely 

rare event (e.g., direct hurricane strike).

In this report, we describe a more tangible impact of SLRrel as an increased frequency of minor 

(nuisance) tidal-related flooding, further refining the unbiased climate-change SLR indicator of 

Parker (1992). The increased frequency of nuisance tidal flooding along U.S. coastal regions is a 

growing problem with societal impacts (http://www.csc.noaa.gov/tidalfloodingvis/). We provide 

insight into patterns and trends associated with a nuisance-flood proxy derived from empirically 

calibrated levels at NWLON gauges, specifically the “minor” threshold elevation established by 

local Weather Forecasting Offices (WFO) of NOAA’s National Weather Service (NWS). 
2

Henceforth, we will refer to the NWS “minor” thresholds as a location’s nuisance flood level,

which have been historically associated with minor coastal flooding impacts. We note that not 

every exceedance above the nuisance flood level implies that noticeable or widespread flooding 

has occurred or will occur; though, when concurrent with localized rainfall or a wind-forced 

storm surge, impacts can become quite severe and more similar to the higher NWS-defined 

levels (i.e., moderate and major) recently analyzed by Kriebel and Geiman (2013). Rather, the 

nuisance flood level provides a measure of localized propensity for community-specific minor 

impacts based upon documented observations. Nuisance flood level thresholds and the land 

elevations susceptible to event inundation are displayed in the “Flood Frequency” tab of the 

NOAA Sea Level Viewer (http://csc.noaa.gov/slr/viewer/) with supporting discussion in Marcy 

et al. (2011). 

Three main questions are addressed in this report: 

1. How has historical SLRrel changed the:

 frequency and duration of nuisance flood events?

 probability of a nuisance flood event?

2. What climatic patterns are associated with year-to-year differences?

3. During what season do nuisance floods typically occur and why?
3

DATA AND METHODS

Hourly water levels, available from the Center for Operational Oceanographic Products and 

Services (CO-OPS) (http://tidesandcurrents.noaa.gov/), are utilized in this report to describe 

nuisance-related impacts. The hourly data and nuisance flood levels are relative to the latest 

National Tidal Datum Epoch (NTDE) which, in all but one instance (Galveston, Texas is a 1997-

2001 epoch), references the 1983-2001 period. The water level observations were further 

decomposed into an astronomical tide (prediction) and a nontidal residual (NTR) component, 

with the latter forming in response to ocean and atmospheric forcing. 

Though NOAA NWLON has 210 water level gauges in its network, with 52 gauges in the Great 

Lakes and 158 along the open coast, only about 75 of the open coast gauges have a minor coastal 

flooding elevation threshold (nuisance flood level) assigned to them by local NOAA NWS 

WFOs. Of these approximately 75 gauges, the majority are along the East and Gulf Coasts since 

these areas have the potential for larger storm surges than the West Coast, where wave impacts 

are more prevalent and whose effects are not generally captured (by design) by coastal water 

level gauges (Ruggiero, 2013). A total of 45 gauges are used in this report including Honolulu, 

Hawaii, whose nuisance flood level is defined and displayed (“high sea level forecasts” tab) by 

the Pacific Integrated Ocean Observing System (PacIOOS; http://oos.soest.hawaii.edu/pacioos) 

rather than the local NWS WFO. Inclusion criterion is based upon: 1) 30 years of verified hourly 

data and 2) sufficient exceedances above the nuisance flood level to produce discernable trends 

or patterns. Figure 1 shows the location and nuisance flood levels for the NOAA gauges used in 

the study. Table 1 provides the gauge name, position, range of data utilized, SLRrel trend for 

study period, and NWS minor (nuisance) coastal flood threshold elevations. 

Figure 1. NOAA water level gauges used in this study and corresponding nuisance flood level.

Since water level record lengths vary by gauge (Table 1), an arbitrary start date of January 1, 

1920 was chosen for the subsequent analysis. The 1920 start date truncates a few gauge records 

but ensures the majority of the other gauge record lengths are incorporated. The end date was 

2013. Multiple analyses were performed and are described below. In “Findings” section, 

regionally representative gauge results will be highlighted to better illustrate the methods. 
4

Cumulative Hours and Days with Nuisance Flooding 

Hourly water level exceedances above the nuisance flood level are used to quantify both duration 

and frequency of historical impacts experienced locally. Two measures are shown in this report: 

1) cumulative hours above the nuisance flood level elevation threshold during a year, and 2)

number of days affected by nuisance level flooding (e.g., one day could represent one hour or an 

entire 24-hour period above the nuisance flood level) during a year. Henceforth, these two 

measures will be referred to as nuisance flood “hours” and “days,” whereas when the term 

“event” is used, both measures are collectively being referenced, though one “day” would more 

closely approximate one “event.” It should be noted that all exceedances above the nuisance 

flood level are accounted for, even the most extreme whose impacts would be considered severe, 

not nuisance. The daily definition as compared to the hourly summation reduces the relative 

contribution of severe storms exceeding the threshold for numerous hours. In semi-diurnal tidal 

regions (i.e., two high and two low tides a day) where two separate exceedances may occur in a 

day, the event is not counted twice. In both cases, results are shown only when 80% of a year’s 

hourly data are available. In this presentation, a year is defined as a meteorological year as to not 

split the winter season, which tends to be the dominant storm season for much of the Northern 

Hemisphere in terms of atmospheric activity (e.g., Hirsch et al., 2001) and related storm surges 

(Sweet et al., 2011; Thompson et al., 2013). We define the meteorological year from May to 

April, e.g., May 2012–April 2013 is reported as year 2012. NOAA provides an inundation 

analysis tool allowing further frequency and duration investigation in context to this report’s 

procedures and findings (http://tidesandcurrents.noaa.gov/inundation). 
5

Table 1. NOAA water level gauges, location, start of analysis, MSL trend, and nuisance flood level (m)

NOAA Tide Gauge St. ID Longitude Latitude

Analysis Start 

(years)

MSL Trend 

(mm/yr)

Nuisance 

Flood Level 

(above MHHW)

1 Boston, MA 8443970 -71.052 42.355 1921 2.8 0.68

2 Providence, RI 8454000 -71.402 41.807 1938 2.26 0.66

3 New London, CT 8461490 -72.087 41.355 1938 2.57 0.60

4 Bridgeport, CT 8467150 -73.182 41.173 1970 2.87 0.48

5 Montauk, NY 8510560 -71.960 41.048 1947 3.2 0.60

6 Kings Point, NY 8516945 -73.765 40.810 1931 2.52 0.52

7 Battery, NY 8518750 -74.015 40.700 1920 3.15 0.50

8 Bergen Point, NY 8519483 -74.147 40.640 1981 4.93 0.52

9 Sandy Hook, NJ 8531680 -74.010 40.467 1922 4.08 0.45

10 Atlantic City, NJ 8534720 -74.418 39.355 1920 4.19 0.43

11 Cape May, NJ 8536110 -74.940 38.968 1965 4.61 0.38

12 Philadelphia, PA 8545240 -75.142 39.933 1920 3.09 0.49

13 Reedy Point, DE 8551910 -75.573 39.558 1979 3.67 0.42

14 Lewes, DE 8557380 -75.120 38.782 1920 3.46 0.41

15 Cambridge, MD 8571892 -76.068 38.573 1979 3.71 0.45

16 Baltimore, MD 8574680 -76.579 39.267 1920 3.25 0.41

17 Annapolis, MD 8575512 -76.482 38.983 1928 3.51 0.29

18 Washington D.C. 8594900 -77.022 38.873 1924 3.21 0.31

19 Wachapreague, VA 8631044 -75.687 37.607 1978 5.52 0.61

20 Kiptopeke, VA 8632200 -75.988 37.165 1976 3.57 0.48

21 Lewisetta, VA 8635750 -76.464 37.996 1970 5.59 0.46

22 Sewell Point, VA 8638610 -76.330 36.947 1927 4.58 0.53

23 Chesapeake Bay Bridge, VA 8638863 -76.113 36.967 1975 6.04 0.64

24 Duck, NC 8651370 -75.747 36.183 1978 4.58 0.55

25 Beaufort, NC 8656483 -76.670 34.720 1973 2.72 0.29

26 Wilmington, NC 8658120 -77.953 34.227 1935 2.02 0.25

27 Springmaid Pier, SC 8661070 -78.918 33.655 1977 3.62 0.58

28 Charleston, SC 8665530 -79.925 32.782 1921 3.11 0.38

29 Fort Pulaski, GA 8670870 -80.902 32.037 1935 3.01 0.46

30 Fernandina Beach, FL 8720030 -81.465 30.672 1920 2.21 0.59

31 Mayport, FL 8720218 -81.430 30.397 1928 2.43 0.44

32 Key West, FL 8724580 -81.808 24.553 1920 2.38 0.33

33 Naples, FL 8725110 -81.807 26.130 1965 2.34 0.35

34 Apalachicola, FL 8728690 -84.982 29.727 1976 1.77 0.42

35 Panama City, FL 8729108 -85.667 30.152 1973 1.57 0.35

36 Bay Waveland, MS 8747437 -89.325 30.325 1978 3.96 0.45

37 Sabine Pass, TX 8770570 -93.870 29.730 1981 5.49 0.58

38 Galveston, TX 8771510 -94.788 29.285 1957 6.61 0.60

39 Port Isabel, TX 8779770 -97.215 26.060 1944 3.79 0.34

40 La Jolla, CA 9410230 -117.257 32.867 1924 2.01 0.51

41 San Francisco, CA 9414290 -122.466 37.806 1920 2.00 0.35

42 Humboldt Bay, CA 9418767 -124.217 40.767 1977 3.93 0.56

43 Toke Point, WA 9440910 -123.967 46.707 1972 0.42 0.63

44 Seattle, WA 9447130 -122.339 47.603 1920 2.24 0.65

45 Honolulu, HI 1612340 -157.867 21.307 1920 1.24 0.22

To provide a physical basis for the trends in nuisance flood days, annual MSL values and their 

long-term trends are also shown. A yearly MSL value, which is an average of hourly water levels 
6

over a year, is not reported if the gauge’s hourly water level record is less than 80% for any 

particular year (as to synchronize with the yearly nuisance event statistics, Table 1). The annual 

MSL values are relative to the gauge’s current MSL datum such that the values range from 

negative to positive with the “zero” near the current epoch’s midpoint. Plotting relative to 

another tidal datum or epoch would have no effect on the magnitude of the SLRrel trend apparent 

in each gauge’s MSL values. The long-term SLRrel trends for each gauge are listed in Table 1 

and closely match those computed by Zervas (2009) and updated through 2012 at 

http://tidesandcurrents.noaa.gov/sltrends.

Current and 1950 Average Recurrence Interval of Daily Nuisance Flood Events

To quantify extreme events, extreme value statistics are employed to characterize the upper tail 

of a water level distribution. A common derived measure is the average recurrence interval, often 

termed return period, which is the inverse of the probability of exceeding a particular elevation 

threshold. A simple and effective method to quantify probabilities is the Annual Maximum 

Method (AMM), which fits a series of annual maximum water level with a Generalized Extreme 

Value (GEV) distribution. Zervas (2013) uses a GEV fit of annual maximum to quantify extreme 

characteristics at NOAA NWLON gauges (http://tidesandcurrents.noaa.gov/est). The main 

weakness of the AMM/GEV is that only one event per year is used, which ignores other 

significant events that occur during the same year and often leads to less robust results for gauges 

with shorter record lengths and higher frequency (<1 year) estimates of lesser extreme events.

In this report we use a Peak Over Threshold (POT)/Point Process approach, which utilizes 

multiple events per year to estimate the return periods for each gauge’s nuisance flood level 

(Coles, 2001). We use the 97th percentile (%) of daily maximum water levels as the high 

threshold (not the nuisance level threshold) to study statistical exceedance properties. 

Consecutive events are filtered by a three-day window to ensure independence resulting in 

approximately eight events per year on average. Similar criteria were used by Mendez et al. 

(2006) for wave data and for water level extremes throughout the Pacific region 

(http://www.pacificstormsclimatology.org) as discussed in Kruk et al. (2013). It is assumed that 

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

threshold excesses (y) are modeled using a Generalized Pareto Distribution (GPD) given by

(1) H(y,σ,ξ) = 1 – (1 +ξy/σ)−1/ξ ξ≠0 

H(y,σ,ξ) = 1 – exp(-y/σ) ξ=0

where σ > 0 is the GPD scale parameter and ξ is the shape parameter. The combination of the 

Poisson and GPD models are related to GEV parameters by σ= σ*+ ξ (u−μ) with μ the GEV

location parameter, u the high threshold and σ* the GEV scale parameter and the event rate, 

√=[(1+ ξ(u−μ)/ σ *]−1/ξ. The return level, yN, is given by Mendez et al. (2006) as

(2) yN = μ - σ */ξ [1-(-log(1-q)]-ξξ≠0

yN = μ - σ *log(-log(1-q)] ξ=0

where 1/q is the return period (years) with 0 < q < 1. The GEV location parameter represents the 

median, the scale parameter (both GEV and GPD) represents the spread, and the shape parameter 

represents the skew of the distribution. Parameters are estimated by the maximum likelihood 

method, and the 95% confidence intervals are estimated via the delta method (Rice, 1994). 
7

For the extreme value analysis, the water level data series are detrended by their local MSL trend 

(Table 1). Detrending normalizes the data respective to the current NTDE in order to compare 

events in time. To estimate current (2012) probabilities, the return level interval curves, which 

are valid for the mid-point (e.g., 1992) of the current epoch (e.g., 1983-2001), are raised to 2012 

MSL elevations (MSL trend multiplied by 20 years). For 1950 probabilities, a gauge’s return 

level interval curves are lowered to 1950 MSL (i.e., a height equal to its MSL trend × 42 years). 

Bottom left plots in Appendix 2 show the GPD Poisson model results for 2012 and 1950 and 

their elevation differences described here. Similar time-adjustment procedures and further 

method description is given by Sweet et al. (2013). The method is a quasi-nonstationary method 

that accounts for long-term SLRrel effects, but no other time-varying considerations (e.g., 

Menendez and Woodworth, 2010).

Monthly Distribution of Nuisance Floods and Related Physical Forcing Processes

The monthly mean distributions of the nuisance flood hours and days are shown for a recent 30-

year period (1980-2009). No attempt is made to discern whether or not seasonal-scale variability 

has been changing in time. In order to identify processes contributing to high water conditions, 

we decomposed the maximum daily water level into three components: 

 A low-frequency seasonal MSL cycle component, which is similar to the amplitudes and 

phases of the annual (Sa) and semi-annual (Ssa) harmonic constituents and the 12-month 

MSL cycle derived by Zervas (2009) 

 The predicted tide without the Sa and Ssa harmonic constituents included using T_tide 

analysis routines (Pawlowicz et al., 2002)

 The remaining NTR after the above components are removed

The maximum water level and its components are identified over the same 30-year period (e.g., 

1980-2009) and for each calendar day of the year (e.g., Jan 1, 2...Dec 31). For the maximum 

water level and its predicted tide and NTR components, a 30-day running mean filter (smoothed) 

has also been applied in order to highlight patterns rather than individual event influences (e.g., 

Figure 3-8 in Marra et al., 2012). Subsequently, component summation is not precisely additive 

due to the smoothing process. But, shown with respect to the nuisance flood level, the 

components provide a sense of process significance during high-water formation typical for 

nuisance flooding events. 
8
9

FINDINGS 

Historical SLRrel and Changing Frequencies of Nuisance Flood Events

A large spatial variability in the frequency of nuisance level flooding exists across the U.S.

Figure 2a shows the average number of nuisance flood days for a recent three-year period of 

2007-2009 (meteorological years: May 2007–April 2010), which corresponds to statistics shown 

on the NOAA Sea Level Viewer for a similar time period. It should be stressed that the elevation 

thresholds for minor nuisance flooding are location-specific elevations and derived empirically 

by NOAA National Weather Service (NWS) Weather Forecasting Offices (WFOs) for NOAA 

coastal water level gauges from local knowledge of impacts over time. Nuisance flood levels 

represent susceptibility to flooding inherent to the natural topography and hydrological 

conditions, as well as reflect any mitigation efforts of the human-altered environment (e.g., 

flood-defense and storm-water measures). Areas with higher values of nuisance flood days (>20 

days) are located along the Mid-Atlantic and in the Chesapeake Bay, the coasts of North and 

South Carolina, and southern Texas. Not surprisingly, a strong negative correlation (p<0.01) 

exists between a gauge’s number of nuisance flood days (2007-2009 mean) and its flood level 

elevation threshold, as shown in Figure 2b for the Northeast and Southeast regions (R2=0.73). 

The variance accounted for by the linear regression model is smaller (R2=0.50) when all gauges 

are included, which is a result of smaller tidal ranges (along the Gulf Coast) and lessened storm 

surge potential (along the West Coast) compared to the U.S. East Coast, which lessen a 

location’s annual occurrences of exceeding its nuisance flood level.

Figure 2. (a) Average number of nuisance flood days between years 2007-2009 (meteorological years) that are 

correlated in (b) with the nuisance flood level elevation threshold by linear regression for the U.S. East Coast 

(NE and SE regions) gauges.

The values shown in Figure 2 are not consistent in time. Rather, nuisance flooding has been 

increasing at NOAA gauges across the U.S. over the last century from increases in local MSL. 

Long-term changes in nuisance flood frequency occur because local SLRrel raises MSL and the 

entire distribution of both high- and low-water events affecting higher and higher elevations in 

time, as illustrated at Sewells Point, Virginia (Figure 3). Trends derived from linear regression 

on the annual number of nuisance flood days are statistically significant at the 90% level at 41 of 
10

the 45 gauges analyzed (Appendix 1). At the majority of the gauges analyzed (28 of 45 gauges),

the rate of change of nuisance flood days has been accelerating (significant at the 90% level) 

over the last half-century, whereas SLRrel rates have not necessarily been accelerating. Several

stations not showing significant acceleration have shorter record lengths (start in 1970s) and thus 

may be unable to distinguish an accelerating rate of change largely initiating in the 1970s-1980s

and observed at the other nearby gauges (e.g., Duck, North Carolina). The response becomes 

nonlinear as the water level distribution increasingly exceeds the nuisance flooding level 

elevation resulting in an accelerating increase of the annual number of event per year (increases 

in MSL result in an increasingly larger “area under the curve” that surpasses the threshold in 

Figure 3). In this regard, the acceleration observed (e.g., in Figures 4a, 5a, 6a) occurs in response 

to SLRrel and not from an increasing storminess trend, which has been relatively unchanged 

within the Mid-Atlantic region over the 20th century (Zhang et al., 2000). Results of linear and 

quadratic regression on the number of days with nuisance flooding from 1950-2012 (or when the 

data record starts) are listed in Appendix 1. 

Figure 3. Hourly water level observations at the NOAA gauge at Sewells Point (Norfolk), Virginia for (a) 1950 

and (b) 2012 and their (c) yearly water level distribution plotted with the nuisance flood level elevation 

threshold. All figures are plotted relative to 1980-2001 MSL datum and reveal in (a) and (b) a monthly springtide influence and a few discrete storm events. Readily apparent in c) is the increase in MSL (change of 

distribution center relative to “0,” which is the 1983-2001 epoch MSL datum elevation) between 1950 and 

2012.

There are regional rate-of-change patterns around the U.S. The following sections provide 

regional views of historical nuisance flood patterns, the low-lying areas within the region 

potentially susceptible to nuisance level flooding, and representative gauges for closer result 

inspection. Gauge-specific results are listed in Appendix 2.

U.S. Northeast (NE) Coast. There has been a significant increase of nuisance flooding 

occurrences along the U.S. NE Atlantic Coast (Figure 4b) largely in response to high regional 

SLRrel rates (approximately 3-5 mm/yr) from vertical land subsidence (Boon et al., 2010; Zervas 

et al., 2013) most notable in the Mid-Atlantic region and lower Chesapeake Bay. In the last 

several decades, there has been a rate increase of nuisance flood days (Ezer, 2014) with 19 of the 

23 NOAA gauges experiencing an accelerating response (Appendix 1). This nuisance flood 

frequency rate increase may reflect multi-decadal rate increases in regional SLR trends (Ezer and 
11

Corlett, 2012; Boon 2012) associated with Gulf Stream system dynamics (Sallenger et al., 2012; 

Knop, 2013), though it is unclear if this regional SLR is from a direct transport slowdown or 

interaction with Mid-Atlantic Bight Slope Current (Ezer et al., 2013; Rossby et al., 2014). The 

New England gauges are an exception, with a lower event frequency, likely due to higher 

nuisance flood level threshold elevations (Figure 1), supportive of recent analysis by Kriebel and 

Geiman (2013). Figure 4a indicates (in red) the topography at or below nuisance flood level 

elevations.

Figure 4. (a) Northeast U.S. coastal topography at or below nuisance flood level elevations (image from 

“Flood Frequency” tab of NOAA Sea Level Viewer with NOAA gauges (green) used in this study). Shown in (b) 

are days per year (color bar not the same scale as “Days per Year” axis) with nuisance flooding at 23 gauges 

from Massachusetts to Virginia and (c) specifically at Atlantic City, New Jersey (gauge 10) plotted with annual 

average MSL. In (d) is a scatter plot of nuisance flood days at Atlantic City, New Jersey fitted with a quadratic 

curve starting in year 1950.

Data from the NOAA gauge (number 10) at Atlantic City, New Jersey is provided as a regionally 

representative gauge. In Figure 4c, nuisance flood hours and days at Atlantic City, NJ are shown 

plotted with the annual average MSL. A high SLRrel trend exists at this location (4.19 mm/yr, 

Table 1) with noticeable interannual MSL and nuisance-event variability (discussed below in 

“...year-to-year differences...” section). Nuisance flood days per year, which are shown as a 
12

scatter plot in Figure 4d, can be seen to accelerate since the 1980s when fitted (R2=0.65) with a 

quadratic curve for the 1950-2012 period.

U.S. Southeast (SE) Atlantic Coast. Large regions of the U.S. Southeast Atlantic Coast are 

susceptible to nuisance level flooding (Figure 5a), occurrences of which have been readily 

increasing since the 1980s (Figure 5b). In fact, five of the eight NOAA gauges are now on an 

accelerating nuisance flood frequency trajectory (Appendix 1). Local rates of SLRrel, which 

largely reflect differences in vertical land subsidence rates, are variable (approximately 2-3 

mm/yr; Zervas et al., 2013) with locally higher rates at Springmaid Pier, South Carolina

(possibly related to a datum shift and/or questionable monthly MSL records) and Duck, North 

Carolina (possibly related to its short data record length). The large increases in nuisance flood 

events found in Charleston, South Carolina and Fort Pulaski, Georgia reflect higher SLRrel rates, 

whereas at Beaufort and Wilmington, North Carolina, lower nuisance flood level thresholds 

themselves are a factor. In this region, sea levels are affected by the Gulf Stream system (e.g., 

Florida Current), whose seasonal variability influences the MSL cycle and short-term 

perturbations contribute to nuisance flood event formation (Sweet et al., 2009). However, there is 

no known evidence of SLRrel trends increasing in this region over the last several decades. Data 

from the NOAA gauge at Charleston, South Carolina (Figure 5c), however, clearly shows the 

acceleration in nuisance flood days since the 1980s (Figure 5d).
13

Figure 5. As in Figure 4, but for the Southeast U.S. coastline that includes 8 NOAA gauges (24-31) between North 

Carolina and the Atlantic coast of Florida. Nuisance flood events are shown for Charleston, South Carolina (gauge 28)

in (c) and (d).

U.S. Gulf Coast. Along Texas and Louisiana, SLRrel rates are often very high (approximately 

5-10 mm/yr) due to land subsidence, which is highest regionally along the Mississippi River 

Delta and in areas affected by human-induced factors such as subsurface freshwater and oil 

withdrawal (Holzer and Galloway, 2005). The number of days with nuisance level flooding has 

also been increasing (Figure 6b), with four of the eight NOAA gauges undergoing response 

acceleration (Appendix 1), affecting highly developed as well as less-developed regions (Figure 

5a). The gauges with highest SLRrel (Galveston and Sabine Pass, Texas) do not, however, 

correspond to the gauges with the current highest number of nuisance events (Figure 2), since 

their nuisance flood level elevations are higher (Figure 1). It is possible that the higher levels 

reflect current flood defense mitigation measures. The NOAA gauge at Naples, Florida shows 

recent multi-decadal increases in nuisance flood hours and days (Figure 6c) similar to the 

Atlantic regions, though with large interannual variability (Figure 6d).
14

Figure 6. As in Figure 4, but for Gulf Coast that includes 8 NOAA gauges (32-39) between Florida and Texas. 

Nuisance flood events are shown for Naples, Florida (gauge 33) in (c) and (d). Note, Louisiana has not yet been 

mapped by the NOAA Sea Level Viewer and is shown with cross-hashes.

U.S. West Coast. Along the U.S. West Coast, long-term SLRrel rates are generally less than 

along the Gulf and East Coasts (Table 1). Here, vertical land subsidence is not a significant 

contributor and there has also been a small apparent decrease in SLR rates over the last several 

decades (NRC, 2012). This slowdown is attributed to a wind-forced response associated with the 

negative phase of the PDO (Bromirski et al., 2011), also involved in recent SLR rate increases 

within the tropical western Pacific basin (Merrifield et al., 2012). Another important factor is that 

ENSO drives large year-to-year MSL variability, such as the MSL rise during the last strong El 

Niño event in 1997 (discussed below in “...year-to-year differences...” section). As such, the 

trend in nuisance flood days has been more gradual since the 1980s as compared to other regions 

(Figure 7b). The West Coast is unlike the Gulf and East Coasts with its narrow continental shelf 

that prohibits large wind-driven storm surge setups and has steeper inland topography, which 

limits the amount of land exposed to potential coastal flooding (Figure 7a). However, this region 

does have a significant wave climate and is susceptible to wave impacts (Ruggiero, 2013), whose 

effects are generally not measured by gauges and not necessarily associated with tidal nuisance 

flooding. The high values in Figure 7b occur at NOAA gauge 45 in Honolulu, Hawaii, which is 

in the middle of the North Pacific Ocean, and reflect its lower nuisance flood elevation threshold

(Table 1). In Figure 7c, nuisance flood hours and days at La Jolla, California are shown. The 

MSL plot (blue line in Figure 7c) reveals the timing and extent of the apparent SLR slow-down 

starting in the 1980s. Large year-to-year variability can be observed in both MSL and nuisance 
15

event frequency and reflects ENSO-forcing. The scatter plot shown in Figure 7d reveals a linear 

increase over time, but is quite noisy (lower R2 values) due to the interannual variability.

Figure 7. As in Figure 4, but for U.S. Pacific coastline that includes 5 NOAA gauges (40-44) between 

California and Washington and gauge 45 at Honolulu, Hawaii (not shown in (a)). Nuisance flood events are 

shown for La Jolla, California (gauge 40) in (c) where the number of days per year with nuisance flooding is 

best fit by linear regression.

Historical SLRrel and Changing Nuisance Flood Event Probabilities

Here we examine how nuisance level events have changed over time in terms of their probability 

of recurrence (bottom left plots in Appendix 2), since this type of estimate is useful for riskexposure planning (Marbaix and Nicholls, 2007). In the mid-20th century (e.g., the year 1950)

when MSL was lower, a more extreme event would have been required to drive water levels to 

the nuisance flood level elevation. In 1950, events causing nuisance flooding generally had 
16

return periods between approximately 1-5 years (black dash and yellow-magenta dash line 

intersections in Appendix 2 plots; Figure 8b). Since then, SLRrel has increased the reach of high 

tides (i.e. MHHW tidal datum elevation) and lesser-magnitude storms can more readily cause 

observable impacts. By 2012 (Figure 8a), the probabilities of a nuisance flood event have 

increased throughout much of the U.S., with return periods typically <0.25 year (3 months) at 

most NOAA gauges.

Figure 8. Return Periods of nuisance level flood events in (a) 1950 and (b) 2012 at NOAA gauges.

Patterns Associated with Year-to-Year Differences in Nuisance Flood Frequency 

Superimposed upon the long-term changes in nuisance flood frequencies are noticeable year-toyear variability present across the regions. Year-to-year variability occurs in response to 

prolonged regional-scale MSL changes and/or differences in typical storm-track patterns (i.e., 

storminess). Diagnosing physical drivers of each gauge’s response is beyond the scope of this 

report. However, there are some broad and recognizable patterns in both MSL and nuisance 

flood event frequency (Figures 4-7; Appendix 2) related to ENSO. We use the Oceanic Niño 

Index (ONI) since it is operationally tracked and updated by NOAA 

(http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ensoyears).

Along the U.S. West Coast, NOAA gauges’ MSL vary coherently (Chelton and Davis 1982) 

with high (low) MSL and number of days with nuisance flooding corresponding to ENSO warm 
17

El Niño (cool La Niña) like conditions (e.g., Figure 7b). Recent pronounced El Niño events 

occurred during the years (meteorological) of 1972, 1982, 1986/87, 1991, 1997, 2004 and 2009 

(Figure 9a). El Niño is characterized by a deepened thermocline along the eastern Pacific 

boundary off of the U.S. West Coast from poleward-propagating Kelvin waves and wind-forced 

shelf processes resulting in an elevated sea level anomaly for months at a time (Enfield and 

Allen, 1980; Chelton and Davis, 1982; Miller et al., 1997). During a pronounced El Niño, 

nuisance flooding often occurs during periods of elevated perigean-spring (aka “King”) tides.

Conditions during notable La Niña, such as 1984, 1988, 1998-2000, 2007 and 2010/11 are 

characterized by lower MSL and less nuisance flooding. Figure 9a illustrates the U.S. West 

Coast MSL-ENSO relationship with data from the NOAA gauge in San Francisco, CA. It can be 

seen that MSL, which has been detrended by its long-term SLRrel rate and smoothed by a 5-

month running mean filter, changes according to ENSO phase by 10-20 cm in magnitude. Close 

inspection of Figure 7c (and other West Coast gauges in Appendix 2) shows a similar pattern of 

elevated (lower) MSL and number of days with nuisance level flooding during warm or El Niño

(cool or La Niña) conditions. The ENSO relationship is slightly obscured by the effect of the 

SLRrel trend itself, which gradually elevates MSL, thereby increasing the likelihood of more days 

above the nuisance flood level in time.

Although ENSO does not have a direct oceanic impact along the U.S Northeast Coast as it does 

along the West Coast, a global teleconnection (e.g., atmospheric-to-oceanic) impact is felt. 

ENSO has been shown to affect year-to-year differences in frequency of winter extratropical 

storms (Hirsch et al., 2001; Eichler and Higgins, 2006). Storms tend to have an increased 

(decreased) likelihood to track northeastward along the U.S. East Coast during the warm (cool) 

ENSO phase, more heavily impacting the coastal regions north of Cape Hatteras, NC (Eichler 

and Higgins, 2006; Thompson et al., 2013). Sweet and Zervas (2011) showed that during cool 

months (October–April) of stronger El Niños since 1960, there was a much higher incidence of 

days with average NTR (approximate storm surge) values >0.3 m (approximately1 foot) and 

higher MSL along the Mid-Atlantic Coast than during neutral or cool La Niña-like conditions. 

This occurred in response to changes in regional sea level pressure fields over Eastern Canada 

and the Gulf of Mexico, which steered a more zonal jet stream and extratropical storm track 

along the East Coast and strengthened the northerly component of the prevailing wind fields off 

the U.S. Northeast Coast. An annual (meteorological) count of daily mean NTR values >0.3 m is 

shown at Sewells Point, Virginia (Figure 9b) to illustrate the relationship found by Sweet and 

Zervas (2011). Similar NTR results exist at other Mid-Atlantic locations, and this pattern 

increases the likelihood for nuisance level flood events independent of spring high-tide synergy. 

At Atlantic City, New Jersey (Figure 4c) and elsewhere along the mid-Atlantic Coast (Appendix 

2), years of stronger El Niños (listed above) are associated with elevated MSL and progressively 

higher incidences (i.e., also affected by SLRrel trend) of nuisance flood events.

Along the Southeast Atlantic Coast, the annual MSL and nuisance level event response to ENSO 

are less defined, and they are largely unrecognizable along the Gulf of Mexico Coast. However, 

during the last strong El Niño in 2009, many gauges showed a similar response (i.e., elevated 

MSL and/or nuisance flood events) though not necessarily from the same underlying processes. 

In these regions as well as the Northeast Coast, MSL and nuisance flood frequencies have 

remained elevated since the 2009 El Niño. Within the Northwest Atlantic Ocean (region offshore 

U.S. Northeast Coast), significant sea surface warming has occurred since 2000 and has been

exceptionally warm since 2012. This ocean warming is associated with the mostly concurrent 
18

negative phase of the North Atlantic Oscillation (NAO) (Xue et al., 2013) coupled with an 

observed northward shift in the jet stream and reduced evaporative cooling (Chen et al., 2014) 

whose net effect has deepened the thermocline and raised sea surface heights. The East Coast 

warming may also be linked to the multi-decadal rate increases in regional mean SLR trends 

(Ezer and Corlett, 2012; Boon 2012) and Gulf Stream system dynamics (Sallenger et al., 2012; 

Knop, 2013).

Figure 9. The Oceanic Niño Index (ONI) plotted with (a) monthly MSL (black line) from San Francisco, 

California that has been detrended and smoothed by a 5-month running filter and (b) annual counts of daily 

average nontidal residual (NTR; green bars) > 0.3 m at Sewells Point, Virginia.

Seasonal Pattern of Nuisance Flood Events and Underlying Processes

In the preceding sections, we show nuisance flood event frequencies increasing in time from 

SLRrel with large year-to-year variability from MSL and/or storminess changes often related to 

ENSO. Here, we provide mean climatology patterns for 1980-2009 that describe typical timing 

of nuisance events during a year. We make no attempt to assess if intra-annual changes are 

occurring in terms of seasonal MSL changes within the Gulf of Mexico (Wahl et al., 2014). 

Figure 10 shows the season with the most occurrences of nuisance flood days. Regional 

differences include a winter-time maximum along the Northeast and Pacific Coasts and a falltime maximum along the Mid-Atlantic, Southern, and Gulf Coasts. Regionally representative 

gauges are examined in Figure 11 to assess how the phasing (timing) of low and high-frequency 

NTR and tidal processes contribute to high-water formation and lead to nuisance flooding. 

Figures for all gauges are shown in Appendix 2. 
19

Figure 10. Season with highest frequency of nuisance flood days over the 1980-2009 period as shown for each 

NOAA gauge in Appendix 2.

The season with highest nuisance event frequency reflects upon one or more regionally 

significant processes. Along the Northeast Atlantic Coast, the winter-time maximum occurs in 

response to northeasterly wind storm event (nor’easters) forcing, which is highest between late 

fall and early spring (Hirsch et al., 2001). As such, NTR frequency and magnitude are enhanced,

as is the frequency of nuisance flood events along much of the mid-Atlantic. This pattern is 

highlighted at the Battery, New York, where a >30 cm changing NTR cycle (green line, Figure 

11a) outweighs the approximately 15-cm MSL cycle (blue dash), which is out of phase to the 

NTR cycle and forms in response to seasonal heating (e.g., coldest in winter, warmest by late 

summer). The tide component shows little seasonal variability in its tide range (blue line is fairly 

flat). Two NOAA gauges (Washington D.C. and Philadelphia, Pennsylvania), whose levels are 

influenced by riverine discharge, reveal spring-time maxima (Figure 10, green dots) associated 

with increased river flows. 

Along the Southeast Atlantic Coast, nor’easters as well as the infrequent hurricane strike can 

elevate sea level; however, typically their NTR signal is less frequent or short-lived, and the net 

contribution (e.g., after 30-day filter smoothing) is less pronounced than in the Northeast. The 

transition to a fall-time maximum southward along the East Coast (Figure 10) occurs largely in 

response to changing strength and phasing of the MSL cycle. The MSL cycle has a prominent 

peak in mid-fall, which is ≥0.25 m higher than in mid-winter (blue dash, Figure 11b). The falltime maximum in the MSL cycle enables modest storm surges to more readily produce nuisance 

level events. Similar to the Northeast, the spring tide range has little seasonal variability.
20

Figure 11. Maximum observed water levels per calendar day over the 1980-2009 period decomposed into a 

low-frequency MSL cycle, predicted tide (without the annual and semi-annual harmonic fits) and remaining 

nontidal residual (NTR) all smoothed by a 30-day running filter shown for (a) the Battery, New York, (b) 

Mayport, Florida, (c) San Francisco, California and (d) Port Isabel, Texas. All series are relative to their 

station MSL datum and plotted with the nuisance flood level (yellow-magenta line) and MHHW datum elevation 

(black dot-dash). In the bottom plots, the number of nuisance flood hours and days (shared y-axis) are averaged 

by calendar month between 1980 and 2009.

Along the Gulf Coast, the NTR is a more significant high water contributor, similar in magnitude 

to the rather small tide range. Similar to the Southeast Atlantic Coast, the NTR reveals little 

seasonal variability, except for the infrequent fall-time NTR spike associated with tropical 

storms (see Appendix 2 for gauges with much higher nuisance hours than impacted days). Also, 
21

the MSL cycle is quite pronounced and similar in magnitude to the NTR. Collectively, the MSL 

cycle and NTR patterns create the observed water level maxima (black line) in the fall, 

exacerbating hurricane impacts and the frequency of nuisance flood events. Similar to the 

Southeast and Mid-Atlantic Coasts, where seasonal changes of the Gulf Stream System drive 

concurrent geostrophic-related MSL changes along the Mid-Atlantic (Sweet et al., 2009; Ezer et 

al., 2013), the annual cycles of MSL in the Gulf and Loop Current System also co-vary. Figure 

12a shows an inverse relationship between seasonal cycles of MSL at Mayport, Florida and Port 

Isabel, Texas (some apparent lag) and volume transport (in Sverdrup, Sv = 106 m

3

/sec) of the 

Florida and Yucatan Currents (data: www.aoml.noaa.gov/phod/altimetry/cvar), which feed the 

Gulf Stream and Loop Current, respectively. MSL and volume transport are computed using data 

from 2000-2009 and are shown relative to their mean value over this period.

Figure 12. (a) Monthly mean volume transport of the Florida and Yucatan Currents over the 2000-2009 with 

their means in parenthesis that reveal a geostrophic-related inverse relationship to MSL cycle at Mayport, 

Florida and Port Isabel, Texas, respectively. In (b) are hourly astronomic tide predictions for San Francisco, 

California showing semi-annual spring tide strengthening during the winter and summer solstice time frames, 

which reach the nuisance flood level.

Along the West Coast, the spring-tide range is a more substantial component than along the East 

or Gulf Coasts. The tide cycle has a larger (15 cm at San Francisco in Figure 11c) semi-annual 

strengthening near the times of perigean spring tides during the winter and summer solstices 

(Figure 12b), which is typical for much of the Northern Pacific Ocean (Merrifield et al., 2007). 

Regionally, the MSL annual cycle has a spring-time low from wind-driven upwelling. The NTR 

component is elevated during the fall-spring stormy season, and more so along the Pacific 

Northwest Coast (Allan and Komar, 2006), where winter storms track east from the Aleutian 

Low atmospheric center of action. But, compared to the other regions, the NTR is generally of 

less significance than the tide contribution due to the narrow continental shelf along the West 

Coast that inhibits the wind-driven component of storm-surge buildup. Large wave events 

typically cause most impacts along the West Coast and Pacific Islands (Ruggiero, 2013; Hoeke 

et al., 2013). In response, nuisance flood events are more frequent at times of highest “king 

tides” along the West Coast and Pacific, and more so in the winter, due to the addition of the 

higher NTR contribution.

A ratio comparing the mean of the NTR contribution (green line) and the maximum water level 

observation (black line in top plot of Figure 11) is helpful in assessing the significance of 
22

individual components of high-water and nuisance flooding. A low ratio, as described by Marra 

et al. (2012) and Merrifield et al. (2013), helps identify regions where the tide range is a much 

larger contributor than the NTR magnitude (Figure 13a). These regions include the West Coast 

(and Honolulu) where the NTR component is small (narrow continental shelf), as well as 

sections of the Southeast and Northeast Atlantic Coast, where the tide range is large. MidAtlantic gauges have larger NTR components and mid-range valued ratios (e.g., due to nor’easter 

storm surges along a wide continental shelf). The Chesapeake Bay and the Gulf of Mexico 

Coasts have large ratios, higher relative importance of the NTR compared to the tidal range. 

The ratio in Figure 13a can also be used to help predict when a nuisance flood might form; 

regions where the ratio is small, higher tides tend to be the event driver, whose timing is readily 

predicted by NOAA (e.g., http://tidesandcurrents.noaa.gov/tide_predictions). In other regions, 

higher NTR contributions generally occur concurrently. A “NTR of concern” (Figure 13b)

provides an estimate for the 1980-2009 period of the height of the nuisance flood level (yellowmagenta line) above the mean tide height (blue line) during maximum water level (smoothed, 

black line), as shown in Figure 11 and in Appendix 2. A smaller value in Figure 13b is of more 

concern because less freeboard exists.

Figure 13. Calendar-day maxima over 1980-2009 (i.e., as shown in top plots of Figure 11a-d) are averaged to 

estimate (a) a ratio between the average of the NTR during (divided by) maximum water level and (b) the 

distance between the NOAA gauge’s nuisance flood level and the average tidal contribution during maximum 

water level.
23

CONCLUDING REMARKS

NOAA water level gauges have been measuring water levels around the U.S. for over a century.

Their observations clearly show that much of the U.S. is experiencing long-term SLRrel

(http://tidesandcurrents.noaa.gov/sltrends), which has been steadily increasing the effects of 

extreme events through time and exacerbating their frequency relative to fixed elevations. What 

is becoming more noticeable and widespread are the high-tide flood events that many coastal 

regions are now perennially experiencing. These impacts today are generally minor, localized 

and a nuisance to the communities in which they occur. These events are typically recognized as 

repetitive flooding of coastal roadways and private and commercial properties during certain 

times of the year. When concurrent with localized rainfall or a wind-forced storm surge, impacts 

are worse, overwhelm storm water drainage systems and further stress other vulnerable public 

works (http://csc.noaa.gov/tidalfloodingvis). The extent and frequency of nuisance tidal flooding 

is of growing concern due to on-going SLRrel and likely future rate acceleration from ocean 

heating and land-ice melt (Church et al., 2013; Parris et al., 2012).

In this report we show that the duration and frequency of nuisance-tidal flooding is intensifying 

around the U.S. We use the NOAA NWS WFO “minor” threshold elevation for coastal flooding 

impacts as our nuisance flood level, which have been empirically calibrated to specific water 

level gauge elevations based upon local historical impact monitoring. Moderate and major 

impact thresholds are also assigned by NOAA NWS WFOs (http://water.weather.gov/ahps). 

There are approximately 75 NOAA gauges around the U.S. with empirically defined flood level 

thresholds, and of those, we analyze 45 gauge records (including one gauge in Honolulu whose 

level is defined locally by PacIOOS researchers). The coastal regions potentially exposed to 

flooding at these elevations are shown under the “Flood Frequency” tab of the NOAA Sea Level 

Viewer (http://csc.noaa.gov/slr/viewer/). 

We derive two measures—cumulative duration (hours) and number of days exceeding the 

nuisance flood level threshold per year—to provide estimates of today’s impact rate and how this 

rate has grown in time. We note several regionally consistent relationships (below).

Relationships of societal importance

1. The lower the threshold, the higher the yearly frequency of nuisance flooding events. The 

annual number of days currently (2007-2009 average) impacted by nuisance level

flooding is highly (negative) correlated to the height of the flood threshold elevation 

(Figure 2b).

2. The frequency of nuisance flooding events is increasing and accelerating in many 

locations. The annual number of days impacted by nuisance flooding is increasing at an 

accelerated rate along much of the U.S. East and Gulf Coasts. 

3. The rate of (above) acceleration is higher as the gap lessens between the local flood 

threshold elevation and MHHW. Acceleration (quadratic) constants characterizing how

nuisance flood days change over time (Appendix 1) versus the nuisance flood levels 

reveals a strong negative correlation (p<0.01) for East Coast gauges (Figure 14). 
24

Figure 14. Bubble plot of nuisance flood level (x-axis) versus quadratic constant (b2; y-axis) from fit of annual 

number of nuisance flood days listed in Appendix 1 for East Coast (NE region in red and SE region in blue) 

gauges. Bubble size represents the goodness-of-fit (R2) of each quadratic model fit. Only gauges with significant 

quadratic fits and hourly data starting prior to 1960 (Appendix 1) are included to minimize quadratic curvefitting discrepancies due to gauge record length.

Relationship (3) occurs as SLRrel increases the rate of annual-event exceedances above the

elevation thresholds characterized by exponential growth in the water level distribution (e.g., 

elevations between the nuisance flood level and MHHW in Figure 3). Relationship (2) depends 

upon the extent of annual variability in local MSL respective to a gauge’s SLRrel trend. The West 

Coast is different than the Gulf and East Coasts due to direct forcing of ENSO, which creates 

prolonged changes in MSL with large year-to-year variability. Strong El Niños like the 1982 and 

1997 events (meteorological years) drive 0.2-0.3 m MSL anomalies for months (e.g., Figure 9, 

though MSL has been smoothed) and a spike in days with nuisance level flooding (e.g., 

Figure 7c). Moreover, since the last strong 1997 El Niño, MSL along the West Coast has 

remained relatively stationary due in part to PDO-related factors (Bromirski et al., 2011) and 

changes in nuisance flood event frequency, which is best characterized as a linear increase with 

higher signal variance (lower R2). Along the U.S. East Coast, strong El Niños increase stormsurge frequency (Sweet and Zervas, 2011; Thompson et al., 2013), but MSL is less affected, 

typically though the preponderance of storm surges. But, East Coast MSLs have been steadily 

increasing over the last several decades (e.g., Figure 3c), and the event rate of nuisance flood

events is accelerating and well characterized by a quadratic relationship (Appendix 1, Figure 14). 

Year-to-year differences in storm surge frequency are presumed of lesser importance, since this 

process has a more stationary behavior than MSL, which is rising (e.g., Zhang et al., 2000).

Interannual storm surge variability might be a factor in some regions like the Gulf Coast where

the tide range is small and nuisance flood level elevations can be relatively high. All of these 

considerations may help explain why not all approximately 75 NOAA gauges with NWS-defined 

nuisance flood levels show discernable time-dependent trends.

In terms of event probabilities, nuisance flood events have clearly changed over time, for 

instance since the 1950s, when many coastal regions were developing. In 1950, such events

would have the probability of recurring every couple of years (Figure 8), whereas today, they 
25

occur so frequently due to decades of SLRrel that they are no longer classified as an extreme

event. To better plan for these recurring impacts, we have quantified the season that typically has 

the highest occurrences of nuisance flooding during the year (Figure 10) and highlighted the 

related physical forcing processes (Figure 11). In regions like the West Coast, where storm surge 

magnitudes are bathymetrically constrained by the narrow continental shelf, nuisance flooding is 

more tidally controlled (Figure 13a) and readily predictable using NOAA Tide Predictions

(http://tidesandcurrents.noaa.gov/tide_predictions). In regions like the Gulf Coast and 

Chesapeake Bay, nuisance flooding typically happens at higher tide levels, but a substantial NTR 

contribution is also needed, either from a local storm or a longer-term regional event contributing 

to a quiet sea level (NTR) anomaly (e.g., Sweet et al., 2009). We have quantified a typical NTR 

contribution required during periods of higher tidal range (spring tides) to cause local nuisance 

level flooding (Figure 13b). 

Together, the relationships of societal importance might be further refined to more broadly 

assess potential impacts from tidal-related coastal flooding over a range of elevations. Such a

refinement might permit flood frequency and duration estimates at particular thresholds for 

locations lacking a nearby water level gauge but having a local tide datum as provided by the 

NOAA Vertical Datum Transformation Tool (vdatum.noaa.gov). These relationships are not 

intended to explicitly determine where and for how long minor flooding will occur, since local 

baseline hydrologic conditions vary with the weather and by topo-bathymetric and land-cover 

response characteristics. The relationships do establish a degree of susceptibility for large 

regions of the U.S. Coast to coastal flooding at various elevations above today’s high tide.

In closing, it is important to stress that SLRrel exacerbates impacts over a range of elevation 

thresholds relative to today’s fixed reference frame (e.g., Figure 3c). At very high thresholds, 

such as those of the 100-year event experienced during rare hurricane strikes (not observable in 

Figure 3c), SLRrel has and will continue to nonlinearly compress recurrence probabilities in the 

future because smaller (with higher probability) storm surges will be able to impact similar 

elevations. The same is true for impacts from lesser extremes or nuisance-like tides, which we 

describe here in terms of average annual frequency and duration. We find that with lower 

threshold elevations, nuisance-level events are more commonplace and their event frequencies 

change in time at increasingly higher rates (Figure 14) simply from linear SLRrel. Any 

acceleration in SLRrel will only further intensify inundation impacts over time, and will further 

reduce the time between flood events. It is therefore apparent that a time horizon exists, largely 

dependent upon the local rate of SLRrel, when critical elevation thresholds for various 

public/private/commercial serving systems will become increasingly compromised by tidal 

flooding in the future. We stress that in many areas, the frequency of nuisance flooding is already 

on an accelerating trajectory, and many other locations will soon follow even with a 

continuation of linear SLRrel rates. This fact needs to be recognized, as it is critical for coastal 

planning entities to prevent critical-system degradation from SLR impacts and to promote 

resiliency efforts in general.
26
27

RECOMMENDATIONS

Continued research of trends and patterns associated with nuisance coastal flooding should help 

identify regionally important processes (e.g., tide variations, ENSO influences, ocean current 

circulation, etc.) involved in event occurrence to facilitate near-term predictions and seasonal 

outlooks of their potential impacts. Systematic score-keeping of locally important (e.g., sectorspecific) threshold exceedances at NOAA gauges by communities would permit monitoring for 

important frequency changes in tidal-related flooding. Coupled with new, innovative, crowdsource-like technologies (e.g., various “King Tide websites”), this effort would help spatially 

delineate vulnerabilities, allowing for better local (street-level) calibration/validation of modelbased decision tools. In short, tracking sensible indicators of SLRrel like nuisance tidal flooding 

and recognizing their impacts will heighten awareness, bridge today’s perceptions with a 

community’s living memory, and facilitate planning and resiliency efforts.

ACKNOWLEDGEMENTS

We would like to thank Doug Marcy, Matt Pendleton, and Billy Brooks of NOAA’s Coastal 

Services Center (CSC) for reviewing this report, providing the high resolution graphics in 

Figures 4a, 5a, 6a, 7a, and advancing the idea of investigating recurrent tidal flooding using 

NWS thresholds in the geographic/spatial (mapping) display of the NOAA Sea Level Viewer.

We would also like to thank Jeff Williams of the U.S. Geological Survey (USGS), Patrick 

O’Brien of the U.S. Army Corps of Engineers, and Jayantha Obeysekera of the South Florida 

Water Management District for their review of this manuscript and constructive comments.
28
29

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33

APPENDIX 1

Gauge name, analysis start date, model coefficients from linear and quadratic fits of days per 

year impacted by nuisance flooding and goodness of fit (R2). Both models use data starting in 

1950 (e.g., t(1950)= 1) or when data becomes available and ends in year (meteorological) 2012. 

Trend (b1) and acceleration coefficients (b2) are bold when significant at the 90% level.
34

 Linear Model y=b1*t + b Quadratic: y=b2*t2 + b1*t + b

Station Name

 Start 

(year) b1 b R

2

 b2 b1 b R

2

1 Boston, MA 1921 0.047 0.7 0.12 0.0035 -0.18 3.2 0.30

2 Providence, RI 1938 0.007 1.1 0.01 0.0017 -0.11 2.9 0.09

3 New London, CT 1938 0.012 0.9 0.03 0.0009 -0.04 1.4 0.07

4 Bridgeport, CT 1970 0.281 -5.2 0.33 0.0240 -1.74 33.5 0.63

5 Montauk, NY 1947 0.023 0.4 0.08 0.0013 -0.06 1.3 0.15

6 Kings Point, NY 1931 0.158 1.9 0.26 0.0083 -0.37 7.5 0.44

7 Battery, NY 1920 0.146 0.2 0.29 0.0064 -0.27 4.7 0.44

8 Bergen Point, NY 1981 0.301 -8.9 0.38 0.0230 -1.92 42.8 0.51

9 Sandy Hook, NJ 1922 0.334 -2.6 0.52 0.0113 -0.39 5.2 0.67

h Atlantic City, NJ 1920 0.327 -2.4 0.51 0.0105 -0.34 4.6 0.65

11 Cape May, NJ 1965 0.652 -14.1 0.54 0.0320 -1.96 33.5 0.74

12 Philadelphia, PA 1920 0.145 0.0 0.23 0.0057 -0.22 4.1 0.33

13 Reedy Point, DE 1979 0.338 -10.8 0.35 0.0207 -1.62 33.9 0.43

14 Lewes, DE 1920 0.251 0.4 0.35 0.0104 -0.43 8.4 0.50

15 Cambridge, MD 1979 0.253 -8.5 0.46 0.0185 -1.46 29.6 0.65

16 Baltimore, MD 1920 0.165 -0.6 0.38 0.0068 -0.27 4.1 0.55

17 Annapolis, MD 1928 0.567 -3.8 0.53 0.0168 -0.51 7.7 0.66

18 Washington D.C. 1924 0.384 1.3 0.37 0.0091 -0.20 7.5 0.42

19 Wachapreague, VA 1978 0.090 -1.9 0.11 0.0009 0.01 -0.1 0.12

20 Kiptopeke, VA 1976 0.208 -5.2 0.28 0.0036 -0.12 1.8 0.29

21 Lewisetta, VA 1970 0.257 -8.0 0.45 0.0111 -0.72 12.0 0.56

22 Sewell Point, VA 1927 0.097 -0.1 0.30 0.0022 -0.05 1.4 0.34

23 Ches. Bay Bridge, VA 1975 0.105 -2.7 0.21 0.0008 0.03 -1.3 0.22

24 Duck, NC 1978 0.159 -3.9 0.25 0.0016 0.01 -0.7 0.25

25 Beaufort, NC 1973 0.894 -26.2 0.69 0.0206 -0.95 12.4 0.73

26 Wilmington, NC 1935 0.542 -6.6 0.57 0.0125 -0.26 2.2 0.66

27 Springmaid Pier, SC 1977 0.060 -1.0 0.08 0.0049 -0.39 8.6 0.13

28 Charleston, SC 1921 0.347 -1.8 0.57 0.0045 0.06 1.4 0.60

29 Fort Pulaski, GA 1935 0.194 0.4 0.37 0.0018 0.08 1.7 0.38

30 Fernandina Beach, FL 1920 0.026 0.1 0.11 0.0011 -0.05 0.9 0.17

31 Mayport, FL 1928 0.068 -0.9 0.24 0.0031 -0.13 1.2 0.38

32 Key West, FL 1920 0.043 -0.7 0.20 0.0020 -0.09 0.8 0.31

33 Naples, FL 1965 0.153 -3.0 0.40 0.0042 -0.18 2.7 0.45

34 Apalachicola, FL 1976 0.096 -1.4 0.12 0.0007 0.03 0.1 0.12

35 Panama City, FL 1973 0.155 -2.4 0.14 0.0118 -0.91 20.0 0.24

36 Bay Waveland, MS 1978 0.259 -4.5 0.27 0.0093 -0.60 14.1 0.30

37 Sabine Pass, TX 1981 0.026 -0.4 0.02 -0.0042 0.44 -10.4 0.05

38 Galveston, TX 1957 0.029 0.0 0.14 0.0010 -0.04 1.0 0.17

39 Port Isabel, TX 1944 0.218 -2.6 0.34 0.0069 -0.22 2.1 0.42

40 La Jolla, CA 1924 0.100 -0.7 0.26 0.0006 0.06 -0.2 0.27

41 San Francisco, CA 1920 0.130 3.0 0.12 -0.0026 0.30 1.2 0.13

42 Humboldt Bay, CA 1977 0.146 -3.2 0.17 -0.0045 0.57 -12.4 0.18

43 Toke Point, WA 1972 0.088 7.0 0.03 -0.0062 0.63 -3.9 0.04

44 Seattle, WA 1920 0.026 0.6 0.05 0.0007 -0.02 1.1 0.06

45 Honolulu, HI 1920 0.278 -0.3 0.19 0.0000 0.28 -0.3 0.19
35

APPENDIX 2

 (top left) show nuisance flood events (cumulative hours and impacted days) per 

meteorological year with annual MSL through 2012 (i.e., May 2012 – April 2013). Note: 

if the number of hours and days are numerically equivalent, only the top values (days in 

yellow) appear. 

 (bottom left) show return level interval curves from a Peak Over Threshold (POT) / Point

Process approach fit to a Generalized Pareto Distribution (GPD). The 2012 modeled 

values (black line), their 95% confidence intervals (red dash) and POT picks (dots) are 

shown respective to the nuisance flood level (yellow-magenta line). 1950 values (black 

dash) are the 2012 values lowered by a distance equal to the local relative sea level rise 

(SLRrel) trend (mm/yr) shown in Table 1 for a 62‐year period.

 (top right) show maximum water levels (black) per calendar day over the 1980‐2009 

period decomposed into a low‐frequency MSL cycle (blue dot), predicted tide (blue; no Sa

and Ssa harmonic fits) and nontidal residual (NTR; green). All series are smoothed by a 

30‐day running filter and plotted relative to each gauge’s MSL tidal datum shown with 

the nuisance flood level (yellow-magenta) and MHHW tidal datum (black dot).

 (bottom right) show average nuisance flood events (shared y-axis) by calendar month 

over 1980‐2009. Note: if the number of hours and days are numerically equivalent, only 

the top values (days in yellow) appear. 
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58

ACRONYMS

AMM Annual Maximum Method

CO-OPS Center for Operational Oceanographic Products and Services

ENSO El Niño Southern Oscillation

GEV Generalized Extreme Value

GPD Generalized Pareto Distribution

MHHW Mean Higher High Water

MSL Mean Sea Level

NAO North Atlantic Oscillation

NOAA National Oceanic and Atmospheric Administration

NTDE National Tidal Datum Epoch

NTR Nontidal Residual

NWLON National Water Level Observation Network

NWS National Weather Service

ONI Oceanic Niño Index

PacIOOS Pacific Integrated Ocean Observing System

PDO Pacific Decadal Oscillation

POT Peak Over Threshold

SLR Sea Level Rise

WFO Weather Forecasting Offices