Photo provided by the Greater Lafourche Photo provided by the Greater Lafourche Port Commission

Global Sea Level Rise Scenarios for the 

United States National Climate Assessment

December 6, 2012
NOAA Technical Report OAR CPO-1

Global Sea Level Rise Scenarios for the United States

National Climate Assessment

Climate Program Office (CPO)

Silver Spring, MD

Climate Program Office

Silver Spring, MD

December 2012

UNITED STATES

DEPARTMENT OF COMMERCE

Rebecca Blank

Acting Secretary

NATIONAL OCEANIC AND

ATMOSPHERIC ADMINISTRATION

Dr. Jane Lubchenco

Undersecretary for Oceans and 

Atmospheres

Office of Oceanic and

Atmospheric Research

Dr. Robert Dietrick

Assistant Administrator
NOTICE from NOAA

Mention of a commercial company or product does not constitute an endorsement by NOAA/OAR. 

Use of information from this publication concerning proprietary products or the tests of such products 

for publicity or advertising purposes is not authorized. Any opinions, findings, and conclusions or 

recommendations expressed in this material are those of the authors and do not necessarily reflect the 

views of the National Oceanic and Atmospheric Administration.
Authors

Adam Parris, Lead, National Oceanic and Atmospheric Administration

Peter Bromirski, Scripps Institution of Oceanography

Virginia Burkett, United States Geological Survey

Dan Cayan, Scripps Institution of Oceanography and United States Geological Survey

Mary Culver, National Oceanic and Atmospheric Administration 

John Hall, Department of Defense

Radley Horton, Columbia University and National Aeronautics and Space Administration

Kevin Knuuti, United States Army Corps of Engineers

Richard Moss, University of Maryland

Jayantha Obeysekera, South Florida Water Management District

Abby Sallenger, United States Geological Survey

Jeremy Weiss, University of Arizona

Contributors

Benjamin Brooks, University of Hawaii (Manoa)

Mark Merrifield, University of Hawaii

Philip Mote, Oregon State University

William Emanuel, Department of Energy

Workshop Participants

Dorothy Koch, Department of Energy

Jo-Ann Leong, Hawaii Institute of Marine Biology and Oregon State University

Tad Pfeffer, University of Colorado

Sandy Lucas, National Oceanic and Atmospheric Administration

Reviewers

James Titus, Environmental Protection Agency 

Jonathan Overpeck, University of Arizona

Stephen Gill, National Oceanic and Atmospheric Administration

John Church, CSIRO

Vivien Gornitz, NASA Goddard Institute for Space Science

Suggested Citation: 

Parris, A., P. Bromirski, V. Burkett, D. Cayan, M. Culver, J. Hall, R. Horton, K. Knuuti, 

R. Moss, J. Obeysekera, A. Sallenger, and J. Weiss. 2012. Global Sea Level Rise Scenarios for the 

US National Climate Assessment. NOAA Tech Memo OAR CPO-1. 37 pp. 

Front cover photo provided by the Greater Lafourche Port Commission

Report Team
Global sea level rise (SLR) has been a persistent trend 

for decades. It is expected to continue beyond the end 

of this century, which will cause significant impacts 

in the United States (US). Over eight million people 

live in areas at risk to coastal flooding, and many of 

the nation’s assets related to military readiness, energy, 

commerce, and ecosystems are already located at or 

near the ocean. 

Past trends provide valuable evidence in preparing 

for future environmental change but, by themselves, 

are insufficient for assessing the risks associated with 

an uncertain future. For example, a number of recent 

studies project an increase in the rate and magnitude 

of global SLR. The US Congress recognizes the need 

to consider future trends in the Global Change 

Research Act (USGCRA), which calls for a National 

Climate Assessment (NCA) every four years. This 

report provides a synthesis of the scientific literature 

on global SLR at the request of a federal advisory 

committee charged with developing the next NCA. 

This report also provides a set of four global mean 

SLR scenarios to describe future conditions for the 

purpose of assessing potential vulnerabilities and 

impacts. 

A wide range of estimates for future global mean 

SLR are scattered throughout the scientific literature 

and other high profile assessments, such as previous 

reports of the NCA and the Intergovernmental Panel 

on Climate Change (IPCC). Aside from this report, 

there is currently no coordinated, interagency effort 

in the US to identify agreed upon global mean SLR 

estimates for the purpose of coastal planning, policy, 

and management. This is an important gap because 

identifying global mean SLR estimates is a critical 

step in assessing coastal impacts and vulnerabilities. 

At present, coastal managers are left to identify global 

SLR estimates through their own interpretation of 

the scientific literature or the advice of experts on 

an ad-hoc basis. Yet, for a great majority of the US 

coastline, relative sea level (RSL)1

 has been rising over 

the past 60 years, consistent with the global trend.

Scenario Planning

Scenarios do not predict future changes, but describe 

future potential conditions in a manner that supports 

decision-making under conditions of uncertainty. 

Scenarios are used to develop and test decisions 

under a variety of plausible futures. This approach 

strengthens an organization’s ability to recognize, 

adapt to, and take advantage of changes over time. 

Using a common set of scenarios across different 

regions and sectors to frame the range of uncertainties 

surrounding future environmental conditions is a 

relatively new and evolving initiative of the NCA. This 

report provides scenarios to help assessment experts 

and their stakeholders analyze the vulnerabilities and 

impacts associated with possible, uncertain futures. 

Probabilistic projections of future conditions are 

another form of scenarios not used in this report 

because this method remains an area of active 

research. No widely accepted method is currently 

available for producing probabilistic projections of sea 

level rise at actionable scales (i.e. regional and local). 

Coastal management decisions based solely on a most 

probable or likely outcome can lead to vulnerable 

assets resulting from inaction or maladaptation. Given 

the range of uncertainty in future global SLR, using 

multiple scenarios encourages experts and decision 

makers to consider multiple future conditions and to 

develop multiple response options. Scenario planning 

offers an opportunity to initiate actions now that 

may reduce future impacts and vulnerabilities. Thus, 

specific probabilities or likelihoods are not assigned to 

individual scenarios in this report, and none of these 

scenarios should be used in isolation.

Global Mean SLR Scenarios

We have very high confidence (>9 in 10 chance) 

that global mean sea level will rise at least 0.2 

meters (8 inches) and no more than 2.0 meters 

(6.6 feet) by 2100.

In recent decades, the dominant contributors to global 

sea level rise have been ocean warming (i.e. thermal 

expansion) and ice sheet loss. The relative magnitude 1 Relative sea level – The height of the sea with respect to a 

specific point on land. 

Global SLR Scenarios supporting the US National Climate Assessment November 2012 | 1

Executive Summary
of each of these factors in the future remains highly 

uncertain. Many previous studies, including the IPCC, 

assume thermal expansion to be the dominant 

contributor. However, the National Research Council 

(NRC) recently reports that advances in satellite 

measurements indicate ice sheet loss as a greater 

contribution to global SLR than thermal expansion 

over the period of 1993 to 2008. Our scenarios are 

based on four estimates of global SLR by 2100 that 

reflect different degrees of ocean warming and ice sheet 

loss (Table ES-1 and Figure ES 1).

Table ES-1. Global SLR Scenarios 

Scenario SLR by 2100 (m)* SLR by 2100 (ft)*

Highest 2.0 6.6

Intermediate-High 1.2 3.9

Intermediate-Low 0.5 1.6

Lowest 0.2 0.7

* Using mean sea level in 1992 as a starting point.

Key Uncertainties on Global SLR

At this stage, the greatest uncertainty surrounding 

estimates of future global SLR is the rate and 

magnitude of ice sheet loss, primarily from Greenland 

and West Antarctica. Our Highest Scenario of global 

SLR by 2100 is derived from a combination of 

estimated ocean warming from the IPCC AR4 global 

SLR projections and a calculation of the maximum 

possible glacier and ice sheet loss by the end of the 

century. The Highest Scenario should be considered 

in situations where there is little tolerance for risk (e.g. 

new infrastructure with a long anticipated life cycle 

such as a power plant).

Our Intermediate-High Scenario is based on an 

average of the high end of semi-empirical, global 

SLR projections. Semi-empirical projections utilize 

statistical relationships between observed global sea 

level change, including recent ice sheet loss, and air 

temperature. Our Intermediate-Low Scenario is 

based on the upper end of IPCC Fourth Assessment 

Report (AR4) global SLR projections resulting from 

climate models using the B1 emissions scenario. 

The Intermediate-High Scenario allows experts and 

decision makers to assess risk from limited ice sheet 

loss. The Intermediate Low Scenario allows experts 

and decision makers to assess risk primarily from 

ocean warming. 

The Lowest Scenario is based on a linear extrapolation 

of the historical SLR rate derived from tide gauge 

records beginning in 1900 (1.7 mm/yr). Global sea 

level has risen 0.2 meters (8 inches) over this period 

of record, and we anticipate at least 8 inches by 2100. 

The rate of global mean SLR derived from satellite 

altimetry (1992 to 2010) has been substantially higher 

(3.2 mm/yr), approaching twice the rate of 

the longer historical record from tide gauges. 

However, the 18-year altimeter record is 

insufficient in duration for projecting centuryscale global SLR. Trends derived from shorter 

records are less reliable as projections because 

they are affected by interannual and decadal 

climate and oceanographic patterns that are 

superimposed upon the long-term rise of global 

sea level. The Lowest Scenario should be considered 

where there is a great tolerance for risk.

There is a highly significant correlation between 

observations of global mean SLR and increasing 

global mean temperature, and the IPCC and more 

recent studies anticipate that global mean sea level 

will continue to rise even if warming ceases. Our 

Intermediate-Low and Lowest Scenarios are optimistic 

scenarios of future environmental change assuming 

rates of ice sheet loss and ocean warming slightly 

higher or similar to recent observations. 

RSL is highly variable over time and along different 

parts of the US coast. Changes in vertical land 

movement and ocean dynamics may be applied with 

different degrees of confidence based on available 

regional or local data. For example, changes in RSL 

observed over multiples decades in the Pacific Ocean 

basin demonstrate that regional-to-global-scale climate 

factors can cause ocean basin-scale patterns that may 

persist for a few decades. In the Pacific Northwest, 

upward vertical land movement reduces RSL on the 

coast of Alaska and parts of Washington and Oregon. 

2 | November 2012

Executive Summary
In the Mississippi River Delta, coastal subsidence 

increases RSL. As such, individual regions should 

expect a set of additional processes beyond global SLR 

that may influence estimates of regional and local sea 

level change. To provide the level of detail required for 

sound coastal assessments, regional and local experts, 

including the NCA chapter authors, are needed 

to evaluate regional and local ocean dynamics and 

vertical land movement and make specific adjustments 

to global scenarios.

SLR and Coastal Flooding

It is certain that higher mean sea levels increase the 

frequency, magnitude, and duration of flooding 

associated with a given storm, which often have 

disproportionately high impacts in most coastal 

regions. Extreme weather events will 

continue to be the primary driver of the 

highest water levels. However, a consensus 

has not yet been reached on how the 

frequency and magnitude of storms may 

change in coastal regions of the US. The 

greatest coastal damage generally occurs 

when high waves and storm surge occur 

during high tide. In many locations along 

the US coast, small increases in sea level over 

the past few decades already have increased 

the height of storm surge and wind-waves. 

Thus, considering the impact of different 

weather events combined with scenarios of 

SLR is crucial in developing hazard profiles 

for emergency planning and vulnerability, 

impact, and adaptation assessments. 

Conclusion

Based on a large body of science, we 

identify four scenarios of global mean SLR 

ranging from 0.2 meters (8 inches) to 2.0 

meters (6.6 feet) by 2100. These scenarios 

provide a set of plausible trajectories of global mean 

SLR for use in assessing vulnerability, impacts, and 

adaptation strategies. None of these scenarios should 

be used in isolation, and experts and coastal managers 

should factor in locally and regionally specific 

information on climatic, physical, ecological, and 

biological processes and on the culture and economy 

of coastal communities. Scientific observations at the 

local and regional scale are essential to action, and 

long-term coastal management actions (e.g. coastal 

habitat restoration) are sensitive to near-term rates 

and amounts of SLR. However, global phenomena, 

such as SLR, also affect decisions at the local scale, 

especially over longer time horizons. Thousands of 

structures along the US coast are over fifty years 

old, including vital storm and waste water systems. 

Thus, coastal vulnerability, impact, and adaptation 

assessments require an understanding of the longterm, global, and regional drivers of environmental 

change. 

Figure ES 1. Global mean sea level rise scenarios. Present Mean Sea Level 

(MSL) for the US coasts is determined from the National Tidal Datum 

Epoch (NTDE) provided by NOAA. The NTDE is calculated using tide gauge 

observations from 1983 – 2001. Therefore, we use 1992, the mid-point of 

the NTDE, as a starting point for the projected curves. The IntermediateHigh Scenario is an average of the high end of ranges of global mean 

SLR reported by several studies using semi-empirical approaches. The 

Intermediate Low Scenario is the global mean SLR projection from the 

IPCC AR4 at the 95% confidence interval.

Global SLR Scenarios supporting the US National Climate Assessment November 2012 | 3

Executive Summary
1. Report Background

Global sea level rise (SLR) has been a persistent 

trend for decades. It is expected to continue beyond 

the end of this century, which will cause significant 

impacts in the United States (US). Over 8 million 

people live in areas at risk to coastal flooding 

(Crowell et al. 2010). Along the Atlantic Coast of 

the US alone, almost 60 percent of the land within a 

meter of sea level is planned for further development, 

with inadequate information on the potential rates 

and amount of SLR (Titus et al. 2009). Many of the 

nation’s assets related to military readiness, energy, 

commerce, and ecosystems that support resourcedependent economies are already located at or near 

the ocean, thus making them exposed to SLR. 

Evidence for global mean SLR has been increasingly 

documented in assessments of the Intergovernmental 

Panel on Climate Change (IPCC), the National 

Research Council (NRC), and a growing body of 

peer-reviewed scientific literature (IPCC 2001, 

IPCC 2007a, Church et al. 2011). The IPCC is 

currently in the process of revising projections 

of global mean SLR, drawing on the knowledge 

and data of the international science community. 

Similarly, the NRC recently established a panel to 

assess SLR in California, Oregon, and Washington. 

State and local governments and the US Army Corps 

of Engineers (USACE) also are developing or have 

already developed their own SLR projections for 

coastal planning, policy, and management from the 

existing body of scientific literature (USACE 2011, 

SFBCDC 2011, SFRCCC, 2011, MDEP 2009, 

MCCC 2008, Horton 2010, Horton 2011). 

There is currently no coordinated, interagency effort 

in the US to identify agreed upon estimates for future 

global mean SLR for the purpose of coastal planning, 

policy, and management. This is an important gap 

because identifying global mean SLR estimates 

is a critical step in assessing coastal impacts and 

vulnerabilities. At present, coastal managers are left 

to identify global SLR estimates through their own 

interpretation of the scientific literature or the advice 

of experts on an ad-hoc basis. 

For these reasons, the NCA Development and 

Advisory Committee (NCADAC), a federal advisory 

committee charged with writing the next NCA, have 

requested this report. The Scenarios Working Group 

(SWG) of the NCADAC is considering climate, sea 

level rise, land use-land cover, and socioeconomic 

scenarios. This report provides a synthesis of the 

scientific literature on global SLR and a set of four 

scenarios of future global SLR. The report includes 

input from national experts in climate science, 

physical coastal processes, and coastal management.

2. Using Scenarios for 

Coastal Risk Analysis

Scenarios do not predict future changes, but describe 

future potential conditions in a manner that supports 

decision-making under conditions of uncertainty 

(Moss et al 2010, Gray 2011, Weeks et al 2011). 

Scenarios are used to develop and test decisions under 

a range of plausible futures. This approach strengthens 

an organization’s ability to recognize, adapt to, and 

take advantage of changes over time. Using a common 

set of scenarios across different regions and sectors to 

frame the range of uncertainties surrounding future 

environmental conditions is a relatively new and 

evolving initiative of the NCA. 

There are many different approaches to developing 

and applying scenarios (Moss et al 2010, Henrich et 

al 2010). Scenarios differ in terms of, among other 

things: varying degrees of qualitative and quantitative 

information, the goals for use of the scenarios, and 

the context for the development of the scenario. 

The purpose may be to explore the consequences 

of alternative response options; identify impacts of 

uncertain future conditions; or develop a consensus 

response option (McKenzie et al 2012). This report 

provides scenarios to aid assessment experts and their 

stakeholders in analyzing the vulnerabilities and 

impacts associated with possible, uncertain futures. 

Specifically, we provide scenarios to help assess the key 

uncertainties surrounding estimates of future global 

SLR: the rates and magnitudes of ocean warming 

(i.e. ocean warming) and ice sheet loss (NRC 2012, 

Horton et al 2010).

Main Report

4 | November 2012
Probabilistic projections of future conditions are 

another form of scenarios not used in this report. An 

early attempt to derive a probability distribution for 

global SLR combines probabilities associated with 

major components such as thermal expansion and 

ice sheet loss (Titus and Narayanan 1995). Given 

the degree of uncertainty surrounding the different 

components of future global SLR, this approach is still 

considered experimental. Horton et al. (2011) provide 

probable SLR estimates for New York City for 

the 2020s, 2050s, and 2080s based on certain 

assumptions. However, this approach requires 

extensive expertise, computing resources, 

and substantial prior research, not typically 

available for many locations of the US. No 

widely accepted method is currently available 

for producing probabilistic projections of SLR 

at actionable scales (i.e. regional and local). 

Coastal management decisions based solely 

on a most probable or likely outcome can lead 

to vulnerable assets resulting from inaction or 

maladaptation (Weeks et al 2011, Gray 2011). 

Given the range of uncertainty in future global 

SLR, using exploratory scenarios in coastal 

planning offers an opportunity to overcome decisionmaking paralysis and initiate actions now that may 

reduce future impacts and vulnerabilities. Using 

multiple scenarios encourages experts and decision 

makers to rehearse multiple future conditions and to 

develop multiple response options. Thus, we do not 

assign specific probabilities or likelihoods to individual 

scenarios because none of these scenarios should be used 

in isolation. We provide two intermediate scenarios 

to avoid the interpretation of a single intermediate 

scenario as most likely. Our approach is consistent 

with US Army Corps of Engineers (USACE) guidance 

for coastal decision makers, (USACE 2011) and draws 

on several commonly used methodologies as the basis 

for developing scenarios (Henrich et al 2010, Weeks 

et al 2011). 

3. Historical Sea Level Trends 

Global SLR is the result of the change in the volume 

of water in the oceans due primarily to changes in 

ocean temperature, melting and increased discharge of 

land-based ice (i.e. glaciers, ice caps, and ice sheets in 

Greenland and Antarctica), and changes in runoff (e.g. 

dam construction or groundwater withdrawal) (Figure 

1). Earth’s climate, and consequently the sea level, 

respond to cycles of alternating glacial and interglacial 

conditions over millions of years, with a periodicity of 

about 100,000 years (Kawamura et al. 2007).

Geological evidence from approximately 120,000 

- 130,000 years ago during the last interglaciation 

(LIG), a period when the configuration of Earth’s ice 

sheets was similar to that of today, suggests that global 

sea level rise rates of a meter or more per century are 

possible (Rohling et al. 2008; Berger 2008). Changes in 

Earth’s orbit during the LIG raised global temperatures 

to values slightly warmer than present (Otto-Bliesner 

et al. 2006; Overpeck et al. 2006), causing losses from 

the Greenland and Antarctic ice sheets that contributed 

substantially to higher seas (Otto-Bliesner et al. 2006; 

Overpeck et al. 2006; Hearty et al. 2007; Kopp 

et al. 2009; McKay et al. 2011). Although sea level 

variability during the LIG is only a partial analogue for 

this century, it nonetheless informs the assessment of 

our scenarios, particularly those that reflect greater ice 

sheet loss. Geologic evidence of the past 2,000 years 

suggests that global mean SLR has been relatively 

stable (approximately -0.1 mm/yr to 0.6 mm/yr) until 

the late 1800s or early 1900s (Kemp et al. 2011).

Figure 1. Causes of sea level change. (IPCC 2001)

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Global SLR Scenarios supporting the US National Climate Assessment November 2012 | 5
Since 1900, global mean sea level has been rising at a 

rate of approximately 1.7 mm/yr as recorded by tide 

gauges (Church and White 2011). Measurements 

from satellite altimetry data, beginning in the 

early 1990s, suggest that this rate has increased to 

approximately 3.2 mm/yr (Ablain et al. 2009, Church 

and White 2011). The apparent recent acceleration in 

global SLR recorded with satellite altimetry may be 

attributed to a combination of decadal-scale climate 

and oceanographic patterns, differences in tide 

gauge and altimetry observation methodologies and 

measurement distribution, and an acceleration of 

global SLR associated with global warming.

Satellite measurements reveal important variations 

in global mean sea level between and within ocean 

basins (Figure 2). For example, large-scale climate 

patterns that fluctuate over years to decades, such as 

the Pacific Decadal Oscillation (PDO), the North 

Atlantic Oscillation (NAO), and the El Niño Southern 

Oscillation (ENSO), may cause variations in the 

Pacific Ocean, the Gulf of Mexico, and the Atlantic 

Ocean. These variations in mean sea level are referred 

to as anomalies (see Appendix 1). The cause of these 

anomalies is still an active area of scientific research.

Tide gauges reveal variations in relative sea level (RSL)2

resulting from additional local factors such as vertical 

2 Relative sea level – The height of the sea with respect to a 

specific point on land. 

Figure 2. Geographic variability in the rate of global sea level change (1992 to 2010) based on three satellite records: TOPEX, 

Jason 1 and Jason 2 (Figure source: NOAA Laboratory for Satellite Altimetry – Accessed November 2, 2011).

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6 | November 2012
land movement (the uplift or subsidence of the land 

surface) (Figure 3). For a great majority of the US 

coastline, RSL has been rising over the past 60 years 

consistent with the global trend, largely due to limited 

vertical land movement (VLM) (Figure 4). In the 

following sections, we discuss patterns and possible 

causes of changes in RSL and mean sea level anomalies 

for different ocean basins adjacent to the US coast. 

3.1 Regional patterns in the Pacific Ocean Basin

RSL has varied dramatically due to vertical land 

movement across the eastern North Pacific Ocean 

(northern California, Oregon, Washington and 

Alaska) and to decadal climate variability (Figure 3). 

Both tide gauges and satellite altimetry indicate that 

RSL has not been rising along the boundary of the 

eastern North Pacific since the early 1980s (Houston 

and Dean 2007, Bromirski et al 2011, Merrifield 2011) 

Figure 3. Relative Sea Level (RSL) Variations of the United States (1854 to 2006). Derived from 128 National Water 

Level Observation Network Stations. Source: Department of Commerce (DOC), National Oceanic and Atmospheric 

Administration (NOAA), National Ocean Service (NOS), Center for Operational Oceanographic Products and Services 

(CO-OPS) - http://tidesandcurrents.noaa.gov/sltrends/sltrends.shtml (accessed August 16, 2012).

Figure 4. Number of US tide gauges reflecting RSL variations.

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Global SLR Scenarios supporting the US National Climate Assessment November 2012 | 7
(Figure 5a). In contrast, RSL in the western tropical 

Pacific (Guam, Kwajalein) has been rising much faster 

than the global trend since the early 1990s (Bromirski 

et al. 2011, Merrifield 2011). Recent studies suggest 

that wind patterns may be 

a primary cause for these 

variations, though the exact 

causes are a topic of active 

investigation.

Bromirski et al. (2011) 

concluded that RSL trends 

over the North Pacific are 

affected by wind stress 

patterns associated with 

the PDO, as well as strong, 

shorter-term fluctuations 

related to the ENSO (Figure 

5b, c). When the PDO 

shifts, wind stress shifts 

between the eastern and 

western boundary of the 

North Pacific Ocean. RSL 

rises faster due to greater 

wind stress curl, the vertical 

component of wind stress 

(see Appendix 1) (Bromirski 

et al. 2011). Bromiski et al. 

(2011) attribute the recent 

trend of below global mean 

SLR along the eastern 

boundary of the North 

Pacific to anomalous wind 

stress curl patterns after the 

mid-1970s regime shift in 

the PDO. Recent levels of 

mean wind stress curl over 

the entire North Pacific 

basin have approached 

pre-regime shift levels, and 

may signal a return shift in 

the PDO. Depending on 

associated changes in wind 

patterns, this shift could result in a persistent period 

of RSL rise along the eastern North Pacific that is 

greater than the global trend (Bromirski et al. 2011).

Similarly, others have concluded that wind patterns 

have contributed to greater RSL rise in the western 

tropical Pacific over the past two decades (Figure 5a) 

(Timmerman et al., 2010; Merrifield, 2011; Merrifield 

and Maltrud, 2011; Becker et 

al. 2012). Merrifield (2011) 

relates this trend to a steady 

increase in the trade winds 

since the early 1990s, rather 

than to interannual ENSO 

events (Figure 5a). However, 

Feng et al. (2010) relate this 

trend to the PDO and low 

frequency ENSO variability.

The recent shift in the PDO 

could cause substantial 

changes in north Pacific winds 

and, consequently, altered RSL 

rise. The rate and magnitude 

of changes in RSL rise would 

depend on the magnitude of 

changes in the PDO, the speed 

and pattern of the trade winds, 

and other regional anomalies 

in wind patterns (Bromirski 

et al. 2011, Merrifield 2011). 

Sea level anomalies related 

to ENSO along the eastern 

Pacific coast can result in as 

much as 20 cm of RSL rise 

for an entire winter season (a 

period of high tides, storms, 

and large waves) (Bromirski 

et al 2003, Bromirski and 

Flick 2008). Regional wind 

patterns are difficult to 

forecast over longer time scales 

(decadal to multi-decadal). 

Although global MSL rise is 

a fundamental consideration, 

RSL height variability along 

coasts can be more critical and 

should be taken into account in assessing local impacts, 

particularly in the North Pacific where the amplitude 

of interannual variability is high. 

Figure 5. (a) Least squares trends in satellite altimetry 

sea level height (SLH) across the North Pacific basin over 

the 1992 to 2009 time period. Observed tide-gauge 

sea level monthly anomalies, with 3-yr running means 

(red lines) at (b) San Francisco (SFO) and (c) La Jolla (SIO) 

(locations in (a)). Note the near-zero trend along the US 

West coast in (a) that is reflected in the SFO and SIO tide 

gauge records since about 1980 (Bromirski et al. 2011)

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8 | November 2012
3.2 Regional patterns in the Gulf of Mexico

RSL along the western coast of the Gulf of 

Mexico (e.g. Texas and Louisiana) has been rising 

substantially faster (5 to 10 mm/yr) than the global 

trend (1.7 mm/yr) primarily due to land subsidence. 

Subsidence rates are highest in the Mississippi River 

Deltaic Plain where geologic and human-induced 

factors are compounded. Geological studies suggest 

that the entire US Gulf Coast region is subsiding 

as a result of glacio-isostatic adjustment (GIA - see 

Section 5.1 for further description) (Mitrovica and 

Milne 2002, Gonzales and Tornquist 2006). Human 

induced factors include consolidation of thick layers 

of loose, unconfined 

sediments; aquifersystem compaction due 

to fluid withdrawal; 

and drainage of organic 

soils.

In addition to high rates 

of RSL rise, evidence 

suggests that mean sea 

level in the Gulf of 

Mexico has been rising 

faster than global trend 

over the past 60 years (IPCC 2007a). Satellite records 

suggest that the average elevation of the sea surface 

in the Gulf of Mexico has increased 3.3 ± 0.4 mm/yr 

since 1992, with some offshore areas potentially rising 

as fast as 5.8 mm/yr (Figures 6 and 7). The higher rates 

of RSL rise across the entire basin may be the result of 

multi-decadal variability or large basin oceanographic 

effects given that the Gulf of Mexico is a large, shallow, 

semi-enclosed basin.

Decadal anomalies in sea level from Galveston, TX 

to Wilmington, DE are coherent and range ± 5 cm 

(Figure 8). While 5 cm of sea level may not seem 

significant, water levels exceeding the height of coastal 

protection by this amount 

can cause substantial damage. 

As seen in the Pacific Ocean 

region, it is important to 

consider interannual and 

decadal anomalies. Experts 

and decision makers 

developing risk-averse, worstcase scenarios in specific 

regions and locations may 

account for the maximum 

observed anomaly.

Figure 7. Northcentral Gulf of Mexico satellite altimetry record 

(1993 to 2011) (Figure source: Brady Couvillion, US Geological 

Survey, Lafayette, LA).

Figure 6. Sea level change in the Gulf of Mexico basin as 

determined from a combination of six satellite altimetry 

records (1993 to 2010). 

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Global SLR Scenarios supporting the US National Climate Assessment November 2012 | 9
3.3 Regional patterns in the US Atlantic

RSL has been rising along the entire US Atlantic 

coast, and it has been rising faster in the Mid-Atlantic 

region (Virgnia, Maryland, and Delaware including 

the Chesapeake Bay) and the Carolinas primarily due 

to subsidence (Figure 3) (CCSP 2009). In the MidAtlantic region, possible causes of subsidence include 

sediment consolidation, GIA, groundwater extraction, 

and tectonics (Poag et al. 2004, Hayden et al. 2008). 

GIA is less of a factor in the Carolinas, where possible 

causes of subsidence are groundwater extraction and 

sediment compaction. 

Sallenger et al. (2012) detect a “hotspot” of accelerated 

sea level rise along the 1,000 km of coast from Cape 

Hatteras to above Boston and suggest it may be 

related to circulation changes in the North Atlantic 

Ocean. Previous analyses along the US Atlantic coast 

using long records of variable length did not detect 

this acceleration (Houston and Dean 2011). The 

presence or absence of accelerations in SLR and the 

causal mechanisms remain an area of scientific debate. 

However, the observed rates of RSL rise and the 

evidence presented by Sallenger et al (2012) and more 

recently by Boon (2012) are sufficient to suggest that 

experts and decision makers may consider accelerated 

rates along the northeastern stretch of coast into their 

risk-averse, worst-case scenarios.

4. Global Mean Sea Level Rise Scenarios

We have very high confidence (>9 in 10 chance) 

that global mean sea level will rise at least 0.2 meters 

(8 inches) and no more than 2.0 meters (6.6 feet) 

by 2100. Global mean SLR can be estimated from 

physical evidence (e.g. observations of sea level and 

land ice variability) (Pfeffer et al. 2008, Katsman et 

al 2011, Jevrejeva et al 2012), expert judgment (NRC 

1987, NRC 2011, NRC 2012), general circulation 

models (GCMs) (IPCC 2007a, Yin 2012), and from 

semi-empirical methods that utilize both observations 

Figure 8. Monthly mean tide gauge sea levels from the Gulf of Mexico (Galveston, TX) to the western North Atlantic 

(Wilmington, DE). A mean annual cycle and trend are removed, and each series is low-passed with a convolution filter passing 

>90% amplitude at periods longer than 1.9 years (Thompson 2011). 

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10 | November 2012
and GCMs (Grinsted et al. 2009, Jevrejeva 

et al. 2010, Vermeer and Rahmstorf 

2009, Horton et al. 2008, Rahmstorf et 

al 2012). We base our confidence in the 

range of estimated global mean SLR on 

a wide range of the estimates reflected in 

the scientific literature (Figure 9), using 

guidance set forth by the NCA (Moss and 

Yohe 2011, IPCC 2001 and 2007a) (Table 

1). This approach has also been applied 

by the New York City Panel on Climate 

Change (NPCC 2010).

In recent decades, the dominant 

contributors to global SLR have been 

ocean warming and ice sheet loss. Many 

previous studies, including the IPCC, 

assume ocean warming to be the dominant 

contributor. However, the NRC (2012) 

recently reports that advances in satellite 

measurements indicate ice sheet loss as 

a greater contributor to global SLR than 

ocean warming over the period of 1993 

to 2008. Our scenarios are based on four 

estimates of global SLR by 2100 that reflect 

different degrees of ocean warming and ice 

sheet loss (Table 2 and Figure 10).

Figure 9. End of century (~2090 – 2100) estimates for global mean 

sea level rise in meters. Meehl et al (2007) is based on climate model 

projections for the IPCC and outlined in black. NRC (1987, 2011, and 2012) 

is based on synthesis of the scientific literature and shown in light gray. 

Vermeer and Rahmstorf (2009), Horton et al (2008), Jevrejeva et al (2010), 

Grinsted et al (2009) are based on semi-empirical approaches and shown 

in dark gray. Pfeffer et al (2008) is a calculation of the maximum possible 

contribution from ice sheet loss and glacial melting and shown in black. 

Table 1. Confidence in the validity of a finding by considering (i) the quality of the evidence and (ii) the level of agreement 

among experts with relevant knowledge (based on Moss and Yohe 2011).

Confidence 

Level Possible Contributing Factors

Very High Strong evidence (established theory, multiple sources, consistent results, well documented 

and accepted methods, etc.), high consensus

High Moderate evidence (several sources, some consistency, methods vary and/or 

documentation limited, etc.), medium consensus

Medium Suggestive evidence (a few sources, limited consistency, models incomplete, methods 

emerging, etc.), competing schools of thought

Low

Inconclusive evidence (limited sources, extrapolations, inconsistent findings, poor 

documentation and/or methods not tested, etc.), disagreement or lack of opinions 

among experts

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Global SLR Scenarios supporting the US National Climate Assessment November 2012 | 11
4.1 Key Uncertainties on the Global SLR Scenarios

At this stage, the greatest uncertainty surrounding 

estimates of future global SLR is the rate and magnitude 

of ice sheet loss, primarily from Greenland and West 

Antarctica. Our Highest Scenario of global SLR by 

2100 is derived from a combination of estimated ocean 

warming from the IPCC AR4 global SLR projections 

and a calculation of the maximum possible glacier and 

ice sheet loss by the end of the century (Pfeffer et al 

2008). The Highest Scenario should be considered in 

situations where there is little tolerance for risk (e.g. 

new infrastructure with a long anticipated life cycle 

such as a power plant).

Our Intermediate-High Scenario is based on an 

average of the high end of semi-empirical, global 

SLR projections (Grinsted et al. 2009, Jevrejeva et al. 

2010, Vermeer and Rahmstorf 2009, Horton et al. 

2008). Semi-empirical projections utilize statistical 

relationships between observed global sea level change, 

including recent ice sheet loss, and air temperature. 

Our Intermediate-Low Scenario is based on 

the upper end of IPCC Fourth Assessment 

Report (AR4) global SLR projections 

resulting from climate models using the B1 

emissions scenarios. The Intermediate-High 

Scenario allows experts and decision makers 

to assess risk from limited ice sheet loss. The 

Intermediate Low Scenario allows experts and 

decision makers to assess risk primarily from 

ocean warming.

Figure 10. Global mean sea level rise scenarios. Present Mean Sea Level (MSL) for the US coasts is determined from the 

National Tidal Datum Epoch (NTDE) provided by NOAA. The NTDE is calculated using tide gauge observations from 1983 

– 2001. Therefore, we use 1992, the mid-point of the NTDE, as a starting point for the projected curves. The Intermediate 

High Scenario is an average of the high end of ranges of global mean SLR reported by several studies using semi-empirical 

approaches. The Intermediate Low Scenario is the global mean SLR projection from the IPCC AR4 at 95% confidence interval. 

Table 2. Global SLR Scenarios 

Scenario SLR by 2100 (m)* SLR by 2100 (ft)*

Highest 2.0 6.6

Intermediate-High 1.2 3.9

Intermediate-Low 0.5 1.6

Lowest 0.2 0.7

* Using mean sea level in 1992 as a starting point.

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12 | November 2012
The Lowest Scenario is based on a linear extrapolation 

of the historical SLR rate derived from tide gauge 

records beginning in 1900 (1.7 mm/yr). Global sea 

level has risen 0.2 meters (8 inches) over this period 

of record, and we anticipate at least another 8 inches 

by 2100. The rate of global mean SLR derived from 

satellite altimetry (1992 to 2010) has been substantially 

higher (3.2 mm/yr), approaching twice the rate of the 

longer historical record from tide gauges. However, 

the 18-year altimeter record is insufficient in duration 

for projecting century-scale global SLR. Trends 

derived from the shorter records are less reliable as 

projections because they are affected by interannual 

and decadal climate and oceanographic patterns that 

are superimposed upon the long-term rise of global sea 

level. The Lowest Scenario should be considered where 

there is a great tolerance for risk.

There is a highly significant correlation between 

observations of global mean SLR and increasing global 

mean temperature (Vermeer and Rahmstorf 2009, 

Rahmstorf et al. 2011), and the IPCC (2007a) and 

more recent studies (Schaeffer et al. 2012) anticipate 

that global mean sea level will continue to rise even if 

warming ceases. Our Highest Scenario is an upper limit 

for SLR by 2100, but the possibility exists that SLR 

could exceed this limit beyond this timeframe (Pfeffer et 

al 2008). Our Intermediate-Low and Lowest Scenarios 

are optimistic scenarios of future environmental change 

assuming rates of ice sheet loss and ocean warming 

slightly higher or similar to recent observations. 

4.2 Ice Sheet Loss

Other studies (e.g. Rohling et al. 2008) have arrived 

at even greater estimates of future global mean SLR 

than our Highest Scenario, but we are not confident 

in the plausibility of those estimates at this time. 

The IPCC AR4 produced some of the more widely 

used projections of global SLR for the 21st century 

(IPCC 2007a). The IPCC projections included ocean 

warming, contributions from glaciers, and modeled 

partial ice sheet contributions. The IPCC AR4 

estimates did not include, however, potential rapid 

dynamic response of Greenland and Antarctic Ice 

Sheets as reflected in our Highest Scenario. 

A growing body of recently published work suggests 

that, due to increasing loss, the great polar ice sheets 

in Greenland and Antarctica will become much more 

significant contributors to global SLR in the future 

(e.g., Rignot et al. 2011, Vermeer and Rahmstorf 2009, 

Van den Broeke et al 2011, NRC 2012). Ice sheet 

contributions to global mean SLR stem from mass loss 

brought about by melting and discharge of ice into the 

ocean at marine-terminating glaciers and ice streams 

(NRC 2012). Multiple reports indicate that mass loss 

of both the Greenland and Antarctic ice sheets may 

have accelerated over the past two decades, despite 

high inter-annual variability in space and time (Chen 

et al. 2011, Rignot et al. 2011, Van den Broeke 2011, 

NRC 2012). For example, regional variability of mass 

loss from the Greenland ice sheet (GIS) over the past 

few years shows that areas of accelerating deterioration 

changed from the southeast part of the ice sheet to the 

northwest part, suggesting high sensitivity of the GIS 

to regional climate (Chen et al. 2011). In Antarctica, 

ice loss is occurring in some coastal areas, and ice 

accumulation is occurring in interior Antarctica. 

While the balance between ice loss and accumulation 

remains an area of investigation, recent observations 

suggest that ice loss has been greater (King et al. 2012).

Most of the ice loss in Antarctica has come from the 

West Antarctic ice sheet (WAIS; Rignot et al. 2008). 

A significant portion of the WAIS is floating at or 

grounded below sea level, as are relatively smaller parts 

of the ice sheets in East Antarctica and Greenland. 

Floating ice shelves support land-based ice sheets. 

Current and future ocean warming below the surface 

make ice shelves susceptible to catastrophic collapse, 

which in turn can trigger increased ice discharge to the 

ocean (Rignot et al. 2004, Scambos et al. 2004, Jacobs 

et al. 2011, Joughlin and Alley 2011, Yin et al. 2011). 

Better understanding of how the polar ice sheets will 

respond to further changes in climatic conditions over 

the 21st century requires continued development of 

physical models (Price et al. 2011). 

Ice sheet losses will lower the gravitational attraction 

ice sheets have for surrounding seas, producing 

spatial variability in changes to global mean sea level 

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Global SLR Scenarios supporting the US National Climate Assessment November 2012 | 13
(Kopp et al. 2010; Mitrovica et al. 2001; Mitrovica 

et al. 2009). Although seemingly counterintuitive, 

sea level falls close to deteriorating ice sheets even 

though ice sheet losses are discharged into the adjacent 

sea. This lowering of sea level is due to gravitational 

effects that can cause SLR up to ~2,000 km from the 

melting ice sheet. SLR resulting from deterioration 

of the GIS is thought to be relatively lower than the 

global average for the contiguous US, Alaska, and US 

territories in the Caribbean Sea and relatively higher 

for Hawaii and US territories in the Pacific Ocean 

(Kopp et al. 2010). SLR resulting from deterioration 

of the WAIS is thought to be relatively higher than the 

global average for all states and territories of the US 

(Mitrovica et al. 2009).

4.3 Methods for Constructing Scenario Data 

Both the rate and magnitude of SLR are important 

for vulnerability and impact assessment because, 

as mentioned below, the time horizon is a critical 

factor affecting risk tolerance for coastal management 

actions. Even long-term coastal management actions 

(e.g. coastal habitat restoration) are sensitive to nearterm rates and amounts of SLR. To address these 

considerations, we provide the following methodology 

for creating curves, anchored to a specific date, and 

yielding estimates for specific time horizons. 

Future estimates for global mean SLR are relative 

to the current elevation of global mean sea level. 

It is important to select a starting point in time 

from which to move forward with the scenarios. 

Present Mean Sea Level (MSL) for the US coasts 

is determined from long-term NOAA tide gauge 

records and is referenced to the current National 

Tidal Datum Epoch (NTDE) provided by NOAA. 

The NTDE is a 19-year period with the current 

NTDE being 1983 to 2001. NOAA uses the 

NTDE as the basis for all tidal datums (i.e., Mean 

High Water and Mean Lower Low Water) and uses 

NTDE MSL as the reference for presentation of 

RSL trends (Figure 3). MSL for the NTDE is the 

mean of hourly heights observed over the entire 19-

year period. Because mean sea level is an average 

over the 19-year NTDE, the mean sea level value is 

associated with the mid-point of the NTDE, which 

is the year 1992. As the mid-point for the NTDE, 

1992 is selected as the start-point for our scenarios 

(Figure 10, also see Flick et al. 2012).

As described above, the Lowest Scenario is a 

linear extrapolation of the historic trend of 20th 

century tide gauge measurements. In contrast, the 

Highest, Intermediate-High and Intermediate-Low 

Scenarios represent possible future acceleration in 

global mean sea level rise and thus are not described 

by linear relationships. To represent the non-linear 

trajectory of SLR in these scenarios, the NRC 

(1987) and USACE (2011) scheme is adopted, 

wherein the future global mean SLR is represented 

by the following quadratic equation:

E(t) = 0.0017t + bt2

 (1)

in which t represents years, starting in 1992, b is a 

constant, and E(t) is the eustatic SLR, in meters, as 

a function of t. To fit the curves to our scenarios, as 

defined above, the constant b has a value of 1.56E04 (Highest Scenario), 8.71E-05 (IntermediateHigh Scenario), and 2.71E-05 (Intermediate-Low 

Scenario). It should be emphasized that this 

straightforward quadratic approach to the time 

evolution is chosen in part for its simplicity; there is 

no scientific reason or evidence to assume that SLR 

will evolve in precisely this smooth manner.

If it is necessary to estimate a projected rise in global 

mean sea level for any of the scenarios, but starting in 

a year more recent than 1992, the following equation 

can be used:

E(t2) – E(t1) = 0.0017(t2 – t1) + b(t2 – t1)2

 (2)

where t1 is the time between the beginning year of 

interest and 1992 and t2 is the time between the 

ending year of interest and 1992 (Knuuti 2002, Flick 

et al. 2012). For example, global mean SLR for any 

of the accelerating scenarios can be calculated over the 

period of time between 2011 and 2050 by using t1 = 

2011-1992 = 19 years and t2 = 2050-1992 = 58 years.

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14 | November 2012
3 Continental crust - The crust is the solid, outermost layer of the Earth 

that makes up the continents (continental crust), including mountain 

ranges, and that lies beneath the oceans (oceanic crust).

5. Enhancing the Global SLR Scenarios 

The development of sea level change scenarios (global, 

regional, and local) is an initial stage in conducting 

coastal vulnerability assessments (Figure 11). We 

recommend that the choice of scenarios involve 

interdisciplinary scientific experts, as well as coastal 

managers and planners who understand relevant 

decision factors. Three decision factors generally 

considered in the choice of sea level scenarios are: 

location, time horizon, and risk tolerance (Mote 2008). 

Location refers to the planning or management area 

for which assessment or analysis is being conducted. 

Time horizon refers to the committed life span of a 

particular use in a coastal area and varies depending 

on whether you are planning temporary flood control, 

building long-term infrastructure such as an airport 

or shipyard, or restoring or preserving ecosystem 

function. Finally, risk tolerance refers to a community’s 

or decision maker’s willingness to accept a higher or 

lower probability of impacts.

Risks associated with SLR may not be evident when 

considering sea level change in isolation from climate 

or over a narrowly defined coastal planning area. Power 

stations or airports at specific locations along the coast 

may be critically important to the regional or national 

economy and thus may be protected with a low tolerance 

for projected long-term, regional, or global scale 

impacts (e.g. a large levee). Such levels of protection, 

however, may have adverse effects on adjacent parts of 

the coast or create a false sense of reduced risk if sea 

level rises and coastal flooding increases (Smits et al. 

2006, Parris and Lacko 2009).

Additional information should be combined with 

the global scenarios to incorporate regional and local 

conditions when conducting risk analysis. These 

factors include regional mean sea level 

variability, local and regional vertical 

land movement, coastal environmental 

processes (geological, ecological, 

biological, and socio-economic), and the 

effect of extreme weather and climate 

on RSL. Much of this information is 

being prepared for the NCA, including 

scenarios of climate, land-use/land 

change, and different socio-economic 

conditions as well as analysis of changes 

in extreme weather and climate. The 

NOAA Coastal Services Center and the 

USGS also provide access to information 

via Digital Coast, including two 

companion reports on developing sea 

level scenarios (NOAA 2012, NOAA 

2010). As mentioned previously, 

regional and local sea level scenarios are 

beyond the scope of this report. We provide Table 3 as 

a basic template for those people who wish to build on 

our scenarios.

5.1 Vertical Land Movement (VLM)

Regional and local sea level scenarios should account 

for vertical land movement. Following the last glacial 

maximum, the Earth’s crust3

 began to rise in response 

to earlier subsidence under the weight of the ice. 

This process, post-glacial rebound, varies across the 

continent and may be a significant factor in vertical 

land movement in some areas. It is typically accounted 

for by estimating GIA.

Figure 11. Developing sea level scenarios (Nicholls et al 2011). MSL – mean sea 

level; ESL – Extreme sea level.

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Global SLR Scenarios supporting the US National Climate Assessment November 2012 | 15
GIA refers to the rise of the Earth’s crust that was 

depressed by the weight of continental ice sheets during 

the last glacial maximum (Appendix 1; Lambeck et 

al. 2010, Mitrovica et al. 2010). The reaction of the 

Earth’s crust to ice load changes is a relatively slow and 

delayed process dependent upon the viscosity of the 

mantle, on which the Earth’s crust rests. This reaction 

continues long after ice sheets melt and water volumes 

stabilize. For example, the continental crust is still 

experiencing post-glacial rebound from the reduction 

of ice sheets present during the last glacial maximum, 

which occurred approximately 21,000 years ago.

Surface deformations from VLM induced by GIA 

can raise or lower RSL, depending on the proximity 

to the prior ice sheet (Lambeck et al. 2010, Mitrovica 

et al. 2010). Glacial rebound in North America is 

largest around Hudson Bay, where the former ice sheet 

was both centered and thickest. Meanwhile, land is 

subsiding further south at and beyond the edges of 

the former ice sheet, in response to the rebound to 

the north. GIA is changing coastal land elevations 

at rates of mm-per-year. As a result, it is necessary to 

consider GIA in the analysis of sea level observations 

and trends. Recent progress in GIA models has 

reduced uncertainties in ice load history and mantle 

viscosity, improving interpretations of sea level analyses 

(Mitrovica et al. 2010, Peltier 2004).

The contribution of GIA to net changes in RSL varies 

for much of the US coastline and its island territories, 

with modeled rates ranging from +0.5 to +2.0 mm/yr for 

much of the mainland 

and northern Alaska 

(Figure 12). Portions 

of the Northeast and 

Northwest mainland 

coasts have modeled 

rates at the upper end 

of this range. Rates vary 

from slightly positive 

to slightly negative for 

only the most southern 

and northern latitudes 

of the mainland, as 

well as for much of 

Alaska and the island 

states and territories. 

Southern Alaska is the 

only region that shows 

locations with a falling 

RSL due to GIA effects, 

with modeled rates 

between -0.5 and -1.7 

mm/yr at a few sites.

With the advent of Global Positioning Systems (GPS), 

precise spatial estimates of vertical and horizontal land 

movement are becoming available. Using over three 

hundred and sixty GPS sites in Canada and United 

States, Sella et al. (2007) produced a map of “vertical 

velocities” which may be used to understand the 

rates of VLM that vary within an order of magnitude 

along much of the coastal region of the east and the 

south (Figure 13). Most of the GPS measurements 

demonstrated consistency with GIA models. The 

magnitude of subsidence along the eastern US is about 1 

to 2 mm. The international community has recognized 

Table 3. Template for developing regional or local sea level scenarios

Contributing Variables

Scenarios of Sea Level Change

Lowest 

Scenario

IntermediateLow ScenarioIntermediateHigh ScenarioHighest 

Scenario

Global mean sea level rise* (m) 0.2 0.5 1.2 2.0

Vertical Land Movement 

(subsidence or uplift)** 

Ocean Basin Trend***

(from tide gauges and satellites)

Total Relative Sea Level Change

Extreme Water Level (from 

existing flood models or 

long-term tide gauges)

* Equations from Section 4.3 can be used to calculate scenarios of sea level change over desired period 

and to populate the global mean SLR term in the first row. 

** This row can be populated using, in part, the information found in Sections 5.1.

*** This row can be populated using, in part, the information found in Sections 3.1, 3.2, 3.3 and 5.3.

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16 | November 2012
Figure 13. Vertical GPS site motions 

with respect to IGb00 (a reference plane) 

as estimated by Sella et al. (2007).

the need to upgrade the observational infrastructure to 

include co-location of continuous GPS receivers and 

tide gauges (see Continuous GPS Update). Nationally, 

NOAA has recognized the need to co-locate these 

systems as much as possible and has already integrated 

repeat static GPS measurements on tidal benchmarks as 

part of the operation and maintenance of the National 

Water Level Observation Network (NWLON).

At some locations along the coastline, VLM may 

be exacerbated by factors other than GIA. Other 

factors of VLM include, but are not limited to: plate 

tectonics; natural compaction of thick layers of loose, 

unconsolidated sediments; sediment compaction due 

to excessive withdrawal of groundwater, oil, or gas; 

and subsidence due to oxidation of organic soil. Sun 

et al. (1998) indicate that land subsidence due to 

groundwater withdrawal in southern New Jersey has 

increased from 2 cm to 3 cm over the past 40 years. 

Along the Gulf coast states, subsidence is widespread 

extending beyond the Mississippi Delta to Mississippi 

and the estimated rates are as high as 25 mm/year 

with much of the delta subsiding at 5 to 10 mm/yr 

(Gonzalez and Tornqvist 2006, Shinkle and Dokka 

2004). In Alaska, the uplift rates are much higher as 

they are caused by significant tectonic activity in the 

region as well as post-glacial rebound (Larsen et al. 

2003, Larsen et al. 2007).

Recent geodetic studies clearly document non-GIA 

VLM and/or RSL trends over spatial scales approaching 

100s of kilometers. For example, traditional geodesy 

and continuous global positioning systems (GPS) 

Figure 12. Contribution of GIA to net changes in RSL varies for much of the US coastline Alaska (A), Hawaii 

(B), Puerto Rico and the US Virgin Islands (C), and the contiguous US (D), as predicted by the ICE-5G(VM2) 

model (Peltier 2004). Rate locations are tide gauge sites in the Permanent Service for Mean Sea Level 

(PSMSL) dataset. Values account for sharp coastal gradients through use of a high spatial resolution model, 

and represent rates averaged over the 20th and 21st centuries. For US territories not shown, rates fall 

within the -0.5 to +0.5 mm/yr range.

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Global SLR Scenarios supporting the US National Climate Assessment November 2012 | 17
studies in the Cascadia subduction zone (Cascadia) 

that spans CA, OR, and WA suggest regional uplift 

signals in the range of 1 to 3mm/yr (Burgette et al. 

2009, Mazzotti et al. 2007). Whether this rate is 

constant over time depends on earthquake variability 

in Cascadia (Wang et al. 2003, Wang 2007). However, 

modern, observable rates in Cascadia essentially negate 

global mean SLR in Alaska and parts of Washington 

and Oregon. More detailed VLM data are provided for 

specific areas in California, including the San Francisco 

Bay area and the Los Angeles Basin (Burgmann et al. 

2005; Brooks et al. 2007). Deep subsidence in the 

Gulf of Mexico has been linked to a combination of 

groundwater withdrawal, regional tectonic loading on 

the Earth’s crust from the Mississippi River Delta, and 

possibly faulting (Dokka 2011). 

5.2 Extremes of Weather and Climate

Coastal managers are most immediately concerned 

with the effect that global, regional, and RSL changes 

have on coastal flooding. In addition to changes in 

mean sea level, consideration of future extremes is 

vitally important for planning and design of coastal 

infrastructure (Zhang et al. 2000). SLR can amplify 

factors that currently contribute to coastal flooding: 

high tides, storm surge, high waves, and high runoff 

from rivers and creeks (Cayan et al. 2008). All of these 

factors change during extreme weather and climate 

events and often have disproportionately high impacts 

in most coastal regions. Although a consensus has not 

yet been reached on how the frequency and magnitude 

of storms may change in coastal regions of the US, it is 

certain that higher mean sea levels increase the frequency, 

magnitude, and duration of coastal flooding associated 

with a given storm. Thus, considering the impact of 

different weather events combined with scenarios of 

sea level change is crucial in developing hazard profiles 

for emergency planning and vulnerability, impact, and 

adaptation assessments.

Several studies indicate that the number and duration 

of extreme high-water events increase during Atlantic 

Multidecadal Oscillation (AMO) warm phases 

around the Florida Peninsula (Park et al 2010a, Park et 

al 2010b, Park et al 2011). As mentioned previously, 

sea level anomalies related to ENSO along the eastern 

Pacific coast can result in as much as 20 cm of RSL 

rise for an entire winter season (a period of high tides, 

storms, and large waves) (Bromirski and Flick 2008). 

In the San Francisco Bay, global mean SLR and the 

ENSO related anomaly are projected to increase the 

number of sea level extremes (Cayan et al. 2008). 

Coastal vulnerability assessments in some urban centers 

of the US have incorporated SLR and climate scenarios 

into probabilistic flood projections. For example, the 

return period concept used in flood control projects 

provides a risk-based approach to select design flood 

conditions based on probability of occurrence (Horton 

et al 2010, Knowles 2010). The occurrence of storm 

surges and high tides have been incorporated into a 

Joint Probability Method (JPM) in an effort to provide 

probabilistic projections of extreme levels, but the 

JPM methods do not account for future changes in sea 

level and runoff due to climate change (Tomasin and 

Pirazzoli 2008, Liu et al. 2010). These methodologies 

may be particularly useful for incorporating sea level 

into a risk management framework as part of any 

assessment process. 

5.3 Dynamic Changes in Ocean Circulation

Regional and local sea level change scenarios also 

should reflect dynamic changes in ocean circulation, 

ice sheet losses, and mass redistributions associated 

with ice sheet losses, though this information 

is very limited at present. Climate models have 

forecast the slowing of the overturning circulation 

in the Atlantic from warming seawater in the north 

Atlantic, introduction of fresh water from GIS, and 

other sources. These factors could slow the boundary 

currents along the US east coast and raise sea levels 

in the northeast (Yin et al. 2009, Yin et al. 2010). 

These changes are not entirely independent from ice 

sheet loss, and can exacerbate or attenuate rises in sea 

level, depending on the region. Climate models forced 

by the SRES A1B scenario reveal a potential slowing 

in the Atlantic meridional overturning circulation 

(AMOC) and regional thermosteric and halosteric 

changes (Yin et al. 2010). Dynamical SLR resulting 

from ocean circulation patterns could be additive to 

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18 | November 2012
the global mean SLR trend, creating even higher sea 

levels and potential coastal impacts in Boston, New 

York, and Washington, DC when compared to the 

Southeastern US (Yin et al. 2010). 

5.4 Other stressors related to Coastal Vulnerability

Coastal land use and landforms affect inundation 

patterns on the coast. In addition to the aforementioned 

factors, a number of local coastal processes determine 

the configuration of coastal landforms (e.g. beach 

profiles, sea cliffs, barrier islands, marshes, atolls, etc.; 

see CCSP 2009). Specific locations where these factors 

dominate coastal processes are difficult to integrate 

into scenarios of environmental change (Cloern 

et al 2011). They should at least be considered in 

determining vulnerability and impacts. These factors 

vary substantially among US coastal areas and include, 

but are not limited to: 

	 • Sediment supply to the coast and associated

transport along the coast

	 • Elevation and range of tides

	 • Wave height, period, and slope of the shoreline

	 • Sediment accumulation rates – physical and

biogeochemical 

	 • Presence or absence and configuration of barriers,

whether human-made or natural, to coastal 

flooding and to constraints on shoreline change 

	 • Permafrost decline – a unique driver of coastal

elevation change in northern Alaska that controls, 

in some locales, the retreat of coastal bluffs.

6. Conclusions

Based on a large body of science, we identify four 

scenarios of global mean SLR ranging from 0.2 meters 

(8 inches) to 2.0 meters (6.6 feet) by 2100. These 

scenarios provide a set of plausible trajectories of global 

mean SLR for use in assessing vulnerability, impacts, 

and adaptation strategies. None of these scenarios 

should be used in isolation, and experts and coastal 

managers should factor in locally and regionally specific 

information on climatic, physical, ecological, and 

biological processes and on the culture and economy 

of coastal communities. Scientific observations at the 

local and regional scale are essential to action, but 

global phenomena, such as SLR, can influence those 

conditions creating unanticipated impacts at the local 

scale, especially over longer time horizons. Thousands 

of structures along the US coast are over fifty years 

old including vital storm and waste water systems. 

Thus, coastal vulnerability, impact, and adaptation 

assessments require an understanding of the long-term, 

global and regional drivers of environmental change.

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Global SLR Scenarios supporting the US National Climate Assessment November 2012 | 19
Ablain, M., A. Cazenave, et al. (2009). “A new assessment of the error budget of global mean sea level rate 

estimated by satellite altimetry over 1993-2008.” Ocean Science 5(2): 193-201.

Becker, M., B. Meyssignac, C. Letetrel, W. Llovel, A. Cazenave, and T. Delcroix (2012) Sea level variations 

at tropical Pacific islands since 1950, Global and Planetary Change, 80-81, 85-98.

Berger WH (2008) Sea level in the late Quaternary: patterns of variation and implications. Int J Earth Sci 

97:1143-1150, doi:10.1007/s00531-008-0343-y

Boon, John D. (2012) “Evidence of Sea Level Acceleration at U.S. and Canadian Tide Stations, Atlantic Coast, 

North America” Journal of Coastal Research, 28(6) 1437:1445.

Bromirski, P., R.E. Flick and D.R. Cayan, 2003: Storminess Variability Along the California Coast: 1858-2000. 

J. Climate, 16(6), 982-993.

Bromirski, P., and R.E. Flick 2008. Storm surge in the San Francisco Bay/Delta and nearby coastal locations. 

Shore and Beach, vol. 76, no. 3 pp 29 - 37. 

Bromirski, P.D., A.J. Miller, R.E. Flick, and G. Auad (2011). Dynamical suppression of SLR along the Pacific 

coast of North America: Indications for imminent acceleration, J. Geophys. Res. – Oceans, 116, C07005, 

doi:10.1029/2010JC006759. 

Brooks, B., M. A. Merrifield, J. Foster, C. L. Werner, F. Gomez, M. Bevis, and S. Gill (2007), Space geodetic 

determination of spatial variability in relative sea level change, Los Angeles Basin, Geophys. Res. Lett., 34, 

L01611, doi:10.1029/2006GL028171.

Burgette, R.J., Weldon II, R.J., and D.A. Schmidt. 2009. Interseismic uplift rates for western Oregon and 

along-strike variation in locking on the Cascadia subduction zone. JOURNAL OF GEOPHYSICAL 

RESEARCH, VOL. 114, B014

Bürgmann, R., Hilley, G., Ferretti, A., and F. Novali. 2005. Resolving vertical tectonics in the San Francisco 

Bay Area from permanent scatterer InSAR and GPS analysis. Geology v. 34 no. 3 p. 221-224

Cayan, D.R., P.D. Bromirski, K. Hayhoe, M. Tyree, M..D. Dettinger and R.E. Flick, 2008: Climate change 

projections of sea level extremes along the California coast. Climatic Change, 87, (Suppl 1):S57-S73, 

doi:10.1007/s10584-007-9376-7.

CCSP, 2009: Coastal Sensitivity to Sea-Level Rise: A Focus on the Mid-Atlantic Region. A report by the US 

Climate Change Science Program and the Subcommittee on Global Change Research. [James G. Titus 

(Coordinating Lead Author), K. Eric Anderson, Donald R. Cahoon, Dean B. Gesch, Stephen K. Gill, 

Benjamin T. Gutierrez, E. Robert Thieler, and S. Jeffress Williams (Lead Authors)]. US Environmental 

Protection Agency, Washington D.C., USA, 320 pp.

Chen JL, Wilson CR, Tapley BD (2011) Interannual variability of Greenland ice losses from satellite gravimetry. 

J Geophys Res 116:B07406 doi:10.1029/2010JB007789

Church, J. A. and N.J. White. 2011. Sea-level rise from the late 19th to the early 21st Century. Surveys in 

Geophysics, doi:10.1007/s10712-011-9119-1 

Cloern JE, Knowles N, Brown LR, Cayan D, Dettinger MD, et al. (2011) Projected Evolution of California’s 

San Francisco Bay-Delta-River System in a Century of Climate Change. PLoS ONE 6(9): e24465. 

doi:10.1371/journal.pone.0024465

Crowell, M, Coulton, K, Johnson, C, Westcott, J, Bellomo, D Edelman, S and E Hirsch. 2010. An Estimate of 

the U.S. Population Living in 100-Year Coastal Flood Hazard Areas. Journal of Coastal Research, v. 26, 

no. 2, 201 – 211.

References

20 | November 2012
Dokka, R. 2011. The role of deep processes in late 20th century subsidence of New Orleans and coastal areas 

of southern Louisiana and Mississippi. JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 116, 

B06403, 25 PP

Feng, M., M. J. McPhaden, and T. Lee (2010), Decadal variability of the Pacific subtropical cells and their 

influence on the southeast Indian Ocean, Geophys. Res. Lett., 37, L09606, doi:10.1029/2010GL042796

Flick E. R, Knuuti, K., and Gill, S.K. (2012) Matching Mean Sea Level Rise Projections to Local Elevation 

Datums. J. Waterway, Port, Coastal, Ocean Eng. doi: 10.1061/(ASCE)WW.1943-5460.0000145

González, J.L. and Törnqvist, T.E., 2006. Coastal Louisiana in crisis: Subsidence or sea level rise? 

Eos, 87: 493, 498.

Gray, S. 2011. From Uncertainty to Action: Climate Change Projections and the Management of Large 

Natural Areas. BioScience 61(7): 504-505. 

Grinsted, A., J. C. Moore, and S. Jevrejeva (2009), Reconstructing sea level from paleo and projected 

temperatures 200 to 2100AD, Clim. Dyn., doi:10.1007/s00382-008-0507-2.

Hayden, T., Kominz, M., Powars, D., Edwards, L., Miller, K., Browning, J., and Kulpecz, A. (2008) Impact 

effects and regional tectonic insights: Backstripping the Chesapeake Bay impact structure. Geology, 

v. 36, p. 327-330

Hearty, P. J., J. T. Hollin, A. Neumann, M. O’Leary, and M. McCulloch (2007), Global sea‐level fluctuations 

during the last interglaciation (MIS 5e), Quat. Sci. Rev., 26, 2090–2112, doi:10.1016/j.quascirev. 

2007.06.019.

Henrichs, T., M. Zurek, B. Eickhout, K. Kok, C. Raudsepp-Hearne, T. Ribeiro, D. van Vuuren, nd A. Volkery. 

2010. “Scenario development and analysis for forward-looking ecosystem assessments.” In Ecosystems and 

human well-being: A manual for assessment practitioners, edited by Neville Ash, Hernan Blanco, Keisha 

Garcia, Thomas Tomich, Bhaskar Vira, Monika B. Zurek and Claire Brown.

Horton, R. M., V. Gornitz, D. A. Bader, A. C. Ruane, R. Goldberg, and C. Rosenzweig, 2011: Climate Hazard 

Assessment for Stakeholder Adaptation Planning in New York City. J Appl Meteorol Clim, 50, 2247-2266. 

doi:10.1175/2011JAMC2521.1.

Horton, R, Gornitz, V, Bowman, M, and Blake, R (2010) Chapter 3: Climate observations and projections in 

Annals of the New York Academy of Sciences - Volume 1196 Climate Change Adaptation in New York 

City: Building a Risk Management Response: New York City Panel on Climate Change 2010 Report

Horton, Radley, Herweijer, Celine, Rosenzweig, Cynthia, Liu, Jiping, Gornitz, Vivien and Ruane, Alex C. 

(2008), Sea level rise projections for current generation CGCMs based on the semi-empirical method, 

Geophysical Research Letters, Vol. 35, L02715, doi: 10.1029/2007GL032486, 2008

Houston, J. R., and R. G. Dean (2011). Sea-level acceleration based on US tide gages and extensions of previous 

global-gage analyses, J. Coastal Res., 27, 409-417.

http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1251&context=scipapers

Intergovernmental Panel on Climate Change (IPCC) (2000) Special Report on Emissions Scenarios. 

(Nakicenovic, N., and R. Swart, eds.). Cambridge University Press, Cambridge, United Kingdom. 

http://www.grida.no/climate/ipcc/emission/

References

Global SLR Scenarios supporting the US National Climate Assessment November 2012 | 21
IPCC (2001) Climate Change 2001: the scientific basis. Contribution of Working Group 1 to the Third 

Assessment Report of the Intergovernmental Panel on Climate Change, edited by J. T. Houghton, Y. Ding, 

D. J. Griggs, M. Noguer, P. J. van der Linden, X. Dai, K. Maskell and C. A. Johnson (eds). Cambridge 

University Press, Cambridge, UK, and New York, USA, 2001.

IPCC (2007a) Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the 

Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, 

M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge 

University Press, Cambridge, United Kingdom and New York, NY, USA.

IPCC (2007b) IPCC Fourth Assessment Report Annex 1: Glossary. In: Climate Change 2007: The Physical 

Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental 

Panel on Climate Change (Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. 

Tignor, and H. L. Miller, eds.). Cambridge University Press, Cambridge, United Kingdom and New York, 

NY, USA. 

Jacobs SS, Jenkins A, Giulivi CF, Dutrieux P (2011) Stronger ocean circulation and increased melting under 

Pine Island Glacier ice shelf. Nat Geosci 4:519-523

Jevrejeva S, Moore JC, Grinsted A. 2010. How will sea level respond to changes in natural and anthropogenic 

forcings by 2100? Geophysical Research Letters 37

Jevejeva, S., J.C. Moore, A. Grinsted (2012) Se a Projections to AD2500 with a new generation of climate change 

scenarios, Global and Planetary Change, 80-81, 14-20.

Joughin, I, and R.B. Alley. 2011. Stability of the West Antarctic ice sheet in a warming world. Nature 

Geoscience 4, 506–513.

Katsman, CA, Sterl, A, Beersma, JJ, van den Brink, HW, Church, JA, Hazeleger, W, Kopp, RE, Kroon, D, 

Kwadijk, J, Lammersen, R, Lowe, J, Oppenheimer, M, Plag, H-P, Ridley, J, von Storch, H, Vaughan, DG, 

Vellinga, P, Vermeersen, LLA, van de Wal, RSW & Weisse, R 2011, ‘Exploring high-end scenarios for local 

sea level rise to develop flood protection strategies for a low-lying delta-the Netherlands as an example’ 

Climatic Change, vol 109, no. 3-4, pp. 617-645.

Kawamura, K., Parrenin, F., Lisiecki, L., Uemura, R., Vimeux, F., Severinghaus, J.P., Hutterli, M., Nakazawa, T., 

Aoki, S., Jouzel, J., Raymo, M., Matsumoto, K., Nakata, H., Motoyama, H., Fujita, S., Goto-Azuma, K., 

Fujii, Y., and Watanabe, O. 2007. Northern Hemisphere forcing of climatic cycles in Antarctica over the 

past 360,000 years. Nature 448: 912-916

Kemp, A. C., Horton, B.P., Donnelly, J.P., Mann, M.E., Vermeer, M., Rahmstorf, S. 2011. Climate related 

sea-level variations over the past two millennia. Proceedings of the National Academy of Sciences. 

DOI 10.1073 PNAS 1015619108

King, M.A., R.J. Bingham, O. Moore, P.L. Whiehouse, M.J. Bentley, and G.A. Milne (2012). Lower 

satellite-gravimetry estimates of Antarctic sea-level contribution, Nature, doi:10.1038/nature11621.

Knowles, Noah. 2010. Potential Inundation Due to Rising Sea Levels in the San Francisco Bay Region. 

California Climate Change Center. San Francisco Estuary and Watershed Science, 8:1.

Knuuti, K. (2002) Planning for Sea-Level Rise: U.S. Army Corps of Engineers Policy. Solutions to Coastal 

Disasters ‘02, ASCE 2002

References

22 | November 2012
Kopp, R., F. J. Simons, J. X. Mitrovica, A. Maloof, and M. Oppenheimer (2009), Probabilistic assessment of 

sea level during the Last Interglacial stage, Nature, 462, 863–867, doi:10.1038/nature08686.

Kopp RE, Mitrovica JX, Griffies, Yin J, Hay CC, Stouffer RJ (2010) The impact of Greenland melt on local 

sea levels: a partially coupled analysis of dynamic and static equilibrium effects in idealized water-hosing 

experiments. Clim Change 103:619-625

Lambeck K., Woodroffe C.D., Antonioli F, Anzidei M, Gehrels WR, Laborel J, Wright AJ (2010) 

Paleoenvironmental records, geophysical modeling, and reconstruction of sea-level trends and variability 

on centennial and longer timescales. In: Church JA, Woodworth PL, Aarup T, Wilson WS (eds) 

Understanding sea-level rise and variability. Blackwell Publishing Ltd, pp 61-121

Larsen, C. F., K. A. Echelmeyer, J. T. Freymueller, and R. J. Motyka (2003) Tide gage records of uplift along the 

northern Pacific-North American plate boundary, 1937 to 2001, 2003. J. Geophys. Res., 108(B4), 2216, 

doi:10.1029/2001JB001685.

Larsen, C.F., R.J. Motyka, A.A. Arendt, K.A. Echelmeyer, and P.E. Geissler (2007) Glacier changes in southeast 

Alaska and northwest British Columbia and contribution to sea level rise. Journal of Geophysical Research 

112, doi:10.1029/2006JF000586

Liu J. C., Lence B. J., Isaacson M. (2010), Direct Joint Probability Method for Estimating Extreme Sea Levels, 

Journal of Waterway, Port, Coastal, and Ocean Engineering, 136 (1), 66-76, DOI: 10.1061/ASCE0733-

950X(2010)136:1(66).

Maine Department of Environmental Protection (MDEP) (2009) People and Nature Adapting to a Changing 

Climate: Charting Maine’s Course. Accessed at: http://www.maine.gov/dep/oc/adapt/Report_final.pdf. 

Accessed October 27, 2011

Mantua, Nathan J. et al.1997. A Pacific interdecadal climate oscillation with impacts on salmon production. 

Bulletin of the American Meteorological Society 78 (6): 1069–1079. 

Maryland Commission on Climate Change (MCCC) (2008) Maryland Climate Action Plan. Accessed at: 

www.mdclimatechange.us/ewebeditpro/items/O40F14798.pdf. Accessed on October 27, 2011.

Mazzotti, S., A. Lambert, N. Courtier, L. Nykolaishen, and H. Dragert (2007), Crustal uplift and sea level rise 

in northern Cascadia from GPS, absolute gravity, and tide gauge data, Geophys. Res. Lett., 34, L15306, 

doi:10.1029/2007GL030283.

McKay NP, JT Overpeck, BL Otto-Bliesner (2011) The role of ocean thermal expansion in Last Interglacial 

sea level rise. Geophysical Research Letters, 38, L14605, doi:10.1029/2011GL048280

McKenzie, E., A. Rosenthal et al. 2012. Developing scenarios to assess ecosystem service tradeoffs: Guidance 

and case studies for InVEST users. World Wildlife Fund, Washington, D.C.

Meehl, G.A., T.F. Stocker, W.D. Collins, P. Friedlingstein, A.T. Gaye, J.M. Gregory, A. Kitoh, R. Knutti, 

J.M. Murphy, A. Noda, S.C.B. Raper, I.G. Watterson, A.J. Weaver and Z.-C. Zhao, 2007. Global Climate 

Projections. In Solomon et al. (Eds.), Climate Change 2007: The Physical Science Basis. Contribution of 

Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. 

Cambridge University Press, Cambridge, United Kingdom and New York, NY, US, pp. 749-845.

Merrifield, M.A. (2011). A shift in western tropical Pacific sea level trends during the 1990s, J. Clim., 

24(15), 4126-4138. 

References

Global SLR Scenarios supporting the US National Climate Assessment November 2012 | 23
Merrifield, M. A., and M. E. Maltrud, (2011) Regional sea level trends due to a Pacific trade wind intensification, 

Geophys. Res. Lett., 38, L21605, doi:10.1029/2011GL049576.

Mitchum, G. (2011). Sea level changes in the Southeastern United States – Past, Present and Future. A report of 

the Florida Climate Institute and the Southeast Climate Consortium. 

Mitrovica JX, Tamisiea ME, Ivins ER, Vermeersen LLA, Milne GA, and Lambeck K (2010) Surface mass loading 

on a dynamic Earth: complexity and contamination in the geodetic analysis of global sea-level trends. 

In: Church JA, Woodworth PL, Aarup T, Wilson WS (eds) Understanding sea-level rise and variability. 

Blackwell Publishing Ltd, pp 285-325

Mitrovica, J.X., Gomez, N., Clark, P., 2009, The Sea-Level Fingerprint of West Antarctic Collapse, Science, 

Vol 323, p. 753.

Mitrovica, J. X. and G. A. Milne. 2002. On the origin of late Holocene sea-level highstands within equatorial 

ocean basins. Quat. Sci. Rev., 21, 2179–2190.

Mitrovica, J.X., Tamisiea, M, Davis, J. and Milne, G., 2001, Recent mass balance of polar ice sheets inferred 

from patterns of global sea-level change, Nature, Vol. 409.

Moss, R.H. and G. Yohe. 2011. Assessing and Communicating Confidence Levels and Uncertainties in the 

Main Conclusions of the NCA 2013 Report: Guidance for Authors and Contributors. National Climate 

Assessment Development and Advisory Committee (NCADAC). 

Moss, R., Edmonds, J. A., Hibbard, K.A., Manning, M.R., Rose, S.K., van Vuuren, D. P., Carter, T., Emori, S., 

Kainuma, M., Kram, T., Meehl, G. A., Mitchell, G. F. B., Nakicenovic, N., Riahi, K., Smith, S.J., Stouffer, 

R.J., Thomson, A.M., Weyant, J.P., and T.J. Wilbanks. 2010. The next generation of scenarios for climate 

change research and assessment. Nature 463, 747-756 (11 February 2010) | doi:10.1038/nature08823

Mote, P., Petersen, A., Reeder, S., Shipman, H. and Binder, L. (2008) Sea Level Rise in the Coastal Waters 

of Washington State. A report by the University of Washington – Climate Impacts Group and the 

Washington Department of Ecology. 

National Research Council (NRC). 1987. Responding to Changes in Sea Level: Engineering Implications. 

National Academy Press: Washington, D.C.

NRC. 2011. Climate Stabilization Targets: Emissions, Concentrations, and Impacts over Decades to Millennia. 

National Academy Press: Washington, D.C.

NRC. 2012. Sea-Level Rise for the Coasts of California, Oregon, and Washington: Past, Present, and Future. 

Washington, DC: The National Academies Press.

New York City Panel on Climate Change (NPCC). 2010. Climate Change Adaptation in New York City: 

Building a Risk Management Response. C. Rosenzweig & W. Solecki, Eds, prepared for use by the

New York City Climate Change Adaptation Task Force, Annals of the New York Academy of Sciences,

New York, NY. 349 pp.

Nicholls, R.J., Hanson, S.E., Lowe, J.A., Warrick, R.A., Lu, X., Long, A.J. and Carter, T.R. 2011. Constructing 

Sea-Level Scenarios for Impact and Adaptation Assessment of Coastal Area: A Guidance Document. 

Supporting Material, Intergovernmental Panel on Climate Change Task Group on Data and Scenario 

Support for Impact and Climate Analysis (TGICA), 47 pp.

National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). 2012. 

Incorporating Sea Level Change Scenarios at the Local Level. NOAA NOS Technical Report. 

Silver Spring, MD: NOAA NOS. 

References

24 | November 2012
National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). 2010. Technical 

Considerations for Use of Geospatial Data in Sea Level Change Mapping and Assessment. NOAA NOS 

Technical Report. Silver Spring, MD: NOAA NOS.

Otto-Bliesner BL, SJ Marshall, JT Overpeck, GH Miller, A u, CAPE Last Interglacial Project members (2006) 

Simulating Arctic Warmth and Icefield Retreat in the Last Interglaciation. Science 311:1751-1753

Overpeck JT, Otto-Bliesner BL, Miller GH, Muhs DR, Alley RB, Kiehl JT (2006) Paleoclimatic evidence for 

future ice-sheet instability and rapid sea-level rise. Science 311:1747-1750

Park J., Obeysekera J., Barnes J. (2010a). Temporal Energy Partitions of Florida Extreme Sea Level Events as a 

function of Atlantic Multidecadal Oscillation, Ocean Science, 6, 587-593 

Park J., Obeysekera J., Barnes J., Irizarry M., Park-Said W. (2010b) Climate Links and Variability of Extreme Sea 

Level Events at Key West, Pensacola, and Mayport Florida, ASCE Journal of Port, Coastal, Waterway and 

Ocean Engineering, 136 (6), 350-356

Park J., Obeysekera J., Irizarry M., Trimble P. (2011). Storm Surge Projections and Implications for Water 

Management in South Florida, Climatic Change, Special Issue: SLR in Florida: An Emerging Ecological 

and Social Crisis, Volume 107, Numbers 1-2, 109-128, 

Parris, A. and L. Lacko 2009: Climate change adaptation in the San Francisco Bay: A case for managed 

realignment. Shore and Beach, vol. 77, pp 46-52. 

Peltier WR (2004) Global glacial isostasy and the surface of the ice-age Earth: the ICE-5G (VM2) model 

and GRACE. Annu. Rev. Earth Planet Sci. 32:111-149

Pfeffer WT, Harper JT, O’Neel S (2008) Kinematic constraints on glacier contributions to 21st century 

sea-level rise. Science 321:1340–1343

Poag, C.W., Koeberl, Christian, Reimold, W.U., 2004, The Chesapeake Bay Crater, Springer, Berlin, Heidelberg, 

New York, 522 p. 

Price SF, Payne AJ, Howat IM, Smith BE (2011) Committed sea-level rise for the next century from Greenland 

ice sheet dynamics during the past decade. Proc Natl Acad Sci USA 108:8978-8983

Rahmstorf, Stefan. 2007. A Semi-Empirical Approach to Projecting Future Sea-Level Rise, Science Vol. 315

Rahmstorf, S., Perrette, M., and M. Vermeer. 2011. Testing the robustness of semi-empirical sea level projections. 

Climate Dynamics. Volume 39, Numbers 3-4 (2012), 861-875

Rignot, E. J., G. Casassa, P. Gogineni, W. Krabill, A. Rivera, and R. Thomas. 2004. Accelerated ice discharge 

from the Antarctic Peninsula following the collapse of Larsen B ice shelf. Geophys. Res. Lett., 31, L18401, 

doi:10.1029/2004GL0697. 

Rignot E, Bamber JL, van den Broeke MR, Davis C, Li Y, van de Berg VJ, van Meijgaard E (2008) Recent 

Antarctic ice mass loss from radar interferometry and regional climate modeling. Nat Geosci 1:106-110

Rignot E, Velicogna I, van den Broeke MR, Monaghan A, Lenaerts J (2011) Acceleration of the contribution of 

the Greenland and Antarctic ice sheets to SLR. Geophys Res Lett 38:L05503 doi:10.1029/2011GL046583

Rohling, E.J., Grant, K., Hemleben, C., Siddall, M., Hoogakker, B.A.A., Bolshaw, M. and Kucera, M. (2008) 

Letter. High rates of sea-level rise during the last interglacial period. Nature Geoscience, 1, 38-42. 

(doi:10.1038/ngeo.2007.28) 

Sallenger, A., Doran, K, and Howd, P., 2012, Hotspot of accelerated sea-level rise on the Atlantic coast of North 

America, Nature Climate Change, DOI: 10.1038/NCLIMATE1597. 

References

Global SLR Scenarios supporting the US National Climate Assessment November 2012 | 25
San Francisco Bay Conservation and Development Commission (SFBCDC) (2011) Living with a Rising Bay. 

Available: http://www.bcdc.ca.gov/BPA/LivingWithRisingBay.pdf. Accessed October 27, 2011. 

Scambos, T.A., J.A. Bohlander, C.A. Shuman, and P. Skvarca. 2004. Glacier acceleration and thinning after ice 

shelf collapse in the Larsen B embayment, Antarctica. Geophys. Res. Lett., 31(18), L18402.

Schaeffer, M., Hare, W., Rahmstorf, S., and M. Vermeer. 2012. Long-term sea-level rise implied by 1.5°C and 

2°C warming levels, Nature Climate Change, doi:10.1038/nclimate1584 

Southeast Florida Regional Climate Change Compact Technical Ad hoc Work Group (SFRCCC). 2011. A 

Unified Sea Level Rise Projection for Southeast Florida. A document prepared for the Southeast Florida 

Regional Climate Change Compact Steering Committee. 27 p

Sella, G.F., Stein, S., Dixon, T.H., Craymer, M., James, T.S., Mazzotti, S. and R.K. Dokka. 2007. Observation 

of glacial isostatic adjustment in ‘‘stable’’ North America with GPS. Geophysical Research Letters, v. 34

Shinkle, K., and Dokka, R. K., 2004, Rates of vertical displacement at benchmarks in the lower Mississippi 

Valley and the northern Gulf Coast: NOAA Technical Report 50, 135 p.

Smits, A.J.M., Nienhuis, P.H., and Saeijs, H.L.F. 2006. Changing Estuaries, Changing Views. Hydrobiologia 

565: 339–355.

Sun. H., Grandstaff. D., R. Shagam., Land subsidence due to groundwater withdrawal: potential damage 

of subsidence and sea level rise in southern New Jersey, USA, Environmental Geology, Vol.37, 1999, 

PP.290-296.

Thompson, P. T. (2011). Sea surface height: A versatile climate variable for investigations of decadal change. 

(Doctoral dissertation).

Timmermann, A., S. McGregor, and F.-F. Jin (2010) Wind effects on past and future regional sea level trends 

in the southern Indo-Pacific, J. Clim, 23, 4429-4437.

Titus, J.G., Hudgens, D.E., Trescott, D.L., Craghan, M., Nuckols, W.H., Hershner, C.H., Kassakian, 

J.M., Linn, C.J., Merritt, P.G., McCue, T.M., O’Connell, J.H., Tanski, J., and J Wang (2009) State and 

local governments plan for development of most land vulnerable to rising sea level along the US Atlantic 

coast. Environ. Res. Lett. 4

Titus James G. and Vijay Narayanan. (1995). The Probability of Sea Level Rise, U.S. Environmental Protection 

Agency. 186 pp. EPA 230-R95-008.

Tomasin A., and P. A. Pirazozoli. (2008). Extreme Sea Levels in the English Channel: Calibration of the Joint 

Probability Method, Journal of Coastal Research, 24(4C),1-13.

US Army Corps of Engineers (2011). Incorporating Sea-Level Change Considerations in Civil Works Programs, 

EC 1165-2-212.

Van den Broeke, M, Bamber, J, Lanaerts, J, and E. Rignot. 2011. Ice Sheets and Sea Level: Thinking Outside the 

Box. Surveys in Geophysics. DOI 10.1007/s10712-011-9137-Z

Vermeer M, Rahmstorf S (2009) Global sea level linked to global temperature. Proc Natl Acad Sci USA 

106:21527–21532

Wang, K., R. Wells, S. Mazzotti, R. D. Hyndman, and T. Sagiya (2003), A revised dislocation model of 

interseismic deformation of the Cascadia subduction zone, J.Geophys. Res., 108(B1), 2026

References

26 | November 2012
Wang, K. (2007), Elastic and viscoelastic models of crustal deformation in subduction earthquake cycles, in 

The Seismogenic Zone of Subduction Thrust Faults, edited by T. Dixon and J. C. Moore, pp. 540–575, 

Columbia Univ. Press, New York.

Weeks, D., Malone, P, and L. Welling. 2011. Climate change scenario planning: A tool for managing parks 

into uncertain futures. Park Science, Volume 28, Number 1. 

Yin J, Griffies SM, Stouffer RJ (2010) Spatial variability of SLR in twenty-first century projections. 

J Climate 23:4585–4607

Yin J, Overpeck JT, Griffies SM, Hu A, Russell JL, Stouffer RJ (2011) Different magnitudes of projected 

subsurface ocean warming around Greenland and Antarctica. Nat Geosci 4:524–528

Yin, J., Schlesinger, M., et al., 2009, Model projections of rapid sea-level rise on the northeast coast of the 

United States, Nature Geoscience, 2(4), p. 262-266.

Yin, J. (2012) Century to multi-century sea level rise projections from CMIP5 models, Geophysical Res. 

Lett., 39.

Zhang K., Douglas B. C., Leatherman S. P. (2000), Twentieth-Century Storm Activity along the U.S. East 

Coast, J. Climate, 13, p1748-61.

References

Global SLR Scenarios supporting the US National Climate Assessment November 2012 | 27
Sources for Appendix Definitions 

NOAA Center for Operational Oceanographic Products and Services

http://tidesandcurrents.noaa.gov/est/faq.shtml#q1

American Meteorological Survey (AMS) Glossary of Meteorology

http://amsglossary.allenpress.com/glossary

Accessed October 27, 2011

National Geodetic Survey

http://www.ngs.noaa.gov/GEOID/geoid_def.html

Accessed October 27, 2011

NOAA AOML

http://www.aoml.noaa.gov/phod/amo_faq.php

Accessed April 27, 2012; NOAA 

CPC

http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ensofaq.shtml#ENSO

Accessed April 27, 2012; 

USGS Earthquake Hazards program

http://earthquake.usgs.gov/learn/glossary/?term=subduction

Accessed April 27, 2012

Glossary of Terms

Anomaly – A mean sea level anomaly occurs when the 5-month average of the interannual variation is greater 

than 0.1 meters (4 inches) or less than -0.1 meters. 

Atlantic Meridional Overturning Circulation (AMOC) – The Meridional Overturning Circulation (MOC) 

is part of the global ocean circulation responsible for large-scale (on the order of 1000 km), low-frequency 

(interannual to multi-decadal), full-depth, meridional flux of mass, heat and freshwater. The Atlantic 

component of this circulation, the Atlantic Meridional Overturning Circulation (AMOC), has long been 

considered the dominant element of the MOC, in large part because the majority of water masses that compose 

the lower limb of the overturning circulation originate in the North Atlantic. (U.S. CLIVAR AMOC Planning 

Team, 2007: Implementation Strategy for a JSOST Near-Term Priority Assessing Meridional Overturning 

Circulation Variability: Implications for Rapid Climate Change. U.S. CLIVAR Report 2007-2, U.S. CLIVAR 

Office, Washington, DC, 20006, 23pp.)

Atlantic Multidecadal Oscillation (AMO) – The AMO is an ongoing series of long-duration changes in the sea 

surface temperature of the North Atlantic Ocean, with cool and warm phases that may last for 20-40 years at a 

time and with a difference of about 1°F between extremes. These changes are natural and have been occurring for 

at least the last 1,000 years.

El Niño Southern Oscillation (ENSO) – The ENSO cycle refers to the coherent, and sometimes very strong, 

year-to-year variations in sea-surface temperatures, convective rainfall, surface air pressure, and atmospheric 

circulation that occur across the equatorial Pacific Ocean. El Niño and La Niña represent opposite extremes in 

the ENSO cycle.

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28 | November 2012
Eustatic sea level rise – Eustatic sea level rise is a change in global average sea level brought about by an increase 

in the volume of the world ocean (IPCC 2007b)

Geoid – The equipotential surface of the Earth’s gravity field which best fits, in a least squares sense, global mean 

sea level.

Global mean sea level (GMSL) – Average height of the Earth’s oceans. Global mean sea level can change globally 

due to (i) changes in the shape of the ocean basins, (ii) changes in the total mass of water (see eustatic sea level rise 

below) and (iii) changes in water density. Sea level changes induced by changes in water density are called steric. 

Density changes induced by temperature changes only are called thermosteric, while density changes induced by 

salinity changes are called halosteric (IPCC 2007b)

Joint Probability Method – Joint Probability Method refers to flood risk calculations using multiple variables, 

such as waves, sea level, river flow, and rainfall, to develop probabilities of flooding.

Local sea level (LSL) – The height of the water as measured along the coast relative to a specific point on land. 

Mean Sea Level (MSL) – Refers to a tidal datum, or frame of vertical reference defined by a specific phase of the 

tide. Tidal datums are locally-derived based on observations at a tide station, and are typically computed over a 

19-year period, known as the National Tidal Datum Epoch (NTDE). The present 19-year reference period used 

by NOAA is the 1983-2001 NTDE. Tidal datums must be updated at least every 20-25 years due to global sea 

level rise. Some stations are more frequently updated due to high relative sea level trends.

Pacific Decadal Oscillation (PDO) – The Pacific Decadal Oscillation (PDO) is the predominant source of 

inter-decadal climate variability in the Pacific Northwest (PNW). The PDO (like ENSO) is characterized by 

changes in sea surface temperature, sea level pressure, and wind patterns (Mantua 1997).

Relative sea level (RSL) – The height of the sea with respect to a specific point on land. 

Steric (Halosteric & Thermosteric) Sea level changes induced by changes in water density are called steric. 

Density changes induced by temperature changes only are called thermosteric, while density changes induced 

by salinity changes are called halosteric.

Subduction – Subduction is the process of the oceanic lithosphere colliding with and descending beneath the 

continental lithosphere.

Wind stress – The resistance per unit area caused by wind shear. For example, the wind stress on the sea surface 

applies a friction force that can drive ocean currents.

Wind stress curl – The vertical component of the (mathematical) curl of the surface wind stress. The large-scale, 

long-term averaged wind stress curl contains the principal information needed to calculate the wind-driven 

mass transport.

Appendix

Global SLR Scenarios supporting the US National Climate Assessment November 2012 | 29