GEOPHYSICAL RESEARCH LETTERS, VOL. 40, 2768–2772, doi:10.1002/grl.50531, 2013

Uncertainty in future regional sea level rise due to internal
climate variability
Aixue Hu1 and Clara Deser1
Received 25 March 2013; revised 30 April 2013; accepted 1 May 2013; published 3 June 2013.

[1] Sea level rise (SLR) is an inescapable consequence ofincreasing greenhouse gas concentrations, with potentiallyharmful effects on human populations in coastal and island
regions. Observational evidence indicates that global sea
level has risen in the 20th century, and climate models
project an acceleration of this trend in the coming decades.
Here we analyze rates of future SLR on regional scales in a
40-member ensemble of climate change projections with theCommunity Climate System Model Version 3. This uniqueensemble allows us to assess uncertainty in the magnitude of
21st century SLR due to internal climate variability alone.
We ﬁnd that simulated regional SLR at mid-century can varyby a factor of 2 depending on location, with the North
Atlantic and Paciﬁc showing the greatest range. This
uncertainty in regional SLR results primarily from internalvariations in the wind-driven and buoyancy-driven
ocean circulations. Citation: Hu, A., and C. Deser (2013),
Uncertainty in future regional sea level rise due to internal climate
variability, Geophys. Res. Lett., 40, 2768–2772, doi:10.1002/grl.50531.

1. Introduction[2] Observational records show that global mean surface
temperatures have warmed since the late 19th century [e.g.,Morice et al., 2012] and that ocean heat content has increased
over at least the past 50 years [Levitus et al., 2012].
Correspondingly, global mean sea level has been rising at
an approximate rate of 1.8 cm/decade over the 20th century[Church and White, 2011], a pace that has accelerated toapproximately 3.1 cm/decade in recent decades [Church
et al., 2011]. Satellite-based observations suggest a signiﬁcant and accelerating mass loss from the Greenland andAntarctic ice sheets, contributing approximately one thirdof the total global sea level rise (SLR) in recent years, withseawater thermal expansion and runoff from glaciers andmountain ice caps accounting for the rest [Rignot et al.,2011; Church et al., 2011; Jacob et al., 2012].
[3] Global mean sea level is controlled primarily byvolume changes of the world’s oceans [e.g., Antonov et al.,
2002; Munk, 2002]. The total volume of seawater is affectedby temperature and salinity changes (thermosteric andAdditional supporting information may be found in the online version ofthis article.
1
Climate and Global Dynamics Division, National Center for
Atmospheric Research, Boulder, Colorado, USA.
Corresponding author: A. Hu, National Center for Atmospheric Research,
PO Box 3000, 1850 Table Mesa Drive, Boulder, CO, 80307–3000, USA.
(ahu@ucar.edu)©2013. American Geophysical Union. All Rights Reserved.
0094-8276/13/10.1002/grl.50531

halosteric components, respectively) and by the buildup or
melt-back of continental ice, including ice sheets, glaciers,
and mountain ice caps (the eustatic component), and may
also be affected by groundwater mining and dam building.
A warmer and fresher ocean or a melt-back of continental
ice will increase seawater volume, leading to a rise in sea
level. Regionally, sea level is also affected by wind- andbuoyancy-driven ocean currents associated with the redistribution of heat and salt in the ocean (the dynamical component). For example, the northward ﬂowing Gulf Stream isbalanced by higher sea level to its east and lower sea level
along the east coast of the U.S. If the transport of the Gulf
Stream diminishes due to changes in the buoyancy-driven
and/or the wind-driven ocean circulation, then sea level
along the eastern seaboard of the U.S. will increase [Seidov
et al., 2001; Yin et al., 2009; Hu et al., 2011; Tebaldi et al.,2012; Sallenger et al., 2012; Merriﬁeld et al., 2012].
[4] Due to warming of the world’s oceans induced byincreasing greenhouse gas (GHG) concentrations, global
mean sea level is projected to rise by 30–42 cm by the endof the 21st century, depending on which Intergovernmental
Panel on Climate Change Special Report on Emission
Scenarios will be realized in the future [Meehl et al., 2007],and could be up to 100 cm based on a semiempirical estimation which relates the observed global mean temperature andsea level changes [Vermeer and Rahmstorf, 2009; Meehl
et al., 2012]. Regionally, because of changes in wind- andbuoyancy-driven ocean currents in response to global
warming, local SLR could be a few times higher or lower
than the global mean [e.g., Nerem et al., 2010]. In addition
to the GHG-forced response, future regional sea levelchanges will be inﬂuenced by internal climate ﬂuctuations
on time scales ranging from years to multiple decades, forexample ENSO, Paciﬁc Decadal Variability [e.g., Deseret al., 2010], and Atlantic Multidecadal Variability [e.g.,
Delworth and Mann, 2000]. In this study, we evaluate theimpact of internal climate variability on uncertainty infuture regional SLR using an unprecedented 40-member
ensemble of climate change projections with the Community
Climate System Model version 3 (CCSM3) over the period
2000–2060. This ensemble has been used previously to investigate uncertainty in projected changes to atmospheric circulation patterns, precipitation, and air temperature [Deser et al.,2012a, 2012b].
[5] Due to the use of the Boussinesq approximation which
requires conservation of the total ocean volume, CCSM3 andmany other climate models are only able to simulate thedynamic component of sea level change associated with theredistribution of heat and salt (this term has a global meanof zero). The steric components of sea level change due toa net gain of heat or freshwater are diagnosed ofﬂine[Greatbatch, 1994]. Currently, the inﬂuence of eustatic sea

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HU AND DESER: SEA LEVEL RISE AND INTERNAL VARIABILITY

Figure 1. Simulated change in sea level (cm) between the periods 2041–2060 and 1980–1999 at selected coastal cities fromthe 40-member CCSM3 ensemble. The top panel shows the city locations, color-coded by region. The bottom panel shows thesea level changes using the same regional color-coding, with open circles for each of the 40 ensemble members and ﬁlled
circles for the ensemble mean.
level change is not incorporated in climate models. Efforts
have been made to count this effect [Mitrovica et al., 2009]
although it has proven to be difﬁcult [Kopp et al., 2010].
Therefore, here we focus on the contribution of the dynamic
and diagnosed thermosteric components of sea level change
only and refer to their sum as the total sea level change.

2. Model and Experiments[6] The version of CCSM3 used here consists ofCommunity Atmospheric Model version 3 at 2.8 horizontal
resolution and 26 levels in the vertical, Parallel Ocean
Program at 1 horizontal resolution with enhanced meridional
resolution to 0.32 at the equator and 40 levels in the vertical,
Community Sea Ice Model version 5 with elastic-viscousplastic dynamics, and a land surface model Community
Land Model, all described in Collins et al. [2006]. Each of
the 40 ensemble members begins at the end of the same 20th
century CCSM3 simulation and is subject to the identical
GHG, stratospheric ozone, solar, and aerosol forcings during
2000–2060 [Deser et al., 2012a]. In these simulations, the initial ocean, sea ice, and land states are identical, but the initialatmospheric conditions are perturbed by selecting atmosphericstates on different days between December 1999 and February
2000 from the 20th century simulation (further details on theexperimental design are provided in Deser et al. [2012a];
perturbing the ocean initial state may increase the uncertainty
sampled here.). Each of the 40 realizations represents a plausible outcome of climate change in the presence of internalvariability over the next 50 years, and their spread represents
the irreducible uncertainty of the predicted future climate[see Deser et al., 2012b].

3. Results[7] Figure 1 (and Table S1 in the supporting online material) shows the ensemble spread of the mean SLR averaged
over the last 20 years of the integration period (2041–2060)
relative to the reference interval 1980–1999 at selected
coastal cities. Although global mean SLR is almost identicalamong the different ensemble members (11  0.2 cm),
regional SLR can vary by a factor of 2 or more at many locations around the globe. For example, the projected range in
SLR is: 4.3–9.6 cm at San Francisco, 4.1–10.3 cm at Los
Angeles, 10.2–20.8 cm at Boston, 3.5–7.2 cm at Buenos
Aires, 6.5–12.1 cm at Hong Kong, 4.6–16.0 cm at

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HU AND DESER: SEA LEVEL RISE AND INTERNAL VARIABILITY

Figure 2. Projected ensemble-mean trends of (a) total and (b) dynamic sea level during 2000–2060 (cm/decade). Figure 2cshows the ratio of the dynamic sea level trend to the total sea level trend, and Figure 2d shows the uncertainty of the total sea
level trend (see text for details).
Shanghai, and 6.1–14.9 cm at Tokyo. Other locations,
including many at low latitudes, show a smaller spread, forexample 12.9–15.6 cm at Miami, 11.9–15.5 cm at Dakar,
10.7–13.9 cm at Cape Town, and 11.1–15.0 cm at Jakarta.
Some places (such as San Francisco and Mumbai) exhibit apeak in the SLR frequency distribution while others (suchas Boston and London) do not (Figure S1). The ranges of
future SLR depicted in Figure 1 could lead to signiﬁcantchallenges in mitigating their potential impacts on society,especially when compounded with storm surges [Tebaldi
et al., 2012]. It is worth emphasizing that the diversity of
SLR projections in this model ensemble is solely a resultof unpredictable, internally generated climate variability.
Structural differences between models and alternative GHG
scenarios constitute additional sources of uncertainty for
SLR projections. However, unlike those associated withinternal climate variability, these additional sources of uncertainty may be reducible as models and predictions of GHG
emissions improve [Deser et al., 2012b].
[8] Figure 2a shows the geographical distribution of the
projected linear trend in total sea level (thermosteric plus
dynamic) over the period 2000–2060, averaged over the 40
ensemble members: This constitutes the forced response toincreasing GHGs in CCSM3. The total sea level trend is positive everywhere except portions of the Southern Ocean, withmaximum values up to 5 cm/decade in the North Atlantic
and Arctic basins. The Paciﬁc shows generally weaker trends(1–2 cm/decade) than the Atlantic (2–3 cm/decade). The
global mean SLR is primarily due to increased ocean heatstorage. Although dynamical effects do not contribute to
the increase in global mean sea level, they signiﬁcantly
impact the regional features of the forced component of total
sea level change (Figure 2b). Without the thermosteric effect,sea level would rise in the Atlantic, Arctic, and North Indian
Ocean basins, and fall in most areas of the Paciﬁc andSouthern Oceans over the next 60 years in response toincreasing GHG. The contribution of dynamical effects tothe change in total sea level is approximately 20–60% in
the Atlantic and Arctic basins and portions of the Paciﬁc,and >100% over parts of the Southern Ocean (Figure 2c).
[9] Uncertainty in the magnitude of future sea level trends
due to internal climate variability is shown in Figure 2d. Here
we deﬁne uncertainty as twice the standard deviation of the
40 sea level trends divided by the ensemble mean sea level
trend at each grid box, in analogy with the 95% conﬁdence
level in the distribution of trends shown in Figure 1. The largest uncertainties occur mainly over middle and high latitudes,with values > 1 in the Southern and Arctic Oceans, andvalues approaching one in regions of the North Paciﬁc,North Atlantic, and equatorial western Paciﬁc. Such highvalues of projected sea level trend uncertainty indicate thatthe contribution from internal climate variability to local
SLR can be comparable to that from GHG forcing in any
single CCSM3 run, consistent with information shown in
Figures 1 and S1. In contrast, much of the tropical eastern
Paciﬁc, tropical Atlantic and northern Indian Oceans exhibit
low uncertainty, with values generally < 0.2 (Figure 2d).
[10] To further illustrate the relative contributions of internal and forced components of SLR in any single realization,
Figure 3 shows the spatial distribution of projected trends intotal sea level for ensemble members #29 and #35. These
members were chosen based on their contrasting sea levelpressure (SLP) trends as discussed below. While there are
overall similarities between the two runs, regional details
differ. For example, the area east of Japan shows a SLR
of 4–5 cm/decade in run 29 (Figure 3a) compared with
0–1 cm/decade in run 35 (Figure 3b), while the region directly
to the south shows a decrease in sea level ( 1 to 0 cm/decade)in run 29 compared with a modest increase (2–3 cm/decade) inrun 35. Differences in regional SLR are also found in the
North Atlantic: Run 29 shows a band of relatively large SLR
extending from Cape Hatteras eastward with maximum values

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HU AND DESER: SEA LEVEL RISE AND INTERNAL VARIABILITY

Figure 3. Projected trends of (a, b) total and (c, d) dynamic
sea level (cm/decade) during 2000–2060 from two selectedensemble members (#29 and #35). The black contours in
Figures 3c and 3d depict the corresponding trends in sea levelpressure (contour interval of 0.1 hPa/decade), with solid(dashed) contours for positive (negative) trends.
of 4–6 cm/decade, while run 35 exhibits minimum values eastof Cape Hatteras (1–2 cm/decade) and maximum values of
only 2–3 cm/decade along the eastern Canadian seaboard.
[11] The dynamical component of SLR associated withchanges in ocean circulation must account for the diversity
in regional sea level trends in the two individual ensemble
members, since the globally uniform thermosteric component is nearly identical for each run (recall Figure 1).
Changes in ocean circulation are caused by variations inwind and buoyancy forcing. Figures 3c and 3d show the
dynamical sea level trends for the same ensemble members
as in Figures 3a and 3b. The accompanying trends in SLP,
an indicator of wind forcing, are superimposed upon the
dynamical sea level trends. The large-scale SLP trend patterns differ markedly between the two realizations. Run #29
exhibits large-amplitude positive SLP trends over the central
North Atlantic and North Paciﬁc and negative SLP trends at
higher latitudes. This pattern resembles the positive phase of
the Northern Annular Mode [Thompson and Wallace, 1998].
In contrast, run #35 exhibits much weaker SLP trends overboth ocean basins.
[12] The contrasting atmospheric circulation trend patterns
and amplitudes between the two ensemble members can be
expected to have signiﬁcantly different consequences forthe wind-driven component of regional dynamic sea level.
For example, the large positive SLP trends in member 29,
corresponding to anticyclonic wind forcing, are associatedwith positive dynamic sea level trends locally and to the west,

in qualitative agreement with simple theory [e.g., Pedlosky,
1998]. On the other hand, the muted SLP trends in member
35 are accompanied by generally weaker dynamic sea level
trends in both basins. There is even a reversal in the sign ofthe dynamic sea level trends in the western portion of theNorth Paciﬁc between runs 35 and 29, presumably associatedwith the different patterns of SLP trends. A quantitative analysis is beyond the scope of this study.
[13] The dynamic component of sea level trends depicted
in Figures 3c and 3d are affected not only by the winddriven gyre circulation but also by the buoyancy-forced
Atlantic Meridional Overturning Circulation (AMOC). The
AMOC is a global-scale ocean circulation that transports
warm, saline surface waters northward into the subpolar
North Atlantic where they lose heat to the overlying atmosphere and become dense and sink to depth, returning southward to eventually invade the rest of the global ocean[Broecker, 1997]. As the climate warms under GHG forcing,
the AMOC is expected to slow down in all ensemble members due to weakened deep convection in the subpolar
North Atlantic caused by changes in surface buoyancy forcing [Gregory et al., 2005]. The expected signature of aslower AMOC in dynamic sea level is an increase of sea levelin the Atlantic, especially along the North American coast
and a decrease in the Paciﬁc [e.g., Yin et al., 2009; Huet al., 2011], consistent with the patterns shown in
Figures 1b, 3c, and 3d. This effect is especially clear in the
North Atlantic in both of the ensemble members shown in
Figures 3c and 3d, despite their different wind forcings,
suggesting the AMOC plays a major role in controlling
SLR in the North Atlantic.

4. Summary[14] A unique 40-member ensemble of climate change
simulations with CCSM3 has been used to isolate uncertainty
in future (2000–2060) sea level trends due to internal climate
variations. This source of uncertainty is distinct from those
associated with structural differences between models andwith different GHG forcing scenarios. In our experiments,
the uncertainties in projected 60 year regional sea level trends
are due to unpredictable internal climate ﬂuctuations. Our
results show that global-mean SLR (not taking into accountland-based ice melt) is primarily controlled by thermal
expansion of seawater: The increase in globally averaged
ocean heat storage varies only slightly among the different
ensemble members. On the other hand, projected changes
in regional sea level at mid-century are subject to considerable uncertainty, varying by a factor of 2 depending on
location, with coastal areas bordering the North Paciﬁc andAtlantic showing the greatest range. This range of projected
SLR is due primarily to internally generated trends in largescale wind patterns and changes in buoyancy forcing.
When compounded with storm surges, this range of uncertainty could pose signiﬁcant challenges for mitigating thepotential threats of regional SLR to society. Changes incontinental water storage, especially runoff from melting
continental ice sheets can also contribute signiﬁcantly tofuture SLR, an aspect not included in our model projections.
As shown by previous studies, this runoff is not uniformly
distributed within the ocean [Mitrovica et al., 2009], adding
another potential source of uncertainty to the projection of
future local SLR.

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HU AND DESER: SEA LEVEL RISE AND INTERNAL VARIABILITY[15] Acknowledgments. We thank Adam Phillips for his help in using
NCL. A portion of this study was supported by the Ofﬁce of Science (BER),
U.S. Department of Energy, Cooperative Agreement DE-FC02-97ER62402.
The National Center for Atmospheric Research is sponsored by the National
Science Foundation.
[16] The Editor thanks two anonymous reviewers for their assistance inevaluating this paper.

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