Climate Models, Projections of
Future Sea Level Change, and
Regional Variations
Jim Carton (UMD) & Laury Miller (NOAA)
{thanks Ron Stouffer, Warren Lipscomb}
Outline
• Global coupled models (IPCC approach) -- predict thermo., add icemelt
• AR4: Bindoff et al., 2007; Meehl et al. 07
• AR5: GFDL, CCSM
• Regional effects/downscaling
• the AMOC: Yin et al. 09; Hu et al. 09; Kuhlbrodt et al. 09: max SLR 80cm
• Downscaling to east coast (SAP4-1)
• Semi-empirical approach
• Ta -> SL Rahmstorf 07; Horton et al. 08; Grinsted et al. 09, etc. However:
von Storch et al. 08
• Finger Printing -- model geoid adjustment to large ice-sheet melt
Third Assessment Report (TAR) (2001)
A range sea level estimates was given: 0.09m to 0.88m
by 2100 (Church 2001). (see: R. Pielke Jr. clarification)
Fourth Assessment Report (AR4) (2007)
Included results from the Coupled Model
Intercomparison Project Phase 3 (23 CGCMs)
Controls: 1860, 1990
Emissions scenarios 2000-2100
A1 (high emissions),
A1B (medium emissions),
B1 (low emissions)
Example: GFDL CM2.1
• Atmosphere/land 2°x2.5°x24lev
– Radiative forcing: CO2, CH4, CFC11, 12, 22, 113, N2O, O3,
natural (sea salt and dust) & anthropogenic aerosols (black
carbon, organic carbon, and sulfate aerosols)
– Runoff in drainage basins goes to ocean
• Ocean MOM4, 1°x1° (1/3° near eq)x50lev
– tripolar grid
– true freshwater flux boundary condition
• Sea ice: GFDL Sea Ice Simulator
– one snow and two ice layers
• No: continental ice (but some hosing expts.), tides,
gravitational effects
700m Temperature difference
CM2.1 - OBS (years 101–200)
AR4 SLR Ensemble Projection
“Thermal expansion is projected to contribute more than half of the
average rise, but land ice will lose mass increasingly rapidly as the
century progresses. An important uncertainty relates to whether
discharge of ice from the ice sheets will continue to increase as a
consequence of accelerated ice flow, as has been observed in recent
years. This would add to the amount of sea level rise, but quantitative
projections of how much it would add cannot be made with confidence”.
(Bindoff et al., 2007)
20-50cm by 2100
AR4 neglected “full
effects of changes
in ice sheet flow”
but did include
current rates of
Greenland and AA
melt. Suggest
+10—20cm
(4mm/yr by 2190)
TAR
Fig 1 from Chapter 5: SLR under A1B
Post-AR4
1. Problems with Obs heat content record have been addressed
2. Mass contributions from melting land ice larger than expected
and apparently growing
3. Global emissions have continued to increase in excess of A1F1
Models are at the low range of obs
Model estimates
(updated from Rahmstorf, et al., Sci., 2007)
GFDL for AR5
CM2.1
CM2.1 2o
mercator atm
CM3-ESM2.1
CM3-ESM2M*
CM3-ESM2G*
Cube-sphere 2°x48-lev
CM2.1 (MOM4p0) ocean & TOPAZ
MOM4p1
TOPAZ
GOLD
TOPAZ
Ice melt stored in a separate
variable (to close water budget).
No land ice model yet.
Investigating allowing the coupled
model to interact with the geoid
*public release: 2013
NCAR’s CCSM for AR5
CCSM3.5
(post-AR4)
CCSM4
(AR5)
CAM3.5
POP1.3
POP2 1ox60lev
CICE4 including aerosol
dep.
POP2 1/2ox60lev
CICE4 including
aerosol dep.
Snow >1m runs off. Research version contains
Glimmer ice sheet model (shallow-ice
approximation), along with a surface mass balance
scheme for ice sheets. POP2 uses virtual salt flux.
No time-dependent geoid model yet
websrv.cs.umt.edu/isis/index.php/Coupling_the_Cryosphere_to_other_Earth_systems%2C_part_II
CCSM: exploring the impact of continental ice
melt
(activity of the Land Ice working group)
With CCSM3 its been found that a melting rate exceeding 0.05 Sv would
weaken the MOC by 9-24% by the end of the 21st century.
CMWG has proposed 2009 experiments with 200yr T42 CCSM3
simulations:
1. West Antarctic ice sheet melting via a constant melting rate of 0.004
Sv (Antartica 2002-2006: 0.0033 Sv; 2006-2009: 246 Gt/year = 0.0078 Sv =
246Gt/yr)
2. Same as 1, but with increase 1% per year (0.04Sv at yr100).
3. Same as 1, but with increase 3% per year (1.34Sv at yr100)
4. Same as 1, but with increase 7% per year (2.91Sv at yr100)
5. Same as 3, but with global runoff increase of 3% per year
6. Same as 5, but adding Greenland melting with 3% increase (20022006: 0.0043 Sv; 2007-2009: 0.0091 Sv)
Ice modeling initiatives: EU: Ice2sea, SeaRISE
Regional Variations/downscaling
AR4 Changes in the AMOC
A1b emissions
GFDL CM2.1
All emission scenarios
Meehl et al. 2007
AR4 10-model Mean SLR
2091-2100 wrt to 1981-2000, ten models, A1B medium emission scenario
Over next 100 years,
dynamic SLR very uneven
(Yin, et al., 2009)
Impact of excess meltwater in Potsdam’s Climber-3α
SLA1FI_090 - SLA1FI_000 in 2150
{A1FI_090 includes 0.09 Sv/K meltwater}
Up to 80 cm
Kuhlbrodt et al. 2009
GFDL CM2.1 Model Simulation vs. Observed Dyn SSH
Observed Dynamic SSH
(1992-2002)
Simulated Dynamic SSH
(1992-2002)
Simulation produces realistic Gulf Stream, Subtropical & Subpolar Gyres
(Yin, et al., 2009)
CM2.1 A1B Scenario: Steric vs. Mass Contributions to SSH
Steric SSH Anomaly A1B Scenario
(2091-2100 wrt 1981-2000)
Decrease in AMOC
decrease in
production of NADW
increase in
steric SLR along path of DWBC
Mass SSH Anomaly A1B Scenario
(2091-2100 wrt 1981-2000)
Sharp steric SSH gradient across shelf
break can’t be balanced by geostrophy,
consequently mass loading along NE
coastline. (Mass redistribution calculated
on basis of bottom pressure change)
(Yin, et al., 2009)
Semi-empirical Approaches
Predicting SLR from Ta
Rate of SLR proportional to magnitude of warming global mean surface
temperature above pre-industrial Age. SL adjusts exponentially to
temperature with a timescale of several hundred years as the heat
gradually penetrates the deep ocean.
Eq. 1
Eq. 2
Uses LSQR estimation of “a” from observations, combined with
temperature projections from TAR (R07) and AR4(H08,G09) to estimate
SLR
• Drawbacks: Estimation of coefficient “a” problematic due to inadequate
observations; method doesn’t allow for non-linear ice melt processes
Rahmstorf 2007, extended by Horton et al. 2008, Grinsted et al. 2009
Estimating Coefficient “a”
• Correlation of T and dH/dt for
period 1881-2001
• Both T and H curves smoothed
by computing non-linear trends
over 15 years
• dH/dt estimated by taking
derivative of H curve
• Data binned in 5 yr avgs
Method relies on heavy smoothing, resulting in
small number of degrees of freedom.
(Rahmstorf, 2007)
SLR hindcast based on surface
temperature observations
dH/dt from tide gauges
dH/dt from dT (eq. 1)
dH from tide gauges
dH from integral of (eq. 1)
(Rahmstorf, 2007)
von Storch, et al. (2008) counters:
Based on ECHO-G simulation (which admittedly
doesn’t include all physical processes), neither
dT or dT/dt are reliable predictors of dH/dt.
Although some agreement on centennial scales,
there are intervals of large errors and even
inverse relationship.
In general, the semi-empirical approach is
problematic. It relies on the statistics of a short,
heavily smoothed observational record, that is
highly autocorrelated, and has strong trends.
Item #3: What type of observations and research
activities should be encouraged in order to
improve sea level projections for the 21st century?
• Need to get the obs and modeling communities to work
together
• Must monitor ice (continental and sea)! We need to know
the range of possible acceleration
• Must monitor salinity, particularly at high latitude
– Need to improve Arctic Ocean processes
References
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Horton, R., C. Herweijer, C. Rosenzweig, J. Liu, V. Gornitz and A.C. Ruane (2008). Sea level rise projections for
Current generation CGCMs based on the semi-empirical method. Geophysical Research Letters, 35: L02725,
doi:10.1029/2007GL032468.
Hu, A., G.A. Meehl, W. Han, and J. Yin, 2009: Transient response of the MOC and climate to potential melting of
the Greenland Ice Sheet in the 21st century, Geophys. Res. Letts., 36, L10707, doi:10.1029/2009GL037998.
Kuhlbrodt, T., et al., 2009: An Integrated Assessment of changes in the thermohaline circulation, Climatic Change,
96, 489–537, DOI 10.1007/s10584-009-9561-y
Meehl et al, 2005: How Much More Global Warming and Sea Level Rise? Science, 307,1769 – 1772.
Rahmstorf, S., 2007: A Semi-Empirical Approach to Projecting Future Sea-Level Rise, Science, 315, 368 – 370.
also: Response to comments on "A semi-empirical approach to projecting future sea-level rise“, Science, 317,
5846.
Sen Gupta A, A. Santoso A., AS Taschetto, CC Ummenhofer, J. Trevena, MH England, 2009: Projected Changes
to the Southern Hemisphere Ocean and Sea Ice in the IPCC AR4 Climate Models, J. Clim., 22, 3047-3078.
Tamsiea, M. E., J.X. Mitrovica, J.L. Davis, and G.A. Milne, 2003: II: SOLID EARTH PHYSICS: Long Wavelength
Sea Level and Solid Surface Perturbations Driven by Polar Ice Mass Variations: Fingerprinting Greenland and
Antarctic Ice Sheet Flux, Space Science Reviews, 108, 1572-, 10.1023/A:1026178014950
Velicogna, I. (2009), Increasing rates of ice mass loss from the Greenland and Antarctic ice sheets revealed by
GRACE, Geophys. Res. Letts., 36, L19503, doi:10.1029/2009GL040222
von Storch H, E. Zorita, JF Gonzalez-Rouco, 2008: Relationship between global mean sea-level and global mean
temperature in a climate simulation of the past millennium, Ocean Dynam., 58, 227-236.
Yin, J., M.E. Schlesinger, and R.J. Stouffer, 2009: Model projections of rapid sea-level rise on the northeast coast
of the United States, Nature Geosci., DOI: 10.1038/NGEO462