AMOC MULTI-DECADAL VARIABILITY:
MECHANISMS, THEIR ROBUSTNESS, AND
IMPACTS OF MODEL CONFIGURATIONS
Gokhan Danabasoglu and Steve Yeager
National Center for Atmospheric Research
OUTLINE
AMOCmax in CCSM3
Many Coupled General
Circulation Models (CGCMs)
exhibit (multi-)decadal
variability in their AMOCs.
T85x1
T42x1
T31x3
• Brief review of some proposed mechanisms and their robustness
- primarily CGCM studies
- few idealized studies
- not comprehensive
•Some results from the Community Climate System Model (CCSM4)
to show impacts of model configuration and parameterizations on
AMOC variability
CONSENSUS: Density anomalies in the sinking regions of AMOC
drive these AMOC fluctuations.
Proposed AMOC Variability Mechanisms
Delworth et al. (1993, DMS93): GFDL R15 coupled model, 40-80 yr period
weak AMOC
AMOCmax vs density regressions
reduced heat transport
cold, dense pool in middle
North Atlantic
T anomalies generate
cyclonic gyre circulation
anomalous circulation
transports S into the
sinking region
S, density, and AMOC
all increase
DMS93 and Griffies & Tziperman (1995): Damped ocean-only mode
excited by atmospheric noise
Weaver & Valcke (1998): coupled mode
Delworth & Greatbatch (2000): Damped ocean-only mode,
continuously excited by low-frequency atmospheric forcing,
implications for NAO
Dai et al. (2005): Same DMS93 mechanism in PCM (25 yr)
Dong & Sutton (2005): Same DMS93 mechanism in HadCM3 (25 yr)
Both Dai et al. (2005) and Dong & Sutton (2005) suggest stronger
ties to the NAO.
Freshwater Transport to / from Arctic Ocean
and Nordic Seas
Delworth et al. (1997), GFDL R15, 40-80 yr: Enhanced transport of
relatively fresh water and sea ice from the Arctic via the East
Greenland Current and Denmark Strait. These anomalies
propagate around the subpolar gyre into the Labrador Sea,
capping the convection. …. Greenland Sea oscillations are
implicated, but how they are generated is unknown.
Jungclaus et al. (2005), ECHAM5/MPI-OM, 70-80 yr: Storage and
release of freshwater from the central Arctic to the Labrador
Sea convection site along with circulation changes in the Nordic
Seas due to Atlantic heat and salt transports. … Damped ocean
mode excited by atmosphere as in DMS93.
Freshwater Transport to / from Arctic Ocean
and Nordic Seas
Oka et al. (2006), MIROC, 30-50 yr: Freshwater transport through
the Denmark Strait results in deep convection see-saw between
the Labrador Sea and Greenland Sea. Wind Stress / NAO
changes are implicated and the variability is interpreted as a
coupled mode.
Winter-time mixed
layer depth (m)
Danabasoglu (2008), CCSM3 T85x1 present-day control, 20 yr:
March-mean boundary layer
depth (BLD) EOF1
AMOCmax vs density regressions
AMOC lagging
-10
m
-5
AMOC leading
0
5
10
Role for NAO
D’Orgeville & Peltier (2009), CCSM3 T31x3 pre-industrial control,
60 yr: Similar in-phase T and S contributions to density, less role
for NAO, but suggest gyre – bathymetry interaction
Same Model and Integration, but 2 Different Mechanisms
(HadCM3, 90 yr)
Vellinga & Wu (2004): Involves large scale air-sea interaction
AMOC +
northward
ITCZ shift
surface salinity
decreases
increased NHT
generates cross
Equatorial SST
gradient
increased rainfall and FW
flux into the ocean
low salinities
advected north into
sinking regions
AMOC -
Same Model and Integration, but 2 Different Mechanisms
(HadCM3, 90 yr)
Hawkins & Sutton (2007): Internal ocean mode
Changes in the Nordic Seas convection lead to AMOC changes.
Variations in salinity transports from the Arctic and from the
North Atlantic are the main controlling feedbacks.
Similar to Delworth et al. (1997) and Jungclaus et al. (2005)…
but convection region, and hence the mechanism, are different.
Role for Southern Ocean
Saenko et al. (2003): AMOC / NADW is affected by the Southern
Ocean freshwater perturbations.
Delworth & Zeng (2008), GFDL CM2.1: Strength and position of the
Southern Hemisphere mid-latitude westerly winds impact AMOC
strength.
Biastoch et el. (2008): Dynamic signals originating in the Agulhas
leakage region have influence on decadal AMOC variability.
Park & Latif (2008), Kiel Climate Model: Multi-centennial and multidecadal variabilities are both associated with sea-ice extent and
the former is driven in the Southern Ocean…. Coupled ocean –
atmosphere – sea-ice mode.
Some Other Mechanism
Marshall et al. (2001): Intergyre gyre concept with links to NAO
Msadek & Frankignoul (2009), IPSL-CM4, ~100 yr: Convection is
primarily influenced by the anomalous advection of salinity due
to changes in the East Atlantic Pattern… coupled mode.
Zhu & Jungclaus (2008), coarse resolution ECHAM5/MPI-OM, 30
and 60 yr: They are interpreted as ocean-only and coupled
modes, respectively. The 30-year variability is related to T
anomalies moving along the cyclonic subpolar gyre and leading to
fluctuations in horizontal density gradients and subsequent
weakening and strengthening of AMOC. …. Consistent with TeRaa
& Dijkstra (2002, 2003).
Timmermann et al. (1998), Farneti & Vallis (2009),
Cheng et al. (2004), ……………………
AMOC in CCSM4
• CCSM4 includes many physical and computational improvements in all
its components compared to CCSM3.
• The ocean model uses spatially and temporally varying eddy mixing
coefficients, submesoscale mixing parameterization, lower horizontal
viscosities, …
• An overflow parameterization is used to represent the Nordic Sea
overflows.
• The ocean model resolution is nominal 1o in the horizontal with 60
vertical levels.
No Overflows (CCSM3)
Sv
With Overflows
(CCSM4)
Sv
AMOC Maximum Transports at 26.5oN in Ocean – Ice
Hindcast Simulations with CORE Forcing
Impacts of surface salinity restoring
Increased
North
Atlantic bias
no restoring
RAPID
4 years
1 year
1 month
Strong salinity restoring reduces model error in the subpolar
seas, but it
• weakens AMOC
• significantly damps AMOC variability north of 30oN
• reduces max Atlantic northward heat transport to below 1 PW
AMOC Properties in Ocean – Ice Hindcast Simulations
AMOC maximum north of 28oN
Case
Mean (Sv)
Std Dev (Sv)
1960-2000
Trend
(Sv/decade)
No restoring
30.2
2.2
1.5
4 years
24.2
1.9
1.2
1 year
20.3
1.7
1.2
1 month
18.5
1.2
0.9
AMOC maximum at 26.5oN
Case
Mean (Sv)
Std Dev
(Sv)
1960-2000
Trend
(Sv/decade)
No restoring
21.2
1.1
0.7
4 years
17.0
1.0
0.6
1 year
15.2
0.92
0.6
1 month
13.8
0.95
0.6
AMOC Maximum Transports in CCSM4 Pre-Industrial
Control Simulations
CCSM4_1: 1o FV
atmosphere
CCSM4_2: 2o FV
atmosphere
12
99% 0
95%
6
7
Impacts of Parameterized Nordic Sea Overflows on
AMOC Variability
Preliminary
CCSM4
present-day
simulations
with 2o
atmosphere
and 1o ocean
resolution
AMOC maximum transport
200+
90
99%
50
70
95%
Period (years)
Period (years)
Density and
section-normal
velocity at 45oW
color: density (kg m-3)
line: velocity (cm s-1)
SUMMARY – WHAT HAVE WE LEARNED IN THE LAST 5 YEARS?
(CGCM view)
• AMOC variability and predictability are (perhaps) more
complicated than originally thought.
• Proposed variability mechanisms are not (really) robust across
different models.
• Unresolved processes, e.g., mesoscale eddies, Nordic Sea
overflows, oceanic mixing, appear to influence AMOC significantly.
• AMOC variability in CCSM4 is muted compared to that of CCSM3
and preliminary results indicate influence of overflows and a
different mechanism than in CCSM3.
Key observational priorities listed in the AMOC 2009 report will be
certainly helpful in discriminating against some of the proposed
mechanisms.
Simplified Diagram of Phase Relationships in CCSM3
negative
NAO
positive
NAO
strong subpolar gyre
-15
-10
-5
0
min
AMOC
max
density
BLD
max
AMOC
- reduced sea-ice cover,
- increased surface heat loss,
- increased upwelling of salt
“max
”
SST
- increased sea-ice cover,
- reduced surface heat loss,
- reduced upwelling of salt,
- diffusive fluxes
D’Orgeville & Peltier (2009), CCSM3 T31x3 pre-industrial control,
60 yr: Similar in-phase T and S contributions to density, less
role for NAO, but suggest gyre – bathymetry interaction
+5