alternatives to nao driving of amoc variability in ccsm4€¦ · •alternatives to nao exist for...
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Alternatives to NAO driving of AMOC variability in CCSM4
Grant Branstator NCARAndrey Gritsun INM/RAS
with help from Andy Mai, Patrick Callaghan, Svetlana Karol & Haiyan Teng
CCSM4 T31, 3° Shields et al. (2012)17200 year control
Mean AMOC
EOF1 35.6% EOF2 19.5%Sv
Sv Sv
CCSM4 DJFM 1yr mean SHF
SHF regressed from NAO
Std dev
EOF1 25.8% Wm-2
Wm-2
50%
(Simplified, Quasi-gaussian) Fluctuation Dissipation Theorem(Leith, 1975; Deker&Haake, 1975; Risken, 1984)
Sufficient data to find CAtmospheric applications:* Gritsun, Branstator (2007)* Gritsun, Branstator, Majda (2008)
Suppose have a discretized dynamical system with noise and a F-P eqn with unique solutions. Also assume gradients of the system PDF are well approximated by a Gaussian fit. Thenthe PDF-averaged response to weak forcing is
For steady forcing
t = 5 yrssingular value decomposition
T31, 3deg CCSM4
SV1 for thermal forcing in top 110m
C/mon Sv
maximizing yr 5 response
8 times average response to random forcing
right SV left SV
Thermal forcing in top 110m
C/mon C/mon
SV1 5 std dev NAO
RMS=0.19C/mon
RMS=0.23C/mon
CESM AMOC response to thermal SV1
30S 0 30N 60N 90N 30S 0 30N 60N 90N
30S 0 30N 60N 90N 30S 0 30N 60N 90N
30S 0 30N 60N 90N
CESM yr 5 response to thermal SV1
FDT yr 5 response to SV1temp
30S 0 30N 60N 90N
3Sv7Sv
Thermal forcing in top 110m
C/mon C/mon
SV1 NAO
CESM yr 5 AMOC response
RMS=0.19C/mon=8 std dev
RMS=0.23C/mon=5 std dev
30S 0 30N 60N 90N
Thermal forcing in top 110m
C/mon
SV2
CESM yr 5 AMOC response
RMS=0.19C/mon
RMS=0.19C/mon
Sv
SV1 NAO
CCSM4 5yr AMOC response
Salinity Forcing
RMS=.015(g/kg)/mon
=5.0 std dev
RMS=.016(g/kg)/mon=10.7 std dev
6Sv 4Sv
(g/kg)/mon (g/kg)/mon
30S 0 30N 60N 90N
AMOC after 5yr mean surface events
thermal SV1 SHF NAO PSL
year 1
year 5 .38 .18
NAO SHF response pattern
thermal SV1response pattern
Persistence of response patterns
lag 0
lag 5
• Alternatives to NAO exist for driving AMOC variability in CCSM4
• Modest changes in surface flux structure can have substantial impacts on AMOC variability
• The most effective surface fluxes excite intrinsically long lasting patterns