alternatives to nao driving of amoc variability in ccsm4€¦ · •alternatives to nao exist for...

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