1.  Sponge δ18O has a significant correlation with the AMO and thus can be used as a proxy for the AMO 2.  Prior to instrumental data, a significant multidecadal trend can be detected until 1700s which suggests

AMO has prevalent at least since the 1700s. 3.  There seems to be no significant detectable external forcings that drive the AMO, suggesting that the

AMO may be an internal mode of the environment.

Conclusions

Atlantic Multidecadal Oscillation (AMO)

•  North Atlantic Ocean sea surface temperature within 0-70W, 0-65N

•  Sea surface temperature (SST) oscillations between warm and cold temperatures with a half period of 20-40 years.

Figure 1: Sea Surface Temperature of AMO Region from instrumental data (SODA) (a) Recorded instrumental

data averaged over 0-70W and 0-65N.

(b) Detrended using splinefit. (c) Blue (red) indicates

significant cooling (warming)

1880 1900 1920 1940 1960 1980 2000

18.2

18.6

19.0

19.4

(a)SODA AMO SST

AnnAvg$YearRd

SST(˚C)

1880 1900 1920 1940 1960 1980 2000

-0.4

0.0

0.2

0.4

-0.2

(b) detrended

AnnAvg$YearRd

SS

T an

omal

y

1880 1900 1920 1940 1960 1980 2000

1025

65

(c) SiZer

year

ban

dwid

th

Why is the AMO important? •  Effects the global climate,including rainfall, hurricane patterns, and

local summer climates (Knight et. al 2006) •  May exaggerate and obscure the increase in global temperature due

to human activity

Graph 1.1: Sponge δ18O values plotted with SODA SST from AMO region. AMO SST from SODA data (orange) and averaged annually

-1.1

-1

-0.9

-0.8

-0.7

-0.6

-0.5

-0.4

-0.3

18

18.2

18.4

18.6

18.8

19

19.2

19.4

19.6

1640 1740 1840 1940

δ18O

(%P

DB

) AM

O S

ST

(˚C

)

Years SODA AMO SST Sponge d18O

P-value = 6.5 x 10-06

(a) RMSE Sponge AMO SST vs Forcings Ensemble 1640-1985 CE 1640-1850 CE 1850-1985 CE

O 0.149 0.131 0.171 OG 0.225 0.122 0.322

OGS 0.205 0.150 0.266 OGSV 0.231 0.176 0.295

(b) RMSE Detrended Sponge AMO SST vs Forcings Ensemble 1640-1985 CE 1640-1850 CE 1850-1985 CE

O 0.127 0.124 0.131 OG 0.121 0.108 0.138

OGS 0.127 0.117 0.139 OGSV 0.151 0.158 0.140

R² = 0.26

AMO(˚C)=1.65(δ18O) + 19.92

Our Jamaican sclerosponge Ceratoporella nicholsoni a good proxy for the AMO

The AMO is not forced by volcanic, solar or anthropogenic external forcing but maybe related to AMOC

1650 1700 1750 1800 1850 1900 1950

-0.4-0.20.0

0.2

0.4

OGSV and Sponge SST Anomaly

Year

SST

OGSV

Sponge

Splinefit

1650 1700 1750 1800 1850 1900 1950

-0.4-0.20.0

0.2

0.4

OGS and Sponge SST Anomaly

Year

SST

OGS

Sponge

Splinefit

1650 1700 1750 1800 1850 1900 1950

-0.4

-0.2

0.0

0.2

0.4

OG and Sponge SST Anomaly

Year

SST

OG

Sponge

Splinefit

1650 1700 1750 1800 1850 1900 1950

-0.4

-0.2

0.0

0.2

0.4

O and Sponge SST Anomaly

Year

SST

O

Sponge

Splinefit

-0.9

-0.8

-0.7

-0.6

-0.5

-0.4

18

19

20

21

22

23

1640 1680 1720 1760 1800 1840

δ18O

sponge (%P

DB

)

AM

OC

Inde

x (S

V)

Year AMOC index Sponge d18O

(a) 1640-1850 CE R² = 0.038 p-value=0.04 (b) 1760-1850 CE R² = 0.31 p-value=1.6x10-4

Graph 3.1. Cumulative Forcings model SST anomaly plotted with sponge AMO SST anomaly. Model forcings include orbital (O), green house gases (G), solar

irradiance(S), and volcanic (v). Orbital shows best relationship to AMO

Table 1. Lowest RMSE (yellow) indicates significant forcing. Solar and Volcanic do not show significant influence on AMO. GHG may show some significance

Graph 3.2 Regression of Atlantic Meridional Overturning Circulation (AMOC) Index and d18O sponge. 1760-1850 show best correlation between AMOC and AMO.

Atlantic Multidecadal Oscillation history using Jamaican sclerosponge δ18O data Alissa Luk1, Casey Saenger, Wei Cheng, University of Washington, New York University1

Jamaican Sclerosponge and δ18O Values •  Discovery Bay, Jamaica sclerosponge

Ceratoporella nicholsoni (1656-1985 CE) •  Milled every 0.4mm (1.6 years) •  U/Th dating shows growth of 0.25 mm/yr •  Measured δ18O changes based on

seawater and temperature

Graph 2. Sponge d18O and AMO SST SiZer (a) Annual averages of the

data is plotted with spline fit (red line), which plots the low frequency trends in the data.

(b) Spline fit subtracted from annual averages give detrended data

(c) SiZer results. Blue (red) indicates significant negative (positive) slope

1. How long has the AMO been around? 2. What causes the AMO?

Instrumental Data •  Simple Ocean Data Assimilation (SODA)

Annually averaged data (1871-2008 CE) (Carton & Giese 2007)

Climate Models •  CSIRO MK3L climate model: Cumulative Forcings data (Phipps et al. 2013) •  CCSM3 model: AMOC index (Landrum et al. 2013)

y = 0.25x + 0.87 R² = 0.998

0 10 20 30 40 50 60 70 80

0 100 200 300

Dep

th in

spo

nge

(mm

)

Age (years before 1980) Graph 1. U/Th Dating of Sponge Milled three samples at 10.5 mm, 25.1 mm and

67.4 mm to create age model

References Carton, J.A. and B. Giese SODA 2.2.4, 2012, IRI Data Library, 1871-2008 Assimilation Run. Knight et al., 2006, AMO Climate Impact, Geophysical Research Letter. DOI: 10.1029/2006GL026242 Phipps et al., 2013, Paleoclimate Data-Model Comparison and the Role of Climate Forcings over the

past 1500 Years, American Meteorological Society DOI: 10.1175/JCLI-D-12-00108.1 Landrum et al. 2013, Last Millenium Climate and Its Variability in CCSM4, Journal of Climate DOI:

10.1175/JCLI-D-11-00326.1 Acknowledgement

1650 1700 1750 1800 1850 1900 1950-1.0

-0.8

-0.6

(a) Sponge Data d18O

AnnAvg$YearRd

δ18O

(‰P

DB

)

1650 1700 1750 1800 1850 1900 1950

-0.2

0.0

0.2

(b) detrended

AnnAvg$YearRd

δ18O

Ano

mal

y

1700 1750 1800 1850 1900 195010

25

63

(c) SiZer

year

ban

dwid

th

Focus Questions

The AMO has been around at least since the 1700s

Methods and Tools