Assessing Low Frequency Variability in North Atlantic Ocean Sea Surface

Temperatures in Global Climate Models

Nicholas G. HeavensCaltech

K.-F. Li, M.-C. Liang, L.-C. Lin, K.-K. Tung, and Y.L. Yung16 December 2009

AGU Fall Meeting Abstract # GC32A-08

NOAA/ESRLNOAA

AMO Should be Simulation Priority• Obscures or enhances global temperature trend

attributed to anthropogenic forcings• Affects climate of North America, Europe, and West Africa

Goldenberg et al., 2001

Janet Nye, NOAA NEFSC

Simulated AMOs are elusive First found byDelworth et al. (1993)before AMO identified(variability in AtlanticMOC)More recent work:1. Atmosphere-ocean vs. ocean alone

2.Hierarchy of model complexity

3. Surveys of IPCC models

Stoner et al. (2009)

Stoner et al. (2009) comparison ofClimate of the 20th Century CMIP3 runs with ERA-40 and Kaplan SST

This study

• Stoner et al. (2009) concerned Climate of 20th century runs too short to assess multi-decadal variability like AMO

• Paleoclimate records indicate AMO pre-dates20th century (last millennium or more)• To what extent do global climate models

simulate the Atlantic Multidecadal Oscillation (AMO) without secular forcing?

Procedure• Find longest pre-industrial run for 22 CMIP3 models

with daily data (100-550 yr. runs)• Calculate AMO Index just like the real ocean• Correlate detrended, deseasonalized annual mean

local time series with AMO Index to get spatial pattern• Power spectrum analysis.• Amplitude based on variance of ten year running

mean• Compare with both modern instrumental and Gray et

al. (2004) AMO reconstruction.

Results: Power SpectraGray et al., 2004(1567-1870)

HadISSTBCCR-BCM2.0

GFDL CM 2.1GISS AOM ECHO-G (MIUB)

CGCM2.3.2 (MRI) PCM1 (NCAR) HadCM3

Results: Spatial Patterns

Summary• Only seven CMIP3 models simulate multi-decadal

variability• ECHO-G has: (1) variability with spectrum similar to

Gray et al. (2004); (2) reasonable amplitude; (3) qualitatively similar spatial pattern to modern (in-family with other models); (4) minimal global SST drift

• Take-home: (1) decadal predictability in NorthAtlantic may prove difficult; (2) period matching of

ECHO-G remarkable (given ENSO…)

AMO Relation to Atlantic MOCPrimary AMO-related change is intensity of sub-circulation controlling downwelling at 50°-60° N,

Mean

Streamfunction(m3s-1)solid line(+ correlationwith AMO Index)dashed (-)

Explanations from previous modeling work, circulation is driven by positive salinity anomaly shut down by:1.Atmospheric feedback with NAO produces weak evaporation in sinking regions (Timmermann et al., 1998):salinity primarily produced in situ

2. Feedback with eddy salinity transportfrom south through sub-polar gyre water temperatures by atmospheric feedback/water accumulation (Dong and Sutton, 2005; Frankignoul and Msadek, 2008) (studies disagree about NAO role)salinity produced elsewhere

The period sensitivity arises through timing of various processes: phase lag

Validation beyond SST?1. Grain size sorting by bottomcurrents: sub-circulation intensityproxy?

Boessenkool et al. (2007)

2. Evaporation rates in LabradorSea: Salt content in downwind ice coresrelated to winds blowing over openwaters. Evaporation proxy?

Roethlisberger et al. (2009)

Take-home: Collection of high-resolution proxies related to deep circulation or salt budget priority for validation of model AMOs

Questions?

References• Boessenkool, K. P., I. R. Hall, H. Elderfield, and I. Yashayaev (2007), North Atlantic climate and deep-ocean

flow speed changes during the last 230 years, Geophys. Res. Lett., 34, L13614, doi:10.1029/2007GL030285.• Delworth T.L, Manabe S., Stouffer R.J. (1993) Interdecadal variations of the thermohaline circulation in a

coupled ocean–atmosphere model. J. Climate, 6, 1993–2011.• Dong B. and R.T. Sutton (2005), Mechanism of interdecadal thermohaline circulation variability in a

coupled ocean–atmosphere gcm, J. Climate, 18, 1117–1135.• Goldenberg, S. B., C. W. Landsea, A. M. Mestas-Nuñez, and W. M. Gray (2001), The recent increase in

Atlantic hurricane activity: Causes and implications, Science, 293, 474–479.• Gray, S.T., L.J. Graumlich, J.L. Betancourt, and G.T. Pederson (2004), A tree-ring based reconstruction of

the Atlantic Multidecadal Oscillation since 1567 A.D. Geophysical Research Letters, 31, L12205, doi:10.1029/2004GL019932.

• Msadek, R. and C. Frankignoul (2008), Atlantic multidecadal oceanic variability and its influence on the atmosphere in a climate model, Climate Dyn., 33, 45-62.

• Roethlisberger, R., X. Crosta, N.J. Abram, L. Armand, and E.W. Wolff, 2009, Potential and limitations of marine and ice core sea proxies: an example from the Indian Ocean sector

• Stoner, A.M.K., K. Hayhoe, and D.J. Wuebbles (2009), Assessing General Circulation Model Simulations of Atmospheric Teleconnection Patterns. J. Climate, 22, 4348–4372.

• Timmermann A, M. Latif, R. Voss, A. Grotzner (1998) Northern hemispheric interdecadal variability: a coupled air–sea mode, J. Climate, 11, 1906–1931