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Mingfang Ting Yochanan Kushnir Cuihua Li Lamont-Doherty Earth Observatory Columbia University

Detection of Forced and Natural Atlantic Multidecadal Variability in Coupled Models and Observations. Mingfang Ting Yochanan Kushnir Cuihua Li Lamont-Doherty Earth Observatory Columbia University. AMO Index (7.5W-75W, 0-60N, ocean only) for Models and Observations. Detrended AMO Index.

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Mingfang Ting Yochanan Kushnir Cuihua Li Lamont-Doherty Earth Observatory Columbia University

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  1. Detection of Forced and Natural Atlantic Multidecadal Variability in Coupled Models and Observations Mingfang Ting Yochanan Kushnir Cuihua Li Lamont-Doherty Earth Observatory Columbia University

  2. AMO Index (7.5W-75W, 0-60N, ocean only) for Models and Observations

  3. Detrended AMO Index

  4. Questions: • How much of the multi-decadal Atlantic SST variability is caused by internal dynamics and how much is externally forced? • Can model ensemble average be taken as forced signals? • How do one separate the natural and forced components in observations?

  5. Focusing on IPCC models with multiple realizations… • NCAR CCSM – 8 members • GFDL CM2.1 – 5 members • GISS_EH – 6 members • GISS_ER – 9 members • MRI – 5 members • NCAR PCM – 4 members

  6. AMO index for NCAR model (dotted line – ensemble average)

  7. AMO for GFDL model (dotted line – ensemble average)

  8. How much of the ensemble average is forced signal? If infinite number of realizations are available, then ensemble average represents true forced signal If only a small number of realizations are available, ensemble average contains internal variability as well as forced signal

  9. EOF analysis of NCAR model’s ensemble average 20th century simulations Correlation between PC and surface temperature 85% 5% 1.5%

  10. GFDL model with 5 ensemble members Correlation between PC and surface temperature 73% 14% 3%

  11. PC1 of the ensemble average 20th Century simulations may be taken as forced signal

  12. Natural and Forced Variability of AMO in NCAR Model Run 7 Run 4 Run 1 Run 2 Run 5 Run 8 Run 6 Run 3 Forced

  13. Natural and Forced Variability of AMO in GFDL Model Run 1 Run 3 Run 5 Run 2 Run 4 Forced

  14. What about observations… • Only one realization, no ensemble average is available • But, we can identify regions where most of the variability is forced

  15. Ratio of variance • Total variance of all member ensembles lumped together, sT2 • Variance of the ensemble average, sa2 • Variance of internal variability, sI2= sT2- sa2 • Ratio of forced and total variance

  16. NCAR (8) GFDL (5) GISS_ER (9) MRI (5) PCM (4) GISS_EH (5) Ratio of Variance for 20th Century IPCC Coupled Models

  17. For Indian Ocean, almost all models show that about 85% of the total variance is forced

  18. Indian Ocean SST Index (50E-100E, 20S-10N) CCSM GFDL MRI GISS_ER GISS_EH PCM

  19. Indian Ocean SST index (ensemble mean + observations)

  20. Correlation between IO index and global TS in observations

  21. Forced Signal AMO Forced Signal MDR Forced Signal Natural Signal AMO Natural Signal MDR Natural Signal Forced versus Natural AMO in Observations

  22. Summary • Ensemble averages of a limited number of realizations do not necessarily represent forced signal. • EOF analysis of the ensemble average can be a useful way to separate the forced and natural components. • Indian Ocean responds primarily to radiative forcing and a large percentage of the total variance is forced. Thus it can be used as the footprint of the forced signal in observations. • Using Indian Ocean SST index to separate the forced and natural AMO and MDR, we found that the forced and natural components are of comparable magnitude in both cases.

  23. Regression of global SST on PC1 NCAR CCSM GFDL CM2.1 GISS EH MRI GISS ER PCM

  24. Spatial structure of natural AMO

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