Climate Dynamics

, Volume 48, Issue 9–10, pp 3139–3160 | Cite as

Understanding the control of extratropical atmospheric variability on ENSO using a coupled data assimilation approach

Article

Abstract

The control of extratropical atmospheric variability on ENSO variability is studied in a coupled general circulation model (CGCM) utilizing an ensemble-based coupled data assimilation (CDA) method in the perfect-model framework. Assimilation is limited to the desired model components (e.g. atmosphere) and spatial areas (e.g. the extratropics) to study the ensemble-mean model response (e.g. tropical response to “observed” extratropical atmospheric variability). The CDA provides continuously “corrected” extratropical atmospheric forcing and boundary conditions for the tropics and the use of ensemble optimizes the observational forcing signal over internal variability in the model component or region without assimilation. The experiments demonstrate significant control of extratropical atmospheric forcing on ENSO variability in the CGCM. When atmospheric “observations” are assimilated only poleward of 20° in both hemispheres, most ENSO events in the “observation” are reproduced and the error of the Nino3.4 index is reduced by over 40 % compared to the ensemble control experiment that does not assimilate any observations. Further experiments with the assimilation in each hemisphere show that the forced ENSO variability is contributed roughly equally and independently by the Southern and Northern Hemisphere extratropical atmosphere. Further analyses of the ENSO events in the southern hemisphere forcing experiment reveal robust precursors in both the extratropical atmosphere over southeastern Pacific and equatorial Pacific thermocline, consistent with previous studies of the South Pacific Meridional Mode and the discharge-recharge paradigm, respectively. However, composite analyses based on each precursor show that neither precursor alone is sufficient to trigger ENSO onset by itself and therefore neither alone could serve as a reliable predictor. Additional experiments with northern hemisphere forcing, ocean assimilation or different latitudes are also performed.

Keywords

ENSO Variability Precursors Coupled model dynamics Coupled data assimilation 

References

  1. Alexander MA et al (2002) The atmospheric bridge: the influence of ENSO teleconnections on air-sea interaction over the global oceans. J Clim 15:2205–2231. doi:10.1175/1520-0442(2002)015<2205:TABTIO>2.0.CO;2 CrossRefGoogle Scholar
  2. Anderson JL (2001) An ensemble adjustment Kalman filter for data assimilation. Mon Weather Rev 129:2884–2903CrossRefGoogle Scholar
  3. Anderson BT (2007) On the joint role of subtropical atmospheric variability and equatorial subsurface heat content anomalies in initiating the onset of ENSO events. J Clim 20:1593–1599. doi:10.1175/JCLI4075.1 CrossRefGoogle Scholar
  4. Anderson BT, Perez RC (2015) ENSO and non-ENSO induced charging and discharging of the equatorial Pacific. Clim Dyn 45:2309–2327. doi:10.1007/s00382-015-2472-x CrossRefGoogle Scholar
  5. Anderson BT, Perez RC, Karspeck A (2013) Triggering of El Niño onset through trade wind-induced charging of the equatorial Pacific. Geophys Res Lett 40:1212–1216. doi:10.1002/grl.50200 CrossRefGoogle Scholar
  6. Cane MA, Zebiak SE (1985) A theory for el nino and the southern oscillation. Science 228:1085–1087. doi:10.1126/science.228.4703.1085 CrossRefGoogle Scholar
  7. Cane MA, Zebiak SE, Dolan SC (1986) Experimental forecasts of El Niño. Nature 321:827–832. doi:10.1038/321827a0 CrossRefGoogle Scholar
  8. Chang P, Zhang L, Saravanan R, Vimont DJ, Chiang JCH, Ji L, Seidel H, Tippett MK (2007) Pacific meridional mode and El Niño-Southern Oscillation. Geophys Res Lett 34. doi:10.1029/2007GL030302
  9. Chiang JCH, Vimont DJ (2004) Analogous pacific and Atlantic meridional modes of tropical atmosphere-ocean variability*. J Clim 17:4143–4158. doi:10.1175/JCLI4953.1 CrossRefGoogle Scholar
  10. Compo GP, Sardeshmukh PD (2010) Removing ENSO-related variations from the climate record. J Clim 23:1957–1978. doi:10.1175/2009JCLI2735.1 CrossRefGoogle Scholar
  11. Cox MD (1984) A primitive equation 3-dimensional model of the ocean. GFDL–Princeton UniversityGoogle Scholar
  12. Deser C et al (2012) ENSO and pacific decadal variability in the community climate system model version 4. J Clim 25:2622–2651. doi:10.1175/JCLI-D-11-00301.1 CrossRefGoogle Scholar
  13. Drake J, Foster I, Michalakes J, Toonen B, Worley P (1995) Design and performance of a scalable parallel community climate model. Parallel Comput 21:1571–1591. doi:10.1016/0167-8191(96)80001-9 CrossRefGoogle Scholar
  14. Hack JJ, Boville BA, Briegleb BP, Kiehl JT, Rasch PJ, Williamson D (1993) Description of the NCAR community climate model (CCM2). Climate and Global Dynamics Division, NCARGoogle Scholar
  15. Hakim GJ, Torn RD (2008) Ensemble synoptic analysis. Meteorol Monogr 33:147–162. doi:10.1175/0065-9401-33.55.147 CrossRefGoogle Scholar
  16. Jacob R (1997) Low frequency variability in a simulated atmosphere ocean system. University of Wisconsin-MadisonGoogle Scholar
  17. Jin FF (1997) An equatorial ocean recharge paradigm for ENSO. Part 1: conceptual model. J Atmos Sci 54:811–829. doi:10.1175/1520-0469(1997)054<0811:Aeorpf>2.0.Co;2 CrossRefGoogle Scholar
  18. Kalnay E, Ota Y, Miyoshi T, Liu J (2012) A simpler formulation of forecast sensitivity to observations: application to ensemble Kalman filters. Tellus A. doi:10.3402/tellusa.v64i0.18462 Google Scholar
  19. Kao HY, Yu JY (2009) Contrasting Eastern-Pacific and Central-Pacific types of ENSO. J Clim 22:615–632. doi:10.1175/2008JCLI2309.1 CrossRefGoogle Scholar
  20. Karspeck AR, Yeager S, Danabasoglu G, Hoar T, Collins N, Raeder K, Anderson JL, Tribbia J (2013) An ensemble adjustment kalman filter for the CCSM4 ocean component. J Clim 26:7392–7413. doi:10.1175/Jcli-D-12-00402.1 CrossRefGoogle Scholar
  21. Kirtman BP (1997) Oceanic Rossby wave dynamics and the ENSO period in a coupled model. J Clim 10:1690–1704. doi:10.1175/1520-0442(1997)010<1690:ORWDAT>2.0.CO;2 CrossRefGoogle Scholar
  22. Kirtman BP, Shukla J (2002) Interactive coupled ensemble: a new coupling strategy for CGCMs. Geophys Res Lett 29:5-1–5-4, doi:10.1029/2002GL014834
  23. Kunii M, Miyoshi T, Kalnay E (2012) Estimating the impact of real observations in regional numerical weather prediction using an ensemble kalman filter. Mon Weather Rev 140:1975–1987. doi:10.1175/Mwr-D-11-00205.1 CrossRefGoogle Scholar
  24. Larson SM, Kirtman BP (2013) The pacific meridional Mode as a trigger for ENSO in a high-resolution coupled model. Geophys Res Lett 40:3189–3194. doi:10.1002/grl.50571 CrossRefGoogle Scholar
  25. Larson SM, Kirtman BP (2014) The pacific meridional mode as an ENSO precursor and predictor in the north American multimodel ensemble. J Clim 27:7018–7032. doi:10.1175/JCLI-D-14-00055.1 CrossRefGoogle Scholar
  26. Larson SM, Kirtman BP (2015a) An alternate approach to ensemble ENSO forecast spread: application to the 2014 forecast. Geophys Res Lett 42:9411–9415. doi:10.1002/2015GL066173 CrossRefGoogle Scholar
  27. Larson SM, Kirtman BP (2015b) Revisiting ENSO coupled instability theory and SST error growth in a fully coupled model. J Clim 28:4724–4742. doi:10.1175/JCLI-D-14-00731.1 CrossRefGoogle Scholar
  28. Lewis M, Carr M, Feldman G, Esaias W, McClain C (1990) Influence of penetrating solar radiation on the heat budget of the equatorial Pacific Ocean. Nature 347:543–545CrossRefGoogle Scholar
  29. Lin JL (2007) The double-ITCZ problem in IPCC AR4 coupled GCMs: ocean-atmosphere feedback analysis. J Clim 20:4497–4525. doi:10.1175/Jcli4272.1 CrossRefGoogle Scholar
  30. Liu Z (1996) Modeling equatorial annual cycle with a linear coupled model. J Clim 9:2376–2385. doi:10.1175/1520-0442(1996)009<2376:MEACWA>2.0.CO;2 CrossRefGoogle Scholar
  31. Liu Z, Alexander M (2007) Atmospheric bridge, oceanic tunnel, and global climatic teleconnections. Rev Geophys 45:RG2005. doi:10.1029/2005RG000172
  32. Liu J, Kalnay E (2008) Estimating observation impact without adjoint model in an ensemble Kalman filter. Q J R Meteorol Soc 134:1327–1335. doi:10.1002/qj.280 CrossRefGoogle Scholar
  33. Liu Z, Xie SS-P (1994) Equatorward propagation of coupled air-sea disturbances with application to the annual cycle of the eastern tropical pacific. J Atmos Sci 51:3807–3822. doi:10.1175/1520-0469(1994)051<3807:EPOCAD>2.0.CO;2 CrossRefGoogle Scholar
  34. Liu Z, Philander SGH, Pacanowski RC (1994) A GCM study of tropical-subtropical upper-ocean water exchange. J Phys Oceanogr 24:2606–2623. doi:10.1175/1520-0485(1994)024<2606:AGSOTU>2.0.CO;2 CrossRefGoogle Scholar
  35. Liu Z, Kutzbach J, Wu LX (2000) Modeling climate shift of El Nino variability in the Holocene. Geophys Res Lett 27:2265–2268. doi:10.1029/2000gl011452 CrossRefGoogle Scholar
  36. Liu Z et al (2007) Simulating the transient evolution and abrupt change of Northern Africa atmosphere–ocean–terrestrial ecosystem in the Holocene. Quat Sci Rev 26:1818–1837. doi:10.1016/j.quascirev.2007.03.002 CrossRefGoogle Scholar
  37. Liu Y, Liu Z, Zhang S, Jacob R, Lu F, Rong X, Wu S (2014a) Ensemble-based parameter estimation in a coupled general circulation model. J Clim 27:7151–7162. doi:10.1175/JCLI-D-13-00406.1 CrossRefGoogle Scholar
  38. Liu Y, Liu Z, Zhang S, Rong X, Jacob R, Wu S, Lu F (2014b) Ensemble-based parameter estimation in a coupled GCM using the adaptive spatial average method. J Clim 27:4002–4014. doi:10.1175/JCLI-D-13-00091.1 CrossRefGoogle Scholar
  39. Lu F, Liu Z, Zhang S, Liu Y, Jacob R (2015) Strongly coupled data assimilation using leading averaged coupled covariance (LACC). Part II: CGCM experiments*. Mon Weather Rev 143:4645–4659. doi:10.1175/MWR-D-15-0088.1 CrossRefGoogle Scholar
  40. Matei D, Keenlyside N, Latif M, Jungclaus J (2008) Subtropical forcing of tropical pacific climate and decadal ENSO modulation. J Clim 21:4691–4709. doi:10.1175/2008JCLI2075.1 CrossRefGoogle Scholar
  41. Murtugudde R, Beauchamp J, McClain CR, Lewis M, Busalacchi AJ (2002) Effects of penetrative radiation on the upper tropical ocean circulation. J Clim 15:470–486. doi:10.1175/1520-0442(2002)015<0470:EOPROT>2.0.CO;2 CrossRefGoogle Scholar
  42. Neelin JD, Battisti DS, Hirst AC, Jin F-F, Wakata Y, Yamagata T, Zebiak SE (1998) ENSO theory. J Geophys Res 103:14261. doi:10.1029/97JC03424 CrossRefGoogle Scholar
  43. Newman M, Alexander MA, Scott JD (2011) An empirical model of tropical ocean dynamics. Clim Dyn 37:1823–1841. doi:10.1007/s00382-011-1034-0 CrossRefGoogle Scholar
  44. Philander SG (1990) El Niño, La Niña, and the Southern Oscillation. ElsevierGoogle Scholar
  45. Pierce DW, Barnett TP, Latif M (2000) Connections between the pacific ocean tropics and midlatitudes on decadal timescales. J Clim 13:1173–1194. doi:10.1175/1520-0442(2000)013<1173:CBTPOT>2.0.CO;2 CrossRefGoogle Scholar
  46. Raeder K, Anderson JL, Collins N, Hoar TJ, Kay JE, Lauritzen PH, Pincus R (2012) DART/CAM: an ensemble data assimilation system for CESM atmospheric models. J Clim 25:6304–6317. doi:10.1175/Jcli-D-11-00395.1 CrossRefGoogle Scholar
  47. Saha S et al (2010) The NCEP climate forecast system reanalysis. Bull Am Meteorol Soc 91:1015–1057. doi:10.1175/2010BAMS3001.1 CrossRefGoogle Scholar
  48. Schneider EK, Zhu Z (1998) Sensitivity of the simulated annual cycle of sea surface temperature in the equatorial Pacific to sunlight penetration. J Clim 11:1932–1950. doi:10.1175/1520-0442(1998)011<1932:SOTSAC>2.0.CO;2 CrossRefGoogle Scholar
  49. Schott FA, Mccreary JP, Johnson GC (2004) Shallow overturning circulations of the tropical- subtropical oceans. Earth’s Clim, pp 261–304Google Scholar
  50. Torn RD, Hakim GJ (2008) Ensemble-based sensitivity analysis. Mon Weather Rev 136:663–677. doi:10.1175/2007MWR2132.1 CrossRefGoogle Scholar
  51. Vimont DJ (2010) Transient growth of thermodynamically coupled variations in the tropics under an equatorially symmetric mean state. J Clim 23:5771–5789. doi:10.1175/2010JCLI3532.1 CrossRefGoogle Scholar
  52. Vimont DJ, Battisti DS, Hirst AC (2001) Footprinting: a seasonal connection between the tropics and mid-latitudes. Geophys Res Lett 28:3923–3926. doi:10.1029/2001GL013435 CrossRefGoogle Scholar
  53. Vimont DJ, Battisti DS, Hirst AC (2003a) The seasonal footprinting mechanism in the CSIRO general circulation models*. J Clim 16:2653–2667. doi:10.1175/1520-0442(2003)016<2653:TSFMIT>2.0.CO;2 CrossRefGoogle Scholar
  54. Vimont DJ, Wallace JM, Battisti DS (2003b) The seasonal footprinting mechanism in the pacific: implications for ENSO*. J Clim 16:2668–2675. doi:10.1175/1520-0442(2003)016<2668:TSFMIT>2.0.CO;2 CrossRefGoogle Scholar
  55. Vimont DJ, Alexander MA, Fontaine A (2009) Midlatitude excitation of tropical variability in the pacific: the role of thermodynamic coupling and seasonality*. J Clim 22:518–534. doi:10.1175/2008JCLI2220.1 CrossRefGoogle Scholar
  56. Vimont DJ, Alexander MA, Newman M (2014) Optimal growth of Central and East Pacific ENSO events. Geophys Res Lett 41:4027–4034. doi:10.1002/2014GL059997 CrossRefGoogle Scholar
  57. Yeh S-W, Wang X, Wang C, Dewitte B (2015) On the relationship between the north pacific climate variability and the central pacific El Niño. J Clim 28:663–677. doi:10.1175/JCLI-D-14-00137.1 CrossRefGoogle Scholar
  58. Yu J-Y, Kao H-Y (2007) Decadal changes of ENSO persistence barrier in SST and ocean heat content indices: 1958–2001. J Geophys Res Atmos 112. doi:10.1029/2006JD007654
  59. Yu J-Y, Kao H-Y, Lee T (2010) Subtropics-related interannual sea surface temperature variability in the central equatorial pacific. J Clim 23:2869–2884. doi:10.1175/2010JCLI3171.1 CrossRefGoogle Scholar
  60. Zhang F, Snyder C, Sun JZ (2004) Impacts of initial estimate and observation availability on convective-scale data assimilation with an ensemble Kalman filter. Mon Weather Rev 132:1238–1253CrossRefGoogle Scholar
  61. Zhang S, Harrison MJ, Rosati A, Wittenberg A (2007) System design and evaluation of coupled ensemble data assimilation for global oceanic climate studies. Mon Weather Rev 135:3541–3564. doi:10.1175/MWR3466.1 CrossRefGoogle Scholar
  62. Zhang L, Chang P, Ji L (2009) Linking the pacific meridional mode to ENSO: coupled model analysis. J Clim 22:3488–3505. doi:10.1175/2008JCLI2473.1 CrossRefGoogle Scholar
  63. Zhang H, Clement A, Di Nezio P (2014) The south pacific meridional mode: a mechanism for ENSO-like variability. J Clim 27:769–783. doi:10.1175/JCLI-D-13-00082.1 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Atmospheric and Oceanic Sciences, Nelson Institute Center for Climatic ResearchUniversity of Wisconsin-MadisonMadisonUSA
  2. 2.Laboratory for Climate, Ocean and Atmosphere StudiesPeking UniversityBeijingChina
  3. 3.Department of Atmospheric and Oceanic Science and Earth System Science Interdisciplinary CenterUniversity of Maryland, College ParkCollege ParkUSA
  4. 4.Geophysical Fluid Dynamics Laboratory, NOAAPrincetonUSA
  5. 5.Mathematics and Computer Science DivisionArgonne National LaboratoryArgonneUSA

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