Climate Dynamics

, Volume 50, Issue 1–2, pp 571–586 | Cite as

Influence of surface nudging on climatological mean and ENSO feedbacks in a coupled model

  • Jieshun ZhuEmail author
  • Arun Kumar


Studies have suggested that surface nudging could be an efficient way to reconstruct the subsurface ocean variability, and thus a useful method for initializing climate predictions (e.g., seasonal and decadal predictions). Surface nudging is also the basis for climate models with flux adjustments. In this study, however, some negative aspects of surface nudging on climate simulations in a coupled model are identified. Specifically, a low-resolution version of the NCEP Climate Forecast System, version 2 (CFSv2L) is used to examine the influence of nudging on simulations of climatological mean and on the coupled feedbacks during ENSO. The effect on ENSO feedbacks is diagnosed following a heat budget analysis of mixed layer temperature anomalies. Diagnostics of the climatological mean state indicates that, even though SST biases in all ocean basins, as expected, are eliminated, the fidelity of climatological precipitation, surface winds and subsurface temperature (or the thermocline depth) could be highly ocean basin dependent. This is exemplified by improvements in the climatology of these variables in the tropical Atlantic, but degradations in the tropical Pacific. Furthermore, surface nudging also distorts the dynamical feedbacks during ENSO. For example, while the thermocline feedback played a critical role during the evolution of ENSO in a free simulation, it only played a minor role in the nudged simulation. These results imply that, even though the simulation of surface temperature could be improved in a climate model with surface nudging, the physics behind might be unrealistic.



We thank NOAA’s Climate Program Office, Climate Observation Division for their support.


  1. An S-I, Jin F-F (2004) Nonlinearity and asymmetry of ENSO. J Clim 17:2399–2412CrossRefGoogle Scholar
  2. Balmaseda M, Mogensen K, Weaver A (2013) Evaluation of the ECMWF ocean reanalysis ORAS4. Quart J R Meteor Soc 139:1132–1161CrossRefGoogle Scholar
  3. Battisti DS (1988) The dynamics and thermodynamics of a warming event in a coupled tropical atmosphere/ocean model. J Atmos Sci 45:2889–2919CrossRefGoogle Scholar
  4. Battisti DS, Hirst AC (1989) Interannual variability in the tropical atmosphere–ocean model: influence of the basic state, ocean geometry and nonlinearity. J Atmos Sci 45:1687–1712CrossRefGoogle Scholar
  5. Behringer DW, Xue Y (2004) Evaluation of the global ocean data assimilation system at NCEP: the Pacific Ocean. Eighth symposium on integrated observing and assimilation systems for atmosphere, oceans, and land surface, AMS 84th Annual Meeting, Washington State Convention and Trade Center, Seattle, Washington, pp 11–15Google Scholar
  6. Bjerknes J (1969) Atmospheric teleconnections from the equatorial Pacific. Mon Weather Rev 97:163–172CrossRefGoogle Scholar
  7. DiNezio PN, Deser C (2014) Nonlinear controls on the persistence of La Nina. J Clim 27:7335–7355. doi: 10.1175/JCLI-D-14-00033.1 CrossRefGoogle Scholar
  8. Huang B, Shukla J (1997) Characteristics of the interannual and decadal variability in a general circulation model of the tropical Atlantic Ocean. J Phys Oceanogr 27:1693–1712CrossRefGoogle Scholar
  9. Jin F-F (1997) An equatorial ocean recharge paradigm for ENSO. Part I: conceptual model. J Atmos Sci 54:811–829CrossRefGoogle Scholar
  10. Jin EK, Coauthors (2008) Current status of ENSO prediction skill in coupled ocean–atmosphere models. Clim Dyn 31:647–664CrossRefGoogle Scholar
  11. Jin F-F, An S-I, Timmermann A, Zhao J (2003) Strong El Niño events and nonlinear dynamical heating. Geophys Res Lett 30(3):1120. doi: 10.1029/2002GL016356 CrossRefGoogle Scholar
  12. Jin F-F, Kim ST, Bejarano L (2006) A coupled-stability index for ENSO. Geophys Res Lett 33:L23708. doi: 10.1029/2006GL027221 CrossRefGoogle Scholar
  13. Kang I-S, An S-I, Jin FF (2001) A systematic approximation of the SST anomaly equation for ENSO. J Meteor Soc Jpn 79:1–10CrossRefGoogle Scholar
  14. Keenlyside NS, Latif M, Botzet M, Jungclaus J, Schulzweida U (2005) A coupled method for initializing El Niño–Southern Oscillation forecasts using sea surface temperature. Tellus 57A:340–356Google Scholar
  15. Keenlyside NS, Latif M, Jungclaus J, Kornblueh L, Roeckner E (2008) Advancing decadal-scale climate prediction in the North Atlantic sector. Nature 453:84–88CrossRefGoogle Scholar
  16. Kim ST, Jin F-F (2011) An ENSO stability analysis. Part I: results from a hybrid coupled model. Clim Dyn 36:1593–1607. doi: 10.1007/s00382-010-0796-0 CrossRefGoogle Scholar
  17. Kohyama T, Tozuka T (2016) Seasonal variability of the relationship between SST and OLR in the Indian Ocean and its implications for initialization in a CGCM with SST nudging. J Oceanogr 72:327–337CrossRefGoogle Scholar
  18. Kröger J, Kucharski F (2011) Sensitivity of ENSO characteristics to a new interactive flux correction scheme in a coupled GCM. Clim Dyn 37:119–137CrossRefGoogle Scholar
  19. Kumar A, Wang H, Xue Y, Wang W (2014a) How much of monthly subsurface temperature variability in the equatorial Pacific can be recovered by the specification of sea surface temperatures? J Clim 27:1559–1577CrossRefGoogle Scholar
  20. Kumar A, Jha B, Wang H (2014b) Attribution of SST variability in global oceans and the role of ENSO. Clim Dyn 43:209–220. doi: 10.1007/s00382-013-1865-y CrossRefGoogle Scholar
  21. Luo J-J, Masson S, Behera S, Shingu S, Yamagata T (2005) Seasonal climate predictability in a coupled OAGCM using a different approach for ensemble forecasts. J Clim 18:4474–4497CrossRefGoogle Scholar
  22. Luo J-J, Masson S, Behera SK, Yamagata T (2007) Experimental forecasts of the Indian Ocean dipole using a coupled OAGCM. J Clim 20:2178–2190CrossRefGoogle Scholar
  23. Luo J-J, Behera S, Masumoto Y, Yamagata T (2011) Impact of global ocean surface warming on seasonal-to-interannual climate prediction. J Clim 24:1626–1646. doi: 10.1175/2010JCLI3645.1 CrossRefGoogle Scholar
  24. Magnusson L, Balmaseda MA, Molteni F (2013a) On the dependence of ENSO simulation on the coupled model mean state. Clim Dyn 41:1509–1525CrossRefGoogle Scholar
  25. Magnusson L, Balmaseda MA, Corti S, Molteni F, Stockdale T (2013b) Evaluation of forecast strategies for seasonal and decadal forecasts in presence of systematic model errors. Clim Dyn 41:2393–2409CrossRefGoogle Scholar
  26. Manganello JV, Huang B (2009) The influence of systematic errors in the Southeast Pacific on ENSO variability and prediction in a coupled GCM. Clim Dyn 32:1015–1034CrossRefGoogle Scholar
  27. Meehl GA, Coauthors (2014) Decadal climate prediction: an update from the trenches. Bull Am Meteor Soc 95:243–267CrossRefGoogle Scholar
  28. Moura AD, Shukla J (1981) On the dynamics of the droughts in northeast Brazil: observations, theory and numerical experiments with a general circulation model. J Atmos Sci 38:2653–2675CrossRefGoogle Scholar
  29. Pan X, Huang B, Shukla J (2011) The influence of mean climate on the equatorial Pacific seasonal cycle and ENSO: simulation and prediction experiments using CCSM3. Clim Dyn 37:325–341. doi: 10.1007/s00382-010-0923-y CrossRefGoogle Scholar
  30. Picaut J, Ioualalen M, Menkes C, Delcroix T, McPhaden M (1996) Mechanism of the zonal displacements of the Pacific warm pool, implications for ENSO. Science 274:1486–1489CrossRefGoogle Scholar
  31. Ray S, Swingedouw D, Mignot J, Guilyardi E (2015) Effect of surface restoring on subsurface variability in a climate model during 1949–2005. Clim Dyn 44:2333–2349CrossRefGoogle Scholar
  32. Reynolds RW, Rayner NA, Smith TM, Stokes DC, Wang W (2002) An improved in situ and satellite SST analysis for climate. J Clim 15:1609–1625CrossRefGoogle Scholar
  33. Saha S, Coauthors (2010) The NCEP climate forecast system reanalysis. Bull Am Meteor Soc 91:1015–1057CrossRefGoogle Scholar
  34. Saha S, Coauthors (2014) The NCEP climate forecast system version 2. J Clim 27:2185–2208CrossRefGoogle Scholar
  35. Sausen R, Barthel K, Hasselmann K (1988) Coupled ocean–atmosphere models with flux correction. Clim Dyn 2:145–163CrossRefGoogle Scholar
  36. Servonnat J, Mignot J, Guilyardi E, Swingedouw D, Séférian R, Labetoulle S (2015) Reconstructing the subsurface ocean decadal variability using surface nudging in a perfect model framework. Clim Dyn 44:315–338. doi: 10.1007/s00382-014-2184-7 CrossRefGoogle Scholar
  37. Spencer H, Sutton R, Slingo JM (2007) El Niño in a coupled climate model: sensitivity to changes in mean state induced by heat flux and wind stress corrections. J Clim 20:2273–2298CrossRefGoogle Scholar
  38. Suarez MJ, Schopf PS (1988) A delayed action oscillator for ENSO. J Atmos Sci 45:3283–3287CrossRefGoogle Scholar
  39. Swingedouw D, Mignot J, Labetoulle S, Guilyardi E, Madec G (2013) Initialisation and predictability of the AMOC over the last 50 years in a climate model. Clim Dyn 40:2381–2399CrossRefGoogle Scholar
  40. Vecchi GA et al (2014) On the seasonal forecasting of regional tropical cyclone activity. J Clim 27:7994–8016. doi: 10.1175/JCLI-D-14-00158.1 CrossRefGoogle Scholar
  41. Wang H, Kumar A, Wang W (2013) Characteristics of subsurface ocean response to ENSO assessed from simulations with the NCEP Climate Forecast System. J Clim 26:8065–8083CrossRefGoogle Scholar
  42. Xiang B, Wang B, Ding Q, Jin F, Fu X, Kim HJ (2012) Reduction of the thermocline feedback associated with mean sst bias in ENSO simulation. Clim Dyn 39:1413–1430CrossRefGoogle Scholar
  43. Xie P, Arkin P (1997) Global precipitation: a 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull Am Meteor Soc 78:2539–2558CrossRefGoogle Scholar
  44. Xue Y, Chen M, Kumar A, Hu Z-Z, Wang W (2013) Prediction skill and bias of tropical Pacific sea surface temperatures in the NCEP Climate Forecast System version 2. J Clim 26:5358–5378CrossRefGoogle Scholar
  45. Zelle H, Appeldoorn G, Burgers G, van Oldenborgh GJ (2004) The relationship between sea surface temperature and thermocline depth in the eastern equatorial Pacific. J Phys Oceanogr 34:643–655. doi: 10.1175/2523.1 CrossRefGoogle Scholar
  46. Zhu J, Shukla J (2013) The role of air-sea coupling in seasonal prediction of Asian-Pacific summer monsoon rainfall. J Clim 26:5689–5697. doi: 10.1175/JCLI-D-13-00190.1 CrossRefGoogle Scholar
  47. Zhu J, Zhou G-Q, Zhang R-H, Sun Z (2011) On the role of oceanic entrainment temperature (Te) in decadal changes of El Niño/Southern Oscillation. Ann Geophys 29:529–540. doi: 10.5194/angeo-29-529-2011 CrossRefGoogle Scholar
  48. Zhu J, Huang B, Balmaseda MA (2012) An ensemble estimation of the variability of upper-ocean heat content over the tropical Atlantic Ocean with multi-ocean reanalysis products. Clim Dyn 39:1001–1020. doi: 10.1007/s00382-011-1189-8 CrossRefGoogle Scholar
  49. Zhu J, Kumar A, Wang H, Huang B (2015a) Sea surface temperature predictions in NCEP CFSv2 using a simple ocean initialization scheme. Mon Weather Rev 143:3176–3191CrossRefGoogle Scholar
  50. Zhu J, Kumar A, Huang B (2015b) The relationship between thermocline depth and SST anomalies in the eastern equatorial Pacific: seasonality and decadal variations. Geophys Res Lett 42:4507–4515. doi: 10.1002/2015GL064220 CrossRefGoogle Scholar
  51. Zhu J, Kumar A, Lee H-C, Wang H (2017a) Seasonal predictions using a simple ocean initialization scheme. Clim Dyn. doi: 10.1007/s00382-017-3556-6 (published online) Google Scholar
  52. Zhu J, Wang W, Kumar A (2017b) Simulations of MJO propagation across the Maritime continent: impacts of SST feedback. J Clim 30:1689–1704. doi: 10.1175/JCLI-D-16-0367.1 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Climate Prediction Center, NOAA/NWS/NCEPCollege ParkUSA
  2. 2.Earth System Science Interdisciplinary CenterUniversity of MarylandCollege ParkUSA

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