Advertisement

Climate Dynamics

, Volume 37, Issue 7–8, pp 1271–1292 | Cite as

The role of atmosphere feedbacks during ENSO in the CMIP3 models. Part II: using AMIP runs to understand the heat flux feedback mechanisms

  • James Lloyd
  • Eric Guilyardi
  • Hilary Weller
Article

Abstract

Several studies using ocean–atmosphere general circulation models (GCMs) suggest that the atmospheric component plays a dominant role in the modelled El Niño-Southern Oscillation (ENSO). To help elucidate these findings, the two main atmosphere feedbacks relevant to ENSO, the Bjerknes positive feedback (μ) and the heat flux negative feedback (α), are here analysed in nine AMIP runs of the CMIP3 multimodel dataset. We find that these models generally have improved feedbacks compared to the coupled runs which were analysed in part I of this study. The Bjerknes feedback, μ, is increased in most AMIP runs compared to the coupled run counterparts, and exhibits both positive and negative biases with respect to ERA40. As in the coupled runs, the shortwave and latent heat flux feedbacks are the two dominant components of α in the AMIP runs. We investigate the mechanisms behind these two important feedbacks, in particular focusing on the strong 1997–1998 El Niño. Biases in the shortwave flux feedback, α SW, are the main source of model uncertainty in α. Most models do not successfully represent the negative αSW in the East Pacific, primarily due to an overly strong low-cloud positive feedback in the far eastern Pacific. Biases in the cloud response to dynamical changes dominate the modelled α SW biases, though errors in the large-scale circulation response to sea surface temperature (SST) forcing also play a role. Analysis of the cloud radiative forcing in the East Pacific reveals model biases in low cloud amount and optical thickness which may affect α SW. We further show that the negative latent heat flux feedback, α LH, exhibits less diversity than α SW and is primarily driven by variations in the near-surface specific humidity difference. However, biases in both the near-surface wind speed and humidity response to SST forcing can explain the inter-model αLH differences.

Keywords

ENSO Atmospheric feedbacks Heat flux AMIP 

Notes

Acknowledgments

We thank Adam Scaife, Sandrine Bony, Richard Allan, Mark Ringer, Claire Barber and Fei-Fei Jin for useful discussions during the course of this work as well as support from the CORDIAL PICS from CNRS and the European Community ENSEMBLES (GOCE-CT-2003-505539, FP6) and EUCLIPSE (ENV/244067, FP7) projects. JL acknowledges support by a CASE grant from the Met Office and thanks Alejandro Bodas-Salcedo for supplying the ISCCP FD-TOA dataset. We also acknowledge the modelling groups, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP’s Working Group on Coupled Modelling (WGCM) for their roles in making available the WCRP CMIP3 multimodel dataset. Support of this dataset is provided by the Office of Science, US Department of Energy.

References

  1. AchutaRao K, Sperber K (2006) ENSO simulations in coupled ocean–atmosphere models: are the current models better? Clim Dyn 27:1–16CrossRefGoogle Scholar
  2. Allan R, Slingo A, Milton SF, Brooks ME (2007) Evaluation of the Met Office global forecast model using Geostationary Earth Radiation Budget (GERB) data. Quart J Roy Meteor Soc 133:1993–2010CrossRefGoogle Scholar
  3. Ambaum M (2010) Thermal physics of the atmosphere. Wiley-Blackwell, NJCrossRefGoogle Scholar
  4. Battisti DS, Hirst AC (1989) Interannual variability in the tropical atmosphere–ocean system: influence of the basic state and ocean geometry. J Atmos Sci 46:1678–1712CrossRefGoogle Scholar
  5. Bjerknes J (1969) Atmospheric teleconnections from the equatorial Pacific. Mon Wea Rev 97:163–172CrossRefGoogle Scholar
  6. Bony S, Dufresne J-L (2005) Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models. Geophys Res Lett 32:L20806CrossRefGoogle Scholar
  7. Bony S, Lau K-M, Sud YC (1997) Sea surface temperature and large-scale circulation influences on tropical greenhouse effect and cloud radiative forcing. J Clim 10:2055–2077CrossRefGoogle Scholar
  8. Capotondi A, Wittenberg A, Masina S (2006) Spatial and temporal structure of tropical Pacific interannual variability in 20th century coupled simulations. Ocean Modell 15:274298CrossRefGoogle Scholar
  9. Chou S-H, Nelkin EJ, Ardizzone J, Atlas RM, Shie C-L (2001) Goddard Satellite-based Surface Turbulent Fluxes (GSSTF) Version 2 documentation. Distributed Active Archive Center (DAAC), NASA Goddard Space Flight Center, Greenbelt, MarylandGoogle Scholar
  10. Collins M, An S-I, Cai W, Ganachaud A, Guilyardi E, Jin F-F, Jochum M, Lengaigne M, Power S, Timmermann A, Vecchi G, Wittenberg A (2010) The impact of global warming on the tropical Pacific and El Niño. Nat Geosci 3:391–397CrossRefGoogle Scholar
  11. Congbin F, Diaz H, Huijun F (1992) Variability in latent heat flux over the tropical Pacific in association with two ENSO events. Adv Atmos Sci 9(3):351–358CrossRefGoogle Scholar
  12. Cronin MF, Bond NA, Fairall CW, Weller RA (2006) Surface cloud forcing in the East Pacific Stratus Deck/Cold Tongue/ITCZ Complex. J Clim 19:392–409CrossRefGoogle Scholar
  13. Davey M, Huddleston M et al (2001) STOIC: a study of coupled model climatology and variability in tropical ocean regions. Clim Dyn 18:403–420Google Scholar
  14. Delecluse P, Davey M, Kitamura Y, Philander S, Suarez M, Bengtsson L (1998) TOGA review paper: coupled general circulation modeling of the tropical Pacific. J Geophys Res 103(C7):14357–14373CrossRefGoogle Scholar
  15. Gill AE (1980) Some simple solutions for heat-induced tropical circulation. Quart J R Met Soc 106:447–462CrossRefGoogle Scholar
  16. Goff JA (1957) Saturation pressure of water on the new Kelvin temperature scale. Trans Am Soc Heat Vent Eng pp 347–354Google Scholar
  17. Goff JA, Gratch S (1946) Low-pressure properties of water from −160 to 212 °F. Trans Am Soc Heat Vent Eng pp 95–122Google Scholar
  18. Guilyardi E (2006) El Niño—mean state—seasonal cycle interactions in a multi-model ensemble. Clim Dyn 26:229–348CrossRefGoogle Scholar
  19. Guilyardi E, Gualdi S, Slingo JM, Navarra A, Delecluse P, Cole J, Madec G, Roberts M, Latif M, Terray L (2004) Representing El Niño in coupled ocean–atmosphere GCMs: the dominant role of the atmospheric component. J. Clim 17:4623–4629CrossRefGoogle Scholar
  20. Guilyardi E, Braconnot P, Jin F-F, Kim ST, Kolasinski M, Li T, Musat I (2009a) Atmosphere feedbacks during ENSO in a coupled GCM with a modified atmospheric convection scheme. J Clim 22:5698–5718CrossRefGoogle Scholar
  21. Guilyardi E, Wittenberg A, Fedorov A, Collins M, Wang C, Capotondi A, van Oldenborgh G (2009b) Understanding El Niño in ocean–atmosphere general circulation models: progress and challenges. Bull Amer Met Soc 90(3):325–340CrossRefGoogle Scholar
  22. Harrison EF, Minnis P, Barkstrom BR, Ramanathan V, Cess RD, Gibson GG (1990) Seasonal variation of cloud radiative forcing derived from the Earth Radiation Budget Experiment. J Geophys Res 95:18687–18703CrossRefGoogle Scholar
  23. Jin FF, Kim ST, Bejarano L (2006) A coupled-stability index for ENSO. Geophys Res Lett 33:L23708CrossRefGoogle Scholar
  24. Kim D, Kug J-S, Kang I-S, Jin F-F, Wittenberg A (2008) Tropical Pacific impacts of convective momentum transport in the SNU coupled GCM. Clim Dyn 31:213–226CrossRefGoogle Scholar
  25. Kim ST, Jin F-F (2010) An ENSO stability analysis. Part II: results from the 20th and 21st century simulations of the IPCC AR4 models. Clim Dyn (accepted)Google Scholar
  26. Klein SA, Hartmann DL (1993) The seasonal cycle of low stratiform clouds. J Clim 6(8):1587–1606CrossRefGoogle Scholar
  27. Latif M, Sperber K, coauthors (2001) ENSIP: the El Niño simulation intercomparison project. Clim Dyn 18:255–276CrossRefGoogle Scholar
  28. Leloup J, Lengaigne M, Boulanger J-P (2008) Twentieth century ENSO characteristics in the IPCC database. Clim Dyn 30:277–291CrossRefGoogle Scholar
  29. Lin J-L (2007) The double-ITCZ problem in IPCC AR4 coupled GCMs: ocean–atmosphere feedback analysis. J Clim 20(18):4497–4525CrossRefGoogle Scholar
  30. Lloyd J, Guilyardi E, Weller H, Slingo J (2009) The role of atmosphere feedbacks during ENSO in the CMIP3 models. Atmos Sci Lett 10(3):170–176CrossRefGoogle Scholar
  31. Marti O, Braconnot P, Dufresne J-L, Bellier J, Benshila R, Bony S, Brockmann P, Cadule P, Caubel A, Codron F, de Noblet N, Denvil S, Fairhead L, Fichefet T, Foujols M-A, Friedlingstein P, Goosse H, Grandpeix J-Y, Guilyardi E, Hourdin F, Idelkadi A, Kageyama M, Krinner G, Levy C, Madec G, Mignot J, Musat I, Swingedouw D, Talandier C (2009) Key features of the IPSL ocean atmosphere model and its sensitivity to atmospheric resolution. Clim Dyn 34(1):1–26CrossRefGoogle Scholar
  32. McPhaden M (1999) Genesis and evolution of the 1997–1998 El Niño. Science 283:950–954CrossRefGoogle Scholar
  33. Meehl GA, Covey C, Delworth T, Latif M, McAvaney B, Mitchell JFB, Stouffer RJ, Taylor KE (2007) The WCRP CMIP3 multimodel dataset: a new era in climate change research. Bull Amer Met Soc 88:1383–1394CrossRefGoogle Scholar
  34. Park S, Leovy CB (2004) Marine low-cloud anomalies associated with ENSO. J Clim 17:3448–3469CrossRefGoogle Scholar
  35. Philander S, Gu D, Lambert G, Li T, Halpern D, Lau N-C, Pacanowski R (1996) Why the ITCZ is mostly North of the Equator. J Clim 9:2958–2972CrossRefGoogle Scholar
  36. Philip S, van Oldenborgh G (2006) Shifts in ENSO coupling processes under global warming. Geophys Res Lett 33:L11704CrossRefGoogle Scholar
  37. Potter GL, Cess RD (2004) Testing the impact of clouds on the radiation budgets of 19 atmospheric general circulation models. J Geophys Res 109:DO2106CrossRefGoogle Scholar
  38. Ramanathan V, Collins W (1991) Thermodynamic regulation of ocean warming by cirrus clouds deduced from observations of the 1987 El Niño. Nature 351:27–32CrossRefGoogle Scholar
  39. Ramanathan V, Cess RD, Harrison EF, Minnis P, Barkstrom BR, Ahmad E, Hartmann D (1991) Cloud-radiative forcing and climate: results from the Earth Radiation Budget Experiment. Science 243:57–63CrossRefGoogle Scholar
  40. Rossow W, Walker A, Beuschel D, Roiter M (1996) International Satellite Cloud Climatology Project (ISCCP) Documentation of New Cloud Datasets, vol 737. WMO/TD-No. 737, World Meteorological Organization, pp 115Google Scholar
  41. Schneider EK (2002) Understanding differences between the equatorial Pacific as simulated by two coupled GCMs. J Clim 15:449–469CrossRefGoogle Scholar
  42. Sun D-Z, Zhang T, Covey C, Klein SA, Collins WD, Hack JJ, Kiehl JT, Meehl GA, Held IM, Suarez M (2006) Radiative and dynamical feedbacks over the equatorial cold tongue: results from nine atmospheric GCMs. J Clim 19:4059–4074CrossRefGoogle Scholar
  43. Sun D-Z, Yu Y, Zhang T (2009) Tropical water vapor and cloud feedbacks in climate models: a further assessment using coupled simulations. J Clim 22:1287–1304CrossRefGoogle Scholar
  44. Uppala SM, Kallberg P, Simmons AJ, Andrae U, Bechtold VDC, Fiorino M, Gibson JK, Haseler J, Hernandez A, Kelly GA, Li X, Onogi K, Saarinen S, Sokka N, Allan RP, Andersson E, Arpe K, Balmaseda MA, Beljaars ACM, Berg LV, Bidlot J, Bormann N, Caires S, Chevallier F, Dethof A, Dragosavac M, Fisher M, Fuentes M, Hagemann S, Holm E, Morcrette J-J, Hoskins BJ, Isaksen L, Janssen PAEM, Jenne R, McNally AP, Mahfouf J-F, Rayner NA, Saunders RW, Simon P, Sterl A, Trenberth KE, Untch A, Vasiljevic D, Viterbo P, Woollen J (2005) The ERA-40 re-analysis. Quart J R Met Soc 131:2961–3012CrossRefGoogle Scholar
  45. van Oldenborgh GJ, Philip SY, Collins M (2005) El Niño in a changing climate: a multi-model study. Ocean Sci 1:81–95CrossRefGoogle Scholar
  46. Weare BC (2004) A comparison of AMIP II model cloud layer properties with ISCCP D2 Estimates. Clim Dyn 22:281–292CrossRefGoogle Scholar
  47. Wu X, Deng L, Song X, Vettoretti G, Peltier W, Zhang G (2007) Impact of a modified convective scheme on the Madden–Julian oscillation and El Niño southern oscillation in a coupled climate model. Geophys Res Lett 34:L16823CrossRefGoogle Scholar
  48. Xie S-P (2005) The shape of continents, air–sea interaction, and the rising branch of the Hadley circulation. Kluwer, Dordrecht Google Scholar
  49. Yu L, Weller RA (2007) Objectively analyzed air–sea heat fluxes (OAFlux) for the global oceans. Bull Amer Met Soc 88:527–539CrossRefGoogle Scholar
  50. Zebiak S, Cane M (1987) A model El Niño-Southern Oscillation. Mon Weather Rev 115:2262–2278CrossRefGoogle Scholar
  51. Zhang GJ, McPhaden MJ (1995) The relationship between sea surface temperature and latent heat flux in the Equatorial Pacific. J Clim 8(3):589–605CrossRefGoogle Scholar
  52. Zhang Y, Rossow WB, Lacis AA, Oinas V, Mishchenko MI (2004) Calculation of radiative fluxes from the surface to top of atmosphere based on ISCCP and other global data sets: refinements of the radiative transfer model and the input data. J Geophys Res 109:D19105CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Department of MeteorologyUniversity of ReadingReadingUK
  2. 2.Department of MeteorologyNCAS-ClimateReadingUK
  3. 3.LOCEAN/IPSL (CNRS/UPMC/IRD)ParisFrance

Personalised recommendations