Editorial Type:
Article
Article Type:
Research Article

The Role of Atmosphere Feedbacks during ENSO in the CMIP3 Models. Part III: The Shortwave Flux Feedback

James Lloyd Department of Meteorology, University of Reading, Reading, United Kingdom

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Eric Guilyardi LOCEAN/IPSL, Paris, France, and NCAS-Climate, Department of Meteorology, University of Reading, Reading, United Kingdom

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Hilary Weller NCAS-Climate, Department of Meteorology, University of Reading, Reading, United Kingdom

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Print Publication:
15 Jun 2012
DOI:
https://doi.org/10.1175/JCLI-D-11-00178.1
Page(s):
4275–4293
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Abstract

Previous studies using coupled general circulation models (GCMs) suggest that the atmosphere model plays a dominant role in the modeled El Niño–Southern Oscillation (ENSO), and that intermodel differences in the thermodynamical damping of sea surface temperatures (SSTs) are a dominant contributor to the ENSO amplitude diversity. This study presents a detailed analysis of the shortwave flux feedback (αSW) in 12 Coupled Model Intercomparison Project phase 3 (CMIP3) simulations, motivated by findings that αSW is the primary contributor to model thermodynamical damping errors.

A “feedback decomposition method,” developed to elucidate the αSW biases, shows that all models underestimate the dynamical atmospheric response to SSTs in the eastern equatorial Pacific, leading to underestimated αSW values. Biases in the cloud response to dynamics and the shortwave interception by clouds also contribute to errors in αSW. Changes in the αSW feedback between the coupled and corresponding atmosphere-only simulations are related to changes in the mean dynamics.

A large nonlinearity is found in the observed and modeled SW flux feedback, hidden when linearly calculating αSW. In the observations, two physical mechanisms are proposed to explain this nonlinearity: 1) a weaker subsidence response to cold SST anomalies than the ascent response to warm SST anomalies and 2) a nonlinear high-level cloud cover response to SST. The shortwave flux feedback nonlinearity tends to be underestimated by the models, linked to an underestimated nonlinearity in the dynamical response to SST. The process-based methodology presented in this study may help to correct model ENSO atmospheric biases, ultimately leading to an improved simulation of ENSO in GCMs.

Corresponding author address: Eric Guilyardi, LOCEAN/IPSL, UPMC, Case 100, 4 Place Jussieu, F-75252 Paris, France. E-mail: eric.guilyardi@locean-ipsl.upmc.fr

Abstract

Previous studies using coupled general circulation models (GCMs) suggest that the atmosphere model plays a dominant role in the modeled El Niño–Southern Oscillation (ENSO), and that intermodel differences in the thermodynamical damping of sea surface temperatures (SSTs) are a dominant contributor to the ENSO amplitude diversity. This study presents a detailed analysis of the shortwave flux feedback (αSW) in 12 Coupled Model Intercomparison Project phase 3 (CMIP3) simulations, motivated by findings that αSW is the primary contributor to model thermodynamical damping errors.

A “feedback decomposition method,” developed to elucidate the αSW biases, shows that all models underestimate the dynamical atmospheric response to SSTs in the eastern equatorial Pacific, leading to underestimated αSW values. Biases in the cloud response to dynamics and the shortwave interception by clouds also contribute to errors in αSW. Changes in the αSW feedback between the coupled and corresponding atmosphere-only simulations are related to changes in the mean dynamics.

A large nonlinearity is found in the observed and modeled SW flux feedback, hidden when linearly calculating αSW. In the observations, two physical mechanisms are proposed to explain this nonlinearity: 1) a weaker subsidence response to cold SST anomalies than the ascent response to warm SST anomalies and 2) a nonlinear high-level cloud cover response to SST. The shortwave flux feedback nonlinearity tends to be underestimated by the models, linked to an underestimated nonlinearity in the dynamical response to SST. The process-based methodology presented in this study may help to correct model ENSO atmospheric biases, ultimately leading to an improved simulation of ENSO in GCMs.

Corresponding author address: Eric Guilyardi, LOCEAN/IPSL, UPMC, Case 100, 4 Place Jussieu, F-75252 Paris, France. E-mail: eric.guilyardi@locean-ipsl.upmc.fr
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  • AchutaRao, K., and K. Sperber, 2006: ENSO simulations in coupled ocean-atmosphere models: Are the current models better? Climate Dyn., 27, 1–16.

    • Search Google Scholar
    • Export Citation

  • Barnett, T. P., M. Latif, E. Kirk, and E. Roeckner, 1991: On ENSO physics. J. Climate, 4, 487–515.

  • Battisti, D. S., and A. C. Hirst, 1989: Interannual variability in a tropical atmosphere–ocean model: Influence of the basic state, ocean geometry and nonlinearity. J. Atmos. Sci., 46, 1678–1712.

    • Search Google Scholar
    • Export Citation

  • Bjerknes, J., 1969: Atmospheric teleconnections from the equatorial Pacific. Mon. Wea. Rev., 97, 163–172.

  • Bony, S., and J.-L. Dufresne, 2005: Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models. Geophys. Res. Lett., 32, L20806, doi:10.1029/2005GL023851.

    • Search Google Scholar
    • Export Citation

  • Bony, S., K.-M. Lau, and Y. C. Sud, 1997: Sea surface temperature and large-scale circulation influences on tropical greenhouse effect and cloud radiative forcing. J. Climate, 10, 2055–2077.

    • Search Google Scholar
    • Export Citation

  • Collins, M., and Coauthors, 2010: The impact of global warming on the tropical Pacific and El Niño. Nat. Geosci., 3, 391–397.

  • Cronin, M. F., N. A. Bond, C. W. Fairall, and R. A. Weller, 2006: Surface cloud forcing in the east Pacific stratus deck/cold tongue/ITCZ complex. J. Climate, 19, 392–409.

    • Search Google Scholar
    • Export Citation

  • Davey, M., and Coauthors, 2001: STOIC: A study of coupled model climatology and variability in tropical regions. Climate Dyn., 18, 403–420.

    • Search Google Scholar
    • Export Citation

  • Delecluse, P., M. K. Davey, Y. Kitamura, S. G. H. Philander, M. Suarez, and L. Bengtsson, 1998: Coupled general circulation modeling of the tropical Pacific. J. Geophys. Res., 103 (C7), 14 357–14 373.

    • Search Google Scholar
    • Export Citation

  • Gordon, C., and R. A. Corry, 1991: A model simulation of the seasonal cycle in the tropical Pacific Ocean using climatological and modeled surface forcing. J. Geophys. Res., 96 (C1), 847–864.

    • Search Google Scholar
    • Export Citation

  • Guilyardi, E., 2006: El Niño-mean state-seasonal cycle interactions in a multi-model ensemble. Climate Dyn., 26, 329–348.

  • Guilyardi, E., and Coauthors, 2004: Representing El Niño in coupled ocean–atmosphere GCMs: The dominant role of the atmospheric component. J. Climate, 17, 4623–4629.

    • Search Google Scholar
    • Export Citation

  • Guilyardi, E., P. Braconnot, F.-F. Jin, S. T. Kim, M. Kolasinski, T. Li, and I. Musat, 2009a: Atmosphere feedbacks during ENSO in a coupled GCM with a modified atmospheric convection scheme. J. Climate, 22, 5698–5718.

    • Search Google Scholar
    • Export Citation

  • Guilyardi, E., A. Wittenberg, A. Fedorov, M. Collins, C. Wang, A. Capotondi, G. van Oldenborgh, and T. Stockdale, 2009b: Understanding El Niño in ocean–atmosphere general circulation models: Progress and challenges. Bull. Amer. Meteor. Soc., 90, 325–340.

    • Search Google Scholar
    • Export Citation

  • Jin, F.-F., S. T. Kim, and L. Bejarano, 2006: A coupled-stability index for ENSO. Geophys. Res. Lett., 33, L23708, doi:10.1029/2006GL027221.

    • Search Google Scholar
    • Export Citation

  • Kanamitsu, M., W. Ebisuzaki, J. Woollen, S.-K. Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter, 2002: NCEP–DOE AMIP-II Reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, 1631–1643.

    • Search Google Scholar
    • Export Citation

  • Kim, D., J.-S. Kug, I.-S. Kang, F.-F. Jin, and A. Wittenberg, 2008: Tropical Pacific impacts of convective momentum transport in the SNU coupled GCM. Climate Dyn., 31, 213–226.

    • Search Google Scholar
    • Export Citation

  • Kim, S. T., and F.-F. Jin, 2011: An ENSO stability analysis. Part II: Results from the twentieth and twenty-first century simulations of the CMIP3 models. Climate Dyn., 36, 1609–1627.

    • Search Google Scholar
    • Export Citation

  • Klein, S. A., and D. L. Hartmann, 1993: The seasonal cycle of low stratiform clouds. J. Climate, 6, 1587–1606.

  • Latif, M., and Coauthors, 2001: ENSIP: The El Niño Simulation Intercomparison Project. Climate Dyn., 18, 255–276.

  • Leloup, J., M. Lengaigne, and J.-P. Boulanger, 2008: Twentieth century ENSO characteristics in the IPCC database. Climate Dyn., 30, 277–291.

    • Search Google Scholar
    • Export Citation

  • Lin, J.-L., 2007: The double-ITCZ problem in IPCC AR4 coupled GCMs: Ocean–atmosphere feedback analysis. J. Climate, 20, 4497–4525.

  • Lloyd, J., E. Guilyardi, H. Weller, and J. Slingo, 2009: The role of atmosphere feedbacks during ENSO in the CMIP3 models. Atmos. Sci. Lett., 10, 170–176.

    • Search Google Scholar
    • Export Citation

  • Lloyd, J., E. Guilyardi, and H. Weller, 2011: The role of atmosphere feedbacks during ENSO in the CMIP3 models. Part II: Using AMIP runs to understand the heat flux feedback mechanisms. Climate Dyn., 37, 1271–1292.

    • Search Google Scholar
    • Export Citation

  • Meehl, G. A., C. Covey, T. Delworth, M. Latif, B. McAvaney, J. F. B. Mitchell, R. J. Stouffer, and K. E. Taylor, 2007: The WCRP CMIP3 multimodel dataset: A new era in climate change research. Bull. Amer. Meteor. Soc., 88, 1383–1394.

    • Search Google Scholar
    • Export Citation

  • Neale, R. B., J. H. Richter, and M. Jochum, 2008: The impact of convection on ENSO: From a delayed oscillator to a series of events. J. Climate, 21, 5904–5924.

    • Search Google Scholar
    • Export Citation

  • Park, S., and C. B. Leovy, 2004: Marine low-cloud anomalies associated with ENSO. J. Climate, 17, 3448–3469.

  • Philander, S., D. Gu, G. Lambert, T. Li, D. Halpern, N.-C. Lau, and R. Pacanowski, 1996: Why the ITCZ is mostly north of the equator. J. Climate, 9, 2958–2972.

    • Search Google Scholar
    • Export Citation

  • Philip, S., and G. J. van Oldenborgh, 2006: Shifts in ENSO coupling processes under global warming. Geophys. Res. Lett., 33, L11704, doi:10.1029/2006GL026196.

    • Search Google Scholar
    • Export Citation

  • Ramanathan, V., and W. Collins, 1991: Thermodynamic regulation of ocean warming by cirrus clouds deduced from observations of the 1987 El Niño. Nature, 351, 27–32.

    • Search Google Scholar
    • Export Citation

  • Reynolds, R. W., N. A. Rayner, T. M. Smith, D. C. Stokes, and W. Wang, 2002: An improved in situ and satellite SST analysis for climate. J. Climate, 15, 1609–1625.

    • Search Google Scholar
    • Export Citation

  • Reynolds, R. W., T. M. Smith, C. Liu, D. B. Chelton, K. S. Casey, and M. G. Schlax, 2007: Daily high-resolution-blended analyses for sea surface temperature. J. Climate, 20, 5473–5496.

    • Search Google Scholar
    • Export Citation

  • Rossow, W., A. Walker, D. E. Beuschel, and M. D. Roiter, 1996: International Satellite Cloud Climatology Project (ISCCP): Documentation of new cloud datasets. WCRP Rep. WMO/TD-737, 115 pp.

  • Sun, D.-Z., and Coauthors, 2006: Radiative and dynamical feedbacks over the equatorial cold tongue: Results from nine atmospheric GCMs. J. Climate, 19, 4059–4074.

    • Search Google Scholar
    • Export Citation

  • Sun, D.-Z., Y. Yu, and T. Zhang, 2009: Tropical water vapor and cloud feedbacks in climate models: A further assessment using coupled simulations. J. Climate, 22, 1287–1304.

    • Search Google Scholar
    • Export Citation

  • Toniazzo, T., M. Collins, and J. Brown, 2008: The variation of ENSO characteristics associated with atmospheric parameter perturbations in a coupled model. Climate Dyn., 30, 643–656.

    • Search Google Scholar
    • Export Citation

  • Uppala, S. M., and Coauthors, 2005: The ERA-40 Re-Analysis. Quart. J. Roy. Meteor. Soc., 131, 2961–3012.

  • van Oldenborgh, G. J., S. Y. Philip, and M. Collins, 2005: El Niño in a changing climate: A multi-model study. Ocean Sci., 1, 81–95.

  • Wittenberg, A. T., T. Rosati, and I. Held, 2003: ENSO in the GFDL coupled model. Eighth Annual CCSM Workshop, Breckenridge, CO, UCAR. [Available online at http://www.gfdl.noaa.gov/~atw/research/conf/ccsm8/talk.pdf.]

  • Wu, X., L. Deng, X. Song, G. Vettoretti, W. R. Peltier, and G. J. Zhang, 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, L16823, doi:10.1029/2007GL030637.

    • Search Google Scholar
    • Export Citation

  • Xie, S.-P., 2005: The shape of continents, air-sea interaction, and the rising branch of the Hadley circulation. The Hadley Circulation: Present, Past and Future, H. F. Diaz and R. S. Bradley, Eds., Advances in Global Change Research, Vol. 21, Kluwer Academic Publishers, 121–152.

  • Yu, L., and R. A. Weller, 2007: Objectively analyzed air–sea heat fluxes for the global ice-free oceans (1981–2005). Bull. Amer. Meteor. Soc., 88, 527–539.

    • Search Google Scholar
    • Export Citation

  • Zebiak, S. E., and M. A. Cane, 1987: A model El Niño–Southern Oscillation. Mon. Wea. Rev., 115, 2262–2278.

  • Zhang, T., and D.-Z. Sun, 2006: Response of water vapor and clouds to El Niño warming in three National Center for Atmospheric Research atmospheric models. J. Geophys. Res., 111, D17103, doi:10.1029/2005JD006700.

    • Search Google Scholar
    • Export Citation

  • Zhang, Y., W. B. Rossow, A. A. Lacis, V. Oinas, and M. I. Mishchenko, 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, D19105, doi:10.1029/2003JD004457.

    • Search Google Scholar
    • Export Citation
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