• Bellenger, H., , E. Guilyardi, , J. Leloup, , M. Lengaigne, , and J. Vialard, 2014: ENSO representation in climate models: From CMIP3 to CMIP5. Climate Dyn., 42, 1999–2018, doi:10.1007/s00382-013-1783-z.

    • Search Google Scholar
    • Export Citation
  • Boyle, J., , and S. A. Klein, 2010: Impact of horizontal resolution on climate model forecasts of tropical precipitation and diabatic heating for the TWP-ICE period. J. Geophys. Res., 115, D23113, doi:10.1029/2010JD014262.

    • Search Google Scholar
    • Export Citation
  • Brient, F., , and S. Bony, 2012: How may low-cloud radiative properties simulated in the current climate influence low-cloud feedbacks under global warming? Geophys. Res. Lett., 39, L20807, doi:10.1029/2012GL053265.

    • Search Google Scholar
    • Export Citation
  • Chen, L., , Y. Yu, , and D.-Z. Sun, 2013: Cloud and water vapor feedbacks to the El Niño warming: Are they still biased in CMIP5 models? J. Climate, 26, 29472961, doi:10.1175/JCLI-D-12-00575.1.

    • Search Google Scholar
    • Export Citation
  • Cole, J., , H. Barker, , N. Loeb, , and K. von Salzen, 2011: Assessing simulated clouds and radiative fluxes using properties of clouds whose tops are exposed to space. J. Climate, 24, 27152727, doi:10.1175/2011JCLI3652.1.

    • Search Google Scholar
    • Export Citation
  • Dai, A., 2006: Precipitation characteristics in eighteen coupled climate models. J. Climate, 19, 46054630, doi:10.1175/JCLI3884.1.

  • Dai, A., , and K. E. Trenberth, 2004: The diurnal cycle and its depiction in the Community Climate System Model. J. Climate, 17, 930951, doi:10.1175/1520-0442(2004)017<0930:TDCAID>2.0.CO;2.

    • 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, 56985718, doi:10.1175/2009JCLI2815.1.

    • Search Google Scholar
    • Export Citation
  • Guilyardi, E., , A. Wittenberg, , A. Fedorov, , M. Collins, , C. Wang, , A. Capotondi, , G. J. van Oldenborgh, , and T. Stockdale, 2009b: Understanding El Niño in ocean–atmosphere general circulation models: Progress and challenges. Bull. Amer. Meteor. Soc., 90, 325340, doi:10.1175/2008BAMS2387.1.

    • Search Google Scholar
    • Export Citation
  • Ham, Y.-G., , and J.-S. Kug, 2014: Effects of Pacific Intertropical Convergence Zone precipitation bias on ENSO phase transition. Environ. Res. Lett., 9, 064008, doi:10.1088/1748-9326/9/6/064008.

    • Search Google Scholar
    • Export Citation
  • Kim, D., , J.-S. Kug, , I.-S. Kang, , F.-F. Jin, , and A. T. Wittenberg, 2008: Tropical Pacific impacts of convective momentum transport in the SNU coupled GCM. Climate Dyn., 31, 213226, doi:10.1007/s00382-007-0348-4.

    • Search Google Scholar
    • Export Citation
  • Kim, D., , Y.-S. Jang, , D.-H. Kim, , Y.-H. Kim, , M. Watanabe, , F.-F. Jin, , and J.-S. Kug, 2011: El Niño–Southern Oscillation sensitivity to cumulus entrainment in a coupled general circulation model. J. Geophys. Res., 116, D22112, doi:10.1029/2011JD016526.

    • Search Google Scholar
    • Export Citation
  • Kim, S. T., , W. Cai, , F.-F. Jin, , and J.-Y. Yu, 2014: ENSO stability in coupled climate models and its association with mean state. Climate Dyn., 42, 3313–3321, doi:10.1007/s00382-013-1833-6.

    • Search Google Scholar
    • Export Citation
  • Klein, S. A., , and D. L. Hartmann, 1993: The seasonal cycle of low stratiform clouds. J. Climate, 6, 15871606, doi:10.1175/1520-0442(1993)006,1587:TSCOLS.2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Li, G., , and G. J. Zhang, 2008: Understanding biases in shortwave cloud radiative forcing in the National Center for Atmospheric Research Community Atmosphere Model (CAM3) during El Niño. J. Geophys. Res., 113, D02103, doi:10.1029/2007JD008963.

    • Search Google Scholar
    • Export Citation
  • Li, L. J., , B. Wang, , and G. J. Zhang, 2014: The role of nonconvective condensation processes in response of surface shortwave cloud radiative forcing to El Niño warming. J. Climate, 27, 67216736, doi:10.1175/JCLI-D-13-00632.1.

    • Search Google Scholar
    • Export Citation
  • Lin, J. L., , B. Mapes, , M. Zhang, , and M. Newman, 2004: Stratiform precipitation, vertical heating profiles, and the Madden–Julian oscillation. J. Atmos. Sci., 61, 296309, doi:10.1175/1520-0469(2004)061<0296:SPVHPA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • 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, 170176, doi:10.1002/asl.227.

    • 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, 12711292, doi:10.1007/s00382-010-0895-y.

    • Search Google Scholar
    • Export Citation
  • Lloyd, J., , E. Guilyardi, , and H. Weller, 2012: The role of atmosphere feedbacks during ENSO in the CMIP3 models. Part III: The shortwave feedback. J. Climate, 25, 42754293, doi:10.1175/JCLI-D-11-00178.1.

    • Search Google Scholar
    • Export Citation
  • Ma, H. Y., , S. Xie, , J. S. Boyle, , S. A. Klein, , and Y. Zhang, 2013: Metrics and diagnostics for precipitation-related processes in climate model short-range hindcasts. J. Climate, 26, 15161534, doi:10.1175/JCLI-D-12-00235.1.

    • Search Google Scholar
    • Export Citation
  • Mauritsen, T., and et al. , 2012: Tuning the climate of a global model. J. Adv. Model. Earth Syst., 4, M00A01, doi:10.1029/2012MS000154.

    • Search Google Scholar
    • Export Citation
  • Nam, C., , S. Bony, , J.-L. Dufresne, , and H. Chepfer, 2012: The ‘too few, too bright’ tropical low-cloud problem in CMIP5 models. Geophys. Res. Lett., 39, L21801, doi:10.1029/2012GL053421.

    • 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, 59045924, doi:10.1175/2008JCLI2244.1.

    • Search Google Scholar
    • Export Citation
  • 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, 29582972, doi:10.1175/1520-0442(1996)009<2958:WTIIMN>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Rayner, N. A., , D. E. Parker, , E. B. Horton, , C. K. Folland, , L. V. Alexander, , D. P. Rowell, , E. C. Kent, , and A. Kaplan, 2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res., 108, 4407, doi:10.1029/2002JD002670.

    • Search Google Scholar
    • Export Citation
  • Robertson, F. R., , D. E. Fitzjarrald, , and C. D. Kummerow, 2003: Effects of uncertainty in TRMM precipitation radar path integrated attenuation on interannual variations of tropical oceanic rainfall. Geophys. Res. Lett., 30, 1180, doi:10.1029/2002GL016416.

    • Search Google Scholar
    • Export Citation
  • Rossow, W. B., , and R. A. Schiffer, 1999: Advances in understanding clouds from ISCCP. Bull. Amer. Meteor. Soc., 80, 22612288, doi:10.1175/1520-0477(1999)080<2261:AIUCFI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Schumacher, C., , and R. A. Houze Jr., 2003: Stratiform rain in the Tropics as seen by the TRMM Precipitation Radar. J. Climate, 16, 17391756, doi:10.1175/1520-0442(2003)016<1739:SRITTA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Schumacher, C., , R. A. Houze Jr., , and I. Kraucunas, 2004: The tropical dynamical response to latent heating estimates derived from the TRMM Precipitation Radar. J. Atmos. Sci., 61, 13411358, doi:10.1175/1520-0469(2004)061<1341:TTDRTL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Seo, K. H., , and W. Q. Wang, 2010: The Madden–Julian oscillation simulated in the NCEP Climate Forecast System model: The importance of stratiform heating. J. Climate, 23, 47704793, doi:10.1175/2010JCLI2983.1.

    • Search Google Scholar
    • Export Citation
  • Shen, X., , Y. Wang, , and X. Li, 2011: Effects of vertical wind shear and cloud radiative processes on responses of rainfall to the large-scale forcing during pre-summer heavy rainfall over southern China. Quart. J. Roy. Meteor. Soc., 137, 236249, doi:10.1002/qj.735.

    • Search Google Scholar
    • Export Citation
  • Shonk, J., , R. Hogan, , G. Mace, , and J. Edwards, 2010: Effect of improving representation of horizontal and vertical cloud structure on the Earth’s global radiation budget. Part I: Review and parametrization. Quart. J. Roy. Meteor. Soc., 136, 11911204, doi:10.1002/qj.647.

    • Search Google Scholar
    • Export Citation
  • Sun, D.-Z., , J. Fasullo, , T. Zhang, , and A. Roubicek, 2003: On the radiative and dynamical feedbacks over the equatorial Pacific cold tongue. J. Climate, 16, 24252432, doi:10.1175/2786.1.

    • Search Google Scholar
    • Export Citation
  • Sun, D.-Z., and et al. , 2006: Radiative and dynamical feedbacks over the equatorial cold tongue: Results from nine atmospheric GCMs. J. Climate, 19, 40594074, doi:10.1175/JCLI3835.1.

    • 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, 12871304, doi:10.1175/2008JCLI2267.1.

    • Search Google Scholar
    • Export Citation
  • Sundqvist, H., 1978: A parameterization scheme for non-convective condensation including prediction of cloud water content. Quart. J. Roy. Meteor. Soc., 104, 677690, doi:10.1002/qj.49710444110.

    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., , R. J. Stouffer, , and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485498, doi:10.1175/BAMS-D-11-00094.1.

    • 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, 643656, doi:10.1007/s00382-007-0313-2.

    • Search Google Scholar
    • Export Citation
  • Uppala, S. M., and et al. , 2005: The ERA-40 Re-Analysis. Quart. J. Roy. Meteor. Soc., 131, 29613012, doi:10.1256/qj.04.176.

  • Vannière, B., , E. Guilyardi, , G. Madec, , F. J. Doblas-Reyes, , and S. Woolnough, 2013: Using seasonal hindcasts to understand the origin of the equatorial cold tongue bias in CGCMs and its impact on ENSO. Climate Dyn., 40, 963981, doi:10.1007/s00382-012-1429-6.

    • Search Google Scholar
    • Export Citation
  • Vannière, B., , E. Guilyardi, , T. Toniazzo, , G. Madec, , and S. Woolnough, 2014: A systematic approach to identify sources of tropical SST errors in coupled models using the adjustment of initialised experiments. Climate Dyn., 43, 22612282, doi:10.1007/s00382-014-2051-6.

    • Search Google Scholar
    • Export Citation
  • Watanabe, M., , M. Chikira, , Y. Imada, , and M. Kimoto, 2011: Convective control of ENSO simulated in MIROC. J. Climate, 24, 543562, doi:10.1175/2010JCLI3878.1.

    • Search Google Scholar
    • Export Citation
  • Webb, M., , C. Senior, , S. Bony, , and J. J. Morcrette, 2001: Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models. Climate Dyn., 17, 905922, doi:10.1007/s003820100157.

    • Search Google Scholar
    • Export Citation
  • Wu, R., , and B. P. Kirtman, 2007: Regimes of seasonal air–sea interaction and implications for performance of forced simulations. Climate Dyn., 29, 393410, doi:10.1007/s00382-007-0246-9.

    • 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.

    • Search Google Scholar
    • Export Citation
  • Xu, K.-M., , and D. A. Randall, 1996: A semiempirical cloudiness parameterization for use in climate models. J. Atmos. Sci., 53, 30843102, doi:10.1175/1520-0469(1996)053<3084:ASCPFU>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zebiak, S. E., , and M. A. Cane, 1987: A model El Niño–Southern Oscillation. Mon. Wea. Rev., 115, 22622278, doi:10.1175/1520-0493(1987)115<2262:AMENO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zhang, M., and et al. , 2005: Comparing clouds and their seasonal variations in 10 atmospheric general circulation models with satellite measurements. J. Geophys. Res., 110, D15S02, doi:10.1029/2004JD005021.

    • Search Google Scholar
    • Export Citation
  • 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, T., , and D.-Z. Sun, 2014: ENSO asymmetry in CMIP5 models. J. Climate, 27, 40704093, doi:10.1175/JCLI-D-13-00454.1.

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The Role of Moist Processes in Shortwave Radiative Feedback during ENSO in the CMIP5 Models

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  • 1 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • | 2 Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, and State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • | 3 Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing, China, and Scripps Institution of Oceanography, La Jolla, California
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Abstract

The weak negative shortwave (SW) radiative feedback αsw during El Niño–Southern Oscillation (ENSO) over the equatorial Pacific is a common problem in the models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). In this study, the causes for the αsw biases are analyzed using three-dimensional cloud fraction and liquid water path (LWP) provided by the 17 CMIP5 models and the relative roles of convective and stratiform rainfall feedbacks in αsw are explored. Results show that the underestimate of SW feedback is primarily associated with too negative cloud fraction and LWP feedbacks in the boundary layers, together with insufficient middle and/or high cloud and dynamics feedbacks, in both the CMIP and Atmospheric Model Intercomparsion Project (AMIP) runs, the latter being somewhat better. The underestimations of SW feedbacks are due to both weak negative SW responses to El Niño, especially in the CMIP runs, and strong positive SW responses to La Niña, consistent with their biases in cloud fraction, LWP, and dynamics responses to El Niño and La Niña. The convective rainfall feedback, which is largely reduced owing to the excessive cold tongue in the CMIP runs compared with their AMIP counterparts, contributes more to the difference of SW feedback (mainly under El Niño conditions) between the CMIP and AMIP runs, while the stratiform rainfall plays a more important role in SW feedback during La Niña.

Corresponding author address: Dr. Lijuan Li, LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, P.O. Box 9804, Beijing 100029, China. E-mail: ljli@mail.iap.ac.cn

Abstract

The weak negative shortwave (SW) radiative feedback αsw during El Niño–Southern Oscillation (ENSO) over the equatorial Pacific is a common problem in the models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). In this study, the causes for the αsw biases are analyzed using three-dimensional cloud fraction and liquid water path (LWP) provided by the 17 CMIP5 models and the relative roles of convective and stratiform rainfall feedbacks in αsw are explored. Results show that the underestimate of SW feedback is primarily associated with too negative cloud fraction and LWP feedbacks in the boundary layers, together with insufficient middle and/or high cloud and dynamics feedbacks, in both the CMIP and Atmospheric Model Intercomparsion Project (AMIP) runs, the latter being somewhat better. The underestimations of SW feedbacks are due to both weak negative SW responses to El Niño, especially in the CMIP runs, and strong positive SW responses to La Niña, consistent with their biases in cloud fraction, LWP, and dynamics responses to El Niño and La Niña. The convective rainfall feedback, which is largely reduced owing to the excessive cold tongue in the CMIP runs compared with their AMIP counterparts, contributes more to the difference of SW feedback (mainly under El Niño conditions) between the CMIP and AMIP runs, while the stratiform rainfall plays a more important role in SW feedback during La Niña.

Corresponding author address: Dr. Lijuan Li, LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, P.O. Box 9804, Beijing 100029, China. E-mail: ljli@mail.iap.ac.cn
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