The Signature of Shallow Circulations, Not Cloud Radiative Effects, in the Spatial Distribution of Tropical Precipitation

Dagmar Fläschner Max Planck Institute for Meteorology, Hamburg, Germany

Search for other papers by Dagmar Fläschner in
Current site
Google Scholar
PubMed
Close
,
Thorsten Mauritsen Max Planck Institute for Meteorology, Hamburg, Germany

Search for other papers by Thorsten Mauritsen in
Current site
Google Scholar
PubMed
Close
,
Bjorn Stevens Max Planck Institute for Meteorology, Hamburg, Germany

Search for other papers by Bjorn Stevens in
Current site
Google Scholar
PubMed
Close
, and
Sandrine Bony LMD/IPSL, CNRS, Sorbonne Universities, Paris, France

Search for other papers by Sandrine Bony in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Recent research suggests cloud–radiation interaction as key for intermodel differences in tropical precipitation change with warming. This motivates the hypothesis that intermodel differences in the climatology of precipitation, and in its response to warming, should reduce in the absence of cloud–radiation interaction. The hypothesis is explored with the aquaplanet simulations by the Clouds On-Off Klimate Intercomparison Experiment performed by seven general circulation models, wherein atmospheric cloud radiative effects (ACREs) are active (ACRE-on) and inactive (ACRE-off). Contrary to expectation, models’ climatology of tropical precipitation are more diverse in the ACRE-off experiments, as measured by the position of the intertropical convergence zone (ITCZ), the subtropical precipitation minima, and the associated organization of the tropical circulation. Also the direction of the latitudinal shift of the ITCZ differs more in simulations with inactive cloud radiative effects. Nevertheless, both in ACRE-on and ACRE-off, the same relationship between tropical precipitation and the mean vertical velocity (zonally, temporally, and vertically averaged) emerges in all models. An analysis framework based on the moist static energy budget and used in the moisture space is then developed to understand what controls the distribution of the mean vertical velocity. The results suggest that intermodel differences in tropical circulation and zonal-mean precipitation patterns are most strongly associated with intermodel differences in the representation of shallow circulations that connect dry and moist regions.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-18-0230.s1.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Bjorn Stevens, bjorn.stevens@mpimet.mpg.de

Abstract

Recent research suggests cloud–radiation interaction as key for intermodel differences in tropical precipitation change with warming. This motivates the hypothesis that intermodel differences in the climatology of precipitation, and in its response to warming, should reduce in the absence of cloud–radiation interaction. The hypothesis is explored with the aquaplanet simulations by the Clouds On-Off Klimate Intercomparison Experiment performed by seven general circulation models, wherein atmospheric cloud radiative effects (ACREs) are active (ACRE-on) and inactive (ACRE-off). Contrary to expectation, models’ climatology of tropical precipitation are more diverse in the ACRE-off experiments, as measured by the position of the intertropical convergence zone (ITCZ), the subtropical precipitation minima, and the associated organization of the tropical circulation. Also the direction of the latitudinal shift of the ITCZ differs more in simulations with inactive cloud radiative effects. Nevertheless, both in ACRE-on and ACRE-off, the same relationship between tropical precipitation and the mean vertical velocity (zonally, temporally, and vertically averaged) emerges in all models. An analysis framework based on the moist static energy budget and used in the moisture space is then developed to understand what controls the distribution of the mean vertical velocity. The results suggest that intermodel differences in tropical circulation and zonal-mean precipitation patterns are most strongly associated with intermodel differences in the representation of shallow circulations that connect dry and moist regions.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-18-0230.s1.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Bjorn Stevens, bjorn.stevens@mpimet.mpg.de

Supplementary Materials

    • Supplemental Materials (PDF 615.44 KB)
Save
  • Back, L. E., and C. S. Bretherton, 2006: Geographic variability in the export of moist static energy and vertical motion profiles in the tropical Pacific. Geophys. Res. Lett., 33, L17810, https://doi.org/10.1029/2006GL026672.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barsugli, J., S.-I. Shin, and P. D. Sardeshmukh, 2005: Tropical climate regimes and global climate sensitivity in a simple setting. J. Atmos. Sci., 62, 12261240, https://doi.org/10.1175/JAS3404.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Becker, T., B. Stevens, and C. Hohenegger, 2017: Imprint of the convective parameterization and sea-surface temperature on large-scale convective self-aggregation. J. Adv. Model. Earth Syst., 9, 14881505, https://doi.org/10.1002/2016MS000865.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bergman, J. W., and H. H. Hendon, 2000: Cloud radiative forcing of the low-latitude tropospheric circulation: Linear calculations. J. Atmos. Sci., 57, 22252245, https://doi.org/10.1175/1520-0469(2000)057<2225:CRFOTL>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bjerknes, J., 1938: Saturated-adiabatic ascent of air through dry-adiabatically descending environment. Quart. J. Roy. Meteor. Soc., 64, 325330.

    • Search Google Scholar
    • Export Citation
  • 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, https://doi.org/10.1029/2005GL023851.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bony, S., J.-L. Dufresne, H. Le Treut, J.-J. Morcrette, and C. Senior, 2004: On dynamic and thermodynamic components of cloud changes. Climate Dyn., 22, 7186, https://doi.org/10.1007/s00382-003-0369-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bony, S., G. Bellon, D. Klocke, S. Sherwood, S. Fermepin, and S. Denvil, 2013: Robust direct effect of carbon dioxide on tropical circulation and regional precipitation. Nat. Geosci., 6, 447451, https://doi.org/10.1038/ngeo1799; Corrigendum, 7, 547, https://doi.org/10.1038/ngeo2192.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bretherton, C. S., and A. H. Sobel, 2002: A simple model of a convectively coupled Walker circulation using the weak temperature gradient approximation. J. Climate, 15, 29072920, https://doi.org/10.1175/1520-0442(2002)015<2907:ASMOAC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bretherton, C. S., and M. F. Khairoutdinov, 2015: Convective self-aggregation feedbacks in near-global cloud-resolving simulations of an aquaplanet. J. Adv. Model. Earth Syst., 7, 17651787, https://doi.org/10.1002/2015MS000499.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bretherton, C. S., P. N. Blossey, and M. Khairoutdinov, 2005: An energy-balance analysis of deep convective self-aggregation above uniform SST. J. Atmos. Sci., 62, 42734292, https://doi.org/10.1175/JAS3614.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bui, H. X., J.-Y. Yu, and C. Chou, 2016: Impacts of vertical structure of large-scale vertical motion in tropical climate: Moist static energy framework. J. Atmos. Sci., 73, 44274437, https://doi.org/10.1175/JAS-D-16-0031.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Byrne, M. P., and T. Schneider, 2016: Energetic constraints on the width of the intertropical convergence zone. J. Climate, 29, 47094721, https://doi.org/10.1175/JCLI-D-15-0767.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cess, R. D., and Coauthors, 1990: Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. J. Geophys. Res., 95, 16 60116 615, https://doi.org/10.1029/JD095iD10p16601.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chou, C., and J. D. Neelin, 2004: Mechanisms of global warming impacts on regional tropical precipitation. J. Climate, 17, 26882701, https://doi.org/10.1175/1520-0442(2004)017<2688:MOGWIO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chou, C., T.-C. Wu, and P.-H. Tan, 2013: Changes in gross moist stability in the tropics under global warming. Climate Dyn., 41, 24812496, https://doi.org/10.1007/s00382-013-1703-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Collins, W. J., and Coauthors, 2011: Development and evaluation of an Earth-system model—HadGEM2. Geosci. Model Dev., 4, 10511075, https://doi.org/10.5194/gmd-4-1051-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coppin, D., and S. Bony, 2015: Physical mechanisms controlling the initiation of convective self-aggregation in a general circulation model. J. Adv. Model. Earth Syst., 7, 20602078, https://doi.org/10.1002/2015MS000571.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Crueger, T., and B. Stevens, 2015: The effect of atmospheric radiative heating by clouds on the Madden-Julian oscillation. J. Adv. Model. Earth Syst., 7, 854864, https://doi.org/10.1002/2015MS000434.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dahms, E., H. Borth, F. Lunkeit, and K. Fraedrich, 2011: ITCZ splitting and the influence of large-scale eddy fields on the tropical mean state. J. Meteor. Soc. Japan, 89, 399411, https://doi.org/10.2151/jmsj.2011-501.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dufresne, J.-L., and Coauthors, 2013: Climate change projections using the IPSL-CM5 Earth System Model: From CMIP3 to CMIP5. Climate Dyn., 40, 21232165, https://doi.org/10.1007/s00382-012-1636-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fermepin, S., and S. Bony, 2014: Influence of low-cloud radiative effects on tropical circulation and precipitation. J. Adv. Model. Earth Syst., 6, 513526, https://doi.org/10.1002/2013MS000288.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Harrop, B. E., and D. L. Hartmann, 2016: The role of cloud radiative heating in determining the location of the ITCZ in aquaplanet simulations. J. Climate, 29, 27412763, https://doi.org/10.1175/JCLI-D-15-0521.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hartmann, D. L., and K. Larson, 2002: An important constraint on tropical cloud–climate feedback. Geophys. Res. Lett., 29, 1951, https://doi.org/10.1029/2002GL015835.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hawkins, E., and R. Sutton, 2011: The potential to narrow uncertainty in projections of regional precipitation change. Climate Dyn., 37, 407418, https://doi.org/10.1007/s00382-010-0810-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hourdin, F., and Coauthors, 2013: LMDZ5B: The atmospheric component of the IPSL climate model with revisited parameterizations for clouds and convection. Climate Dyn., 40, 21932222, https://doi.org/10.1007/s00382-012-1343-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Inoue, K., and L. E. Back, 2015a: Column-integrated moist static energy budget analysis on various time scales during TOGA COARE. J. Atmos. Sci., 72, 18561871, https://doi.org/10.1175/JAS-D-14-0249.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Inoue, K., and L. E. Back, 2015b: Gross moist stability assessment during TOGA COARE: Various interpretations of gross moist stability. J. Atmos. Sci., 72, 41484166, https://doi.org/10.1175/JAS-D-15-0092.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Johnson, N. C., and S.-P. Xie, 2010: Changes in the sea surface temperature threshold for tropical convection. Nat. Geosci., 3, 842845, https://doi.org/10.1038/ngeo1008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kirtman, B. P., and E. K. Schneider, 2000: A spontaneously generated tropical atmospheric general circulation. J. Atmos. Sci., 57, 20802093, https://doi.org/10.1175/1520-0469(2000)057<2080:ASGTAG>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Knutti, R., and J. Sedláček, 2013: Robustness and uncertainties in the new CMIP5 climate model projections. Nat. Climate Change, 3, 369373, https://doi.org/10.1038/nclimate1716.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Landu, K., L. R. Leung, S. Hagos, V. Vinoj, S. A. Rauscher, T. Ringler, and M. Taylor, 2014: The dependence of ITCZ structure on model resolution and dynamical core in aquaplanet simulations. J. Climate, 27, 23752385, https://doi.org/10.1175/JCLI-D-13-00269.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, Y., D. W. J. Thompson, and S. Bony, 2015: The influence of atmospheric cloud radiative effects on the large-scale atmospheric circulation. J. Climate, 28, 72637278, https://doi.org/10.1175/JCLI-D-14-00825.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, Y., L. Guo, G. Wu, and Z. Wang, 2010: Sensitivity of ITCZ configuration to cumulus convective parameterizations on an aqua planet. Climate Dyn., 34, 223240, https://doi.org/10.1007/s00382-009-0652-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mauritsen, T., R. G. Graversen, D. Klocke, P. L. Langen, B. Stevens, and L. Tomassini, 2013: Climate feedback efficiency and synergy. Climate Dyn., 41, 25392554, https://doi.org/10.1007/s00382-013-1808-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Medeiros, B., B. Stevens, and S. Bony, 2015: Using aquaplanets to understand the robust responses of comprehensive climate models to forcing. Climate Dyn., 44, 19571977, https://doi.org/10.1007/s00382-014-2138-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Möbis, B., and B. Stevens, 2012: Factors controlling the position of the intertropical convergence zone on an aquaplanet. J. Adv. Model. Earth Syst., 4, M00A04, https://doi.org/10.1029/2012MS000199.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neale, R. B., and B. J. Hoskins, 2000: A standard test for AGCMs including their physical parametrizations: I: The proposal. Atmos. Sci. Lett., 1, 101107, https://doi.org/10.1006/asle.2000.0019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neelin, J. D., and I. M. Held, 1987: Modeling tropical convergence based on the moist static energy budget. Mon. Wea. Rev., 115, 312, https://doi.org/10.1175/1520-0493(1987)115<0003:MTCBOT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neelin, J. D., and N. Zeng, 2000: A quasi-equilibrium tropical circulation model—Formulation. J. Atmos. Sci., 57, 17411766, https://doi.org/10.1175/1520-0469(2000)057<1741:AQETCM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Numaguti, A., 1993: Dynamics and energy balance of the Hadley circulation and the tropical precipitation zones: Significance of the distribution of evaporation. J. Atmos. Sci., 50, 18741887, https://doi.org/10.1175/1520-0469(1993)050<1874:DAEBOT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oueslati, B., and G. Bellon, 2013a: Convective entrainment and large-scale organization of tropical precipitation: Sensitivity of the CNRM-CM5 hierarchy of models. J. Climate, 26, 29312946, https://doi.org/10.1175/JCLI-D-12-00314.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oueslati, B., and G. Bellon, 2013b: Tropical precipitation regimes and mechanisms of regime transitions: Contrasting two aquaplanet general circulation models. Climate Dyn., 40, 23452358, https://doi.org/10.1007/s00382-012-1344-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oueslati, B., S. Bony, C. Risi, and J.-L. Dufresne, 2016: Interpreting the inter-model spread in regional precipitation projections in the tropics: Role of surface evaporation and cloud radiative effects. Climate Dyn., 47, 28012815, https://doi.org/10.1007/s00382-016-2998-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peters, M. E., Z. Kuang, and C. C. Walker, 2008: Analysis of atmospheric energy transport in ERA-40 and implications for simple models of the mean tropical circulation. J. Climate, 21, 52295241, https://doi.org/10.1175/2008JCLI2073.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Popp, M., and N. J. Lutsko, 2017: Quantifying the zonal-mean structure of tropical precipitation. Geophys. Res. Lett., 44, 94709478, https://doi.org/10.1002/2017GL075235.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Popp, M., and L. G. Silvers, 2017: Double and single ITCZs with and without clouds. J. Climate, 30, 91479166, https://doi.org/10.1175/JCLI-D-17-0062.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ramanathan, V., 1987: The role of Earth radiation budget studies in climate and general circulation research. J. Geophys. Res., 92, 40754095, https://doi.org/10.1029/JD092iD04p04075.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Randall, D. A., Harshvardhan, D. A. Dazlich, and T. G. Corsetti, 1989: Interactions among radiation, convection, and large-scale dynamics in a general circulation model. J. Atmos. Sci., 46, 19431970, https://doi.org/10.1175/1520-0469(1989)046<1943:IARCAL>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Raymond, D. J., S. L. Sessions, A. H. Sobel, and Ž. Fuchs, 2009: The mechanics of gross moist stability. J. Adv. Model. Earth Syst., 1, 9, https://doi.org/10.3894/JAMES.2009.1.9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shepherd, T. G., 2014: Atmospheric circulation as a source of uncertainty in climate change projections. Nat. Geosci., 7, 703708, https://doi.org/10.1038/ngeo2253.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sherwood, S. C., V. Ramanathan, T. P. Barnett, M. K. Tyree, and E. Roeckner, 1994: Response of an atmospheric general circulation model to radiative forcing of tropical clouds. J. Geophys. Res., 99, 20 82920 845, https://doi.org/10.1029/94JD01632.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Slingo, A., and J. M. Slingo, 1988: The response of a general circulation model to cloud longwave radiative forcing. I: Introduction and initial experiments. Quart. J. Roy. Meteor. Soc., 114, 10271062, https://doi.org/10.1002/qj.49711448209.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Slingo, J. M., and A. Slingo, 1991: The response of a general circulation model to cloud longwave radiative forcing. II: Further studies. Quart. J. Roy. Meteor. Soc., 117, 333364, https://doi.org/10.1002/qj.49711749805.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sobel, A. H., J. Nilsson, and L. M. Polvani, 2001: The weak temperature gradient approximation and balanced tropical moisture waves. J. Atmos. Sci., 58, 36503665, https://doi.org/10.1175/1520-0469(2001)058<3650:TWTGAA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stevens, B., and S. Bony, 2013: What are climate models missing? Science, 340, 10531054, https://doi.org/10.1126/science.1237554.

  • Stevens, B., S. Bony, and M. Webb, 2012: Clouds On-Off Klimate Intercomparison Experiment (COOKIE). EUCLIPSE Tech. Rep., 12 pp., http://www.euclipse.eu/downloads/Cookie.pdf.

  • Stevens, B., and Coauthors, 2013: Atmospheric component of the MPI-M Earth System Model: ECHAM6. J. Adv. Model. Earth Syst., 5, 146172, https://doi.org/10.1002/jame.20015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tian, B., and V. Ramanathan, 2002: Role of tropical clouds in surface and atmospheric energy budget. J. Climate, 15, 296305, https://doi.org/10.1175/1520-0442(2002)015<0296:ROTCIS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., D. P. Stepaniak, and J. M. Caron, 2000: The global monsoon as seen through the divergent atmospheric circulation. J. Climate, 13, 39693993, https://doi.org/10.1175/1520-0442(2000)013<3969:TGMAST>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vial, J., J.-L. Dufresne, and S. Bony, 2013: On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates. Climate Dyn., 41, 33393362, https://doi.org/10.1007/s00382-013-1725-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Voigt, A., and T. A. Shaw, 2015: Circulation response to warming shaped by radiative changes of clouds and water vapour. Nat. Geosci., 8, 102106, https://doi.org/10.1038/ngeo2345.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Voigt, A., S. Bony, J.-L. Dufresne, and B. Stevens, 2014: The radiative impact of clouds on the shift of the intertropical convergence zone. Geophys. Res. Lett., 41, 43084315, https://doi.org/10.1002/2014GL060354.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Voldoire, A., and Coauthors, 2013: The CNRM-CM5.1 global climate model: Description and basic evaluation. Climate Dyn., 40, 20912121, https://doi.org/10.1007/s00382-011-1259-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Watanabe, M., and Coauthors, 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 63126335, https://doi.org/10.1175/2010JCLI3679.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wetherald, R. T., and S. Manabe, 1988: Cloud feedback processes in a general circulation model. J. Atmos. Sci., 45, 13971416, https://doi.org/10.1175/1520-0469(1988)045<1397:CFPIAG>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williamson, D. L., and Coauthors, 2013: The Aqua-Planet Experiment (APE): Response to changed meridional SST profile. J. Meteor. Soc. Japan, 91A, 5789, https://doi.org/10.2151/jmsj.2013-A03.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wing, A. A., K. Emanuel, C. E. Holloway, and C. Muller, 2017: Convective self-aggregation in numerical simulations: A review. Surv. Geophys., 38, 11731197, https://doi.org/10.1007/s10712-017-9408-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xie, S.-P., and Coauthors, 2015: Towards predictive understanding of regional climate change. Nat. Climate Change, 5, 921930, https://doi.org/10.1038/nclimate2689.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yu, J.-Y., C. Chou, and J. D. Neelin, 1998: Estimating the gross moist stability of the tropical atmosphere. J. Atmos. Sci., 55, 13541372, https://doi.org/10.1175/1520-0469(1998)055<1354:ETGMSO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yuan, J., and D. L. Hartmann, 2008: Spatial and temporal dependence of clouds and their radiative impacts on the large-scale vertical velocity profile. J. Geophys. Res., 113, D19201, https://doi.org/10.1029/2007JD009722.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yukimoto, S., and Coauthors, 2012: A new global climate model of the Meteorological Research Institute: MRI-CGCM3—Model description and basic performance. J. Meteor. Soc. Japan, 90A, 2364, https://doi.org/10.2151/jmsj.2012-A02.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zeng, N., J. D. Neelin, and C. Chou, 2000: A quasi-equilibrium tropical circulation model—Implementation and simulation. J. Atmos. Sci., 57, 17671796, https://doi.org/10.1175/1520-0469(2000)057<1767:AQETCM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1486 862 23
PDF Downloads 432 57 7