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Tristan S. L’Ecuyer and Greg McGarragh

, F. E. Volz , and J. S. Goring , 1972 : Optical properties of the atmosphere. 3rd ed. Air Force Cambridge Research Laboratory Tech. Rep. AFCRL-72-0497, 102 pp . McFarlane , S. A. , J. H. Mather , and T. P. Ackerman , 2007 : Analysis of tropical radiative heating profiles: A comparison of models and observations. J. Geophys. Res. , 112 , D14218 . doi:10.1029/2006JD008290 . Miles , N. L. , J. Verlinde , and E. E. Clothiaux , 2000 : Cloud droplet size distributions in

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Shoichi Shige, Yukari N. Takayabu, Satoshi Kida, Wei-Kuo Tao, Xiping Zeng, Chie Yokoyama, and Tristan L’Ecuyer

, cloud radiative forcing makes the largest contribution to the total diabatic heating after latent heating. Tao et al. (2003b , 2004) reported that net radiation (cooling) accounts for about 20% or more of the net condensation for the SCSMEX cloud systems simulated by the GCE model. The vertical profile of Q R can be estimated from the TMI and Visible and Infrared Scanner (VIRS) aboard the TRMM ( L’Ecuyer and Stephens 2003 ). The vertical profile of Q R estimated from the TRMM for the SCSMEX

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Wei-Kuo Tao, Stephen Lang, Xiping Zeng, Shoichi Shige, and Yukari Takayabu

others) wherein clouds are simulated under prescribed large-scale forcing. The default numerical experiment is two-dimensional (2D), using a 1-km horizontal resolution and vertical resolution that ranges from 42.5 m at the bottom to 1 km at the model top, which is at 22.5 km. The model uses a time step of 6 s and 512 × 41 grid points for integration. Please see Zeng et al. (2008 , 2009) for more details. b. Data 1) Oceanic convective systems (GATE, TOGA COARE, and SCSMEX) The South China Sea

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Yukari N. Takayabu, Shoichi Shige, Wei-Kuo Tao, and Nagio Hirota

convergence zones in both hemispheres along the equator (double ITCZ). Also, Bony and Dufrence (2005) reported that the largest disagreements in sensitivity of cloud radiative forcing (CRF) among climate models and between models and observations are found in regions of large-scale subsidence. Their study indicates that at least some of the cumulus parameterizations utilized in AGCMs do not properly represent the suppression of deep convection under the large-scale subsidence. These results strongly

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Shaocheng Xie, Timothy Hume, Christian Jakob, Stephen A. Klein, Renata B. McCoy, and Minghua Zhang

intertropical convergence zone of the eastern Atlantic. J. Atmos. Sci. , 36 , 53 – 72 . Vömel , H. , and Coauthors , 2007 : Radiation dry bias of the Vaisala RS 92 humidity sensor. J. Atmos. Oceanic Technol. , 24 , 953 – 963 . Xie , S. , S. A. Klein , M. Zhang , J. J. Yio , R. T. Cederwall , and R. McCoy , 2006 : Developing large-scale forcing data for single-column and cloud-resolving models from the Mixed-Phase Arctic Cloud Experiment. J. Geophys. Res. , 111 , D19104

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Yasu-Masa Kodama, Masaki Katsumata, Shuichi Mori, Sinsuke Satoh, Yuki Hirose, and Hiroaki Ueda

1. Introduction The global distribution of precipitation is related to water circulation in the climate system and to latent heating (LH) in the atmosphere, which is an important heat source driving atmospheric circulation ( Nigam et al. 2000 ). Characteristics of precipitation change greatly over a wide spectrum according to precipitation type and surface and atmospheric conditions. Satellite observations of clouds have provided useful but indirect information on precipitation. Precipitation

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Mircea Grecu, William S. Olson, Chung-Lin Shie, Tristan S. L’Ecuyer, and Wei-Kuo Tao

, nonprecipitating cloud ice, snow, and graupel. Precipitation and latent + eddy heating profiles are evaluated every hour of simulation time at each model horizontal gridpoint. The model is run for three 30-day periods, nudged by the large-scale advective forcing of temperature, humidity, and horizontal winds, using the method described in Tao et al. (2003b) . Advective forcings are derived from rawinsonde array observations from the South China Sea Monsoon Experiment (SCSMEX) Northern Enhanced Sounding Array

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Manuel D. Zuluaga, Carlos D. Hoyos, and Peter J. Webster

studies assume spatially and temporally uniform vertical heating profiles, even though it has been demonstrated that the structure of heating in precipitating cloud systems is highly variable ( Houze 1982 ). For example, Schumacher et al. (2004) show that geographical and temporal variability in convective and stratiform rain fractions, both of which have different vertical heating distributions, plays an important role in shaping the structure of the large-scale tropical circulation response

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Xianan Jiang, Duane E. Waliser, William S. Olson, Wei-Kuo Tao, Tristan S. L’Ecuyer, Jui-Lin Li, Baijun Tian, Yuk L. Yung, Adrian M. Tompkins, Stephen E. Lang, and Mircea Grecu

(below 500 hPa). During convectively active phases of the MJO, the radiative cooling rate is about 0.5 K day −1 , while it is about 1.5 K day −1 during convectively inactive phases of the MJO. The large variations in tropospheric radiative cooling could be a result of the atmospheric longwave cloud radiative forcing due to high cloud variations associated with the MJO (e.g., Tian et al. 2001 ; Tian and Ramanathan 2002 ; Lin et al. 2004 ). To summarize, compared to the TRMM estimates, the EC

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