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Sue Chen, Maria Flatau, Tommy G. Jensen, Toshiaki Shinoda, Jerome Schmidt, Paul May, James Cummings, Ming Liu, Paul E. Ciesielski, Christopher W. Fairall, Ren-Chieh Lien, Dariusz B. Baranowski, Nan-Hsun Chi, Simon de Szoeke, and James Edson

. Smith , J. Dykes , S. Chen , and R. Allard , 2011 : Air–sea interaction in the Ligurian Sea: Assessment of a coupled ocean–atmosphere model using in situ data from LASIE07 . Mon. Wea. Rev. , 139 , 1785 – 1808 , doi: 10.1175/2010MWR3431.1 . Smith , T. A. , and Coauthors , 2013 : Ocean–wave coupled modeling in COAMPS-TC: A study of Hurricane Ivan (2004) . Ocean Modell. , 69 , 181 – 194 , doi: 10.1016/j.ocemod.2013.06.003 . Sobel , A. , and E. Maloney , 2013 : Moisture modes

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James H. Ruppert Jr. and Fuqing Zhang

rainfall peak over the islands ( Ichikawa and Yasunari 2006 ; Fujita et al. 2011 ; Rauniyar and Walsh 2011 ; Sakaeda et al. 2017 ). With the arrival of the MJO envelope, in contrast, early-morning rainfall over the coastal and offshore regions is enhanced, while the diurnal variation over land is suppressed. A similar projection of diurnal rainfall variation onto the intraseasonal cycle has been documented in coastal South China ( Chen et al. 2019 ). Yet the interaction between the MC and MJO is

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Richard H. Johnson and Paul E. Ciesielski

. Hagos , Z. Feng , B. Yang , and M. Huang , 2016 : Assessing impacts of PBL and surface layer schemes in simulating the surface–atmosphere interactions and precipitation over the tropical ocean using observations from AMIE/DYNAMO . J. Climate , 29 , 8191 – 8210 , doi: 10.1175/JCLI-D-16-0040.1 . 10.1175/JCLI-D-16-0040.1 Rowe , A. K. , and R. A. Houze Jr. , 2015 : Cloud organization and growth during the transition from suppressed to active MJO conditions . J. Geophys. Res. Atmos

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Richard H. Johnson, Paul E. Ciesielski, James H. Ruppert Jr., and Masaki Katsumata

, 519 – 541 , doi: 10.1175/2009JCLI3018.1 . Lee , M.-I. , I.-S. Kang , J.-K. Kim , and B. E. Mapes , 2001 : Influence of cloud-radiation interaction on simulating tropical intraseasonal oscillation with an atmosphere general circulation model . J. Geophys. Res. , 106 , 14 291 – 14 233 , doi: 10.1029/2001JD900143 . Lin , J.-L. , and B. E. Mapes , 2004 : Radiation budget of the tropical intraseasonal oscillation . J. Atmos. Sci. , 61 , 2050 – 2062 , doi: 10

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Wen-wen Tung, Dimitrios Giannakis, and Andrew J. Majda

. , and F. Liu , 2011 : A model for scale interaction in the Madden–Julian oscillation . J. Atmos. Sci. , 68 , 2524 – 2536 , doi: 10.1175/2011JAS3660.1 . Webster , P. , and R. Lukas , 1992 : TOGA COARE: The Coupled Ocean–Atmosphere Response Experiment . Bull. Amer. Meteor. Soc. , 73 , 1377 – 1416 , doi: 10.1175/1520-0477(1992)073<1377:TCTCOR>2.0.CO;2 . Wheeler , M. , and G. N. Kiladis , 1999 : Convectively coupled equatorial waves: Analysis of clouds and temperature in the

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Weixin Xu and Steven A. Rutledge

convection is believed to be the primary limiting factor in MJO simulation and prediction ( Randall et al. 2003 ; Lin et al. 2006 ; Zhang et al. 2006 ; Benedict and Randall 2009 ). To improve parameterizations of clouds and physical precipitation processes in numerical models, it is important to quantify the evolution of convective cloud populations and convective/microphysical characteristics, understand the interaction between convection and the local environment (e.g., moisture and heating), and

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Emily M. Riley Dellaripa, Eric Maloney, and Susan C. van den Heever

with the microphysics and surface schemes. The Land Ecosystem–Atmosphere Feedback model, version 3 (LEAF-3), submodel within RAMS is used to represent surface–atmosphere heat and moisture exchange ( Walko et al. 2000 ). The RAMS simulations were approximately centered over the DYNAMO northern sounding array (NSA; Fig. 1 ). Simulations were run at two resolutions. A 1.5-km horizontal simulation was conducted with interactive LHFLXs to evaluate the convective-scale relationship of MJO precipitation

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Naoko Sakaeda, Scott W. Powell, Juliana Dias, and George N. Kiladis

suppressed envelopes. Therefore, further examination of how rain and cloud types vary diurnally and with the MJO is critical for a better understanding the diurnal cycle and its interactions with large-scale variability. Over open tropical oceans, the diurnal cycle of rainfall tends to have peak total rainfall in the early morning hours, in contrast to the late afternoon peaks over land ( Yang and Slingo 2001 ; Nesbitt and Zipser 2003 ; Kikuchi and Wang 2008 ). This early morning peak in rainfall over

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Simon P. de Szoeke, Eric D. Skyllingstad, Paquita Zuidema, and Arunchandra S. Chandra

2013 ; Moum et al. 2014 ; de Szoeke et al. 2015 ) documented the evolution of the structure and energy budgets of the atmosphere and upper ocean, of the interactions between the atmosphere and ocean, and of the convective population during the passage of two intraseasonal Madden–Julian oscillation (MJO) convective events. This study focuses on the statistics of convective cold pools and their effect on atmosphere–ocean interactions, as observed from the Revelle . Their effect will also be

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H. Bellenger, R. Wilson, J. L. Davison, J. P. Duvel, W. Xu, F. Lott, and M. Katsumata

1. Introduction To correctly represent Earth’s climate, it is imperative to understand and quantify the processes that play a role in water vapor variability. The nonlinear relationship between free-tropospheric moisture and outgoing longwave radiation at the top of the atmosphere (e.g., Spencer and Braswell 1997 ) is a well-known example of the importance of these processes for global climate. In addition, the characteristics of tropical moist convection strongly depend on the tropospheric

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