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Hyodae Seo, Aneesh C. Subramanian, Arthur J. Miller, and Nicholas R. Cavanaugh

shallow cumulus convection scheme ( Park and Bretherton 2009 ) and an updated moist boundary layer scheme by Bretherton and Park (2009) , produces a reasonably realistic intraseasonal lead–lag relationship between SST and convection (not shown). The WRF Model is also run with the Rapid Radiation Transfer Model (RRTM; Mlawer and Clough 1997 ) and the Goddard scheme ( Chou and Suarez 1999 ) for longwave and shortwave radiation transfer through the atmosphere. The Noah land surface model is used for

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Kunio Yoneyama, Chidong Zhang, and Charles N. Long

studies on convection–circulation coupling of the MJO. The 2011–12 MJO field campaign provided observations that are unique in several aspects in comparison to previous tropical field campaigns that aimed at interactions between atmospheric convection and its large-scale environment and between the atmosphere and ocean. It is the only one in the tropical IO with continuous time series of atmospheric and upper-ocean profiles. It is the first time the entire cloud population ranging from shallow

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Adrian J. Matthews, Dariusz B. Baranowski, Karen J. Heywood, Piotr J. Flatau, and Sunke Schmidtko

1. Introduction Ocean–atmosphere interaction is a key process in tropical weather and climate. The moisture flux from the ocean to atmosphere increases approximately exponentially with sea surface temperature (SST) through the Clausius–Clapeyron and bulk flux relationships ( Fairall et al. 1996b ). These processes are core to the evolution of El Niño–Southern Oscillation (ENSO; Neelin et al. 1998 ) on interannual time scales. On shorter, intraseasonal time scales, ocean–atmosphere interaction

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Shuguang Wang, Adam H. Sobel, Fuqing Zhang, Y. Qiang Sun, Ying Yue, and Lei Zhou

-scale structure of dynamical variables (temperature, zonal winds, humidity, and vertical motion) derived from the sounding network ( Johnson and Ciesielski 2013 ; Ciesielski et al. 2014 ), the cloud population observed from the ground-based precipitation radars (e.g., Zuluaga and Houze 2013 ; Powell and Houze 2013 ), the air and sea processes regulating the atmosphere–ocean interaction ( Moum et al. 2013 ), and the budget of moist static energy in the northern sounding array ( Sobel et al. 2014 , hereafter

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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 N. Moum, Simon P. de Szoeke, William D. Smyth, James B. Edson, H. Langley DeWitt, Aurélie J. Moulin, Elizabeth J. Thompson, Christopher J. Zappa, Steven A. Rutledge, Richard H. Johnson, and Christopher W. Fairall

Observations from 1 km beneath to 25 km above the sea surface reveal the complex interactions in Indian Ocean westerly wind bursts associated with the Madden–Julian oscillation. The Madden–Julian oscillation (MJO; Madden and Julian 1971 , 1972 ) is a disturbance of the atmosphere over tropical oceans associated with surface westerly wind bursts, deep convection, and heavy precipitation. MJO convection typically initiates in the Indian Ocean, travels eastward at roughly 5 m s −1 along the

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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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Kacie E. Hoover, John R. Mecikalski, Timothy J. Lang, Xuanli Li, Tyler J. Castillo, and Themis Chronis

directed to Yoneyama et al. (2013) for the setup of the project, to Gottschalck et al. (2013) for the large-scale conditions, and to de Szoeke et al. (2015) for air–sea interactions. The first three MJO events of DYNAMO are interesting because they can each be labeled as high-frequency, or short interval, MJO events that each had an approximately 30-day oscillation. The RMM index for these events can be seen in Fig. 1 , which was used to classify a given MJO’s intensity. From Fig. 1 , the

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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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