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Michael S. Pritchard and Christopher S. Bretherton

focuses on just the role of the rotational component of the moisture advection and 2) that it focuses on a version of the Superparameterized Community Atmosphere Model (SPCAM) that has a well-validated MJO signal and a realistic (real geography) basic state. The first point is inspired by a philosophical view that vorticity is one of the likely sources of memory available in the tropics to help explain the slowness of the MJO as an internal atmospheric disturbance. The second point aims to break

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Simon P. de Szoeke, James B. Edson, June R. Marion, Christopher W. Fairall, and Ludovic Bariteau

1. Introduction The Madden–Julian oscillation (MJO) is the leading intraseasonal (30–60 day) mode of atmospheric variability of the equatorial atmosphere [ Madden and Julian (1971) , reviewed in Waliser (2006) ]. It comprises alternating zonal wind anomalies in the lower and upper troposphere of the planetary zonal scale. Deep convection accompanies surface convergence and upper-level divergence, and suppressed convection accompanies surface divergence. The 30–60-day time scale of the MJO is

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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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Eric D. Skyllingstad and Simon P. de Szoeke

1. Introduction Within 10° latitude of the equator, organized atmospheric convection occurs across scales ranging from individual thunderstorm systems to planetary-scale disturbances such as the Madden–Julian oscillation (MJO). Understanding what drives these different scales is a key question for tropical weather prediction and accurate simulation of the atmospheric general circulation. At the cloud scale, we have a fairly good knowledge of convective system structure and the processes that

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Tim Li, Chongbo Zhao, Pang-chi Hsu, and Tomoe Nasuno

radiation (OLR), confirmed the planetary scale of the MJO ( Weickmann 1983 ; Murakami and Nakazawa 1985 ; Lau and Chan 1986 ; Li and Zhou 2009 ). Studies also show that the oscillation is more broadband than the original 40–50-day period identified by Madden and Julian (1971) and can span a range of 20–100 days (e.g., Krishnamurti and Subrahmanyam 1982 ; Annamalai and Slingo 2001 ; Lau and Waliser 2005 ; Zhang 2005 ; Li and Wang 2005 , Waliser 2006 ). As the most significant variability

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Kai-Chih Tseng, Chung-Hsiung Sui, and Tim Li

1. Introduction Since Madden and Julian (1972) found the eastward-propagating oscillations over the tropical Indo-Pacific region, many observational analyses have revealed a slowly eastward-propagating convective envelope characterized by planetary-scale circulation with a broad life span of 30–60 days (e.g., Lau and Chan 1986 ; Hendon and Salby 1994 ; Zhang 2005 ; Lau and Waliser 2005 ). Despite numerous studies about the Madden–Julian oscillation (MJO), some fundamental questions still

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Samson M. Hagos, Zhe Feng, Casey D. Burleyson, Chun Zhao, Matus N. Martini, and Larry K. Berg

surface rainfall as well as observed top-of-atmosphere and surface radiation based on the method developed by Zhang et al. (2001) . Three versions of the forcing data using the above-mentioned precipitation products are used to account for uncertainties in the rainfall estimates. The forcing dataset is used as a proxy for observations in this study rather than to drive model simulations (as they are commonly used). The length of the forcing time series is 90 days (1 October–31 December 2011). The

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Simon P. de Szoeke

moisture, parameterized in general circulation models, can be assessed directly by eddy covariance in cloud-permitting models, and these model results can be constrained by verification against observations of the BL budgets of conserved variables. The conserved variables also constrain direct estimates of MSE fluxes at the BL top by remote sensing. Noting relatively uniform temperature of the tropical atmosphere ( Sobel et al. 2001 ), moisture-mode theories (e.g., Sugiyama 2009 ; Raymond and Fuchs

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Richard H. Johnson and Paul E. Ciesielski

cycle climatology of planetary boundary layer height . J. Climate , 23 , 5790 – 5809 , doi: 10.1175/2010JCLI3552.1 . 10.1175/2010JCLI3552.1 Malkus , J. S. , 1958 : On the structure of the trade wind moist layer. MIT and WHOI Papers in Physical Oceanography and Meteorology, Vol. 13, No. 2, 47 pp., doi: 10.1575/1912/1065 . 10.1575/1912/1065 Malkus , J. S. , and M. E. Stern , 1953 : The flow of a stable atmosphere over a heated island, part 1 . J. Meteor. , 10 , 30 – 41 , doi: 10

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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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