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Brian Mapes, Arunchandra S. Chandra, Zhiming Kuang, Siwon Song, and Paquita Zuidema

divergence can be interpreted to within observational error as “diabatic divergence,” denoted herein as D d ( Raymond 1983 ; Mapes and Houze 1995 ), which is the pressure vertical derivative of the quotient of total heating rate Q 1 = Q + Q R divided by a static stability profile. In this work, static stability is taken to be time independent, from a time-mean tropical profile of virtual temperature, and we neglect the contribution of Q R . One check that our radar-derived divergence D is a

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James H. Ruppert Jr. and Richard H. Johnson

advancement beyond medium-range predictability ( Hendon et al. 2000 ; Waliser et al. 2003 , 2012 ; Lin et al. 2006 ; Moncrieff et al. 2012 ). While studies have elucidated the principal diabatic heating structure and convective cloud evolution of the MJO, the physics governing the transition from predominant shallow cumuli to widespread, organized deep convection during MJO convective initiation remains largely unsolved ( Bladé and Hartmann 1993 ; Maloney and Hartmann 1998 ; Johnson et al. 1999

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Adam Sobel, Shuguang Wang, and Daehyun Kim

, even though the conclusions necessarily lack the generality associated with statistical analyses of longer records. Our expectations, based on previous work (e.g., Sobel et al. 2008 , 2010 ; Maloney 2009 ; Kiranmayi and Maloney 2011 ; Ma and Kuang 2011 ; Andersen and Kuang 2012 ; Kim et al. 2014 ) are the following. Precipitation and column-integrated MSE are approximately in phase [or MSE leads slightly (e.g., Yasunaga and Mapes 2012 )]. Radiative heating is approximately in phase with

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Ji-Eun Kim, Chidong Zhang, George N. Kiladis, and Peter Bechtold

in section 3c . The remaining two main diabatic components are produced by parameterization schemes for cumulus convection and microphysics. The realism of these two schemes is impossible to know without more detailed observations. We therefore put our faith in these components from the IFS, present their results in the next section, and trust that they will be further validated in the future. 4. Structural evolution of heating and moistening In this section, we examine the structural evolution

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Walter M. Hannah, Brian E. Mapes, and Gregory S. Elsaesser

appropriate. It would be very convenient if the vertical structure of the diabatic heating profile (i.e., M 1 and M 2 ) or a characterization of the cloud population was sufficient to determine the sign of the LCT. Figures 16b and 18 – 21 suggest that this is not possible because none of the heating modes or cloud types is confined to one sign of the LCT. This also holds when variations of surface evaporation are considered (not shown). In other words, there is no threshold of shallow convective

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Matthew A. Janiga and Chidong Zhang

tropics, vertical velocity is closely related to the diabatic heating within clouds ( Sobel et al. 2001 ). Taking advantage of this fact, Chikira (2014) used a global model with parameterized convection to examine the contribution of different physics processes to the moisture tendency observed during the passage of an MJO envelope. This included the contribution of each process to the large-scale moisture advection diagnosed by relating large-scale velocity and simulated diabatic heating. In this

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

platforms: cloud and precipitation radars, profilers, sounding networks, aircraft, and satellites. This study focuses primarily on one aspect of the DYNAMO measurement system—the sounding network—to compute heat and moisture budgets following the procedures of Yanai et al. (1973) , with the goal of inferring properties of convective systems and their roles of latent heating and moistening/drying within the MJO. While there have been numerous studies investigating diabatic heating in the MJO using

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Paul E. Ciesielski, Richard H. Johnson, Wayne H. Schubert, and James H. Ruppert Jr.

their diurnal trend is similar if contributions from these other “less certain” stratiform categories are included. For the results to be shown, we define the column-integrated diabatic heating following Yanai et al. (1973) as where <()> is the vertical integral from the tropopause pressure level p T to the surface pressure p S , Q 1 the diabatic heating, Q conv the convective heating, S the surface sensible heat flux, P o the surface precipitation, L the latent heat of vaporization

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Michael S. Pritchard and Christopher S. Bretherton

different story about SPCAM's MJO amplitude response to α than a wind-centric amplitude metric. Figure 3 indicates that, opposite to the wind amplitude response, intraseasonal OLR variance actually tends to decrease at high α . The question naturally arises as to how it is possible for amplified MJO wind anomalies to occur in tandem with weaker diabatic heating anomalies. One hypothesis is that environmental dry static stability decreases with α such that the mean-state arguments of Knutson and

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David M. Zermeño-Díaz, Chidong Zhang, Pavlos Kollias, and Heike Kalesse

1. Introduction In the tropics, shallow cumulus clouds (herein called shallow clouds) are the most populous cloud type ( Lau and Wu 2003 ; Masunaga and Kummerow 2006 ) and produce about 20% of the total rainfall ( Short and Nakamura 2000 ). They are embryos for tropical deep convective disturbances in different time scales ( Mapes et al. 2006 ). Diabatic heating and moistening effects from shallow clouds have been suggested to be particularly important to the Madden–Julian oscillation (MJO

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