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Adam Sobel, Shuguang Wang, and Daehyun Kim

with energy fluxes at the boundaries—surface turbulent fluxes and radiative fluxes—is important to its growth and maintenance (e.g., Sobel et al. 2008 , 2010 ; see also Emanuel 1987 ; Neelin et al. 1987 ; Raymond 2001 ; Bony and Emanuel 2005 ). This view follows earlier theoretical and modeling studies which posited that the MJO might be driven by feedbacks involving surface turbulent fluxes ( Emanuel 1987 ; Neelin et al. 1987 ) or radiative fluxes ( Raymond 2001 ; Bony and Emanuel 2005

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

independent estimates of surface fluxes to compute surface precipitation and net tropospheric radiative heating rates for the months of October and November 2011. Two prominent MJO events occurred during this period ( Gottschalck et al. 2013 ; Yoneyama et al. 2013 ; Johnson and Ciesielski 2013 ). The findings are then compared to satellite-based estimates of those quantities. The DYNAMO sounding array analyses have already formed the basis for large-scale forcing fields being used by various authors, so

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James H. Ruppert Jr. and Richard H. Johnson

population alone. For instance, while large-scale subsidence and horizontal moisture advection, exert control over column humidity, and therefore over moist convection, clouds can reduce column radiative cooling. This reduction can in turn reduce large-scale subsidence (e.g., Mapes 2001 ), assuming negligible temperature variations, thereby providing a link between clouds and the large-scale column moisture source ( Chikira 2014 ). Local processes that augment moist convection (e.g., mesoscale organized

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

; Wang and Rui 1990 ), surface enthalpy fluxes ( Emanuel 1987 ; Neelin et al. 1987 ), radiative feedback ( Hu and Randall 1994 ; Raymond 2001 ; Bony and Emanuel 2005 ), a combination of both surface turbulent enthalpy fluxes and radiative feedback as sources of moist static energy ( Sobel et al. 2008 , 2010 ), and moisture modes coupling temporal and spatial variation of moisture with dry dynamics (e.g., Sobel et al. 2001 ; Sobel and Maloney 2012 , 2013 ; Fuchs and Raymond 2002 ; Raymond and

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Eric D. Skyllingstad and Simon P. de Szoeke

with higher surface winds and suppressed MJO phase moisture convergence to examine how increased surface fluxes from stronger winds affect convective activity versus externally forced moisture convergence. Simulations are conducted using a version of the Skyllingstad and Edson (2009) LES model that includes parameterizations for the radiative transfer of infrared and solar radiation ( Mlawer et al. 1997 ) along with a seven-component cloud microphysics scheme ( Thompson et al. 2008 ). Model

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

. Longwave radiative forcing associated with moisture and cloud anomalies is also often cited as the main source of moist static energy for the MJO ( Andersen and Kuang 2012 ; Sobel et al. 2014 ). For example, in the Chikira and Sugiyama (2013) cumulus scheme, radiative heating anomalies moisten the lower and middle troposphere through vertical advection. Finally, a convection–surface flux feedback through nonlinear wind-induced surface heat exchange (WISHE) was proposed by Maloney and Sobel (2004

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

systems measured mean air temperature, humidity (at 15 m above sea level), vector wind (~20 m), sea surface temperature at 0.1-m depth (SST), and downwelling solar and longwave infrared radiative fluxes each minute. The DYNAMO observations are described further in appendix A . Unless otherwise noted, in this paper we use 10-min averages of the DYNAMO surface meteorology and flux variables. Fluxes shown herein are computed from the 10-min averages with the COARE version 3.5 bulk aerodynamic formula

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

. Using observations, Tobin et al. (2012) found that more aggregated (or organized) convective systems are associated with higher surface fluxes (both latent and sensible) than less aggregated convective systems. Idealized radiative convective equilibrium (RCE) CRM studies have also examined the importance of surface fluxes for convective organization (e.g., Bretherton et al. 2005 ; Muller and Held 2012 ; Wing and Emanuel 2014 ; Wing and Cronin 2016 ; Holloway and Woolnough 2016 ). In these

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

–convective instability for the MJO or intraseasonal oscillation based on this 20% criterion ( Lin and Mapes 2004 ; Johnson et al. 2015 ; Ciesielski et al. 2017 ). Lin and Mapes (2004) showed that the RRC in the tropics is typically about 10%–15%. Since this ratio can be extremely high with a small amount of precipitation, a definitive value would not be a necessary condition for radiative–convective instability under all conditions. Rather, the combined effect of enhanced radiative heating and surface fluxes

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

mean BL air mixture is 51% entrainment, 22% downdrafts, and 27% in equilibrium with the sea surface. Bursts of high downdraft fractions f d indicate times when undiluted downdraft air was recently injected into the BL. 2 Does radiative heating of the boundary layer affect the mixing fractions? The effect of radiative heating is added to (1) as where The first quantity in square brackets scales the radiative flux difference to the known surface sensible heat flux H . We diurnally average the

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