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  • Mesoscale forecasting x
  • DYNAMO/CINDY/AMIE/LASP: Processes, Dynamics, and Prediction of MJO Initiation x
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Yue Ying and Fuqing Zhang

.1175/1520-0493(2002)130<1617:MPOTSS>2.0.CO;2 Zhang , F. , C. Snyder , and R. Rotunno , 2003 : Effects of moist convection on mesoscale predictability . J. Atmos. Sci. , 60 , 1173 – 1185 , doi: 10.1175/1520-0469(2003)060<1173:EOMCOM>2.0.CO;2 . 10.1175/1520-0469(2003)060<1173:EOMCOM>2.0.CO;2 Zhang , F. , A. M. Odins , and J. W. Nielsen-Gammon , 2006 : Mesoscale predictability of an extreme warm-season precipitation event . Wea. Forecasting , 21 , 149 – 166 , doi: 10.1175/WAF909.1 . 10.1175/WAF909.1 Zhang

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H. Bellenger, K. Yoneyama, M. Katsumata, T. Nishizawa, K. Yasunaga, and R. Shirooka

, 2006 : The mesoscale convection life cycle: Building block or prototype for large-scale tropical waves? Dyn. Atmos. Oceans , 42 , 3 – 29 , doi: 10.1016/j.dynatmoce.2006.03.003 . Masunaga , H. , 2013 : A satellite study of tropical moist convection and environmental variability: A moisture and thermal budget analysis . J. Atmos. Sci. , 70 , 2443 – 2464 , doi: 10.1175/JAS-D-12-0273.1 . Nasuno , T. , 2013 : Forecast skill of Madden–Julian Oscillation events in a global nonhydrostatic

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James H. Ruppert Jr. and Fuqing Zhang

( Dai 2001 ; Cronin et al. 2015 ; Yamanaka et al. 2018 ). Owing to the prevailing importance of local mesoscale circulations in the MC, adequately modeling weather and climate here has been a major longstanding challenge—a challenge that links to weather prediction across a vast range of space and time scales ( Neale and Slingo 2003 ; Waliser et al. 2003 ; Dai and Trenberth 2004 ; Love et al. 2011 ). Here we seek to address this challenge by investigating diurnal convective systems in the MC

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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

sea temperature measurements from ship, moorings, and a glider are then presented in section 3 to establish the large-scale and mesoscale moisture environments of two MJO events. Section 4 compares results from real-time and hindcast model runs made with a nested, cloud-resolving, and fully coupled (air–ocean–wave) version of the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS). Here specific attention is given to an examination of the effect of air–ocean coupling on the

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Ji-Hyun Oh, Xianan Jiang, Duane E. Waliser, Mitchell W. Moncrieff, Richard H. Johnson, and Paul Ciesielski

Bretherton 2001 ; Tung and Yanai 2002a , b ; Lin et al. 2005 ). Using Doppler radar data, Houze et al. (2000) identified strong midlevel inflow in the stratiform regions of mesoscale convective systems (MCSs) during the westerly onset and in regions of strong westerly winds associated with the Kelvin–Rossby wave pattern. They postulated that the mesoscale inflow transports easterly momentum downward, reducing the westerlies near the surface in the westerly onset region, while in the strong westerly

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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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Weixin Xu and Steven A. Rutledge

Program (GARP) Atlantic Tropical Experiment (GATE; Cheng and Houze 1979 ; Barnes and Seickman 1984 ; Szoke and Zipser 1986 ), the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE; LeMone 1983 ; LeMone et al. 1998 ; Rickenbach and Rutledge 1998 , hereafter RR98 ), the South China Sea Monsoon Experiment ( Johnson et al. 2005 ), the Equatorial Mesoscale Experiment ( Alexander and Young 1992 ), and experiments in northern Australia ( Keenan and Carbone 1992

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Hungjui Yu, Richard H. Johnson, Paul E. Ciesielski, and Hung-Chi Kuo

a life cycle similar to that of organized mesoscale convective systems (MCSs) or long-lived squall lines, with a transition from predominantly shallow to deep to stratiform convection ( Hendon and Liebmann 1994 ; Takayabu et al. 1996 ), which repeated at quasi-2-day intervals from local observations. To explain the quasi-2-day intervals of occurrence, Chen and Houze (1997) suggested that the near-2-day periodicity results from an interaction between the 2-day waves and convection. A

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

and space scales, including feedbacks onto the larger MJO convective envelope. The observational work of Maloney and Esbensen (2007) , Araligidad and Maloney (2008) , and RDM2015 used spatial and temporal averaging to remove the effects of mesoscale and synoptic wind–flux feedbacks on MJO convection in order to assess how these scales contributed to the positive relationship of precipitation and LHFLX at intraseasonal time scales. In all three studies, the regression coefficient between

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

terms from parameterization schemes with global and long-term coverage. Examples of such products are the Modern-Era Retrospective Analysis for Research and Applications (MERRA; Rienecker et al. 2011 ; Mapes and Bacmeister 2012 ) and Year of Tropical Convection (YOTC) European Centre for Medium-Range Weather Forecasts database, known as the YOTC analysis ( Moncrieff et al. 2012 ; Waliser et al. 2012 ). Obviously, these products include errors from parameterization schemes. Cloud-permitting model

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