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Jun-Ichi Yano and Joseph J. Tribbia

that the same could be true for the whole tropical planetary-scale circulations. Such a new perspective may have an immediate impact on global model initialization strategy over the tropics: the current basic strategy is an initialization based on a linear equatorial wave decomposition (cf. Žagar et al. 2005 ). The proposed MJO–modon theory suggests a nonlinear balance initialization ( Baer and Tribbia 1977 ; Kasahara 1982 ; Tribbia 1984b ) as the key for a successful MJO forecast. From a

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Yue Ying and Fuqing Zhang

predictability of the tropical weather systems and CCEWs. The first ensemble simulation designed to examine the practical predictability limits starts from 18 October to 2 November (corresponding to the MJO phases 1–3). The IC and LBC ensemble perturbations are sampled from the operational European Centre for Medium-Range Weather Forecasts (ECMWF) global ensemble forecasts archived in The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE). 1 The TIGGE

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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

Colombo launched four sondes per day. The DYNAMO soundings and dropsondes were assimilated into the operational models including COAMPS. The real-time soundings contained a small daytime dry bias on the order of a few percent relative humidity (RH) at low levels and increased to ~5% at upper levels. Soundings subsequently processed for the analyses presented in this paper used level 4 (L4) processed sonde data, which are quality controlled and bias corrected ( Ciesielski et al. 2012 ). Fig . 1

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

various processes involved in the wind evolution associated with the MJO over the IO during DYNAMO using European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses. This study focuses on the zonal momentum budget, since the circulation during MJO life cycle is more noticeable in zonal than meridional winds ( Madden and Julian 1971 ). In addition to the analysis of the momentum budget to shed light on common features of the MJO events in 2011 DYNAMO, the unusual behavior of MJO2 is

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

on Colombo soundings ( Ciesielski et al. 2014b ). Blockage of the low-level flow by the island terrain frequently disrupts the winds at Colombo below about 2 km. This local effect is aliased onto larger scales and impairs computations of divergence over the NSA. The procedure developed by Ciesielski et al. (2014b) mitigates the impacts of Sri Lanka flow blocking on budgets over the NSA by using European Centre for Medium-Range Weather Forecasts (ECMWF) Operational Analysis (OA) data away from

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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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Weixin Xu, Steven A. Rutledge, Courtney Schumacher, and Masaki Katsumata

resolution (every 1–2 s) during the IOP (1 October 2011–15 January 2012) of DYNAMO ( Ciesielski et al. 2014 ). Soundings and associated derived products have been rigorously quality controlled ( Ciesielski et al. 2014 ). Vertical velocity was derived from sounding array data and supplemented with European Centre for Medium-Range Weather Forecasts (ECMWF) Operational Analysis when one or both research ships were offsite ( ). Table 1

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

features to be studied with this campaign. The importance of this preconditioning for deep convection associated with the MJO has been stressed by many observational (e.g., Johnson et al. 1999 ; Kikuchi and Takayabu 2004 ; Holloway and Neelin 2009 ) and modeling studies (e.g., Zhang and Song 2009 ; Cai et al. 2013 ). A possible consequence of our lack of understanding of the origin of this preconditioning is the limitation of the forecast skill of the timing of the MJO triggering. Indeed, forecast

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

al. 2000 ). Data from Manus also included observations from a microwave radiometer (MWR), upper-air soundings, a micropulse lidar (MPL), a ceilometer, and optical rain gauges. Other data used are rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM 3B42v7; 0.25° × 0.25°; Kummerow et al. 2000 ); rainfall, specific humidity, and its physical tendency term from the operational analysis (0.56° × 0.56°) of the European Centre for Medium Range Weather Forecasts (ECMWF) prepared for

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Matthew A. Janiga and Chidong Zhang

it propagates while the associated latent heat release generates teleconnection patterns that affect global weather and climate (e.g., Zhang 2005 , 2013 ). The ability of global operational and climate models to capture moisture–convection interactions within this convective envelope is closely related to their being able to simulate its growth and propagation (e.g., Bechtold et al. 2008 ; Hirons et al. 2013b , a ; Kim et al. 2014 ; Klingaman et al. 2015 ). Observational studies have

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