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Kacie E. Hoover, John R. Mecikalski, Timothy J. Lang, Xuanli Li, Tyler J. Castillo, and Themis Chronis

initial condition of WRF Model contains errors and uncertainties. Through data assimilation methods, many of the DYNAMO observations that are not routinely available to operational centers (e.g., the National Centers for Environmental Prediction, the European Centre for Medium-Range Weather Forecasts) were subsequently included in an updated initial condition dataset. This updated initial condition, obtained through an assimilation step, is used to begin our WRF Model simulations. The WRF three

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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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Nick Guy and David P. Jorgensen

phenomena (e.g., El Niño–Southern Oscillation, North Atlantic Oscillation, Indian Ocean dipole); discussed further in Lau and Waliser (2005) and Zhang (2005) . Given the extensive impact of the MJO on global circulations, it is important to correctly simulate the MJO in forecast and climate models. However, current model simulations do not represent the MJO well ( Lin et al. 2006 ; Benedict and Randall 2009 ). This is due in part to an incomplete understanding of convective dynamics and

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George N. Kiladis, Juliana Dias, Katherine H. Straub, Matthew C. Wheeler, Stefan N. Tulich, Kazuyoshi Kikuchi, Klaus M. Weickmann, and Michael J. Ventrice

. Bull. Amer. Meteor. Soc. , in press . Gloeckler , L. C. , and P. E. Roundy , 2013 : Modulation of the extratropical circulation by combined activity of the Madden–Julian Oscillation and equatorial Rossby waves during boreal winter . Mon. Wea. Rev. , 141 , 1347 – 1357 , doi:10.1175/MWR-D-12-00179.1 . Gottschalck , J. , and Coauthors , 2010 : A framework for assessing operational Madden–Julian oscillation forecasts: A CLIVAR MJO working group project . Bull. Amer. Meteor. Soc. , 91

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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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Brandon W. Kerns and Shuyi S. Chen

) operational analysis is used. These data were provided in real time in support of field campaign forecasting efforts. The dataset benefits from 4D variational data assimilation (4DVar), including the DYNAMO field observations. For this study, the 0.25° pressure-level data are used. c. Infrared satellite data Infrared (IR) satellite coverage during DYNAMO was provided by Meteorological Satellite-7 ( Meteosat-7 ). For this study, the data were interpolated to a 0.05° grid. The focus is on latitude

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Simon P. de Szoeke and Eric D. Maloney

.1029/2003JC002092 . 10.1029/2003JC002092 Gottschalck , J. , and Coauthors , 2010 : A framework for assessing operational Madden–Julian oscillation forecasts . Bull. Amer. Meteor. Soc. , 91 , 1247 – 1258 , . 10.1175/2010BAMS2816.1 Hendon , H. H. , and J. Glick , 1997 : Intraseasonal air–sea interaction in the tropical Indian and Pacific Oceans . J. Climate , 10 , 647 – 661 ,<0647:IASIIT>2.0.CO;2 . 10

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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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