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Denny P. Alappattu and Qing Wang

1. Introduction For decades, airborne expendable bathythermographs (AXBTs) have been used extensively for sampling ocean temperature profiles for oceanic surveys and research (e.g., Bane and Sessions 1984 ; Dinegar Boyd 1987 ; Watts et al. 1989 ; Price et al. 1994 ; Rodríguez-Santana et al. 1999 ). Recently, airborne expendable conductivity–temperature–depth (AXCTD) probes were developed to obtain both temperature and salinity profiles ( Chu and Fan 2001 ; Shay and Brewster 2010 ). These

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Matthew A. Janiga and Chidong Zhang

. Bechtold , P. , M. Köhler , T. Jung , F. Doblas-Reyes , M. Leutbecher , M. J. Rodwell , F. Vitart , and G. Balsamo , 2008 : Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time scales . Quart. J. Roy. Meteor. Soc. , 134 , 1337 – 1351 , doi: 10.1002/qj.289 . Benedict , J. J. , and D. A. Randall , 2007 : Observed characteristics of the MJO relative to maximum rainfall . J. Atmos. Sci. , 64 , 2332 – 2354 , doi: 10.1175/JAS

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

. Vitart , and G. Balsamo , 2008 : Advances in predicting atmospheric variability with the ECMWF model: From synoptic to decadal time-scales . Quart. J. Roy. Meteor. Soc. , 134 , 1337 – 1351 , https://doi.org/10.1002/qj.289 . 10.1002/qj.289 Bechtold , P. , N. Semane , P. Lopez , J.-P. Chaboureau , A. Beljaars , and N. Bormann , 2014 : Representing equilibrium and nonequilibrium convection in large-scale models . J. Atmos. Sci. , 71 , 734 – 753 , https://doi.org/10

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Weixin Xu and Steven A. Rutledge

.1175/1520-0493(1984)112<1782:TEOFAS>2.0.CO;2 . Bechtold , P. , M. Köhler , T. Jung , F. Doblas-Reyes , M. Leutbecher , M. J. Rodwell , F. Vitart , and G. Balsamo , 2008 : Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time-scales . Quart. J. Roy. Meteor. Soc. , 134 , 1337 – 1351 , doi: 10.1002/qj.289 . Bladé , I. , and D. L. Hartmann , 1993 : Tropical intraseasonal oscillations in a simple nonlinear model . J. Atmos. Sci. , 50 , 2922 – 2939 , doi

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Weixin Xu and Steven A. Rutledge

variability in the tropics and plays important roles at climate and weather system scales ( Zhang 2013 ). Despite decades of study, the MJO is not well understood and therefore MJO prediction skill is limited, especially for initiation over the Indian Ocean ( Bechtold et al. 2008 ; Kim et al. 2009 ; Vitart and Molteni 2010 ). Meanwhile, the MJO has been poorly simulated by several generations of general circulation models (GCMs) ( Lin et al. 2006 ; Hung et al. 2013 ). The representation of cumulus

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

1. Introduction The diurnal cycle is a fundamental mode of the circulation and precipitation variability in the tropics. While its characteristics and governing mechanisms over land and coastal regions have been extensively studied and are well understood, the same cannot be said for over the open ocean, where the paucity of observations has limited our ability to fully describe and understand it. Making creative use of surface observations (e.g., COADS, buoy, and scatterometer winds), several

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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

1. Introduction The Madden–Julian oscillation (MJO) is a low-frequency atmospheric anomaly traveling along the equatorial belt with a period of 30–60 days ( Madden and Julian 1971 , 1972 ). The MJO has a broad influence on the weather and climate systems by influencing the intraseasonal and interannual variability of atmosphere and ocean ( Lau and Waliser 2005 ; Zhang 2005 ). Numerous studies have characterized the large-scale environmental changes relative to MJO onset in terms of an

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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

made in understanding and forecasting the MJO over the past four decades, it remains a significant outstanding problem in tropical meteorology (see Zhang et al. 2013 ). As discussed in detail by Straub (2013 , hereafter S13 ), one of the challenges faced by researchers studying the MJO has to do not only with tracking the disturbance through time, but simply defining it. This difficulty stems from the fact that the MJO is associated with strong planetary circulation anomalies, and similar

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Rachel C. Zelinsky, Chidong Zhang, and Chuntao Liu

1. Introduction The Madden–Julian oscillation (MJO; Madden and Julian 1971 , 1972 ) is the strongest source of intraseasonal variability in the tropics ( Zhang 2005 ). It is an important link between weather and climate ( Zhang 2013 ). The MJO provides a major source of subseasonal (2–12 weeks) predictability ( Waliser et al. 2003 ), making it a key target for the improvement of subseasonal-to-seasonal (S2S) prediction ( Vitart 2009 ; Zhang 2013 ). Theories have been developed to explain the

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

an areal mean might partially come from temporal smoothing (see section 3 ). Although it is not clear what the area for the mean should be for point measurements, it will be shown that the moisture variability observed by Manus soundings is comparable to that from EC-ARM interpolated to Manus and from ERAI averaged over a domain of 10° × 10°centered at Manus (herein called the Manus domain; see Fig. C1 in appendix C ). This suggests that Eqs. (1) and (2) can be applied to temporally

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