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Yue Ying and Fuqing Zhang

1. Introduction The tropical atmosphere consists of weather systems spanning a wide range of spatial and temporal scales. At the planetary scale, the Madden–Julian oscillation (MJO) is found to be the dominant mode of intraseasonal variability with typical periods of 20–100 days ( Madden and Julian 1971 , 1972 ; Zhang 2005 ). The active phase of an MJO is characterized by enhanced deep convection and intense precipitation that propagates eastward at a speed around 5 m s −1 . Within the MJO

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Jennifer L. Davison

. (2013b) for a discussion of the interchangeability of these two variables with respect to this technique. b. Modifications for use with RHI data The attributes that makes RHI data valuable for this study (i.e., the large number and range of beam-elevation angles) also present complications that require adjustment of the BSL analysis technique developed for PPI data. The complications are twofold: 1) the vertical cross-section lengths sampled at a given range gate vary quite drastically (see Fig. 4

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Nick Guy and David P. Jorgensen

1. Introduction A dominant component of intraseasonal tropical variability is the Madden–Julian oscillation (MJO; Madden and Julian 1971 , 1972 ), characterized by an eastward-moving envelope of organized, deep convection (and precipitation) and westerly winds. The MJO has been shown to influence monsoon systems (e.g., Asia, Africa, and Australia), tropical cyclones in all cyclone basins, midlatitude weather (e.g., rainfall and temperature variability), and other atmospheric and ocean

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Tomoe Nasuno, Tim Li, and Kazuyoshi Kikuchi

1. Introduction The Madden–Julian oscillation (MJO; Madden and Julian 1971 , 1972 ) is a prominent tropical disturbance that has a broad impact on the global weather and climate ( Zhang 2013 ; Gottschalck et al. 2010 ). The MJO is related to a wide variety of tropical and extratropical ocean and atmosphere phenomena, ranging from local to global spatial scales and diurnal to interannual time scales. Therefore, it is an important target of extended-range weather forecasting. However

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James N. Moum, Simon P. de Szoeke, William D. Smyth, James B. Edson, H. Langley DeWitt, Aurélie J. Moulin, Elizabeth J. Thompson, Christopher J. Zappa, Steven A. Rutledge, Richard H. Johnson, and Christopher W. Fairall

equator until reaching the central Pacific, and then accelerates as it circumnavigates the globe with a recurrence period between 30 and 90 days ( Zhang 2005 ). This phenomenon exerts a strong influence on Earth's weather and climate systems, acting globally on intraseasonal time scales ( Zhang 2013 ). Yet MJO prediction is unsatisfactory, in large part because of insufficient representation of the multiscale processes in models. Parameterizations of these processes are limited by a lack of

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

-spatiotemporal-resolution ocean surface wind speed data. Specifically, CYGNSS will be able to retrieve surface wind speed information in regions of moderate to heavy precipitation, unlike the scatterometer instruments listed above. The CYGNSS instrument is also expected to be useful for measuring a variety of other weather phenomena that occur in the tropics, in particular the deep convection associated with the Madden–Julian oscillation (MJO; Madden and Julian 1971 , 1972 ). The CYGNSS constellation was launched on 15

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Hyodae Seo, Aneesh C. Subramanian, Arthur J. Miller, and Nicholas R. Cavanaugh

1. Introduction The Madden–Julian oscillation (MJO) is the dominant form of intraseasonal variability in Earth’s atmospheric system. Characterized by large-scale, eastward-propagating, equatorially trapped, baroclinic oscillations in the tropical wind field at periods of 30–90 days ( Madden and Julian 1971 , 1994 ), the MJO has predictability time scales of 10–30 days, far beyond the usual time scales of weather prediction (e.g., Hendon et al. 2000 ; Waliser et al. 2003 ). Although the MJO

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Richard H. Johnson and Paul E. Ciesielski

1. Introduction A major challenge in numerical weather and climate prediction is the realistic treatment of the atmospheric boundary layer (ABL) ( Teixeira et al. 2008 ). Complicating factors include the coupling of the boundary layer with the underlying surface, stratification effects, surface inhomogeneities, complex turbulent structures, intermittency, and nonlocal mixing. An additional difficulty, particularly in the tropics, is the coupling of the ABL with the cloud layer, including

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Eric D. Skyllingstad and Simon P. de Szoeke

1. Introduction Within 10° latitude of the equator, organized atmospheric convection occurs across scales ranging from individual thunderstorm systems to planetary-scale disturbances such as the Madden–Julian oscillation (MJO). Understanding what drives these different scales is a key question for tropical weather prediction and accurate simulation of the atmospheric general circulation. At the cloud scale, we have a fairly good knowledge of convective system structure and the processes that

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

1. Introduction The Madden–Julian oscillation (MJO; Madden and Julian 1971 , 1972 ) is an intraseasonal weather phenomenon in the tropics. Because of its influence on global weather and climate ( Zhang 2005 ), understanding, simulation, and prediction of the MJO have great scientific and societal value. Modeling and prediction of MJO initiation in the Indian Ocean remains a long standing challenge. The field campaign Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year

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