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  • Lidar observations x
  • DYNAMO/CINDY/AMIE/LASP: Processes, Dynamics, and Prediction of MJO Initiation x
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Samson M. Hagos, Zhe Feng, Casey D. Burleyson, Chun Zhao, Matus N. Martini, and Larry K. Berg

surface rainfall as well as observed top-of-atmosphere and surface radiation based on the method developed by Zhang et al. (2001) . Three versions of the forcing data using the above-mentioned precipitation products are used to account for uncertainties in the rainfall estimates. The forcing dataset is used as a proxy for observations in this study rather than to drive model simulations (as they are commonly used). The length of the forcing time series is 90 days (1 October–31 December 2011). The

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Simon P. de Szoeke, James B. Edson, June R. Marion, Christopher W. Fairall, and Ludovic Bariteau

15 W m −2 are shown with a contour interval of 3 W m −2 , yellow contour is 21 W m −2 ]. (b) Zonal wind stress (shaded) and wind stress vectors from SCOW. The zero zonal wind stress contour is gray. The standard deviation of intraseasonal zonal wind stress is contoured at 0.015 (dashed), 0.02 (light), and 0.025 (thick) N m −2 . Locations of DYNAMO (80.5°E) and TOGA COARE (156°E) ship observations used in this paper are marked with yellow stars. Three MJO convective events and their accompanying

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Kai-Chih Tseng, Chung-Hsiung Sui, and Tim Li

of moisture in the lower troposphere can destabilize the atmosphere for the following development of convection. Del Genio et al. (2012) analyzed CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) data. Their composite of 10 MJO events revealed shallow and congestus clouds in advance of the peak deep clouds. Hsu and Li (2012) utilized 20-yr reanalysis data to show that the vertical advection, which results from boundary layer convergence, is the

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