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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

, between the horn of India and Revelle , intensified. This region was identified by the U.S. Joint Tropical Warning Center (JTWC) as a tropical disturbance and upgraded to a tropical depression on 26 November. This event was forecast with a lead time of 6 days and was not unexpected; nevertheless, it caused significant loss of life and property damage along Sri Lanka's southeast coast (see sidebar on the impact of tropical cyclone 05A on Sri Lanka ). IMPACT OF TROPICAL CYCLONE 05A ON SRI LANKA As the

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

, 4970–4995 , doi: 10.1175/JCLI-D-13-00760.1 . de Szoeke , S. P. , and J. B. Edson , 2014 : Intraseasonal air–sea interaction and convection observed in DYNAMO/CINDY/AMIE. The Global Monsoon System: Research and Forecast, C. P. Chang, Ed., World Scientific, in press . Donlon , C. J. , M. Martin , J. Stark , J. Roberts-Jones , E. Fiedler , and W. Wimmer , 2012 : The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system . Remote Sens. Environ. , 116 , 140

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Walter M. Hannah, Brian E. Mapes, and Gregory S. Elsaesser

column temperature variations. For these reasons, here we confine ourselves to the relatively straightforward business of the moisture budget at 0.25° and 6-hourly scales. 3. Data sources The analysis reported here utilized several data sources. Gridded humidity and wind data for budget calculations are taken from the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis and also from the CSU interpolated analysis of the DYNAMO large-scale sounding array ( Johnson and

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Jean-Philippe Duvel

of a few days. Many studies also show the more specific relation between the MJO and tropical cyclones (TCs) in different parts of the globe (e.g., Liebmann et al. 1994 ; Maloney and Hartmann 2000a , b ; Hall et al. 2001 ; Bessafi and Wheeler 2006 ; Ho et al. 2006 ; Camargo et al. 2009 ; Ramsay et al. 2012 ; Klotzbach 2014 ). The modulation of the cyclogenesis by the MJO is an important issue for forecasting the TC activity during a cyclone season. It is also important for understanding

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Weixin Xu and Steven A. Rutledge

– 2836 , doi: 10.1175/1520-0477(1997)078<2817:SRRPWT>2.0.CO;2 . Steiner , M. , R. A. Houze Jr. , and S. E. Yuter , 1995 : Climatological characterization of three-dimensional storm structure from operational radar and rain gauge data . J. Appl. Meteor. , 34 , 1978 – 2007 , doi: 10.1175/1520-0450(1995)034<1978:CCOTDS>2.0.CO;2 . Szoke , E. J. , and E. J. Zipser , 1986 : A radar study of convective cells in mesoscale systems in GATE. Part II: life cycles of convective cells . J

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Naoko Sakaeda, Scott W. Powell, Juliana Dias, and George N. Kiladis

% of total rain. b. DYNAMO gridded dataset This study uses CSU-DYNAMO upper-air and surface gridded analysis version 3b data ( Ciesielski et al. 2014 ), which combines several observational datasets including soundings, satellite data, and European Centre for Medium-Range Weather Forecasts operational analysis to generate 3-hourly, 1° × 1° data with a vertical resolution of 25 hPa from 1 October 2011 to 31 December 2011. Further details on the gridded dataset are provided by Ciesielski et al

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Weixin Xu and Steven A. Rutledge

. A. Houze Jr. , and S. E. Yuter , 1995 : Climatological characterization of three-dimensional storm structure from operational radar and rain gauge data . J. Appl. Meteor. , 34 , 1978 – 2007 , doi: 10.1175/1520-0450(1995)034<1978:CCOTDS>2.0.CO;2 . Stephens , G. L. , P. J. Webster , R. H. Johnson , R. Engelen , and T. S. L’Ecuyer , 2004 : Observational evidence for the mutual regulation of the tropical hydrological cycle and tropical sea surface temperatures . J

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