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C. Faccani, F. Rabier, N. Fourrié, A. Agusti-Panareda, F. Karbou, P. Moll, J.-P. Lafore, M. Nuret, F. Hdidou, and O. Bock

reorganization of the observation network mainly concerned the radiosonde network, which, before AMMA, had only a few operating stations in the World Meteorological Organization (WMO) Global Telecommunication System (GTS). Radiosonde data are an extremely important source of information over land for weather forecast models, because they provide the assimilation procedure with a complete description of the three-dimensional structure of the atmosphere. Other available data, such as satellite radiances

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Fatima Karbou, Florence Rabier, Jean-Philippe Lafore, Jean-Luc Redelsperger, and Olivier Bock

clouds and over land surfaces. The assimilation of cloud-affected Special Sensor Microwave Imager (SSM/I) observations has been operational at the European Centre for Medium-Range Weather Forecasts (ECMWF) since June 2005 ( Bauer et al. 2006a , b ). Significant headway was made possible when a two-step method [one- and four-dimensional variational data assimilation (1D + 4DVAR)] was adopted to assimilate a selection of cloudy, sea SSM/I observations. In parallel, studies have been carried out in

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Fatima Karbou, Elisabeth Gérard, and Florence Rabier

1. Introduction Microwave observations from the Advanced Microwave Sounding Unit-A and -B [AMSU-A and -B; or Microwave Humidity Sounder (MHS)] instruments have been widely used in numerical weather prediction (NWP) to improve the initial conditions for short-range forecasts. AMSU instruments are on board low-orbiting satellites such as the different generations of the National Oceanic and Atmospheric Administration (NOAA) satellites, the National Aeronautics and Space Administration’s (NASA

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Peter Knippertz and Andreas H. Fink

, KF08 hypothesized that the strong extratropical influences may imply a comparably good predictability of such events that would allow a timely warning of the population and therefore a mitigation of detrimental impacts as well as an exploitation of beneficial effects. To test this hypothesis, the present study gives a statistical evaluation of boreal winter precipitation forecasts made by the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis project (ERA-40; Uppala et

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Benjamin Sultan, Serge Janicot, and Cyrille Correia

( Ingram et al. 2002 ), as the occurrence of dry spells can strongly impact yields of rain-fed crops ( Sultan et al. 2005 ). Although there is more and more evidence of specific intraseasonal variability in convective activity during the West African monsoon ( Janicot and Sultan 2001 ; Sultan and Janicot 2003 ; Matthews 2004 ; Mounier and Janicot 2004 ; Mounier et al. 2008 ), no study has investigated its predictability. Nevertheless, there are many examples of skillful forecasts of intraseasonal

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Adrian M. Tompkins and Laura Feudale

. 1992 ; Fontaine and Bigot 1993 ; Opokuankomah and Cordery 1994 ; Fontaine and Janicot 1996 ; Zheng et al. 1999 ; Vizy and Cook 2001 ; Giannini et al. 2003 ). Nevertheless, actual seasonal forecasts using dynamical models have not historically performed reliably in these regions relative to other parts of the globe ( Wang et al. 2008 ). This shortfall in realized model skill is due to a number of reasons. First, in terms of SSTs, global coupled models have their greatest success in the

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Anna Agustí-Panareda, Anton Beljaars, Carla Cardinali, Iliana Genkova, and Chris Thorncroft

1. Introduction The West African monsoon provides most of the annual precipitation over the drought-prone Sahel. However, numerical weather prediction (NWP) precipitation forecasts are generally poor during the wet West African monsoon season from June to September, partly because of the lack of observations available. Before the African Monsoon Multidisciplinary Analysis (AMMA) field experiment in 2006, the radiosonde network was quite sparse and only a small amount of data was received via

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Sen Chiao and Gregory S. Jenkins

–vortex near the western African coastline. Model forecasts of the AEW associated with Tropical Storm Debby were used to address the items above with an emphasis placed on aspects of the MCS–vortex before tropical cyclogenesis in association with the AEW–MCS transition from continental to oceanic environments from 19 to 21 August 2006. There is a discussion on the spatial structure and temporal evolution of the pre–TD 4 environment during 19–21 August in section 2 . The numerical model and experiment

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Xuefeng Cui, Douglas J. Parker, and Andrew P. Morse

surface evaporation, and other processes (see, e.g., Eltahir 1998 ). Wallace and Holwill (1997) have indicated that in the vicinity of Niamey most of the evaporation occurs during the first day directly after rain. Currently, it is not realistic to ask the operational NWP models to represent this type of feedback in terms of precipitation forecasting in West Africa as the diurnal variation of the atmospheric boundary layer in this area is complex ( Parker et al. 2005 ). However, it is important to

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Ryan D. Torn

Hoskins 1994 ). More recent studies have emphasized the importance of diabatic processes linked to deep convection associated with AEWs ( Berry and Thorncroft 2005 ; Hsieh and Cook 2007 ). Numerical weather prediction (NWP) model forecasts of AEWs suffer from a number of problems related to errors in the initial conditions and model formulations. Much of North Africa is characterized by a lack of in situ observations; thus, NWP systems rely on remote sensing data and prior forecasts to generate an

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