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Benjamin Sultan, Serge Janicot, and Cyrille Correia

al. 1996 ). This dataset consists of a reanalysis of the global observational network of meteorological variables (wind, temperature, geopotential height, humidity on pressure levels, surface variables, and flux variables such as precipitation rate) with a “frozen” state-of-the-art analysis and forecast system at a triangular spectral truncation of T62 to perform data assimilation throughout the period from 1948 to the present. This circumvents problems with previous operational analyses due to

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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

observations and the background information (short-range forecast from a previous analysis). The 2-month assimilation experiments have been run using the ARPEGE system in its July 2006 operational version. The assimilation system has a 6-hourly cycle at T358 spectral truncation on a stretched sphere with a stretching factor of 2.4 and 46 vertical levels (from 17 m to 45 km). This configuration leads to a horizontal resolution that varies from 23 km over Europe to 135 km over the antipodes. The operational

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O. Bock and M. Nuret

centers for assimilation since March 2006 (and throughout 2007). In addition to the enhanced radiosoundings, many other observations were made during AMMA, among which some also entered into the operational NWP models. As a consequence, there is much interest in using NWP model analyses and forecasts during AMMA since their performance is expected to be improved compared to past periods. In the present paper we focus on atmospheric humidity, which is one essential component of the West African monsoon

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Adrian M. Tompkins and Laura Feudale

), the limited sample size (11 yr) and tercile probabilistic nature of these forecasts hinder this process and imply that validation efforts remain focused on the individual contributing forecasting systems. The ECMWF forecast model is central to the PRESAO process, but while the operational analyses and atmosphere-only medium-range forecasts have been periodically subjected to evaluation over Africa (e.g., Reed et al. 1988 ; Kamga et al. 2000 ; Tompkins et al. 2005b ), this is less the case for

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Ryan D. Torn

analysis in this area (e.g., Tompkins et al. 2005 ). Furthermore, the relationship between diabatic heating, large-scale convection, and AEWs suggests that the formulation of the convective parameterization plays a significant role in the model evolution. Berry et al. (2009, manuscript submitted to Wea. Forecasting ) evaluated the skill of AEW forecasts within four different operational NWP systems during 2007. Although each modeling system’s West Africa analysis has nearly identical errors with

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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

around 7000 soundings during the period June–September 2006. Twenty-one of these stations are still operational, whereas the others were used only for the 2006 campaign. For an extensive and complete description of the AMMA contribution to the establishment of the African radiosonde network, see Parker et al. (2008) . This large amount of additional radiosonde data is expected to have positive impacts on the weather forecasts over western Africa. In this paper, the influences of the number of

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

entrainment and adjustment, vertical diffusion reduction in the free atmosphere, new soil hydrology, and new operational radiosonde temperature and humidity bias correction. Bechtold et al. (2008) showed that the changes in the model physical parameterizations led to an improved precipitation forecast in the short range over the tropics and in particular over West Africa, where the ITCZ shifts northward by approximately 1° ( Agustí-Panareda and Beljaars 2008 ). The AMMA radiosonde humidity bias

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Peter Knippertz and Andreas H. Fink

). Eleven out of the 34 events in the ERA-40 forecasts did not verify in the GPCP data, leading to a false alarm rate ( F ) of 0.02 and a false alarm ratio (FAR) of 0.32. Here, F is the proportion of nonoccurrences that were incorrectly forecasted, whereas FAR is the proportion of forecasts of occurrence that did not verify. For a rare event like a dry-season rainfall, FAR is of more interest as an operational application. Too few events in the ERA-40 forecasts result in a frequency bias ( B ) of 0

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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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