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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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Benjamin Sultan, Serge Janicot, and Cyrille Correia

convection anomalies associated with the MJO for up to 7 days ( Hendon et al. 2000 ; Waliser et al. 1999 ). On the other hand, several statistical methods, such as principal oscillation pattern (POP) techniques ( von Storch and Xu 1990 ) or singular value decomposition (SVD) methods ( Waliser et al. 1999 ), have been used to produce skillful forecasts of large-scale intraseasonal anomalies of convection. Until now, the comparisons between dynamical and empirical predictions of the intraseasonal

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Ryan D. Torn

qualitatively similar to the KF results (cf. Fig. 3h ). The consistent sensitivity for the KF and Grell schemes suggests that these techniques have a greater memory of the initial-condition errors as compared to BMJ. In contrast to MKE, the initial-condition sensitivity for AEW longitude demonstrates more consistency among the various cumulus parameterization schemes. The 12-h AEW longitude forecasts are most sensitive to the θ e on the west side of the AEW; increasing θ e by one standard deviation

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Adrian M. Tompkins and Laura Feudale

function based correction technique ( Hopson 2006 ; Ines and Hansen 2006 ; Piani et al. 2009 ) or techniques such as the singular value decomposition method applied in Kang et al. (2004) . Here, we apply a very simple correction by progressively shifting the target area to determine which latitudinal offset maximizes the correlation between the observations and the model forecasts. The impacts on the rainfall correlation of the systematic southerly shift of the rainband are assessed and the

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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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Peter Knippertz and Andreas H. Fink

presumably due to both better data availability and improvements to the model and data assimilation system, in particular the change from optimum interpolation to 3DVAR in 1996 and to 4DVAR techniques in 1997. The overall satisfactory performance of the ERA-40 forecasts at the “extreme” end of the precipitation distribution in a tropical region was not to be expected a priori and corroborates the speculation by KF08 that dry-season precipitation in West Africa might in fact be better predicted by state

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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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O. Bock and M. Nuret

1. Introduction Numerical weather prediction (NWP) models play an increasing role in our everyday life. Short- to medium-range weather forecasts are used to anticipate severe weather events, which have increasing socioeconomic impacts within the context of climate change and variability. NWP models serve also as the basis for developing seasonal weather prediction and climate projection systems, which both are of crucial importance for vulnerable regions, such as the Sahel. NWP model analyses

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