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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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O. Bock and M. Nuret

are also extensively used for scientific research, either as large-scale forcings for mesoscale atmospheric simulations in case study experiments or as a full three-dimensional description of the atmospheric and surface parameters for climate research. In this latter case, reanalyses are of special interest since they are produced with a fixed version of an NWP model and the only changes in analysis and forecast performance result from changes in the observations that are assimilated. Within the

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

chosen, as it rains on the first and last days while on the whole keeping dry in most of West Africa (see detailed description in section 2 ) between the two rain events. Both observations and a model simulation are used in this study, and they will be briefly introduced in section 3 . We will focus on the Niamey site in section 4 to examine the model performance at a single grid point and then extend the analysis to the whole model domain in order to undertake statistical analysis in section 5

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Fatima Karbou, Elisabeth Gérard, and Florence Rabier

EXP3. The best results are obtained in EXP3 with an improvement to the correlations of about 20% over many areas. EXP3 appears to be very promising as it provides better model equivalents to AMA4 and AMB2 over land. However, more in-depth studies are still needed before advocating this method. Further tests will deal with some surface temperature evaluation against independent measurements; they will also study possible emissivity error propagation into surface temperature estimates and consider

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Adrian M. Tompkins and Laura Feudale

the coupled seasonal forecast system. An earlier release of the coupled model (called system 2) has been evaluated within the context of its contribution to the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) forecasting system ( Palmer et al. 2004 ), and Stockdale et al. (2006) revealed that performance in SST predictions in the tropical and southern subtropical Atlantic in this system did not exceed that of persistence, while skill in the

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

significant number of observations over land have been assimilated in EXP4, as compared with the CTL experiment. To evaluate the performances of the observation operator over land and over sea, the differences between observed and simulated radiances using the background fields have been computed. The first-guess (FG) departures have been computed with and without bias correction. Global statistics for the August 2006 FG departures for assimilated AMSU-B channel 5 are presented in Fig. 2 . The results

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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

radiosonde sites, the relevance of vertical high-resolution soundings, and the effects of a humidity bias correction are assessed. The paper is organized as follows. Sections 2 and 3 of this paper describe the data processing and the model setup. The results of the assimilation diagnostics and forecast performance are discussed, respectively, in sections 4 and 5 . Conclusions are presented in section 6 . 2. Data processing Figure 1 shows the distribution of the western African GTS radiosonde

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Peter Knippertz and Andreas H. Fink

evaluate the ability of a state-of-the-art numerical weather prediction (NWP) model to forecast such events, and (d) to investigate in what way the degree of extratropical influence is related to forecast skill. The remainder of the paper is structured as follows. Section 2 provides information on the employed observational and forecast data. Section 3 contains an exemplary case study. Section 4 describes the identification of dry-season wet events and their climatology, while section 5

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Sen Chiao and Gregory S. Jenkins

design are described in section 3 . The results of our model simulations are discussed and evaluated against observations in section 4 , followed by discussion and conclusions in section 5 . 2. MCS progression and TD formation TD 4 developed near 11.6°N and 21.7°W at 1800 UTC 21 August 2006 ( Jenkins et al. 2008 ), from a series of MCSs that propagated westward across western Africa. Figures 1a–d depict the evolution of the MCS using infrared (IR) cloud-top temperatures from 1200 UTC 19 August

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Benjamin Sultan, Serge Janicot, and Cyrille Correia

variability of convection in other regions of the tropics. Most of these examples concern the prediction of the Madden–Julian oscillation (MJO), which is the dominant oscillatory mode in the tropics ( Madden and Julian 1972 ). Skillful predictions of the MJO have been obtained at a medium lead time (less than 10 days) using either dynamical forecasts or statistical methods. For instance, the National Centers for Environmental Prediction (NCEP) Medium-Range Forecast (MRF) model shows skillful forecasts of

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