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O. Bock and M. Nuret

during the AMMA EOP. However, the assessment of NWP models makes sense only when independent observations are used. Hence, in the present work we use precipitable water vapor (PWV) estimates provided by a network of ground-based global positioning system (GPS) receivers, the data of which are not presently assimilated into the currently used NWP models. The GPS technique is known to provide very accurate estimates of PWV (usually considered at the level 1–2 kg m −2 ) with high temporal resolution

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

1. Introduction The West African monsoon (WAM) is still far from being well represented in numerical weather prediction (NWP) models. The WAM is governed by multiple mechanisms, which show very complex interactions that are not yet fully understood. Not surprisingly, a realistic representation of the spatial distribution, the strength, and the duration of the WAM remains a great challenge. The atmospheric water vapor is responsible for the cloud formation and plays a crucial role in convection

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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

the lower troposphere (up to 850 hPa, not shown). A quantification of the changes produced in the humidity field by using the special AMMA campaign soundings can be seen when looking at the total-column water vapor. Figure 3 shows the mean total-column water vapor (TCWV) over the period 1 August–14 September 2006 for the PREAMMA experiment, and the differences that result from the other experiments. PREAMMA ( Fig. 3 , top left) shows a large area of high water vapor (orange and red) over the

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Sen Chiao and Gregory S. Jenkins

, a wide area of precipitable water vapor, strong convergence in the low- and midtropospheric layers, and an easterly vertical shear of the zonal wind. Thus, before moving away from the coast of Senegal this perturbation was named Tropical Storm Cindy. The AEW life cycle can be categorized into three different phases: initiation, the growth of the AEW over western Africa that results from baroclinic and barotropic processes ( Thorncroft 1995 ), and coastal development ( Berry and Thorncroft 2005

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Françoise Guichard, Nicole Asencio, Christophe Peugeot, Olivier Bock, Jean-Luc Redelsperger, Xuefeng Cui, Matthew Garvert, Benjamin Lamptey, Emiliano Orlandi, Julia Sander, Federico Fierli, Miguel Angel Gaertner, Sarah C. Jones, Jean-Philippe Lafore, Andrew Morse, Mathieu Nuret, Aaron Boone, Gianpaolo Balsamo, Patricia de Rosnay, Bertrand Decharme, Philip P. Harris, and J.-C. Bergès

northern maximum obtained in HIGHRES (at 1300 UTC; see Fig. 16a ). By midnight, the atmosphere has evolved into a moister state in LOW_RES. PW is higher (lower) than at 0600 UTC in LOW_RES (HIGHRES). This occurs despite the cumulative rainfall being 1 mm higher in LOW_RES compared to HIGHRES. The early and widespread rainfall simulated in LOW_RES is associated with stronger evapotranspiration from a wetter surface. In both simulations, E accounts for a significant water vapor input into the

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

an improved precipitation forecast in the ECMWF Integrated Forecasting System (IFS). A validation of the corrected AMMA radiosondes shows good agreement with independent ground-based global positioning system (GPS) total column water vapor (TCWV) measurements at several AMMA sites. Faccani et al. (2009) tested the impacts of this bias correction scheme on the AMMA soundings in the French Action de Recherche Petite Echelle Grande Echelle (ARPEGE) assimilation system ( Gauthier and Thépaut 2001

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Fatima Karbou, Elisabeth Gérard, and Florence Rabier

distribution in the atmosphere, thanks to 11 out of 15 channels, which are located near the oxygen absorption band (50–60 GHz). AMSU-B makes measurements at five frequencies; three of them are located near the strong water vapor line and are used to measure the humidity in the atmosphere. Besides their sounding capabilities, AMSU-A and -B have the so-called window channels, which give measurements that are sensitive to the surface and to low-level atmospheric layers (23.8, 31.4, 50.3, 89, and 150 GHz

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Adrian M. Tompkins and Laura Feudale

2005 ); and significant alterations to the parameterization of deep convection, altering the convective mass-flux scheme closure time scale and the treatment of convective entrainment, rendering convection more sensitive to water vapor without suppressing the convection parameterization activity. Many of these upgrades are described in Bechtold et al. (2008) and Jung et al. (2009, manuscript submitted to Quart. J. Roy. Meteor. Soc .) documenting improvements in the simulation of tropical

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Robert S. Ross, T. N. Krishnamurti, S. Pattnaik, and A. Simon

similarity between Figs. 13a and 6 for NAMMA wave 2. Both show a singular burst of heating during the wave stage of the system. In Fig. 13a , the heating quickly rises to a maximum at 0600 UTC 11 September and at 1200 UTC 11 September, and just as quickly dissipates beyond these times in the depression and storm stages. It is interesting to note that this maximum burst in heating occurs at all three levels defining the 800–400-hPa layer ( Fig. 13b ). The Meteosat water vapor images (6.2 μ m) in

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Peter Knippertz and Andreas H. Fink

: Evolution of tropical plumes in VAS water vapor imagery. Mon. Wea. Rev. , 118 , 1758 – 1766 . 10.1175/1520-0493(1990)118<1758:EOTPIV>2.0.CO;2 Mecikalski, J. R. , and Tripoli G. J. , 1998 : Inertial available kinetic energy and the dynamics of tropical plume formation. Mon. Wea. Rev. , 126 , 2200 – 2216 . 10.1175/1520-0493(1998)126<2200:IAKEAT>2.0.CO;2 Meier, F. , and Knippertz P. , 2009 : Dynamics and predictability of a heavy dry-season precipitation event over West Africa

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