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Sophie Bastin, Philippe Drobinski, Vincent Guénard, Jean-Luc Caccia, Bernard Campistron, Alain M. Dabas, Patricia Delville, Oliver Reitebuch, and Christian Werner

examines the mechanisms driving the unsteady and inhomogeneous aspects of the flow structure at the Rhône Valley exit. Section 6 concludes the study. 2. Measurements and model a. Observations During the ESCOMPTE experiment, a wide range of instruments was deployed around Marseille, leading to a dense network of observations available from Doppler and ozone lidars, wind profilers, sodars, radiosoundings, and meteorological surface stations (see the details in Cros et al. 2004 ). The aim of this

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Richard Swinbank and Alan O'Neill

)ABSTRACT A data assimilation system has been developed at the UK Meteorological Office to analyze the mix of observations available in the troposphere and stratosphere. The data assimilation system is based on the analysiscorrection scheme used at the UK Meteorological Office for operational weather forecasting. The assimilation system is currently being used to supply near real-time analyses of meteorological fieldsfrom the troposphere and stratosphere to the Upper Atmosphere Research Satellite

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J. K. Angell and J. Korshover

hemispheric mean surface temperature. J. Atmos. $ci., 33, 2094-2106.Cadle, R. D., C. S. Kiang and J. F. Louis, 1976: The global scale dispersion of the eruption clouds from major volcanic eruptions. J. Geophys. Res., 81, 3125-3132.--, F. G. Fernald and C. L. Frush, 1977: Combined use of lidar and numerical diffusion models to estimate the quantity and dispersion of volcanic eruption clouds in the strato sphere: Vulcfin Fuego, 1974, and Augustine, 1976. J. Geo phys. Res., 82, 1783

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S. Lu, H. X. Lin, A. W. Heemink, G. Fu, and A. J. Segers

ash emissions ( Mastin et al. 2009 ). For instance, the empirical relationship between plume height above vent and total volume is built up to determine total emission rates from plume altitude observations. This plume height could be obtained from aircraft measurements ( Mankin et al. 1992 ) or ground-based radar or lidar observations ( Wang et al. 2008 ), which are often not available. Then, in practice, explicit assumptions on the vertical distribution have to be made such as a uniform

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Tammy M. Weckwerth, Lindsay J. Bennett, L. Jay Miller, Joël Van Baelen, Paolo Di Girolamo, Alan M. Blyth, and Tracy J. Hertneky

observations (i.e., CAPE of 377 J kg −1 , CIN of −94 J kg −1 , and LFC of 3.0 km) but both the observations and simulations suggested limited CI potential at Achern. Indeed, convection was not initiated at the Achern site. Winds were not retrieved by this sounding, so the wind profilers from two Achern instruments are shown: the U.K. National Centre for Atmospheric Science (NCAS) wind profiler and the University of Salford Doppler lidar. The WRF wind profile was consistent with the observed wind profiles

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Angela Benedetti and Marta Janisková

(CPR) on board CloudSat, and the cloud–aerosol lidar with orthogonal polarization (CALIOP) on board CALIPSO are revealing the complex two-dimensional and three-dimensional structures of clouds ( Stephens et al. 2002 ). The challenge now is to extract the largest amount of information about the cloudy atmosphere from this wealth of data by using state-of-the-art modeling and assimilation systems. The assimilation of cloud observations, using global numerical weather prediction (NWP) systems, has

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Larry K. Berg, William I. Gustafson Jr., Evgueni I. Kassianov, and Liping Deng

results from the four WRF grid points closest to the SGP have been averaged together. The default version of the model generally underpredicts the cloud fraction compared to the observations derived from the cloud radar and lidar. The KF-CuP simulations do a better job, but still tend to underpredict the cloud fraction at the SGP ( Fig. 6 ). The actual cloud fraction, however, can have a significant amount of spatial variability, as highlighted in the visible satellite images shown in Fig. 3

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Fanglin Yang, Hua-Lu Pan, Steven K. Krueger, Shrinivas Moorthi, and Stephen J. Lord

; Xie and Zhang 2000 ; Xu et al. 2002 ; Luo et al. 2003 ; Lenderink et al. 2004 ; Luo et al. 2005 ). Even though the initial motive of the ARM program was to improve the performance of climate models, in recent years a few investigators have successfully applied ARM observations to the evaluation of numerical weather prediction (NWP) models at operational weather forecast centers (e.g., Mace et al. 1998 ; Hinkelman et al. 1999 ; Morcrette 2002 ; Luo et al. 2005 ). ARM provides certain unique

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Kozo Okamoto, Kazumasa Aonashi, Takuji Kubota, and Tomoko Tashima

information from space-borne radar and lidar: Experimental study using a 1D+4D-Var technique . Quart. J. Roy. Meteor. Soc. , 141 , 2708 – 2725 , doi: 10.1002/qj.2558 . Janisková , M. , P. Lopez , and P. Bauer , 2012 : Experimental 1D+4D-Var assimilation of CloudSat observations . Quart. J. Roy. Meteor. Soc. , 138 , 1196 – 1220 , doi: 10.1002/qj.988 . JMA , 2013 : Outline of the operational numerical weather prediction at the Japan Meteorological Agency. Appendix to WMO technical progress

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Thomas A. Jones, Jason A. Otkin, David J. Stensrud, and Kent Knopfmeier

the initial cloud analysis is also improved through assimilation of either direct or indirect observations of cloud properties. Several potential data sources exist, but none can provide the complete answer alone. Observations of cloud properties from surface-based disdrometers, aircraft, and surface or satellite-based lidars represent the most direct measurements, but they are not optimal for large-scale data assimilation since they provide observations for very limited spatial and temporal

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