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Kenneth Sassen and James R. Campbell

Cirrus Experiment (ICE) ( Raschke et al. 1990 ). As part of our participation in Project FIRE, we began in 1987 supporting the extended time observations (ETO) component by collecting polarization lidar and passive radiometric data from high clouds at the University of Utah Facility for Atmospheric Remote Sensing (FARS) during times of Geostationary Operational Environmental Satellite (GOES) and polar-orbiting satellite local imagery. The nature of this unique long-term dataset is reviewed in

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Roni Avissar, Edwin W. Eloranta, Kemal Gürer, and Gregory J. Tripoli

designed for that purpose and, therefore, no perfect dataset is currently available. Yet during a few days of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), volume-imaging lidar (VIL) and simultaneous observations of land-surface heat fluxes, atmospheric profiles of wind, temperature, and specific humidity were carried out. While not ideal, this dataset contains interesting information worth comparing with LES outputs. The research described in this

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Katrina S. Virts and John M. Wallace

effects of water vapor on the GPS signal. We make use of these corrected profiles even though the water vapor effect is small in the relatively dry and cold TTL and lower stratosphere ( Kursinski et al. 1996 ; Anthes et al. 2008 ). The Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) and Aura are polar-orbiting satellites in National Aeronautics and Space Administration (NASA)’s Afternoon constellation (or “A train”); Aura flies just minutes behind CALIPSO in the

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Y. Takano and K. N. Liou

probablybecause the hollow depths of longer columnar crystalssuch as needles are deeper than those of shorter columns. Table .5 lists the computed (5 values and hollowdepths, which can be used as a guideline to investigatebackscattering depolarization involving hollow columns. The (5 values for the other crystal shapes (bulletrosettes, dendrites, and capped colunms) differ onlyslightly from those for the corresponding simple solidcrystals. The polarization lidar observations reported by Sassen (1991b) show

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C. M. R. Platt, S. C. Scott, and A. C. Dilley

the year. Observations of cirrus are sparse. Uthe and Russell(1976) observed some cases of high-altitude tropicalcirrus at Kwajalein atoll with lidar. Gdffith et al. (1980)observed two cases of tropical cirrus in situ duringGATE. Probably the earliest measurements were thoseof Davis (1970) during BOMEX. Heymsfield andJohnsen (1974)'reported observation of one isolatedcase near the Marshall Islands. Ground-based measurements of cirrus are also assuming importance for validation of satellite

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Jean-Christopher Lambert, Michel Van Roozendael, Martine De Mazière, Paul C. Simon, Jean-Pierre Pommereau, Florence Goutail, Alain Sarkissian, and James F. Gleason

ground-based and space-based studies of features such as the diurnal variability of mesospheric ozone (Ricaud et al. 1996). If degraded to the vertical resolution of the satellite instrument by means of its averaging kernels, profile observations at high vertical resolution (ozonesonde and lidar) can be valuable in testing the satellite retrieval algorithms. Finally, information on the vertical distribution of ozone is also derived from Dobson and Brewer observations of the Umkehr effect ( Götz et al

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Robert J. States and Chester S. Gardner

system was modifiedfor daytime operation. This lidar technique has been described in detail in several papers ( Bills et al. 1991 ; She et al. 1992 ; Bills and Gardner 1993 ; Papen et al. 1995 ), and the modifications of the Illinois lidar for daytime operation are described by Yu et al. (1997) . Initial observations of tides in the temperature and meridional wind perturbations in the spring and fall at Urbana have been reported by Yu et al. (1997) and States and Gardner (1998) . In this paper

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Nedjeljka Žagar

. Nehrkorn , 1990 : Assessment of the impact of simulated satellite lidar wind and retrieved 183 GHz water vapor observations on a global data assimilation system. Mon. Wea. Rev , 118 , 2513 – 2542 . Kistler , R. , and Coauthors , 2001 : The NCEP–NCAR 50-year reanalysis: Monthly means CD-ROM and documentation. Bull. Amer. Meteor. Soc , 82 , 247 – 267 . Le Dimet , F-X. , and O. Talagrand , 1986 : Variational algorithms for analysis and assimilation of meteorological observations

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David M. Romps and Andrew M. Vogelmann

campaigns and at meteorological stations, cloud sizes are usually inferred indirectly from linear sampling by aircraft, radar, lidar, or radiometer. Unfortunately, the distribution of cloud-chord lengths measured in this way is not the same as the distribution of cloud sizes. This mismatch is primarily caused by two effects: 1) an off-center sampling of a cloud will tend to yield a chord that is smaller than the true diameter, biasing the distribution to smaller sizes, and 2) large clouds are more

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Frédérick Chosson, Paul A. Vaillancourt, Jason A. Milbrandt, M. K. Yau, and Ayrton Zadra

more wall-clock CPU time). 5. Test of SCPF in GEM In this section, we present a comparison of the performance of MY2, MY2 + SCPF (in both cases the sub-time-stepping method is used), and SUND in the context of an operational NWP model. Satellite cloud products from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) and CloudSat measurements will be used as a basis for evaluation. a. Case study, model setup, and remote sensing dataset The NWP framework is GEM with 15

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