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M. Christian Schwartz, Virendra P. Ghate, Bruce. A. Albrecht, Paquita Zuidema, Maria P. Cadeddu, Jothiram Vivekanandan, Scott M. Ellis, Pei Tsai, Edwin W. Eloranta, Johannes Mohrmann, Robert Wood, and Christopher S. Bretherton

sampling strategies and the mean conditions observed during CSET can be found within Albrecht et al. (2019) , Mohrmann et al. (2019, manuscript submitted to Mon. Wea. Rev .), and Bretherton et al. (2019) . A notable feature of the CSET campaign was the first deployment of the HIAPER W-band Doppler cloud radar (HCR), together with the high-spectral-resolution lidar (HSRL). These systems were included on the CSET GV deployment to remotely sense cloud and precipitation. A cloud and precipitation data

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Jing-Wu Liu, Shang-Ping Xie, Joel R. Norris, and Su-Ping Zhang

Infrared Pathfinder Satellite Observations ( CALIPSO ) satellite was launched on 28 April 2006 by the National Aeronautics and Space Administration (NASA) and the French Centre National d’Études Spatiales (CNES) to study the impact of clouds and aerosols on Earth’s radiation budget and climate ( Winker et al. 2009 ). A selective, iterated boundary location algorithm is used to detect cloud layers from the lidar backscatter signals ( Vaughan et al. 2009 ). CALIPSO provides a cloud-layer product with

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Steven D. Miller, Courtney E. Weeks, Randy G. Bullock, John M. Forsythe, Paul A. Kucera, Barbara G. Brown, Cory A. Wolff, Philip T. Partain, Andrew S. Jones, and David B. Johnson

-profile information from the CloudSat ( Stephens et al. 2002 ) and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ; Winker et al. 2010 ) active sensors is combined with traditional two-dimensional (2D) observations of cloud properties from the Moderate Resolution Imaging Spectroradiometer (MODIS, carried on the Aqua satellite) to provide an ability to evaluate 3D model cloud fields. This evaluation requires innovations to existing MET tools as well as the introduction of new

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Robert Atlas, Ross N. Hoffman, Zaizhong Ma, G. David Emmitt, Sidney A. Wood Jr., Steven Greco, Sara Tucker, Lisa Bucci, Bachir Annane, R. Michael Hardesty, and Shirley Murillo

). The OAWL sensor is described in section 2a . c. Summary of past global OSSEs The basic methodology for OSSEs, as modified by Atlas and others in the early 1980s ( Atlas et al. 1985a ), is illustrated in Fig. 1 . An OSSE begins with an NR generated by a state-of-the-art atmospheric model. From the NR all currently available observations, as well as any new observations to be evaluated, are simulated. In the experiments reported here, for the wind lidar, a very detailed lidar simulation model is

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Reinout Boers, James D. Spinhirne, and William D. Hart

JULY 1988 REINOUT BOERS, JAMES D. SPINHIRNE AND WILLIAM D. HART 797Lidar Observations of the Fine-Scale Variability of Marine Stratocumulus Clouds REINOUT BOERS~'*, JAMES D. SPINHIRNE~ AND WILLIAM D. HART***NAS~t/Goddard Space Flight Center, Laboratory for Atmospheres, Code 617, Greenbelt, Maryland*Department of Meteorology, University of Maryland, College Park, Maryland**Science Systems and Applicalions, Inc

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Shane D. Mayor

observations presented here are unique because 1) they include both in situ and scanning lidar data, 2) the lidar images reveal the microscale structure and motion of the fronts on horizontal and vertical cross sections, and 3) the dataset contains 7 fronts out of the nearly-continuous 77 days of data available. The Raman-shifted Eye-safe Aerosol lidar (REAL; Mayor et al. 2007 ) was deployed in Dixon, California, between 15 March and 11 June 2007 as an appendix to the Canopy Horizontal Array Turbulence

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Tammy M. Weckwerth, Kristy J. Weber, David D. Turner, and Scott M. Spuler

forecasting skill and for obtaining improved accuracy in QPF skill. This latter report noted that “moisture and BL wind field observations are likely to be even more important on the mesoscale.” ( NRC 2012 , p. 87). Optimal temporal resolution requirements for profiling water vapor ranges from better than 1 h for monitoring purposes to better than 1 min for turbulence studies (e.g., Weckwerth et al. 1999 ; Turner et al. 2014 ; Wulfmeyer et al. 2015 ). The differential absorption lidar (DIAL) validated

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Lindsay J. Bennett, Tammy M. Weckwerth, Alan M. Blyth, Bart Geerts, Qun Miao, and Yvette P. Richardson

studies showing horizontal maps of the moisture in the CBL from an airborne water vapor lidar. The structure of the paper is as follows. The layout and description of instrumentation are described in section 2 and the general meteorological situation in section 3 . Observations of the evolution of the early morning boundary layer are presented in section 4 , the development of the convective boundary layer in section 5 , and the characteristics of the open cells in section 6 . A summary of the

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Timothy J. Wagner and Jessica M. Kleiss

observational accuracy of sky cover, it is necessary to compare these observations to a similar instrument with greater vertical range. The micropulse lidar (MPL) is an eye-safe ground-based lidar that operates at 532 nm and is capable of observing cloud-base heights up to 20 km ( Wang and Sassen 2001 ). This instrument provides a dataset of sky cover observations that is qualitatively similar to that of the ceilometer; however, with over 5 times the vertical range, it is capable of observing clouds that

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Min Deng, Gerald G. Mace, Zhien Wang, J.-L. F. Li, and Yali Luo

that this result may not be exactly applicable to other datasets since the definition of lidar–radar regions depends on the sensitivities of instruments used in different projects. For the three-species ice-phase scheme in models, the cloud ice mass is generally contributed by the small particles, given the small size assumption of cloud ice. However, snow and graupel are not equivalent to the median and large modes in observations, respectively. Therefore, they need to be repartitioned with a

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