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Dominique Bouniol, Rémy Roca, Thomas Fiolleau, and D. Emmanuel Poan

and lidar) is in the expected range for tropical cirrus. Table 1. Number of MCS subregions [convective (conv), stratiform (strat), and cirriform (cirri)] and the corresponding number of profiles sampled at each normalized life step (between 1 and 10) for the three geographical areas. Boldface numbers in the table highlight the subregions that were sampled in less than 20 independent MCSs. Fig . 1. Mean cloud-top height evolution over the MCS life cycle retrieved from radar data (solid line) and

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Haruka Hotta, Kentaroh Suzuki, Daisuke Goto, and Matthew Lebsock

of anthropogenic gases and aerosols were set to present-day emissions. The simulated results were analyzed to show the mean state of the last three years unless otherwise stated. d. COSP To facilitate the quantitative evaluation of clouds in MIROC6 against satellite observations, we used the satellite simulator COSP version 1.4 ( Bodas-Salcedo et al. 2011 ). In this study, low-level (>680 hPa) CF of MIROC6 diagnosed by the COSP lidar module was evaluated against CALIPSO remote sensing using the

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Yun Hang, Tristan S. L’Ecuyer, David S. Henderson, Alexander V. Matus, and Zhien Wang

), on top-of-atmosphere and surface radiation balance ( Fig. 1 ). This combination of radar and lidar measurements provide a near-global view of the vertical structure of clouds, and allows direct observations of multilayered cloud systems, that are found to make the largest contribution to the energy budget ( Sassen and Wang 2012 ; Part I ). At the top-of-atmosphere (TOA), multilayered cloud systems reduce outgoing longwave radiation (OLR) by 13.2 W m −2 , and increase outgoing shortwave radiation

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Ying Li and David W. J. Thompson

hydrometeor layers within Earth’s atmosphere. 2) CloudSat cloud radiative heating rates Cloud radiative heating rates are derived from the combined CloudSat – CALIPSO 2B-FLXHR-lidar product (version P2R04), which utilizes the combined CloudSat – CALIPSO cloud observations and lidar-based aerosol retrievals ( Henderson et al. 2013 ). The product provides profiles of estimates of the 1) upward and downward longwave radiative fluxes, 2) upward and downward shortwave radiative fluxes, and 3) all

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James H. Mather

-of-the-atmosphere perspective and to relate the observations at Manus to the surrounding region. 2. Cloud observations at Manus The two primary instruments for detecting clouds over the ARM sites are the millimeter cloud radar ( Moran et al. 1998 ) and the micropulse lidar ( Spinhirne 1993 ). Figure 3 plots the frequency with which these instruments observe clouds in a vertical column over Manus as a function of time and altitude for the period August 1999–November 2000. This period represents the longest period of

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Bryan C. Weare and Amip Modeling Groups

) ABSTRACT Estimates of zonally averaged cloudiness at each pressure level in 24 models participating in the AtmosphericModel Intercomparison Project are compared with the ISCCP C2 as well as the Nimbus 7 (N7) and Warren et al.(hereafter WH) observations. The global means of model high cloudiness are about two to five times greater thanthe C2 satellite observations. The large differences are probably related to excessive high, thin cloud in most models.Nearly all of the models have the observed

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Bryan C. Weare

1. Introduction Recently the first results of the reanalysis undertaken by the National Centers for Environmental Prediction (NCEP formally known as the National Meteorological Center, NMC) and the National Center for Atmospheric Research (NCAR) have been described ( Kalnay et al. 1996 ). This reanalysis is the result of a tremendous effort to develop a high quality homogeneous dataset of most relevant atmospheric variables over the period of modern observations. Monthly means of the analyses

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Shaocheng Xie, Xiaohong Liu, Chuanfeng Zhao, and Yuying Zhang

Intercomparison Project (AMIP II) ( Gates et al. 1999 ) with sea surface temperatures (SST) and sea ice prescribed from the observations. The last 10 yr of data for these two runs are analyzed and compared. c. Observations The data used to compare with model simulations include clouds measured from the International Satellite Cloud Climatology Project (ISCCP; Rossow and Schiffer 1999 ), the Moderate Resolution Imaging Spectroradiometer (MODIS; Platnick et al. 2003 ), and the Cloud–Aerosol Lidar and

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Matthew D. Shupe and Janet M. Intrieri

. Observations of cloud presence and base height were made at SHEBA by a combination of lidar and radar measurements. The Depolarization and Backscatter Unattended Lidar (DABUL; Alvarez et al. 1998 ) measured profiles of returned power and depolarization ratio for 9 months of the SHEBA year. The Millimeter Cloud-Radar (MMCR; Moran et al. 1998 ) operated for over 11 months of the SHEBA year and provided profiles of radar reflectivity. The collocated measurements from the DABUL and the MMCR were combined to

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Peter T. May, Charles N. Long, and Alain Protat

and height. The second approach is to examine several years of cloud profile data collected at the Darwin ARCS site with a 35-GHz cloud radar and micropulse lidar. The radar–lidar observations include “ice cloud” profiles (defined as not having a liquid layer below the ice, such as nonprecipitating ice anvils, altocumulus/altostratus clouds, and cirrus clouds) and “convective ice” profiles (the ice part of precipitating systems). Care has been taken to split the datasets into ice clouds and

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