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Jothiram Vivekanandan, Virendra P. Ghate, Jorgen B. Jensen, Scott M. Ellis, and M. Christian Schwartz

spectra collected by in situ cloud and drizzle probes on the NSF–NCAR C-130 aircraft during VAMOS in the southeastern Pacific Ocean were used as input to the simulations of radar and lidar observations. The simulated radar and lidar observations were used for developing a retrieval method for estimating cloud microphysical products, namely, characteristic particle diameter and LWC. The practical applicability of the retrieval method was demonstrated using the radar and lidar measurements from CSET

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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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Christopher S. Bretherton, Isabel L. McCoy, Johannes Mohrmann, Robert Wood, Virendra Ghate, Andrew Gettelman, Charles G. Bardeen, Bruce A. Albrecht, and Paquita Zuidema

potential cloud-controlling factors, inversion stability and cloud droplet number concentration. Section 6 compares observations from an illustrative CSET flight with reanalysis and a weather-nudged climate model, followed by a summary in section 7 . 2. CSET observations and analysis methods a. Measurements used in this study The G-V instrumentation used for CSET was described in detail by A19 . It included a 94-GHz cloud radar, a high spectral resolution lidar, dropsondes, and in situ probes for

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Robert Wood, Kuan-Ting O, Christopher S. Bretherton, Johannes Mohrmann, Bruce. A. Albrecht, Paquita Zuidema, Virendra Ghate, Chris Schwartz, Ed Eloranta, Susanne Glienke, Raymond A. Shaw, Jacob Fugal, and Patrick Minnis

Wisconsin high spectral resolution lidar . Opt. Eng. , 30 , 6 – 12 , . 10.1117/12.55766 Guzman , R. , and Coauthors , 2017 : Direct atmosphere opacity observations from CALIPSO provide new constraints on cloud-radiation interactions . J. Geophys. Res. Atmos. , 122 , 1066 – 1085 , . 10.1002/2016JD025946 Hindman , E. E. , W. M. Porch , J. G. Hudson , and P. A. Durkee , 1994 : Ship-produced cloud lines of 13 July

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Bruce Albrecht, Virendra Ghate, Johannes Mohrmann, Robert Wood, Paquita Zuidema, Christopher Bretherton, Christian Schwartz, Edwin Eloranta, Susanne Glienke, Shaunna Donaher, Mampi Sarkar, Jeremy McGibbon, Alison D. Nugent, Raymond A. Shaw, Jacob Fugal, Patrick Minnis, Robindra Paliknoda, Louis Lussier, Jorgen Jensen, J. Vivekanandan, Scott Ellis, Peisang Tsai, Robert Rilling, Julie Haggerty, Teresa Campos, Meghan Stell, Michael Reeves, Stuart Beaton, John Allison, Gregory Stossmeister, Samuel Hall, and Sebastian Schmidt

Pincus 1995 ; Bretherton et al. 1995 ). The ASTEX Lagrangian studies, however, were not made in classic trade wind flow conditions and lacked the aircraft-based lidar and radar observations needed to provide a detailed mapping of cloud and precipitation structures. Fig . 1. (top left) Photo of NSF–NCAR GV and (top right) GOES visible image with aircraft path on 27 Jul 2015 RF10 during CSET. The red points indicate where dropsonde launches were made. (bottom) Photos from this flight were taken by a

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Mampi Sarkar, Paquita Zuidema, Bruce Albrecht, Virendra Ghate, Jorgen Jensen, Johannes Mohrmann, and Robert Wood

⁡ ( RWC i υ i L υ , i ) − ⁡ ( RWC i − 1 υ i − 1 L υ , i − 1 ) . The rainwater content at cloud base is set equal to that from the in-cloud leg. Although collision–coalescence will increase the rainwater content between in-cloud leg and cloud base, the assumption that the raindrop size distribution measured during in-cloud leg scales well with cloud-base precipitation is supported by observations ( Wood 2005a ). The mean cloud base height is derived from lidar measurements from the nearest 150-m level

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Johannes Mohrmann, Christopher S. Bretherton, Isabel L. McCoy, Jeremy McGibbon, Robert Wood, Virendra Ghate, Bruce Albrecht, Mampi Sarkar, Paquita Zuidema, and Rabindra Palikonda

was empirically chosen to balance the competing interests in reducing noise in box-averaged quantities while avoiding including observations from regions subject to significantly different large-scale forcings; a comparison of the GOES cloud fraction estimate to that derived from a radar-lidar cloud mask can be found in Bretherton et al. (2019) . Supplemental data are drawn from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis, version 5 (ERA5) [ Copernicus Climate Change

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