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  • Author or Editor: Sally A. McFarlane x
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Jennifer M. Comstock, Robert d'Entremont, Daniel DeSlover, Gerald G. Mace, Sergey Y. Matrosov, Sally A . McFarlane, Patrick Minnis, David Mitchell, Kenneth Sassen, Matthew D. Shupe, David D. Turner, and Zhien Wang

The large horizontal extent, with its location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the Earth's radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud-scale processes in largescale models and for accurately predicting the Earth's future climate. A number of passive and active remote sensing retrieval algorithms exist for estimating the microphysical properties of upper-tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade; however, there is room for improvement. Members of the Atmospheric Radiation Measurement (ARM) program Cloud Properties Working Group are involved in an intercomparison of optical depth τ and ice water path in ice clouds retrieved using ground-based instruments. The goals of this intercomparison are to evaluate the accuracy of state-of-the-art algorithms, quantify the uncertainties, and make recommendations for their improvement.

Currently, there are significant discrepancies among the algorithms for ice clouds with very small optical depths (τ < 0.3) and those with 1 < τ < 5. The good news is that for thin clouds (0.3 < τ < 1), the algorithms tend to converge. In this first stage of the intercomparison, we present results from a representative case study, compare the retrieved cloud properties with aircraft and satellite measurements, and perform a radiative closure experiment to begin gauging the accuracy of these retrieval algorithms.

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CLOUDS AND MORE: ARM Climate Modeling Best Estimate Data

A New Data Product for Climate Studies

Shaocheng Xie, Renata B. McCoy, Stephen A. Klein, Richard T. Cederwall, Warren J. Wiscombe, Michael P. Jensen, Karen L. Johnson, Eugene E. Clothiaux, Krista L. Gaustad, Charles N. Long, James H. Mather, Sally A. McFarlane, Yan Shi, Jean-Christophe Golaz, Yanluan Lin, Stefanie D. Hall, Raymond A. McCord, Giri Palanisamy, and David D. Turner

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Andrew M. Vogelmann, Greg M. McFarquhar, John A. Ogren, David D. Turner, Jennifer M. Comstock, Graham Feingold, Charles N. Long, Haflidi H. Jonsson, Anthony Bucholtz, Don R. Collins, Glenn S. Diskin, Hermann Gerber, R. Paul Lawson, Roy K. Woods, Elisabeth Andrews, Hee-Jung Yang, J. Christine Chiu, Daniel Hartsock, John M. Hubbe, Chaomei Lo, Alexander Marshak, Justin W. Monroe, Sally A. McFarlane, Beat Schmid, Jason M. Tomlinson, and Tami Toto

A first-of-a-kind, extended-term cloud aircraft campaign was conducted to obtain an in situ statistical characterization of continental boundary layer clouds needed to investigate cloud processes and refine retrieval algorithms. Coordinated by the Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF), the Routine AAF Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign operated over the ARM Southern Great Plains (SGP) site from 22 January to 30 June 2009, collecting 260 h of data during 59 research flights. A comprehensive payload aboard the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft measured cloud microphysics, solar and thermal radiation, physical aerosol properties, and atmospheric state parameters. Proximity to the SGP's extensive complement of surface measurements provides ancillary data that support modeling studies and facilitates evaluation of a variety of surface retrieval algorithms. The five-month duration enabled sampling a range of conditions associated with the seasonal transition from winter to summer. Although about twothirds of the flights during which clouds were sampled occurred in May and June, boundary layer cloud fields were sampled under a variety of environmental and aerosol conditions, with about 77% of the cloud flights occurring in cumulus and stratocumulus. Preliminary analyses illustrate use of these data to analyze aerosol– cloud relationships, characterize the horizontal variability of cloud radiative impacts, and evaluate surface-based retrievals. We discuss how an extended-term campaign requires a simplified operating paradigm that is different from that used for typical, short-term, intensive aircraft field programs.

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