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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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https://doi.org/10.5194/amt-2017-327
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
19 Sep 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).
Improved Cloud Phase Determination of Low Level Liquid and Mixed Phase Clouds by Enhanced Polarimetric Lidar
Robert A. Stillwell1,2, Ryan R. Neely III3,4, Jeffrey P. Thayer2, Matthew D. Shupe5,6, and David D. Turner6 1Advanced Study Program, National Center for Atmospheric Research, 3450 Mitchell Lane, Bldg 1, CO 80301, USA
2Aerospace Engineering Sciences, University of Colorado at Boulder, ECNT 320, 431 UCB, University of Colorado, Boulder, CO 80309, USA
3School of Earth and Environment, University of Leeds, LS2 9JT, Leeds, UK
4National Centre for Atmospheric Science, University of Leeds, LS2 9JT, Leeds, UK
5Cooperative Institute for Research in Environmental Sciences, University of Colorado at Boulder, 216 UCB, University of Colorado, Boulder, CO 80309, USA
6Earth System Research Laboratory, National Oceanic and Atmospheric Administration, 325 Broadway, Boulder, CO 80309, USA
Abstract. The unambiguous retrieval of cloud phase from polarimetric lidar observations is dependent on the assumption that only cloud scattering processes affect polarization measurements. A systematic bias of the traditional lidar depolarization ratio can occur due to a lidar system's inability to accurately measure the entire backscattered signal dynamic range, and these biases are not always identifiable in traditional polarimetric lidar systems. This results in a misidentification of liquid water in clouds as ice, which has broad implications on evaluating surface energy budgets. The Clouds Aerosol Polarization and Backscatter Lidar at Summit, Greenland employs multiple planes of linear polarization, and photon counting and analog detection schemes, to self evaluate, correct, and optimize signal combinations to improve cloud classification. Using novel measurements of diattenuation that are sensitive to both horizontally oriented ice crystals and counting system non-linear effects, unambiguous measurements are possible by over constraining polarization measurements. This overdetermined capability for cloud phase determination allows for system errors to be identified and quantified in terms of their impact on cloud properties. It is shown that lidar system dynamic range effects can cause errors in cloud phase fractional occurrence estimates on the order of 30% causing errors in attribution of cloud radiative effects on the order of 10%-30%. This paper presents a method to identify and remove lidar system effects from atmospheric polarization measurements and uses co-located sensors at Summit to validate this method.

Citation: Stillwell, R. A., Neely III, R. R., Thayer, J. P., Shupe, M. D., and Turner, D. D.: Improved Cloud Phase Determination of Low Level Liquid and Mixed Phase Clouds by Enhanced Polarimetric Lidar, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-327, in review, 2017.
Robert A. Stillwell et al.
Robert A. Stillwell et al.
Robert A. Stillwell et al.

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Short summary
This work focuses on making unambiguous measurements of Arctic cloud phase and assessing those measurements within the context of cloud radiative effects. It is found that effects related to lidar data recording systems can cause retrieval ambiguities that alter the interpretation of cloud phase in as much as 30 % of the available data. This misinterpretation of cloud phase data can cause a misinterpretation of the effect of cloud phase on the surface radiation budget by as much as 10 % to 30 %.
This work focuses on making unambiguous measurements of Arctic cloud phase and assessing those...
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