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© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 15 Mar 2019

Submitted as: research article | 15 Mar 2019

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This discussion paper is a preprint. A revision of the manuscript is under review for the journal Atmospheric Chemistry and Physics (ACP).

Aerosol–Cloud Closure Study on Cloud Optical Properties using Remotely Piloted Aircraft Measurements during a BACCHUS Field Campaign in Cyprus

Radiance Calmer1, Gregory C. Roberts1,2, Kevin J. Sanchez1,2, Jean Sciare3, Karine Sellegri4, David Picard4, Mihalis Vrekoussis3,5,6, and Michael Pikridas3 Radiance Calmer et al.
  • 1Centre National de Recherches Météorologiques (CNRM), UMR 3589, Météo-France/CNRS, Toulouse, France
  • 2Scripps Institution of Oceanography, University of California, San Diego, CA
  • 3Energy, Environment and Water Research Center, The Cyprus Institute, 2121 Nicosia, Cyprus
  • 4LaMP, Laboratoire de Météorologie Physique CNRS UMR6016, Observatoire de Physique du Globe de Clermont-Ferrand, Université Clermont Auvergne, Aubière, France
  • 5Institute of Environmental Physics and Remote Sensing (IUP-UB), University of Bremen, 28359 Bremen, Germany
  • 6Center of Marine Environmental Sciences (MARUM), University of Bremen, 28359 Bremen, Germany

Abstract. In the framework of the EU-FP7 BACCHUS project, an intensive field campaign was performed in Cyprus (2015/03). Remotely Piloted Aircraft System (RPAS), ground-based instruments, and remote-sensing observations were operating in parallel to provide an integrated characterization of aerosol-cloud interactions. Remotely Piloted Aircraft (RPA) were equipped with a 5-hole probe, pyranometers, pressure, temperature and humidity sensors, and measured updraft velocity at cloud base and cloud optical properties of a stratocumulus layer. Ground-based measurements of dry aerosol size distributions and cloud condensation nuclei spectra, and RPA observations of vertical wind velocity and meteorological state parameters are used here to initialize an Aerosol–Cloud Parcel Model (ACPM) and compare the in situ observations of cloud optical properties measured by the RPA to those simulated in the ACPM. Two different cases are studied with the ACPM, including an adiabatic case and an entrainment case, in which the in-cloud temperature profile from RPA is taken into account. Adiabatic ACPM simulation yields cloud droplet number concentrations at cloud base (ca. 400 cm−3) that are similar to those derived from a Hoppel minimum analysis. Cloud optical properties have been inferred using the transmitted fraction of shortwave radiation profile measured by downwelling and upwelling pyranometers mounted on a RPA, and the observed transmitted fraction of solar radiation is then compared to simulations from the ACPM. ACPM simulations and RPA observations show better agreement when associated with entrainment compared to that of an adiabatic case. The mean difference between observed and adiabatic profiles of transmitted fraction of solar radiation is 0.12, while this difference is only 0.03 between observed and entrainment profiles. A sensitivity calculation is then conducted to quantify the relative impacts of two-fold changes in aerosol concentration, and updraft velocity to highlight the importance of accounting for the impact of entrainment in deriving cloud optical properties, as well as the ability of RPAs to leverage ground-based observations for studying aerosol–cloud interactions.

Radiance Calmer et al.
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Status: final response (author comments only)
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Radiance Calmer et al.
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Publications Copernicus
Short summary
Unmanned Aerial Vehicles (UAV) bring new opportunities to study clouds, and better represent these in models. This analysis presents a comparison between direct observations in cloud from a UAV flight and results of a one-dimension model. The experiment is part of the European BACCHUS project, and took place in Cyprus, considered as a polluted environment. The study shows the importance of taking into account mixing air at cloud top to better match the model results with the UAV observations.
Unmanned Aerial Vehicles (UAV) bring new opportunities to study clouds, and better represent...