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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 23
Atmos. Chem. Phys., 11, 11937-11949, 2011
https://doi.org/10.5194/acp-11-11937-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 11, 11937-11949, 2011
https://doi.org/10.5194/acp-11-11937-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 02 Dec 2011

Research article | 02 Dec 2011

Using surface remote sensors to derive radiative characteristics of Mixed-Phase Clouds: an example from M-PACE

G. de Boer1,2,3, W. D. Collins1, S. Menon1, and C. N. Long4 G. de Boer et al.
  • 1Lawrence Berkeley National Laboratory, Berkeley, CA, USA
  • 2Cooperative Institute for Research of Environmental Sciences, Boulder, CO, USA
  • 3NOAA Earth System Research Laboratory, Physical Sciences Division, Boulder, CO, USA
  • 4Pacific Northwest National Laboratory, Richland, WA, USA

Abstract. Measurements from ground-based cloud radar, high spectral resolution lidar and microwave radiometer are used in conjunction with a column version of the Rapid Radiative Transfer Model (RRTMG) and radiosonde measurements to derive the surface radiative properties under mixed-phase cloud conditions. These clouds were observed during the United States Department of Energy (US DOE) Atmospheric Radiation Measurement (ARM) Mixed-Phase Arctic Clouds Experiment (M-PACE) between September and November of 2004. In total, sixteen half hour time periods are reviewed due to their coincidence with radiosonde launches. Cloud liquid (ice) water paths are found to range between 11.0–366.4 (0.5–114.1) gm−2, and cloud physical thicknesses fall between 286–2075 m. Combined with temperature and hydrometeor size estimates, this information is used to calculate surface radiative flux densities using RRTMG, which are demonstrated to generally agree with measured flux densities from surface-based radiometric instrumentation. Errors in longwave flux density estimates are found to be largest for thin clouds, while shortwave flux density errors are generally largest for thicker clouds. A sensitivity study is performed to understand the impact of retrieval assumptions and uncertainties on derived surface radiation estimates. Cloud radiative forcing is calculated for all profiles, illustrating longwave dominance during this time of year, with net cloud forcing generally between 50 and 90 Wm−2.

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