ACP Atmospheric Chemistry and Physics ACP 1680-7324 Copernicus GmbH Göttingen, Germany 10.5194/acp-11-11937-2011 Using surface remote sensors to derive radiative characteristics of Mixed-Phase Clouds: an example from M-PACE de Boer G. 1 2 3 Collins W. D. 1 Menon S. 1 Long C. N. 4 Lawrence Berkeley National Laboratory, Berkeley, CA, USA Cooperative Institute for Research of Environmental Sciences, Boulder, CO, USA NOAA Earth System Research Laboratory, Physical Sciences Division, Boulder, CO, USA Pacific Northwest National Laboratory, Richland, WA, USA 02 12 2011 11 23 11937 11949 This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This article is available from http://www.atmos-chem-phys.net/11/11937/2011/acp-11-11937-2011.html The full text article is available as a PDF file from http://www.atmos-chem-phys.net/11/11937/2011/acp-11-11937-2011.pdf

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<sup>−2</sup>, 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<sup>−2</sup>.

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