The Effect of Ice Nuclei Efficiency on Arctic Mixed-Phase Clouds from Large-Eddy Simulations [electronic resource]

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Bibliographic Details
Online Access: Full Text (via OSTI)
Corporate Author: Oak Ridge National Laboratory (Researcher)
Format: Electronic eBook
Language:English
Published: Washington, D.C. : Oak Ridge, Tenn. : United States. Department of Energy. Office of Science ; Distributed by the Office of Scientific and Technical Information, U.S. Department of Energy, 2017.
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Abstract:The effects of ice nuclei (IN) efficiency on the persistent ice formation in Arctic mixed-phase clouds (AMCs) are investigated using a large-eddy simulation model, coupled to a bin microphysics scheme with a prognostic IN formulation. In the three cases where the IN efficiency is high, ice formation and IN depletion are fast. When the IN concentration is 1 and 10 g<sup>-1</sup>, IN are completely depleted and the cloud becomes purely liquid phase before the end of the 24-h simulation. When the IN concentration is 100 g<sup>-1</sup>, the IN supply is sufficient but the liquid water is completely consumed so that the cloud dissipates quickly. In the three cases when the IN efficiency is low, ice formation is negligible in the first several hours but becomes significant as the temperature is decreased through longwave cooling. Before the end of the simulation, the cloud is in mixed phase when the IN concentration is 1 and 10 g<sup>-1</sup> but dissipates when the IN concentration is 100 g<sup>-1</sup>. In the case where two types of IN are considered, ice formation persists throughout the simulation. Analysis shows that as the more efficient IN are continuously removed through ice formation, the less efficient IN gradually nucleate more ice crystals because the longwave cooling decreases the cloud temperature. This mechanism is further illustrated with a simple model. These results indicate that a spectrum of IN efficiency is necessary to maintain the persistent ice formation in AMCs.
Item Description:Published through Scitech Connect.
11/27/2017.
"Journal ID: ISSN 0022-4928."
Fu, Shizuo ; Xue, Huiwen ;
Physical Description:Size: p. 3901-3913 : digital, PDF file.