Open AccessInvestigating ice nucleation in cirrus clouds with an aerosol‐enabled Multiscale Modeling Framework
Author(s) -
Zhang Chengzhu,
Wang Minghuai,
Morrison Hugh,
Somerville Richard C. J.,
Zhang Kai,
Liu Xiaohong,
Li JuiLin F.
Publication year - 2014
Publication title -
journal of advances in modeling earth systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.03
H-Index - 58
ISSN - 1942-2466
DOI - 10.1002/2014ms000343
Subject(s) - ice nucleus , cirrus , aerosol , ice crystals , supersaturation , atmospheric sciences , troposphere , environmental science , nucleation , snow , ice cloud , liquid water content , liquid water path , sea ice growth processes , climatology , meteorology , geology , cloud computing , radiative transfer , sea ice thickness , arctic ice pack , physics , sea ice , thermodynamics , quantum mechanics , computer science , operating system
Abstract In this study, an aerosol‐dependent ice nucleation scheme has been implemented in an aerosol‐enabled Multiscale Modeling Framework (PNNL MMF) to study ice formation in upper troposphere cirrus clouds through both homogeneous and heterogeneous nucleation. The MMF model represents cloud scale processes by embedding a cloud‐resolving model (CRM) within each vertical column of a GCM grid. By explicitly linking ice nucleation to aerosol number concentration, CRM‐scale temperature, relative humidity and vertical velocity, the new MMF model simulates the persistent high ice supersaturation and low ice number concentration (10–100/L) at cirrus temperatures. The new model simulates the observed shift of the ice supersaturation PDF toward higher values at low temperatures following the homogeneous nucleation threshold. The MMF model predicts a higher frequency of midlatitude supersaturation in the Southern Hemisphere and winter hemisphere, which is consistent with previous satellite and in situ observations. It is shown that compared to a conventional GCM, the MMF is a more powerful model to simulate parameters that evolve over short time scales such as supersaturation. Sensitivity tests suggest that the simulated global distribution of ice clouds is sensitive to the ice nucleation scheme and the distribution of sulfate and dust aerosols. Simulations are also performed to test empirical parameters related to auto‐conversion of ice crystals to snow. Results show that with a value of 250 μm for the critical diameter, Dcs, that distinguishes ice crystals from snow, the model can produce good agreement with the satellite‐retrieved products in terms of cloud ice water path and ice water content, while the total ice water is not sensitive to the specification of Dcs value.