Testing Cloud Microphysics Parameterizations in NCAR CAM5 with ISDAC and M-PACE Observations

• Published in: Journal of Geophysical Research
• Main Authors: Liu, Xiaohong, Xie, Shaocheng, Boyle, James, Klein, Stephen A., Shi, Xiangjun, Wang, Zhien, Lin, Wuyin, Ghan, Steven J., Earle, Michael, Liu, Peter S. K., Zelenyuk, Alla
• Format: Other Non-Article Part of Journal/Newspaper
• Language: English
• Published: University of Wyoming. Libraries 2011
• Subjects: Aerosol concentration; Arctic clouds; Atmospheric radiation measurements; Autoconversion; Cloud fraction; Cloud liquid waters; Cloud microphysics; Community atmospheric model; Conversion rates; Freezing temperatures; Frontal clouds; Long waves; Low bias; Mixed-phase cloud; Model performance; Model physics; National center for atmospheric researches; New-ice; North Slope of Alaska; Parameterizations; Radiative fluxes; Single layer; Single-column model; Time-stepping; U.S. Department of Energy; Atmospheric aerosols; Atmospheric radiation; Climatology; Clouds; Computer simulation; Parameterization; Rain; Liquids; arctic environment; atmospheric modeling; boundary layer; cloud condensation nucleus; freezing; future prospect; longwave radiation; radiative transfer; rainfall; seasonality; spatial distribution; stratocumulus; testing method; water content; weather forecasting; Alaska; North Slope; United States; Arctic; Alaska North Slope; north slope
• Online Access: https://hdl.handle.net/20.500.11919/718; https://doi.org/10.1029/2011JD015889

©2011 by the American Geophysical Union. Arctic clouds simulated by the National Center for Atmospheric Research (NCAR) Community Atmospheric Model version 5 (CAM5) are evaluated with observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Indirect and Semi-Direct Aerosol Campaign (ISDAC) and Mixed-Phase Arctic Cloud Experiment (M-PACE), which were conducted at its North Slope of Alaska site in April 2008 and October 2004, respectively. Model forecasts for the Arctic spring and fall seasons performed under the Cloud-Associated Parameterizations Testbed framework generally reproduce the spatial distributions of cloud fraction for single-layer boundary-layer mixed-phase stratocumulus and multilayer or deep frontal clouds. However, for low-level stratocumulus, the model significantly underestimates the observed cloud liquid water content in both seasons. As a result, CAM5 significantly underestimates the surface downward longwave radiative fluxes by 20-40 W m-2. Introducing a new ice nucleation parameterization slightly improves the model performance for low-level mixed-phase clouds by increasing cloud liquid water content through the reduction of the conversion rate from cloud liquid to ice by the Wegener-Bergeron-Findeisen process. The CAM5 single-column model testing shows that changing the instantaneous freezing temperature of rain to form snow from -5°C to -40°C causes a large increase in modeled cloud liquid water content through the slowing down of cloud liquid and rain-related processes (e.g., autoconversion of cloud liquid to rain). The underestimation of aerosol concentrations in CAM5 in the Arctic also plays an important role in the low bias of cloud liquid water in the single-layer mixed-phase clouds. In addition, numerical issues related to the coupling of model physics and time stepping in CAM5 are responsible for the model biases and will be explored in future studies.