A new double-moment microphysics parameterization for application in cloud and climate models. Part II: Single-column modeling of arctic clouds

• Published in: Journal of the atmospheric sciences Vol. 62; no. 6; pp. 1678 - 1693
• Main Authors: MORRISON, H, CURRY, J. A, SHUPE, M. D, ZUIDEMA, P
• Format: Journal Article
• Language: English
• Published: Boston, MA American Meteorological Society 01.06.2005
• Subjects: Aerosols; Atmospheric models; Climate models; Climatology; Clouds; Earth, ocean, space; Exact sciences and technology; External geophysics; Heat budget; Ice; Meteorology; Physics; Weather forecasting; Arctic region; PN, Arctic; short period waves; Climatology; Long wave; sensitivity analysis; aerosols; heat balance; Radiation flux; Cloud fraction; Stratus cloud; Climate models; Parameterization; Modeling; Ice cloud; downwelling; Liquid water path; polar regions; solubility; Phase partition; Mixing ratio
• ISSN: 0022-4928; 1520-0469
• DOI: 10.1175/JAS3447.1

The new double-moment microphysics scheme described in Part I of this paper is implemented into a single-column model to simulate clouds and radiation observed during the period 1 April-15 May 1998 of the Surface Heat Budget of the Arctic (SHEBA) and First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment-Arctic Clouds Experiment (FIRE-ACE) field projects. Mean predicted cloud boundaries and total cloud fraction compare reasonably well with observations. Cloud phase partitioning, which is crucial in determining the surface radiative fluxes, is fairly similar to ground-based retrievals. However, the fraction of time that liquid is present in the column is somewhat underpredicted, leading to small biases in the downwelling shortwave and longwave radiative fluxes at the surface. Results using the new scheme are compared to parallel simulations using other microphysics parameterizations of varying complexity. The predicted liquid water path and cloud phase is significantly improved using the new scheme relative to a single-moment parameterization predicting only the mixing ratio of the water species. Results indicate that a realistic treatment of cloud ice number concentration (prognosing rather than diagnosing) is needed to simulate arctic clouds. Sensitivity tests are also performed by varying the aerosol size, solubility, and number concentration to explore potential cloud-aerosol-radiation interactions in arctic stratus.