Extended Abstract (284K)P2.5
Simulation of Arctic cloud properties during the spring season of SHEBA/FIRE-ACE experiment using a statistical cloud scheme in the CCCMA single-column model
Junhua Zhang, Dalhousie University, Halifax, NS, Canada; and U. Lohmann
The statistical cloud scheme in the single-column model (SCM) of Canadian Centre for Climate Modeling and Analysis (CCCMA) was used to simulate the cloud properties in the Arctic during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. In this study, a new statistically based parameterization of the autoconversion rate and aggregation rate that account for the in-cloud variability are used. Also, a theoretically based method of calculating the condensation and deposition rates is implemented into the cloud scheme. Sensitive studies have been performed to determine the proper values of other parameters in the cloud scheme, especially for the Arctic area. The results of the sensitive experiments show that the homogeneous ice formation temperature, the threshold of ice water content for the Bergeron-Findeisen process, and the threshold of relative humidity used in the statistical cloud scheme for calculating the standard deviation of the saturation deficit may impact the cloud cover, cloud water content and precipitation substantially. The simulated water phase, cloud cover, liquid water path and precipitation agree well with the observations from aircraft, Millimeter-Wavelength Cloud Radar (MMCR), Microwave Radiometer (MWR) and rain gauge, although the simulated precipitation is smaller than observed. The SCM using the new autoconversion and aggregation rate significantly improves the simulation of the liquid water path and precipitation. Compared with the MMCR observations, the SCM predicts more realistic boundary layer clouds (fog) using the new condensation and deposition rate.
Poster Session 2, Cloud Physics Poster Session II
Tuesday, 4 June 2002, 1:00 PM-4:00 PM
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