Multimodel evaluation of cloud phase transition using satellite and reanalysis data

被引:105
作者
Cesana, G. [1 ]
Waliser, D. E. [1 ]
Jiang, X. [1 ,2 ]
Li, J. -L. F. [1 ]
机构
[1] CALTECH, Jet Prop Lab, Pasadena, CA 91125 USA
[2] Univ Calif Los Angeles, Joint Inst Reg Earth Syst Sci & Engn, Los Angeles, CA USA
基金
美国国家航空航天局;
关键词
GCMs; cloud phase; evaluation; satellite; CALIPSO; multimodel; VERTICAL VELOCITY; WATER-CONTENT; CLIMATE; MODEL; PRECIPITATION; SIMULATIONS; REPRESENTATION; MICROPHYSICS; VARIABILITY; PERFORMANCE;
D O I
10.1002/2014JD022932
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
We take advantage of climate simulations from two multimodel experiments to characterize and evaluate the cloud phase partitioning in 16 general circulation models (GCMs), specifically the vertical structure of the transition between liquid and ice in clouds. We base our analysis on the ratio of ice condensates to the total condensates (phase ratio, PR). Its transition at 90% (PR90) and its links with other relevant variables are evaluated using the GCM-Oriented Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation Cloud Product climatology, reanalysis data, and other satellite observations. In 13 of 16 models, the PR90 transition height occurs too low (6km to 8.4km) and at temperatures too warm (-13.9 degrees C to -32.5 degrees C) compared to observations (8.6km, -33.7 degrees C); features consistent with a lack of supercooled liquid with respect to ice above 6.5km. However, this bias would be slightly reduced by using the lidar simulator. In convective regimes (more humid air and precipitation), the observed cloud phase transition occurs at a warmer temperature than for subsidence regimes (less humid air and precipitation). Only few models manage to roughly replicate the observed correlations with humidity (5/16), vertical velocity (5/16), and precipitation (4/16); 3/16 perform well for all these parameters (MPI-ESM, NCAR-CAM5, and NCHU). Using an observation-based Clausius-Clapeyron phase diagram, we illustrate that the Bergeron-Findeisen process is a necessary condition for models to represent the observed features. Finally, the best models are those that include more complex microphysics.
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页码:7871 / 7892
页数:22
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