Details

Autor(en) / Beteiligte

• Cesana, G.
• Waliser, D. E.
• Jiang, X.
• Li, J.-L. F.

Titel

Multimodel evaluation of cloud phase transition using satellite and reanalysis data

Ist Teil von

• Journal of geophysical research. Atmospheres, 2015-08, Vol.120 (15), p.7871-7892

Ort / Verlag

Washington: Blackwell Publishing Ltd

Erscheinungsjahr

2015

Link zum Volltext

Quelle

Wiley Online Library Journals Frontfile Complete

Beschreibungen/Notizen

• 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 (6 km to 8.4 km) and at temperatures too warm (−13.9°C to −32.5°C) compared to observations (8.6 km, −33.7°C); features consistent with a lack of supercooled liquid with respect to ice above 6.5 km. 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. Key Points Cloud phase intermodel differences are very large Prognostic cloud phase scheme is necessary to reproduce realistic cloud phase These results could lead to an improvement of the next generation of GCMs