New paper finds climate models simulate or predict only about 6% of altocumulus clouds
A paper published today in Atmospheric Research finds “Altocumulus clouds are important, yet climate models have difficulties in simulating and predicting these clouds” and “Approximately 93.6% of Altocumulus clouds cannot be resolved by climate models with a grid resolution of 1°.”
Thus, only 6.4% of observed altocumulus clouds are simulated or predicted by climate models. Needless to say, clouds have profound effects on Earth’s radiative balance and climate; a mere 1-2% change in global cloud cover alone can account for global warming or cooling. Among their many failings, climate models are unable to simulate clouds, ocean oscillations, solar amplification mechanisms, precipitation, sea ice, albedo, convection, etc. etc.
Spatial scales of altocumulus clouds observed with collocated CALIPSO and CloudSat measurements
Damao Zhanga, , ,
Climatology of Ac horizontal scale and vertical depth is presented.
93.6% of Altocumulus clouds cannot be resolved by GCMs with a grid resolution of 1°.
Ac scale distributions are related to their formation mechanisms.
Ac vertical depth is impacted by CTT and environmental humidity.
Altocumulus (Ac) clouds are important, yet climate models have difficulties in simulating and predicting these clouds, due to their small horizontal scales and thin vertical extensions. In this research, 4 years of collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar and CloudSat radar measurements is analyzed to study the along-track horizontal scales and vertical depths of Ac clouds. Methodology to calculate Ac along-track horizontal scale and vertical depth using collocated CALIPSO and CloudSat measurements is introduced firstly. The global mean Ac along-track horizontal scale is 40.2 km, with a standard deviation of 52.3 km. Approximately 93.6% of Altocumulus clouds cannot be resolved by climate models with a grid resolution of 1°. The global mean mixed-phase Ac vertical depth is 1.96 km, with a standard deviation of 1.10 km. Global distributions of the Ac along-track horizontal scales and vertical depths are presented and possible factors contributing to their geographical differences are analyzed. The result from this study can be used to improve Ac parameterizations in climate models and validate the model simulations.