Observational Analysis of Cloud and Precipitation in Midlatitude Cyclones:...

Naud, C. M., D. J. Posselt, and S. van den Heever (2012), Observational Analysis of Cloud and Precipitation in Midlatitude Cyclones: Northern versus Southern Hemisphere Warm Fronts, J. Climate, 25, 5135-5151, doi:10.1175/JCLI-D-11-00569.1.
Abstract: 

Extratropical cyclones are responsible for most of the precipitation and wind damage in the midlatitudes during the cold season, but there are still uncertainties on how they will change in a warming climate. A ubiquitous problem among general circulation models (GCMs) is a lack of cloudiness over the southern oceans that may be in part caused by a lack of clouds in cyclones. This study analyzes CloudSat, Cloud– Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) observations for three austral and boreal cold seasons, and composites cloud frequency of occurrence and precipitation at the warm fronts for Northern and Southern Hemisphere oceanic cyclones. The authors find that cloud frequency of occurrence and precipitation rate are similar in the early stage of the cyclone life cycle in both the Northern and Southern Hemispheres. As cyclones evolve and reach their mature stage, cloudiness and precipitation at the warm front increase in the Northern Hemisphere but decrease in the Southern Hemisphere. This is partly caused by lower amounts of precipitable water being available to Southern Hemisphere cyclones, and smaller increases in wind speed as the cyclones evolve. Southern Hemisphere cloud occurrence at the warm front is found to be more sensitive to the amount of moisture in the warm sector than to wind speeds. This suggests that cloudiness in Southern Hemisphere storms may be more susceptible to changes in atmospheric water vapor content, and thus to changes in surface temperature than their Northern Hemisphere counterparts. These differences between Northern and Southern Hemisphere cyclones are statistically robust, indicating A-Train-based analyses as useful tools for the evaluation of GCMs in the next Intergovernmental Panel on Climate Change (IPCC) report.

PDF of Publication: 
Download from publisher's website.