Using HYSPLIT Back Trajectories to Improve Understanding of Tropical Thin Cirrus Cloud Formation Mechanisms

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Sunday, 23 January 2011
Using HYSPLIT Back Trajectories to Improve Understanding of Tropical Thin Cirrus Cloud Formation Mechanisms
Travis D. Toth, PNNL, Grand Forks, ND; and S. McFarlane and L. Riihimaki

Tropopause transition layer cirrus (TTLC) are thin subvisible ice clouds primarily observed at high altitudes in the Tropics. They may significantly affect the Earth's radiation budget, exchanges between the troposphere and stratosphere, and could aid in dehydrating the lower stratosphere. TTLC formation mechanisms are not fully understood, but likely impact the radiative and microphysical properties of the clouds. Thus, a better understanding of these mechanisms should increase our scientific knowledge of cloud influences on climate. In this investigation, TTLC from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were used along with two distinct methods to examine TTLC formation mechanisms. First, the object classification method was checked in order to determine whether a significant percentage of convective TTLC in December 2008 appeared to have been formed by convective detrainment. Visual inspection indicated that about 80% of convective TTLC objects are part of an anvil cloud and are assumed to be formed by convective detrainment. Next, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was automated to process kinematic back trajectories from February to December 2008. Statistics were examined to determine patterns in trajectory characteristics, and trajectories from June 2008 were matched with satellite brightness temperature data to evaluate if they traced back to large-scale convective systems. Patterns in trajectory ending location, starting height, and TTLC length were found. These patterns were credited to the Walker Circulation, level of the tropical tropopause, and to changing atmospheric dynamics, respectively. Brightness temperature data revealed only 32.6% of the back trajectories from June 2008 traced back to convection. More convective TTLC (34.9%) than non-convective TTLC (31.1%) traced back to convection. It is surprising that only 35% of the TTLC identified as convective from the observation classification method traced back to convection, but may be due to the use of a single month or the coarse resolution of the brightness temperature dataset used. Further research includes extending the trajectory analysis to an entire year and exploring the sensitivity to the thresholds and resolution of the dataset used to identify convection.