Articles | Volume 16, issue 9
https://doi.org/10.5194/acp-16-5891-2016
https://doi.org/10.5194/acp-16-5891-2016
Research article
 | 
13 May 2016
Research article |  | 13 May 2016

Marine boundary layer structure as observed by A-train satellites

Tao Luo, Zhien Wang, Damao Zhang, and Bing Chen

Abstract. The marine boundary layer (MBL) structure is important to the marine low cloud processes, and the exchange of heat, momentum, and moisture between oceans and the low atmosphere. This study examines the MBL structure over the eastern Pacific region and further explores the controlling factors of MBL structure over the global oceans with a new 4-year satellite-based data set. The MBL top (boundary layer height, BLH) and the mixing layer height (MLH) were identified using the MBL aerosol lidar backscattering from the CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations). Results showed that the MBL is generally decoupled with MLH ∕ BLH ratio ranging from  ∼  0.5 to  ∼  0.8 over the eastern Pacific Ocean region. The MBL decoupling magnitude is mainly controlled by estimated inversion strength (EIS), which in turn controls the cloud top entrainment process. The systematic differences between drizzling and non-drizzling stratocumulus tops also show dependence on EIS. This may be related to the meso-scale circulations or gravity wave in the MBL. Further analysis indicates that the MBL shows a similar decoupled structure for clear-sky and cumulus-cloud-topped conditions, but is better mixed under stratiform cloud breakup and overcast conditions.

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Short summary
With a new 4-year satellite-based data set, the cloud-free marine boundary layer (MBL) structure characteristics over the eastern Pacific region were presented and analyzed together with the stratiform cloud top as the cloudy MBL top. Results showed that the behavior of MBL decouple structure and drizzling and non-drizzling stratiform cloud tops was mainly controlled by the inversion near the MBL top. Results in this paper will be valuable to evaluate and improve model simulation.
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