Real-time observations of dust-cloud interactions based on polarization and Raman lidar measurements

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Abstract

Dust aerosols have significant impact on the environment and climate through long-range transport. We report, in this paper, a case of dust-cloud interaction process using combined measurements of a ground-based polarization and Raman (PR) lidar systems, and implemented by the spaceborne Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar observations. The dust event occurred on 14 March 2009 over East Asia. During the two hours of observing time, the ground-based lidar observed an ongoing process of decreasing of the depolarization ratio (DR) accompanied by the increase of the water vapor simultaneously, indicating a dust-cloud interaction and particle transformation. CALIPSO measurements also found similar layers of dusts and clouds over lands and oceans with properties similar to the ground based lidar measurements. Our observation was a real-time dust-cloud process with the observation of occurrence of particle transformation. The depolarization reduced from 0.2 to 0.1 corresponding to a change of aspect ratio from 1.2 to 1.1. A discussion of a dust-cloud interaction in terms of three-stage cloud processes is made based on back-trajectory analyses and lidar observations. The result shows that dust aerosols decrease the cloud extinction coefficient by 41% but increase the cloud optical depth (COD) of water cloud by 12.79%, compared with that of pure water clouds. Furthermore, if dust aerosols participate as cloud condensation nuclei (CCN) in cloud physical processes, then they significantly reduce the size of the cloud droplet by 44-79%. Finally, based on three-year collocated CALIPSO and CloudSat measurements from 2007 to 2010, we found approximately one-third of clouds are originally dusty in the spring over the Pacific Coast areas.

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Huang, Z., Nee, J. B., Chiang, C. W., Zhang, S., Jin, H., Wang, W., & Zhou, T. (2018). Real-time observations of dust-cloud interactions based on polarization and Raman lidar measurements. Remote Sensing, 10(7). https://doi.org/10.3390/rs10071017

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