Abstract
Cloud microphysical data obtained from aircraft measurements during the GoAmazon2014/5 campaign were analyzed to examine the differences in cloud microphysical properties and relationships between the wet and dry seasons and their implications on cloud microphysical processes. Basically, the distinct differences in cloud microphysical properties between the wet and dry seasons were considered to be due to higher concentration of aerosols and their larger sizes in the dry season, leading to higher droplet concentration. Analyses of cloud microphysical relationships and mixing diagrams strongly suggest homogeneous mixing for most cloud segments in both the wet and dry seasons: diluted cloud parcels with smaller liquid water content (L) and lower droplet concentration (N) generally had smaller mean volume of cloud droplets (V). However, in the dry season some cloud segments included cloud parcels that had high N of small cloud droplets, which led to a low correlation between N and V and also between N and L. These features are speculated to be due to secondary activation of cloud droplets from the cloud condensation nuclei in the entrained air, which seemed more likely to occur in the dry season due to more favorable conditions for such a process, including larger sizes of entrained aerosols, higher fluctuation of vertical velocity and lager turbulent dissipation rate.
Original language | English |
---|---|
Article number | 104648 |
Journal | Atmospheric Research |
Volume | 230 |
DOIs | |
Publication status | Published - 2019 Dec 1 |
Bibliographical note
Funding Information:This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI2018-03511. Data used in this study are from the U.S. Department of Energy ARM Aerial Facility's GoAmazon Campaign (http://www.arm.gov/). The contributions from Micael A. Cecchini were funded by FAPESP grant 2017/04654-6.
Funding Information:
This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI2018-03511 . Data used in this study are from the U.S. Department of Energy ARM Aerial Facility's GoAmazon Campaign ( http://www.arm.gov/ ). The contributions from Micael A. Cecchini were funded by FAPESP grant 2017/04654-6 .
Publisher Copyright:
© 2019
All Science Journal Classification (ASJC) codes
- Atmospheric Science