Developing new methods to retrieve MBL cloud and drizzle microphysical properties using ground-based and aircraft in situ measurements during ACE-ENA

 

Authors

Peng Wu — University of Arizona
Xiquan Dong — University of Arizona
Baike Xi — University of Arizona

Category

Microphysics (cloud, aerosol and/or precipitation)

Description

Marine boundary layer (MBL) clouds frequently produce drizzle, which has been shown to be a strong modulator in stratocumulus-to-cumulus transition (Yamaguchi et al. 2017). Reliable retrievals of cloud and drizzle microphysical properties are crucial in studying drizzle formation process (Wu et al. 2017) and in constraining model parameterizations (Wu et al. 2018). However, due to a few large drizzle particles contribute majority of the reflectivity, it is difficult to apply traditional radar-radiometer techniques (e.g., Frisch et al. 1995; Dong et al. 1998, Dong and Mace, 2003) to retrieve both cloud and drizzle properties simultaneously within the cloud layer. In this study, we will develop new methods to retrieve MBL cloud and drizzle microphysical properties in the cloud by taking advantage of comprehensive aircraft and surface datasets collected during ACE-ENA IOP. In retrieving drizzle properties, the vertical air velocity (w) from Doppler lidar below the cloud base is used to approximately represent w within the cloud. The difference between Doppler velocity (vd) measured by Ka-band ARM cloud radar (KAZR) and w is assumed to be drizzle terminal velocity. Drizzle particle size (rd) is then estimated from particle size-terminal velocity relationship as in Frisch et al., (1995). Drizzle number concentration (Nd) and size distribution shape parameter (µ) are estimated from Nd and µ below cloud base, which are retrieved using the method proposed by O’Connor et al., (2005). Drizzle reflectivity (Zd) and liquid water content (LWC) can then be calculated from the size distribution. Cloud contribution to the reflectivity (Zc) is then estimated by subtracting Zd from KAZR measurement. The layer-mean cloud particle effective radius ((r_c ) ̅) is retrieved using the method in Dong et al., (1998), which uses solar mission as a constraint and is less affected by the presence of a few drizzle particles. The profiles of rc(z), follow the method of Dong and Mace (2003), are estimated by distributing (r_c ) ̅ according to Zc. Finally, the vertical profiles of the retrieved cloud and drizzle particle size and LWCs, as well as layer-mean number concentrations, will be compared with aircraft in situ measurements during ACE-ENA over the Azores. Both case studies and statistics will be shown for the ACE-ENA campaign.