249 Relationships between Ice Nucleation Process and Crystal Habit for Arctic Mixed-Phase Clouds—a Numerical Study

Monday, 8 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
Tempei Hashino, Kyushu Univ., Kasuga, Japan; and G. de Boer, H. Okamoto, and G. J. Tripoli

In this presentation, we discuss relationships between the ice nucleation processes and ice crystal habits for Arctic mixed-phase stratus. In recent years, a rapid increase of surface temperature and sea ice melting were observed in Arctic region. The cloud-precipitation system plays an important role in the surface energy budget through radiation (Curry and Ebert 1990, Hashino et al. 2016). Mixed-phase stratiform clouds are dominant in western Arctic, and one quarter of the clouds were observed to last more than 10 hours (Shupe et al. 2011). The modes of ice nucleation and types of ice nuclei active in the clouds are still under debate (Fridlind et al. 2007, Paukert and Hoose 2014). In our previous studies (de Boer et al. 2010, 2013), it was hypothesized that the immersion freezing process is the key self-regulating process where the large droplets freeze quickly and fall out of the super-cooled layer. This time we test a classical nucleation theory approach to deal with the ice nucleation modes more rigorously and implement 3D LES experiments.

The dynamic model is UW-NMS (Tripoli and Smith 2014ab) and the cloud microphysical scheme is AMPS (Hashino and Tripoli 2007, 2008, 2011ab). The ice part of AMPS (SHIPS) is designed to predict ice crystal habits explicitly, thus it is suitable to study ice nucleation process for the mixed-phased clouds. The case studies were chosen from SHEBA (Surface Heat Budget of the Arctic Ocean) and ISDAC (Indirect and Semi-Direct Aerosol Campaign) field campaigns.

So far, we have found, in a parcel model setting, that a Bigg-type time-dependent immersion freezing parameterization (Kao-Bigg) differs from the classical nucleation theory approach (CNT) significantly in terms of the temperature of nucleation and resulting number concentration. Differences also appear on the spatial distribution of habits in 2D LES simulation. For the SHEBA case, the immersion freezing with CNT triggers freezing of droplets right after they are activated, so the active region is collocated with small droplets and temperature of irregular polycrystals. On the other hand, Kao-Bigg is associated with large cloud droplets and temperature of planar growth. We will discuss more on the simulated habits with 3D LES in the presentation.

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner