Ice Nucleation by Laboratory-Generated and Ambient Particles, Its Representation in Global Models, and the Role of Secondary Ice Multiplication Processes

 

Authors

Daniel Knopf — Stony Brook University
Benny Wong — Stony Brook University
Peiwen Wang — Texas A&M University
Yijie Lu — Stony Brook University
Joseph Charnawskas — Stony Brook University
Cao Cong — Stony Brook University

Daniel Veghte — Pacific Northwest National Laboratory
Fraund Matthew — University of the Pacific
Alexander Laskin — Purdue University
Ryan Moffet — Sonoma Technology Inc.
Mary Gilles — Lawrence Berkeley National Laboratory
Jian Wang — Washington University in St. Louis
Assaf Zipori — Weizmann Institute of Science
Yinon Rudich — Weizmann Insitute of Science
Daniel Rosenfeld — The Hebrew University of Jerusalem
Jan P. Perlwitz — Climate, Aerosol, and Pollution Research, LLC
Ann M. Fridlind — NASA - Goddard Institute for Space Studies
Ron L Miller — NASA - Goddard Institute for Space Studies
Carlos Pérez García-Pando — Barcelona Supercomputing Center

Category

Microphysics (cloud, aerosol and/or precipitation)

Description

Ice nucleation experiments on particles collected during the Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) campaign have been complemented with single particle micro-spectroscopic analysis of identified ice nucleating particles (INPs) and ambient particle population. During summer 2017, ground site collected samples show different particle and INP types between day and nighttime periods, where fresh marine particles likely stem from the marine boundary layer (MBL) and aged particles likely originate from long distance sources. Modification of the ice nucleation experiment allows for examination of ACE-ENA samples collected by aircraft using the time resoled aerosol collector (TRAC). First experimental results on the ice nucleation propensity of aerosol particles collected above and in the MBL will be shown. Immersion freezing results of mineral dusts including illite, kaolinite, and feldspar when present in external and internal mixtures applying constant cooling rate and isothermal freezing experiments are presented. Freezing data are evaluated by stochastic and deterministic freezing models. Derived parameter sets of single dust component droplet freezing are utilized in prediction of freezing of internal and external dust mixtures. We obtained laboratory immersion freezing data from particles filtered from rainwater. We compared these data with satellite-retrieved cloud top glaciation temperatures of the same raining clouds. An ice nucleation model is used to reconstruct cloud glaciation temperature considering primary ice nucleation only. These results show that primary ice nucleation does not support observed cloud glaciation but supports the occurrence of secondary ice multiplication processes. We carried out experiments with NASA GISS's Earth system ModelE2. The dust modules in the model allows to take into consideration the different efficiency of mineral species to serve as INPs. Using the simulated mineral fields from the model, we calculate INP number concentration, by applying different parameterizations such as time independent active size parameterizations for illite, kaolinite, and K-feldspar, and the water activity-based immersion freezing model for illite, kaolinite, K-feldspar, and hematite. We compare the resulting INP concentrations with respect to their sensitivity to fundamental dust properties like emitted mineral size distribution and internal versus external mixing.