Ice nucleation by aerosols from anthropogenic pollution

Creators: Zhao, Bin; Wang, Yuan; Gu, Yu; Liou, Kuo-Nan; Jiang, Jonathan H.; Fan, Jiwen; Liu, Xiaohong; Huang, Lei; Yung, Yuk L.

Abstract

The formation of ice particles in the atmosphere strongly affects cloud properties and the climate. While mineral dust is known to be an effective ice nucleating particle, the role of aerosols from anthropogenic pollution in ice nucleation is still under debate. Here we probe the ice nucleation ability of different aerosol types by combining 11-year observations from multiple satellites and cloud-resolving model simulations. We find that, for strong convective systems, the ice particle effective radius near cloud top decreases with increasing loading of polluted continental aerosols, because the ice formation is dominated by homogeneous freezing of cloud droplets, which are smaller under more polluted conditions. By contrast, an increase in ice particle effective radius with polluted continental aerosols is found for moderate convection. Our model simulations suggest that this positive correlation is explained by enhanced heterogeneous ice nucleation and prolonged ice particle growth at higher aerosol loading, indicating that polluted continental aerosols contain a considerable fraction of ice nucleating particles. Similar aerosol–ice relationships are observed for dust aerosols, further corroborating the ice nucleation ability of polluted continental aerosols. By catalysing ice formation, aerosols from anthropogenic pollution could have profound impacts on cloud lifetime and radiative effect as well as precipitation efficiency.

Additional Information

© 2019 Springer Nature Publishing AG. Received 16 December 2018; Accepted 15 May 2019; Published 01 July 2019. Data availability: The satellite and meteorology data products used in this study are publicly available at the following sites: MODIS/Aqua MYD04 and MYD06 products: https://earthdata.nasa.gov/ CALIOP/CALIPSO 05kmMLay and 05kmAPro products: https://eosweb.larc.nasa.gov/ AIRS/Aqua AIRIBRAD product: https://disc.gsfc.nasa.gov/ NCEP Final Analysis product: https://rda.ucar.edu/datasets/ds083.2/ Other data supporting the findings of this study are available within the Article and Supplementary Information. Code availability: The code of the WRF-SBM model is available at http://www2.mmm.ucar.edu/wrf/users/download/get_source.html. The scripts used to process the satellite data can be requested from the corresponding authors. This study is supported by the NASA ROSES TASNPP (80NSSC18K0985) and NSF AGS-1701526, AGS-1700727 and AGS-1642289 grants. We acknowledge the support of the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA, and the Joint Institute for Regional Earth System Science and Engineering at the University of California Los Angeles. The effort of J.F. was supported by the US Department of Energy (DOE) Early Career Research Program. X.L. was supported by the US DOE Atmospheric System Research Program (grants DE-SC0014239 and DE-SC0018926). We would like to acknowledge high-performance computing support from Cheyenne (https://doi.org/10.5065/D6RX99HX) provided by NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation. Author Contributions: B.Z., Y.G. and Y.W. designed the research; B.Z., Y.G., Y.W. and L.H. performed the satellite data analysis; Y.W., B.Z. and J.F. performed the model simulation; B.Z., Y.W., Y.G., K.-N.L., J.F., J.H.J. and X.L. analysed the results; B.Z., Y.W., Y.G., K.-N.L., J.H.J., J.F., X.L. and Y.L.Y. wrote the paper. The authors declare no competing interests.

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