Aerosol–Ice Formation Closure: A Southern Great Plains Field Campaign

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  • 1 1 Stony Brook University, Stony Brook, NY 11794, USA
  • | 2 2 Colorado State University, Fort Collins, CO 80523, USA
  • | 3 3 Carnegie Mellon University, Pittsburgh, PA 15213, USA
  • | 4 4 Purdue University, West Lafayette, IN 47907, USA
  • | 5 5 West Texas A&M University, Canyon, TX 79016, USA
  • | 6 6 Texas A&M University, College Station, TX 77843, USA
  • | 7 7 Michigan Technological University, Houghton, MI 49931, USA
  • | 8 8 Environmental Molecular Sciences Laboratory/Pacific Northwest National Laboratory, Richland, WA 99354, USA
  • | 9 9 Laboratory of Environmental Chemistry, Paul Scherrer Institute, 5232 Villigen, Switzerland
  • | 10 10 Sonoma Technology, Inc., Petaluma, CA 94954, USA
  • | 11 11 NASA Goddard Institute for Space Studies, New York, NY 10025, USA
  • | 12 12 University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
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Abstract

Prediction of ice formation in clouds presents one of the grand challenges in the atmospheric sciences. Immersion freezing initiated by ice-nucleating particles (INPs) is the dominant pathway of primary ice crystal formation in mixed-phase clouds, where supercooled water droplets and ice crystals coexist, with important implications for the hydrological cycle and climate. However, derivation of INP number concentrations from an ambient aerosol population in cloud-resolving and climate models remains highly uncertain. We conducted an aerosol-ice formation closure pilot study using a field-observational approach to evaluate the predictive capability of immersion freezing INPs. The closure study relies on co-located measurements of the ambient size-resolved and single-particle composition and INP number concentrations. The acquired particle data serve as input in several immersion freezing parameterizations, that are employed in cloud-resolving and climate models, for prediction of INP number concentrations. We discuss in detail one closure case study in which a front passed through the measurement site, resulting in a change of ambient particle and INP populations. We achieved closure in some circumstances within uncertainties, but we emphasize the need for freezing parameterization of potentially missing INP types and evaluation of the choice of parameterization to be employed. Overall, this closure pilot study aims to assess the level of parameter details and measurement strategies needed to achieve aerosol-ice formation closure. The closure approach is designed to accurately guide immersion freezing schemes in models, and ultimately identify the leading causes for climate model bias in INP predictions.

Corresponding author: Daniel.Knopf@stonybrook.edu

Abstract

Prediction of ice formation in clouds presents one of the grand challenges in the atmospheric sciences. Immersion freezing initiated by ice-nucleating particles (INPs) is the dominant pathway of primary ice crystal formation in mixed-phase clouds, where supercooled water droplets and ice crystals coexist, with important implications for the hydrological cycle and climate. However, derivation of INP number concentrations from an ambient aerosol population in cloud-resolving and climate models remains highly uncertain. We conducted an aerosol-ice formation closure pilot study using a field-observational approach to evaluate the predictive capability of immersion freezing INPs. The closure study relies on co-located measurements of the ambient size-resolved and single-particle composition and INP number concentrations. The acquired particle data serve as input in several immersion freezing parameterizations, that are employed in cloud-resolving and climate models, for prediction of INP number concentrations. We discuss in detail one closure case study in which a front passed through the measurement site, resulting in a change of ambient particle and INP populations. We achieved closure in some circumstances within uncertainties, but we emphasize the need for freezing parameterization of potentially missing INP types and evaluation of the choice of parameterization to be employed. Overall, this closure pilot study aims to assess the level of parameter details and measurement strategies needed to achieve aerosol-ice formation closure. The closure approach is designed to accurately guide immersion freezing schemes in models, and ultimately identify the leading causes for climate model bias in INP predictions.

Corresponding author: Daniel.Knopf@stonybrook.edu
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