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References: ice phase

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Sylwester Arabas edited this page Dec 2, 2021 · 18 revisions

terminology, basics:

books:

aerosol size/composition/mixing state vs. IN:

  • Riemer et al. 2019
    "Aerosol Mixing State: Measurements, Modeling, and Impacts"

    6.3.2 Mixing State Impacts on Ice Nucleating Particles (INPs)

stochasticity:

Monte-Carlo simulation of immersion freezing:

  • Vali 1971
    "Quantitative Evaluation of Experimental Results an the Heterogeneous Freezing Nucleation of Supercooled Liquids"

    Consecutive sets of numbers were assigned to each successive temperature interval in proportion to the assumed concentrations for the intervals. Random numbers generated in the computer were then compared to the assigned numbers and the temperatures to which those numbers belonged were taken as the freezing temperatures of drops.

  • Alpert & Knopf 2016
    "Analysis of isothermal and cooling-rate-dependent immersionfreezing by a unifying stochastic ice nucleation model"

    For IFSs (immersion freezing simulations) in which a cooling rate, r, is applied, J_het as a function of T and aqueous solution water activity, aw, can be calculated following the water activity-based immersion freezing model (ABIFM) applicable for both pure water (aw=1.0) and aqueous solution (aw<1.0) droplets. These IFSs generate frozen and unfrozen droplet fraction data, fufz and ffrz, respectively, and using a Monte Carlo method in which 10^5 IFSs are performed under the same conditions, 5th and 95th percentile bounds are derived as uncertainty estimates

  • Kubota 2019 (Cryst. Eng. Comm.)
    "Random distribution active site model for ice nucleation in water droplets"

    Monte Carlo simulations are performed to generate both the nucleation time distributions and the nucleation temperature distributions

  • Shima et al. 2020 (Geosci. Model Dev.)
    "Predicting the morphology of ice particles in deep convection using the super-droplet method: development and evaluation of SCALE-SDM 0.2.5-2.2.0, -2.2.1, and -2.2.2"

    The freezing temperature Tfz corresponds to the highest temperature at which the first INAS appears on the insoluble substance's surface. Let A_insol be the insoluble substance's surface area. Then, the probability that Tfz is larger than T can be calculated as P(T_fz > T)=1−exp[−A_insol n_S(T)]... We can determine Tfz by selecting a random number that follows this probability distribution.

kinematic 1D/2D prescribed-flow model studies with ice phase:

parameterisations of immersion freezing:

  • as a function of water activity (ABIFM):
  • as a function of temperature (INAS / singular hypothesis / deterministic approach):
    • Connolly et al. 2009
      "Studies of heterogeneous freezing by three different desert dust samples"
    • DeMott et al. 2010
      "Predicting global atmospheric ice nuclei distributions and their impacts on climate"
    • Niemand et al. 2012
      "A particle-surface-area-based parameterization of immersion freezing on desert dust particles"
    • DeMott et al 2015 (Atmos. Chem. Phys.)
      "Integrating laboratory and field data to quantify the immersion freezing ice nucleation activity of mineral dust particles"

sedimentation & collisions:

bacteria:

measurement-LES corroboration:

  • Fridlind et al. 2012
    "A FIRE-ACE/SHEBA Case Study of Mixed-Phase Arctic Boundary Layer Clouds: Entrainment Rate Limitations on Rapid Primary Ice Nucleation Processes"
  • Savre & Ekman 2015
    "Large-eddy simulation of three mixed-phase cloud events during ISDAC: Conditions for persistent heterogeneous ice formation"

particle-based modelling:

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