Understanding cirrus ice crystal number variability for different heterogeneous ice nucleation spectra

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Abstract

Along with minimizing parameter uncertainty, understanding the cause of temporal and spatial variability of the nucleated ice crystal number, Ni, is key to improving the representation of cirrus clouds in climate models. To this end, sensitivities of Ni to input variables like aerosol number and diameter provide valuable information about nucleation regime and efficiency for a given model formulation. Here we use the adjoint model of the adjoint of a cirrus formation parameterization (Barahona and Nenes, 2009b) to understand Ni variability for various ice-nucleating particle (INP) spectra. Inputs are generated with the Community Atmosphere Model version 5, and simulations are done with a theoretically derived spectrum, an empirical lab-based spectrum and two field-based empirical spectra that differ in the nucleation threshold for black carbon particles and in the active site density for dust. The magnitude and sign of Ni sensitivity to insoluble aerosol number can be directly linked to nucleation regime and efficiency of various INP. The lab-based spectrum calculates much higher INP efficiencies than field-based ones, which reveals a disparity in aerosol surface properties. Ni sensitivity to temperature tends to be low, due to the compensating effects of temperature on INP spectrum parameters; this low temperature sensitivity regime has been experimentally reported before but never deconstructed as done here.

Figures

  • Table 1. Adjustable parameters for ABN15 simulations.
  • Figure 1. (a) Nucleation regimes of cirrus in the log-log INP-ice crystal number space. At low INP numbers, nucleation is predominantly homogeneous. At intermediate INP numbers, nucleation is competitive between homogeneous and heterogeneous. Beyond the threshold INP number, Nlim, nucleation is purely heterogeneous; (b) threshold supersaturations for homogeneous nucleation and heterogeneous nucleation on mineral dust and BC with different organic coatings, FOC between 190 and 240 K for the PDA08 and PDA13 nucleation spectra. Both use the same correlation for dust.
  • Figure 2. Measurement–model comparison of probability distributions in ice crystal number concentrations. Data distributions come from the Video Ice Particle Sampler (VIPS) and the two-dimensional stereo (2DS) probe during April 2011 of the MACPEX campaign and the Forward-Scattering Spectrometer (FSSP) during January 2010 of the SPARTICUS campaigns. Only measurements from the 10–20 µm bin of the VIPS; the 5–15 µm bin of the 2DS; and the 0.89, 1.90, 3.80, 5.85, 8.30, 11.45, 14.25, 17.15 and 20.45 µm-centered bins of the 2DS are used, as approximations to the newly nucleated ice crystal number. Measurements are also filtered for altitudes of 232± 20 hPa and for uniformity, lasting at least 45 s. Distributions of simulation output, i.e. of the annually averaged output nucleated ice crystal number, Ni, as in Fig. 3, are shown using the (a) PDA08, (b) PDA13, (c) CNT and (d) AIDA nucleation spectra. Different independent axes are used in panels (c) and (d).
  • Table 2. Range of predicted ice-nucleating particle numbers and abundances for different nucleation spectra.
  • Figure 3. Annually averaged output nucleated ice crystal number, Ni from the cirrus formation parameterization for (a) PDA08, (b) PDA13, (c) CNT, (d) AIDA nucleation spectra.
  • Figure 4. Annually averaged contributions of dust and BC to heterogeneously formed ice crystal number. (a) Dust contribution in PDA08; (b) dust contribution in PDA13; (c) black carbon contribution in PDA08; and (d) black carbon contribution in PDA13.
  • Figure 5. Annually averaged accumulation-mode dust number sensitivities for (a) PDA08, (b) PDA13, (c) CNT and (d) AIDA.
  • Figure 6. Time series of accumulation-mode dust number sensitivities (green, in LL−1) and input updraft velocities (blue, in ms−1) over Indonesia at 2.9◦ S, 135◦ E for (a) PDA08 and (b) PDA13; and over South America at 0.95◦ N , 64◦W for (c) PDA08 and (d) PDA13.

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CITATION STYLE

APA

Sullivan, S. C., Morales Betancourt, R., Barahona, D., & Nenes, A. (2016). Understanding cirrus ice crystal number variability for different heterogeneous ice nucleation spectra. Atmospheric Chemistry and Physics, 16(4), 2611–2629. https://doi.org/10.5194/acp-16-2611-2016

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