Physical processes controlling ice concentrations in synoptically-forced

Numerical simulations and airborne measurements are used to evaluate the impact of physical processes on synoptically forced, midlatitude cirrus ice concentrations. The agreement within a factor of 2 between ice concentrations measured with independent techniques (replicators and optical imaging probes) provides confidence in the accuracy of the in situ measurements. We use a computationally efficient modeling approach that incorporates the key cirrus physical processes, such that thousands of cloud cases can be simulated and the model results can be statistically compared with observations. One-dimensional simulations with detailed treatments of cloud microphysical processes are driven by temperatures and vertical winds extracted from meteorological analyses. Small-scale temperature and vertical wind perturbations associated with mesoscale waves are superimposed on the analysis fields. We find that in simulations with only homogeneous freezing nucleation, ice concentration statistics are very sensitive to the specified mesoscale wave vertical wind perturbations. With the frequency distribution of vertical winds adjusted to agree with aircraft observations, we obtain good agreement between the simulated and observed ice concentration frequency distributions. Both the observations and simulations indicate that relatively high ice concentrations (≥1000 L−1) occur rarely in these clouds (less than 1% of the time). Simulations including both homogeneous and heterogeneous nucleation indicate that even with moderate concentrations of ice nuclei (20 L−1), heterogeneous nucleation is an important ice production process, particularly for relatively low ice concentrations and warm temperatures. With enhanced ice nuclei concentrations (100 L−1), heterogeneous nucleation dominates ice production in the model. We find that it is critically important to include the impact of sedimentation on the evolution of ice concentrations when comparing model results with observations. Ice crystal collection efficiencies are poorly constrained at low temperatures, and we find that aggregation can significantly reduce ice concentrations. Sensitivity tests indicate that neither the agreement between observed and simulated ice crystal statistics nor the sensitivities indicated by the simulations are significantly affected by model assumptions such as the time periods simulated, geographic domain covered, trajectory paths calculated, or ice crystal habit assumed.