Numerical evidence that the impact of CCN and INP concentrations on mixed-phase clouds is observable with cloud radars
Abstract. In this research, we delve into the influence of cloud condensation nuclei (CCN) and ice-nucleating particles (INP) concentrations on the morphology and abundance of ice particles in mixed-phase clouds, emphasizing the consequential impact of ice particle shape, number, and size on cloud dynamics and microphysics. Leveraging the synergy of the Advanced Microphysics Prediction System (AMPS) and the Kinematic Driver (KiD) model, we conducted simulations to capture cloud microphysics across diverse CCN and INP concentrations. The Passive and Active Microwave radiative TRAnsfer (PAMTRA) radar forward simulator further augmented our study, offering insights into how the concentrations of CCN and INP affect radar reflectivities.
Our experimental framework encompassed CCN concentrations ranging from 10 to 5000 cm−3 and INP concentrations from 0.001 to 10 L−1. Central to our findings are the observation that increased INP concentrations yield smaller ice particles, while a surge in CCN concentrations leads to a subtle growth in their dimensions. Consistent with existing literature, our results spotlight plate-like crystals as dominant between temperatures of −20 to −16 °C. Notably, high INP scenarios unveiled a significant prevalence of irregular polycrystals. The Aspect Ratio (AR) of ice particles exhibited a decline with the rise in both CCN and INP concentrations, highlighting the nuanced interrelation between CCN levels and ice particle shape, especially its ramifications on the riming mechanism.
The forward-simulated radar reflectivities, spanning from −11.83 dBZ (low-INP, 0.001 L−1) to 4.65 dBZ (high-INP, 10 L−1), elucidate the complex dynamics between CCN and INP in determining mixed-phase cloud characteristics. Comparable differences in radar reflectivity were also reported from observational studies of stratiform mixed-phase clouds in contrasting aerosol environments. Our meticulous analysis of KiD-AMPS simulation outputs, coupled with insights into aerosol-driven microphysical changes, thus underscores the significance of this study in refining our ability to understand and interpret observations and climate projections.
