Ice Particle Properties Inferred From Aggregation Modelling

Abstract

We generated a large number 105,000 of aggregates composed of various monomer types and sizes using an aggregation model. Combined with hydrodynamic theory, we derived ice particle properties such as mass, projected area, and terminal velocity as a function of monomer number and size. This particle ensemble allows us to study the relation of particle properties with a high level of detail which is often not provided by in situ measurements. The ice particle properties change rather smoothly with monomer number. We find very little differences in all particle properties between monomers and aggregates at sizes below 1 mm which is in contrast to many microphysics schemes. The impact of the monomer type on the particle properties decreases with increasing monomer number. Whether, for example, the terminal velocity of an aggregate is larger or smaller than an equal‐size monomer depends mostly on the monomer type. We fitted commonly used power laws as well as Atlas‐type relations, which represent the saturation of the terminal velocity at large sizes (terminal velocity asymptotically approaching a limiting value) to the data set and tested the impact of incorporating different levels of complexity with idealized simulations using a 1D Lagrangian super particle model. These simulations indicate that it is sufficient to represent the monomer number dependency of ice particle properties with only two categories (monomers and aggregates). The incorporation of the saturation velocity at larger sizes is found to be important to avoid an overestimation of self‐aggregation of larger snowflakes.

Evaluation of ice particle growth in ICON using statistics of multi‐frequency Doppler cloud radar observations

“…For example, an overestimation of the terminal velocity of snowflakes as recently found in Karrer et al . (2020) could easily compensate for a potential underestimation of ice particle concentrations in terms of snow rate. Also processes in the transition from ice to liquid phase might mask the discrepancies found in the snow.…”

“…Our observations do not support such a sudden “jump” in terminal velocities which would manifest itself as a bimodality. The rather smooth transition of particle properties from single crystals to aggregates is also found for simulated aggregates of various monomer types and hydrodynamic theory (Karrer et al ., 2020).…”

“…The median MDV in the simulation reach −1 m·s −1 at a temperature of −20 °C, while in the observations the increase is much slower and the −1 m·s −1 are only reached at −5 °C. These effects can be explained by the general overestimation of terminal velocities of snow particles in the SB06 scheme (Karrer et al ., 2020). When the particle sizes further increase due to stronger aggregation, the power law relations between terminal velocity and size implemented in the SB06 scheme cause the terminal velocities to continuously increase.…”

“…When the particle sizes further increase due to stronger aggregation, the power law relations between terminal velocity and size implemented in the SB06 scheme cause the terminal velocities to continuously increase. In reality, the terminal velocity for unrimed snow particles is found to saturate at around −1 m·s −1 (Mitchell and Heymsfield, 2005; von Lerber et al ., 2017; Karrer et al ., 2020). This effect of overestimating the terminal velocities of large snow particles is again most evident in the profiles of precipitating events (Figure 8c, d).…”

“…As reviewed in Grabowski et al (2019), even more process complexity can be added in bin microphysical schemes or in Lagrangian super-particle models, which allow us to trace the entire history of single hydrometeors (Shima et al, 2009). These models allow a continuous representation of the particle properties caused by riming (Brdar and Seifert, 2018;Seifert et al, 2019) or aggregation (Karrer et al, 2020). Clearly, the evolution of models requires an advanced observational framework, which is capable of capturing the complexity of cloud microphysical simulations.…”