Aerosol- and Droplet-Dependent Contact Freezing: Parameterization Development and Case Study

Hande, Luke B.; Hoose, Corinna; Barthlott, Christian

doi:10.1175/jas-d-16-0313.1

Cited by 6 publications

(4 citation statements)

References 47 publications

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“…Recent work has made significant progress in the development of detailed parameterisations for deposition nucleation, immersion freezing, and contact freezing (Niemand et al, 2012;Tobo et al, 2013;DeMott et al, 2010DeMott et al, , 2015Hiranuma et al, 2014;Steinke et al, 2015;Diehl and Mitra, 2015;Ullrich et al, 2017;Hande et al, 2017). These parameterisations were developed either from observations or theory, and are representative of nucleation on a variety of aerosol species.…”

Section: Model Descriptionmentioning

confidence: 99%

Partitioning the primary ice formation modes in large eddy simulations of mixed-phase clouds

Hande

Hoose

2017

Atmos. Chem. Phys.

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Abstract. State-of-the-art aerosol-dependent parameterisations describing each heterogeneous ice nucleation mode (contact, immersion, and deposition ice nucleation), as well as homogeneous nucleation, were incorporated into a large eddy simulation model. Several cases representing commonly occurring cloud types were simulated in an effort to understand which ice nucleation modes contribute the most to total concentrations of ice crystals. The cases include a completely idealised warm bubble, semi-idealised deep convection, an orographic cloud, and a stratiform case. Despite clear differences in thermodynamic conditions between the cases, the results are remarkably consistent between the different cloud types. In all the investigated cloud types and under normal aerosol conditions, immersion freezing dominates and contact freezing also contributes significantly. At colder temperatures, deposition nucleation plays only a small role, and homogeneous freezing is important. To some extent, the temporal evolution of the cloud determines the dominant freezing mechanism and hence the subsequent microphysical processes. Precipitation is not correlated with any one ice nucleation mode, instead occurring simultaneously when several nucleation modes are active. Furthermore, large variations in the aerosol concentration do affect the dominant ice nucleation mode; however, they have only a minor influence on the precipitation amount.

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Section: Model Descriptionmentioning

confidence: 99%

Partitioning the primary ice formation modes in large eddy simulations of mixed-phase clouds

Hande

Hoose

2017

Atmos. Chem. Phys.

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“…The second setup is semiidealized, with realistic topography and an initial temperature and humidity profile (CAPE of 774 J/kg) from radiosoundings near Jülich, Germany (Hande & Hoose, ; Hande et al, ). The initial wind profile is taken from Weisman and Klemp (; unidirectional shear of 5 m/s, with a wind direction of 225° ), and the boundary conditions are fixed.…”

Section: Methodsmentioning

confidence: 99%

Cloud Top Phase Distributions of Simulated Deep Convective Clouds

2018

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Space‐based observations of the thermodynamic cloud phase are frequently used for the analysis of aerosol indirect effects and other regional and temporal trends of cloud properties; yet they are mostly limited to the cloud top layers. This study addresses the information content in cloud top phase distributions of deep convective clouds during their growing stage. A cloud‐resolving model with grid spacings of 300 m and lower is used in two different setups, simulating idealized and semiidealized isolated convective clouds of different strengths. It is found that the cloud top phase distribution is systematically shifted to higher temperatures compared to the in‐cloud phase distribution due to lower vertical velocities and a resultingly stronger Wegener‐Bergeron‐Findeisen process at the cloud top. Sensitivity studies show that heterogeneous freezing can modify the cloud top glaciation temperature (where the ice pixel fraction reaches 50%) and ice multiplication via rime splintering is visible in an early ice onset at temperatures around −10°C. However, if the analyses are repeated with a coarsened horizontal resolution (above 1 km, similar to many satellite data sets), a significant part of this signal is lost, which limits the detectability of these microphysical fingerprints in the observable cloud top phase distribution. In addition, variation in the cloud dynamics also impacts the cloud phase distribution but cannot be quantified easily.

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“…F INP values for mineral dust ranged from 0.1 to 10 % and for biological particles from 0.001 to 0.01 %. These values were used in Diehl and Mitra (2015) according to results from field measurements of cloud droplet residuals and background aerosols (e.g., Bauer et al, 2002;Twohy and Anderson, 2008;Kamphus et al, 2010;Hiranuma et al, 2013;Schmidt et al, 2017). In both cases the highest values are slightly overestimated, while the other values represent realistic situations.…”

Section: Freezing Processes and Inp Types And Fractionsmentioning

confidence: 99%