2017
DOI: 10.5194/gmd-2017-164
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Prognostic parameterization of cloud ice with a single category in the aerosol-climate model ECHAM(v6.3.0)-HAM(v2.3)

Abstract: Abstract.A new scheme for stratiform cloud microphysics has been implemented in the ECHAM6-HAM2 general circulation model. It features a widely used description of cloud water with two categories for cloud droplets and rain drops. The unique aspect of the scheme is the break with the traditional approach to describe cloud ice analogously. Here we parameterize cloud ice with a single, prognostic category as it has been done in regional models and most recently also in the global model CAM5.A single category doe… Show more

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Cited by 6 publications
(16 citation statements)
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“…The two-moment ice microphysics scheme by Lohmann et al (2007), used in the default version of ECHAM6.3-HAM2.3, was succeeded by the Predicted bulk Particle Properties (P3) scheme by Morrison and Milbrandt (2015) that was ported to ECHAM-HAM by Dietlicher et al (2018Dietlicher et al ( , 2019. It replaces an earlier method of artificially separating ice particles into different size classes (Levkov et al, 1992), rendering the use of the tuning parameter for the rate of snow formation unnecessary (Dietlicher et al, 2019).…”
Section: Model Descriptionmentioning
confidence: 99%
“…The two-moment ice microphysics scheme by Lohmann et al (2007), used in the default version of ECHAM6.3-HAM2.3, was succeeded by the Predicted bulk Particle Properties (P3) scheme by Morrison and Milbrandt (2015) that was ported to ECHAM-HAM by Dietlicher et al (2018Dietlicher et al ( , 2019. It replaces an earlier method of artificially separating ice particles into different size classes (Levkov et al, 1992), rendering the use of the tuning parameter for the rate of snow formation unnecessary (Dietlicher et al, 2019).…”
Section: Model Descriptionmentioning
confidence: 99%
“…In addition, arbitrary unphysical parameter, such as the ice‐to‐snow autoconversion threshold size, should be avoided in a further model development. Taking this into account, incorporation of a single ice parameterization (Morrison & Milbrandt, ) into GCMs could be one of the solutions for better describing ice morphology while ensuring continuity of ice growth (Dietlicher et al, ; Eidhammer et al, ; Zhao et al, ).…”
Section: Summary and Future Workmentioning
confidence: 99%
“…We refer to Figure 1 of Morrison and Milbrandt () or Figure 1 of Dietlicher et al. () for graphical context of how the m‐D relationship varies for each PSD size range. For each range, all m‐D relationships follow a power law: m=aDb. For spherical particles, the parameter a is proportional to the bulk density of ice ( ρ ), defined as particle mass divided by the volume of a sphere for a given D , and is given by a=ρπ6. …”
Section: Scheme Developmentmentioning
confidence: 99%