Data · dataset · 2026
A method for adaptive habit prediction in bulk microphysical models. Part II: Parcel model corroboration
Listed in National Center for Atmospheric Research
It is common for cloud microphysical models to use a single axis length to characterize ice crystals.
Description
These methods use either the diameter of an equivalent sphere or mass-size equations in conjunction with the capacitance model to close the equations for ice vapor diffusion. Single-axis methods unnaturally constrain growth because real crystals evolve along at least two axis directions.
Thus, they are unable to reproduce the simultaneous variation in mass mixing ratio, maximum dimension, and mass-weighted fall speeds. While mass-size relations can at times capture the evolution of one of these with relatively low errors, the other properties are generally under- or overpredicted by 20%-40%. Part I of this study describes an adaptive habit method that evolves two axis dimensions, allowing feedbacks between aspect ratio changes and mass mixing-ratio evolution.
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The adaptive habit method evolves particle habit by prognosing number and mass mixing ratios along with two axis length mixing ratios. Compared with a detailed Lagrangian bin representation of ice habit distribution evolution in a parcel framework, the bulk method reproduces the ice mass mixing ratio, mean axis lengths, and mass-weighted fall speeds generally to within less than 5% relative error for layered and deeper mixed-phase clouds.
Links
Get the data
- Publisher page n2t.org/ark:/85065/d7q81dxv ↗
documentation · download · from data ucar edu
Where it is published
- data.ucar.edu /dataset/a-method-for-adaptive-habit-prediction-in-bulk-microph… ↗
National Center for Atmospheric Research dataset page
landing page · from data ucar edu
Catalogue records · 1
- CKAN API data.ucar.edu/api/3/action/package_show?id=3d795612-b9d2-4c49-9e0b-5b8763031… ↗
metadata API · from data ucar edu
Topics
- From keywords
- Earth & Environmental Science · Ocean & Atmospheric Science
Provenance · 1 source records, 7 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| National Center for Atmospheric Research | 3d795612-b9d2-4c49-9e0b-5b87630316d8 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].local:field:earth-environmental | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| concepts[field].local:field:ocean-atmospheric | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| created_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| description | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /notes |
| publication_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| title | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /title |
| updated_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 |