Data · dataset · 2026
Pi Chamber Simulation with Superdroplets
Listed in National Center for Atmospheric Research
These data come from numerical simulations of turbulent moist RayleighâBénard convection driving cloud condensation nuclei (CCN) activation and cloud droplet growth in the laboratory Pi chamber.
Description
Lagrangian particle-based microphysics is used to represent CCN deliquescence and droplet growth with kinetic, solute, and surface tension effects included. The dataset includes the numerical code for the chamber simulation and two output files that include evolutions of 1) the dynamics and thermodynamic three-dimensional fields, and 2) positions and sizes of the Superdroplets.
The dataset is created per journal publication requirement. The dataset includes a Fortran code for the Pi chamber simulation and two output binary files written by the code. The simulation solves model equations on the 51**3 grid that covers the Pi chamber and follows about 3.8 million of computational particles (referred to as Superdroplets) that represent CCN and cloud droplets.
Read the rest (1 more)
The simulation covers 20 minutes of the chamber simulation. Dynamic and thermodynamic fields (velocity components, temperature, humidity) are saved every 12 seconds. Superdroplets data (positions and radii) are saved every minute.
Links
Get the data
- Resource Homepage doi.org/10.5065/7e21-j337 ↗
download · DOI / persistent id · from data ucar edu
Where it is published
- data.ucar.edu /dataset/pi-chamber-simulation-with-superdroplets ↗
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=d96717f3-989d-434f-a75e-289c0b746… ↗
metadata API · from data ucar edu
Topics
- From keywords
- Earth & Environmental Science · Ocean & Atmospheric Science
- Inferred from text
- Cloud physics 76% · Simulation 75%
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| National Center for Atmospheric Research | d96717f3-989d-434f-a75e-289c0b74693e | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:field:370107 | enrichment · data ucar edu | taxonomy-embedding@1.1.0 | title+keywords+description (76%) |
| 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 | |
| concepts[method].local:method:simulation | enrichment · data ucar edu | keyword-concept-rules@1.0.0 | title+description (75%) |
| 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 |