Data · dataset · 2026
Assessing clouds in GFDL's AM4.0 with different microphysical parameterizations using the satellite simulator package COSP
Listed in National Center for Atmospheric Research
We evaluate cloud simulations using satellite simulators against multiple observational data sets.
Description
These simulators have been run within the Geophysical Fluid Dynamics Laboratory's Atmosphere Model version 4.0 (AM4.0), as well as an alternative configuration where a fully two‐moment Morrison‐Gettelman cloud microphysical parameterization with prognostic precipitation (MG2) is applied, denoted as AM4‐MG2. The modeled cloud spatial distributions, vertical profiles, phase partitioning, cloud‐to‐precipitation transitions, and radiative effects compare reasonably well with satellite observations.
Model biases include the under‐prediction of total and low‐level clouds, especially optically thin/intermediate clouds with cloud optical depth of less than 23, but the over‐prediction of thick clouds, indicating “too few, too bright” biases. These biases counteract each other, and give rise to reasonable estimates of cloud radiative effects. The underestimate of low‐level clouds is associated with too early and too frequent drizzle/precipitation formation.
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The precipitation bias is improved in AM4‐MG2, where the autoconversion scheme initiates the precipitation more realistically. There also exist discrepancies between models and observations for midlevel and high‐level clouds. Additional biases include the underestimate of liquid cloud fraction and the overestimate of ice cloud fraction.
Links
Get the data
- Publisher page n2t.net/ark:/85065/d7jw8kbm ↗
documentation · download · from data ucar edu
Where it is published
- data.ucar.edu /dataset/assessing-clouds-in-gfdls-am4-0-with-different-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=48b574ed-7c94-4291-8642-5a821d0e1… ↗
metadata API · from data ucar edu
Topics
- From keywords
- Earth & Environmental Science · Ocean & Atmospheric Science
- Inferred from text
- Cloud physics 79% · Satellite remote sensing 65%
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| National Center for Atmospheric Research | 48b574ed-7c94-4291-8642-5a821d0e1d91 | 10 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 (79%) |
| 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[modality].local:modality:remote-sensing | enrichment · data ucar edu | keyword-concept-rules@1.0.0 | title+description (65%) |
| 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 |