Data · dataset · 2026
Retrieval of flow structures in a convective boundary layer using an adjoint model: Identical twin experiments
Listed in National Center for Atmospheric Research
The applicability of a four-dimensional variational data assimilation (4DVAR) technique to retrieval of microscale turbulent structures in a convective boundary layer is assessed.
Description
Two new features are implemented into the existing 4DVAR model: a height-dependent eddy viscosity and a surface flux model. The identical twin experiments approach is adopted to utilize the model itself to generate 13 instantaneous three-dimensional radial velocity datasets uniformly spanning 5 min.
An ideal experiment, using these datasets as the observations, is first tested. After 400 iterations, the resulting correlation coefficients between retrieved and exact data are 0.99 for velocity and 0.97 for temperature fields. To emulate the lidar scanning feature, the 13 three-dimensional datasets are used to construct two volume scan datasets with each horizontal data slice taken from different instantaneous datasets.
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Using these data as the input, the correlation coefficients for horizontal, spanwise, and vertical velocity fluctuations and temperature can still reach 0.97, 0.97, 0.94, and 0.72 after 400 iterations. Addition of a surface flux model improves retrieval quality. Allowing height-dependent eddy viscosity and diffusivity does not improve retrieval quality, whereas doubling the value of eddy diffusivity improves retrieval quality.
Implementation of temporal and spatial smoothness penalty functions significantly improves retrieval quality in the presence of various sources of error.
Links
Get the data
- Publisher page n2t.org/ark:/85065/d74t6jjq ↗
documentation · download · from data ucar edu
Where it is published
- data.ucar.edu /dataset/retrieval-of-flow-structures-in-a-convective-boundary-… ↗
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=8962c64b-4bd6-4cf6-96f4-9000a9ad7… ↗
metadata API · from data ucar edu
Topics
- From keywords
- Earth & Environmental Science · Ocean & Atmospheric Science
- Inferred from text
- Atmospheric sciences 73%
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| National Center for Atmospheric Research | 8962c64b-4bd6-4cf6-96f4-9000a9ad7ce0 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:3701 | enrichment · data ucar edu | taxonomy-embedding@1.1.0 | title+keywords+description (73%) |
| 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 |