Data · dataset · 2026
Assessing the impact of surface and wind profiler data on fog forecasting using WRF 3DVAR: An OSSE study on a dense fog event over North China
Listed in National Center for Atmospheric Research
Because fog is a high-impact weather phenomenon, there has been increased demand for its accurate prediction.
Description
Both surface data and wind profiler data possess great potential for improved fog prediction. This study aimed to quantitatively assess the impact of surface and wind profiler data on fog prediction in terms of their spatial resolutions and distributions and also to assess the relative effect of these two types of observations.
A dense fog event in northern China that occurred on 20 February 2007 was studied using the Weather Research and Forecasting (WRF) Model's three-dimensional variational data assimilation (3DVAR) system with observing system simulation experiments (OSSE). The results indicated that the incorporation of surface data has an obvious positive impact on fog forecasts, especially with respect to effective assimilation of automated weather station data.
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Dense planetary boundary layer (PBL) wind profilers are more beneficial for fog forecasting than troposphere wind profilers, and an even spatial distribution over a large region is superior to a localized distribution. Surface data show greater benefit for fog forecasting than wind profiler data, with a 6.6% increase of skill score as a result of the improvement of near-surface thermal stratification. Moreover, combining both types of data greatly enhances fog predictive skill, with a 13.6% increase in skill score relative to the experiment assimilating only surface data, as a result of better dynamically balanced fields of thermodynamic and kinematic variables within the PBL with the assimilation of PBL wind profiler data.
Links
Get the data
- Publisher page n2t.org/ark:/85065/d7jw8gs6 ↗
documentation · download · from data ucar edu
Where it is published
- data.ucar.edu /dataset/assessing-the-impact-of-surface-and-wind-profiler-data… ↗
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=b8caeb05-44a2-421a-a09e-702d7e324… ↗
metadata API · from data ucar edu
Topics
- From keywords
- Earth & Environmental Science · Ocean & Atmospheric Science
- Inferred from text
- Simulation 75%
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| National Center for Atmospheric Research | b8caeb05-44a2-421a-a09e-702d7e32447b | 8 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 | |
| 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 |