Data · dataset · 2026
Diagnosing Hurricane Barry track errors and evaluating physics scalability in the UFS Short-Range Weather Application
Listed in National Center for Atmospheric Research
To assess the performance and scalability of the Unified Forecast System (UFS) Short-Range Weather (SRW) application, case studies are chosen to cover a wide variety of forecast applications.
Description
Here, model forecasts of Hurricane Barry (July 2019) are examined and analyzed. Several versions of the Global Forecast System (GFS) and Rapid Refresh Forecast System (RRFS) physics suites are run in the UFS-SRW at grid spacings of 25 km, 13 km, and 3 km.
All model configurations produce significant track errors of up to 350 km at landfall. The track errors are investigated, and several commonalities are seen between model configurations. A westerly bias in the environmental steering flow surrounding the tropical cyclone (TC) is seen across forecasts, and this bias is coincident with a warm sea surface temperature (SST) bias and overactive convection on the eastern side of the forecasted TC.
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Positive feedback between the surface winds, latent heating, moisture, convection, and TC intensification is initiated by this SST bias. The asymmetric divergent flow induced by the excess convection results in all model TC tracks being diverted to the east as compared to the track derived from reanalysis. The large differences between runs using the same physics packages at different grid spacing suggest a deficiency in the scalability of these packages with respect to hurricane forecasting in vertical wind shear.
Links
Get the data
- Publisher page n2t.org/ark:/85065/d7j67n0p ↗
documentation · download · from data ucar edu
Where it is published
- data.ucar.edu /dataset/diagnosing-hurricane-barry-track-errors-and-evaluating… ↗
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=245afb69-e0b7-4936-b722-c573012d2… ↗
metadata API · from data ucar edu
Topics
- From keywords
- Earth & Environmental Science · Ocean & Atmospheric Science
- Inferred from text
- Atmospheric sciences 69%
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| National Center for Atmospheric Research | 245afb69-e0b7-4936-b722-c573012d2316 | 13 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 (69%) |
| 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 |