Data · dataset · 2026
Atmospheric River detection under changing seasonality and meanâstate climate: ARTMIP tier 2 paleoclimate experiments
Listed in National Center for Atmospheric Research
Atmospheric rivers (ARs) are filamentary structures within the atmosphere that account for a substantial portion of poleward moisture transport and play an important role in Earth's hydroclimate.
Description
However, there is no one quantitative definition for what constitutes an atmospheric river, leading to uncertainty in quantifying how these systems respond to global change. This study seeks to better understand how different AR detection tools (ARDTs) respond to changes in climate states utilizing single‐forcing climate model experiments under the aegis of the Atmospheric River Tracking
Method
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Intercomparison Project (ARTMIP). We compare a simulation with an early Holocene orbital configuration and another with CO 2 levels of the Last Glacial Maximum to a preindustrial control simulation to test how the ARDTs respond to changes in seasonality and mean climate state, respectively. We find good agreement among the algorithms in the AR response to the changing orbital configuration, with a poleward shift in AR frequency that tracks seasonal poleward shifts in atmospheric water vapor and zonal winds.
In the low CO 2 simulation, the algorithms generally agree on the sign of AR changes, but there is substantial spread in their magnitude, indicating that mean‐state changes lead to larger uncertainty. This disagreement likely arises primarily from differences between algorithms in their thresholds for water vapor and its transport used for identifying ARs. These findings warrant caution in ARDT selection for paleoclimate and climate change studies in which there is a change to the mean climate state, as ARDT selection contributes substantial uncertainty in such cases.
Links
Get the data
- Publisher page n2t.net/ark:/85065/d7sj1qzd ↗
documentation · download · from data ucar edu
Where it is published
- data.ucar.edu /dataset/atmospheric-river-detection-under-changing-seasonality… ↗
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=e946d515-540a-4b6a-ae5f-cf93c0084… ↗
metadata API · from data ucar edu
Topics
- From keywords
- Earth & Environmental Science · Ocean & Atmospheric Science
- Inferred from text
- Atmospheric sciences 73% · Climate model simulation 65% · Simulation 75%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| National Center for Atmospheric Research | e946d515-540a-4b6a-ae5f-cf93c00848d4 | 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 | |
| concepts[method].local:method:climate-model | enrichment · data ucar edu | keyword-concept-rules@1.0.0 | title+description (65%) |
| 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 |