Peng et al. (2026) Linkage in the Diversity of Atmospheric Rivers: A Global Perspective on Multi‐Framework Classification
⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.
Identification
- Journal: Geophysical Research Letters
- Year: 2026
- Date: 2026-09-15
- Authors: Yongmao Peng, Gang Fu, Peng Hu, Jing Ni, Wen Chen
- DOI: 10.1029/2026gl123330
Research Groups
- Department of Atmospheric Science, University of California, Los Angeles (UCLA)
- National Center for Atmospheric Research (NCAR)
Short Summary
This study provides the first global quantification of statistical linkages among atmospheric river (AR) classifications, revealing a unified "wind-driven, cyclone-associated" archetype. The research integrates fragmented understandings of AR diversity, offering a consolidated reference for forecasting and climate modeling.
Objective
- Investigate the interconnections among different atmospheric river classification frameworks
Study Configuration
- Spatial Scale: Global
- Temporal Scale: Long-term (not specified)
Methodology and Data
- Models used: Not specified
- Data sources: Not specified
Main Results
- A unified "wind-driven, cyclone-associated" archetype is identified among high-frequency, windy, and cyclone-related ARs.
- Non-cyclone-related ARs represent a broad residual category with mixed characteristics.
Contributions
- Provides the first global quantification of statistical linkages among AR classifications.
- Integrates fragmented understandings of AR diversity, offering a consolidated reference for forecasting and climate modeling.
Funding
- Not specified
Citation
@article{Peng2026Linkage,
author = {Peng, Yongmao and Fu, Gang and Hu, Peng and Zhu, Kexu and Ni, Jing and Chen, Wen},
title = {Linkage in the Diversity of Atmospheric Rivers: A Global Perspective on Multi‐Framework Classification},
journal = {Geophysical Research Letters},
year = {2026},
doi = {10.1029/2026gl123330},
url = {https://doi.org/10.1029/2026gl123330}
}
Original Source: https://doi.org/10.1029/2026gl123330