A database of objectively identified atmospheric rivers based on a multi-method fusion algorithm

Chen, Hongbin; Rao, Jian; Son, Seok-Woo; Guan, Bin; Pan, Mengxin

doi:10.5194/essd-18-5357-2026

Articles | Volume 18, issue 7

https://doi.org/10.5194/essd-18-5357-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-18-5357-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 7

Data description article

|

24 Jul 2026

Data description article |

| 24 Jul 2026

A database of objectively identified atmospheric rivers based on a multi-method fusion algorithm

Hongbin Chen, Jian Rao, Seok-Woo Son, Bin Guan, and Mengxin Pan

Data sets

A database of objectively identified atmospheric rivers based on a multi-method fusion algorithm Hongbin Chen and Jian Rao https://doi.org/10.5281/zenodo.18051602

Atmospheric river (AR) fused identification dataset from 1980 to 2016 H.-R. Wang https://doi.org/10.5281/zenodo.10229029

Short summary

We present a global atmospheric river (AR) database derived from ERA5 reanalysis (1940–2024). By employing a novel multi-method fusion algorithm, this database provides AR identification results at a horizontal resolution of 1° × 1° and a temporal resolution of 6 hours. Characterized by enhanced algorithmic robustness and extensive temporal coverage, it offers a valuable resource for further weather and climate research.