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

Atmospheric rivers (ARs) are long, narrow corridors of enhanced water vapor transport that play an important role in transporting moisture from lower latitudes toward the extratropical and polar regions. On one hand, ARs can cause precipitation, end drought, accumulate snowpacks, and support ecosystems and society. On the other hand, ARs also represent a type of hazard and are responsible for economic losses, such as by extreme precipitation and winds, rain on existing snowpacks, or causing debris flows and landslides. Given the importance of ARs, this paper proposes a multi-method fusion algorithm for more objectively identifying ARs on a global scale. The proposed algorithm, based on the vertically integrated water vapor transport (IVT), integrates advanced strategies from multiple existing algorithms and introduces a dual-axis test method to enhance the stability of AR identification. Using IVT data from ERA5, a global AR database is constructed at a 1° × 1° horizontal resolution and a six-hourly temporal resolution for 1940–2024, and is publicly available at https://doi.org/10.5281/zenodo.18051602 (Chen and Rao, 2025). Comparative evaluation against established AR databases reveals strong agreement in mid-latitude ocean basins where ARs are most active. The usefulness of the new AR database is also demonstrated by examining the role of ARs in two extreme events in the recent past: atypical AR activity during the East Asian Meiyu rainfalls in late June 2018, and rare AR activity during the Australian Black Summer in late January 2020. The results show that the new AR database helps to reduce the uncertainty in AR identification and to better understand extreme events and their variations in time and space.