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

Abstract. Atmospheric rivers (ARs) are long, narrow corridors in the atmosphere that transport immense amounts of water vapor poleward across the mid-latitudes. On one hand, ARs can act as one of the precipitation sources, end drought, accumulate snowpacks, and support ecosystems and the society. One 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 horizontal resolution of 1° × 1° and a time interval of six hours from 1940 to 2024. 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.