A Novel Algorithm to Develop a Satellite-Based Atmospheric River Database

Atmospheric rivers (ARs) feature transient, long, narrow filaments of strong moisture transports and can lead to intense rainfall and flooding when they reach continents. So far, most studies of atmospheric rivers (ARs) utilize atmospheric reanalysis datasets, which are known to more or less differ from the real world especially for those synoptic-scale phenomena. Therefore, there is an urgent need to develop an observation-based AR database. In this study, we propose an algorithm to reconstruct the vertically integrated vapor transport (IVT) field using two satellite-observed variables, vertically integrated water vapor (IWV) and surface winds. This algorithm has been tested successful with atmospheric reanalysis datasets and climate model simulations and is then applied to the observations for real-world reconstruction. The reconstructed global IVT field with high resolutions in both time and space, given the advantages of satellite observations, is used to develop a satellite-based global AR database. The identified AR features with this new dataset will be presented.