An Algorithm to Develop a Satellite-Based Atmospheric River Database

Atmospheric rivers (ARs) feature transient filaments of enhanced moisture transports. Given their significant influence on regional weather extremes and global hydrological cycle, there have been extensive AR studies based on reanalyses or in-situ measurements. However, reanalyses may misrepresent real-world ARs, and in-situ measurements are only available for limited space and time. In this study, we propose an algorithm to reconstruct the observed vertically integrated vapor transport (IVT) field using two satellite-observed quantities, vertically integrated water vapor (IWV) and sea surface winds. This algorithm is firstly validated by atmospheric reanalyses with high correlations of IVT and is then applied to satellite observations for real-world IVT reconstruction. The developed satellite-based AR database shows similar large-scale statistics with major atmospheric reanalyses but distinct regional and local features. Furthermore, the satellite-based AR events show better agreement with the observed extreme rainfall events than reanalysis-based AR events. This new AR database with high spatial and temporal resolutions can therefore provide a unique observational archive for studying ARs and related rainfall extremes.