The 15-year satellite MCS database was used to develop a precipitation feature (PF) algorithm based on NLDAS precipitation data alone by deriving the precipitation characteristics of MCSs. The PF algorithm was then used to construct an independent MCS database, which was validated against the satellite MCS database. The MCS database constructed by the PF algorithm provides consistent MCS rainfall compared with the satellite MCS database, with a majority of the normalized monthly MCS rainfall bias within 15% (see more detail description in ‘Developing the precipitation feature method'). The PF algorithm was then applied to the full NLDAS data set to construct a 36-year MCS database from 1979 to 2014. The days with land-falling tropical cyclones in the United States are excluded from the analysis to remove any potential impact of tropical cyclones on precipitation. After MCSs are identified, the total hourly precipitation is separated into MCS and non-MCS (isolated convection or weak stratiform) precipitation at each grid point.