Heavy　rainfall,　as　a　kind　of　adverse　weather　condition,　can　have　an　extremely　negative　impact　on　subway　ridership.　This　paper　proposed　a　comprehensive　framework　to　analyze　the　rainfall　impact　on　subway　transit　ridership.　Firstly,　rainfall　events　were　detected　from　the　precipitation　data.　Then,　heterogeneous　characteristics　of　subway　transit　trips,　such　as　the　trip　duration,　the　functionality　of　subway　stations,　and　the　trip　elasticity,　were　extracted　from　smart　card　data.　Finally,　ridership　fluctuation　coefficient　was　calculated　to　measure　the　rainfall-induced　ridership　fluctuation　degree　quantitatively.　It　figured　out　that　heavy　rainstorm　could　cause　as　much　as　forty　percent　of　reduction　on　ridership.　Meanwhile,　different　kinds　of　trips　showed　different　levels　of　sensitivity　to　rainfall.　Long　or　elastic　trips　were　more　vulnerable,　and　trips　flowing　to　airports　or　tourist　spots　could　be　sharply　cut　down　by　rainfall　events.　The　research　results　can　help　metro　operators　improve　their　service　quality　under　certain　forecasted　weather　conditions.　©　ASCE.