Metro　is　a　green　travel　mode,　which　is　an　important　approach　to　mitigate　urban　traffic　jams.　Metro　ridership　is　influenced　by　many　factors.　Weather　changes　quickly　and　can　lead　to　variations　in　ridership.　Understanding　the　relationship　between　metro　ridership　and　weather　can　help　to　set　up　the　corresponding　measures　for　transportation　organization.　This　paper　aims　to　analyze　weather＇s　impacts　on　metro　ridership.　Due　to　the　limitation　of　the　traditional　weather　index,　a　comfort　index　is　incorporated.　The　multiple　linear　regression　is　built　between　metro　ridership　and　weather　factors　(atmosphere　pressure,　relative　humidity,　wind　velocity,　rainfall,　wind-chill　index,　comprehensive　comfort　index,　etc.)　to　quantify　the　influence.　As　the　travel　patterns　are　different　on　workdays　and　non-workdays,　two　regression　models　are　developed.　Results　show　that　rainfall,　wind-chill　index,　and　comprehensive　comfort　index　are　significant　for　metro　ridership　on　workdays,　and　rainfall,　atmospheric　pressure,　relative　humidity,　wind-chill　index,　and　comprehensive　comfort　index　are　significant　for　metro　ridership　on　non-workdays.　In　general,　the　ridership　is　more　sensitive　to　weather　factors　on　non-work　days.　Copyright　©　2021　by　Science　Press.