Understanding　the　impacts　of　weather　conditions　on　metro　ridership　can　provide　insights　to　improve　the　resilience　of　metro　systems.　However,　there　are　few　studies　to　examine　the　weather-metro　ridership　relationship　in　multiple　cities　with　a　framework　to　obtain　generalizable　and　robust　results.　This　study　aims　to　fill　this　gap　by　establishing　reliable　models　to　investigate　the　impacts　of　weather　conditions　on　metro　ridership　in　three　mega　cities　with　different　weather　conditions　in　China,　namely　Beijing,　Shanghai　and　Shenzhen.　We　collect　daily　metro　ridership　and　weather　parameters　of　three　cities　for　a　12　month　period　in　2019,　and　the　multiple　linear　regression　models　with　9-term　moving　average　are　utilized　to　investigate　the　weather-metro　ridership　relationship　in　each　city.　The　metro　ridership　residual　is　selected　as　the　dependent　variable,　and　independent　variables　include　weather　variables,　seasonal　variables,　comprehensive　comfort　index　and　air　quality　index.　In　addition,　socioeconomic　characteristics　are　also　considered　in　the　generalized　linear　mixed-effect　models　with　multiple　cities.　Results　highlight　that　independent　variables　have　significant　impacts　on　metro　ridership　in　all　models.　Although　significances　of　variables　are　various　in　different　models,　most　variables　have　the　same　influence　direction　in　different　models　on　both　weekdays　and　weekends.　As　a　whole,　temperature　residual,　spring,　summer,　and　fall　have　a　positive　impact　on　metro　ridership,　while　relative　humidity　residual,　wind　speed　residual,　and　precipitation　are　negatively　associated　with　metro　ridership.　Besides,　the　ridership　on　weekends　is　more　severely　affected　by　weather　conditions　compared　to　that　on　weekdays.　In　the　overall　models,　socioeconomic　characteristics　are　significant　on　weekdays,　but　they　are　insignificant　on　weekends.　It　should　be　noted　that　the　comprehensive　comfort　index　and　air　quality　index　are　significantly　associated　with　metro　ridership　in　specific　models,　and　they　should　be　considered　in　further　weather-ridership　modeling.　The　findings　can　deepen　our　understandings　about　weather-metro　ridership　relationship　and　the　differences　among　cities,　which　would　provide　valuable　information　for　scheduling　and　management　of　metro　systems.　©　2022　Hong　Kong　Society　for　Transportation　Studies