This　article　categorizes　climate　risk　into　transition　risk　and　physical　risk.　We　developed　the　climate　transition　risk　index　and　climate　physical　risk　index　through　manual　collection　of　textual　data,　and　employed　high-frequency　data　and　the　TVP-VAR-DY　model　to　assess　risk　spillover　in　the　Chinese　stock　market.　Subsequently,　the　causal　forest　method　was　applied　to　analyze　the　causal　relationships　between　these　risks　and　their　impact　on　risk　spillovers　across　various　Chinese　stock　markets.　The　research　findings　indicate　that　both　transition　risk　and　physical　risk　significantly　influence　stock　market　risk　spillover,　demonstrating　a　suppressive　effect.　Additionally,　this　study　explored　the　testing　of　mechanisms　related　to　public　concern　about　climate,　geopolitical　risks,　the　risk　aversion　index,　epidemic　uncertainty,　and　China＇s　trade　policy　uncertainty.　It　also　examines　the　impact　of　domestic　and　international　policy　environments　and　the　dynamics　of　upward　and　downward　risk　spillovers,　revealing　significant　heterogeneity,　notably　widespread　negative　risk　spillover　effects.　Finally,　we　measured　risk　spillovers　in　stock　markets　of　varying　sizes　using　TVP-VAR-BK　and　analyzed　the　relationship　between　climate　risk　and　stock　market　risk　spillovers　with　the　causal　forest　algorithm.　We　found　that　climate　risk　significantly　suppresses　risk　spillovers　in　stock　markets　of　varying　sizes.