By　regarding　the　Chinese　financial　and　economic　sectors　as　a　system,　this　article　studies　the　stock　volatility　spillover　in　the　system　and　explores　its　effects　on　the　overall　performance　of　the　macroeconomy　in　China.　The　recent　outbreak　of　COVID-19,　U.S.-China　trade　friction,　and　three　historical　financial　turbulences　are　involved　to　distinguish　the　changes　in　the　spillover　in　these　distinct　crises,　which　has　seldom　been　unveiled　in　the　literature.　By　considering　that　the　stock　volatility　spillover　may　vary　over　distinct　timescales,　the　spillovers　are　disclosed　through　innovatively　constructing　the　multi-scale　spillover　networks,　followed　by　connectedness　computation,　based　on　variational　mode　decomposition　(VMD)　and　generalized　vector　autoregression　(GVAR)　process.　Our　empirical　analysis　first　demonstrates　the　different　levels　of　increases　in　the　total　sectoral　volatility　spillover　and　changes　in　the　roles　of　the　sectors　in　the　system　under　the　aforementioned　crises.　Besides,　the　increases　in　the　sectoral　spillover　in　the　long-term　are　verified　to　negatively　impact　the　macroeconomy　and　can　thereby　act　as　warning　signals.