Research　on　how　terrestrial　ecosystems　respond　to　climate　change　can　reveal　the　complex　interactions　between　vegetation　and　climate.　net　primary　productivity　(NPP),　an　important　vegetation　parameter　and　ecological　indicator,　fluctuates　within　any　given　ecological　environment　or　regional　carbon　budget.　In　this　study,　spatial　interpolation　was　used　to　generate　a　spatial　dataset,　with　1-km　spatial　resolution,　with　meteorological　data　from　736　observation　stations　across　China.　An　improved　CASA　model　was　used　to　simulate　NPP　over　the　period　of　2001-2013　by　taking　into　account　land-cover　change　in　every　year　during　the　same　period.　We　propose　the　gridbased　spatial　patterns　and　dynamics　of　annual　NPP,　annual　average　temperature,　and　annual　total　precipitation　based　on　the　model.　We　also　used　the　model　to　demonstrate　the　spatial　correlation　between　NPP,　temperature,　and　precipitation　in　the　study　area　with　special　focus　on　the　impact　of　climate　change　in　the　early　21st　century.　Results　showed　that　the　spatial　pattern　of　NPP　over　all　of　China　is　characterized　by　higher　values　in　the　southeast　and　lower　values　in　the　northwest.　The　spatial　pattern　of　temperature　indicates　substantial　latitudinal　differences　across　the　country,　and　the　spatial　pattern　of　precipitation　shows　a　ribbon　of　decline　from　the　southeast　coast　to　the　northwest　inland.　Most　areas　show　an　upward　trend　in　NPP.　Temperatures　appear　to　decrease　across　the　country　during　the　global　warming　hiatus　(1998-2008),　and　are　accompanied　by　an　increase　in　precipitation　over　most　regions.　The　correlation　between　NPP　and　annual　average　temperature　is　weak.　Alternatively,　NPP　and　annual　total　precipitation　are　positively　correlated　in　northern　and　central　China　at　a　coefficient　above　0.64　(p　＜　0.01)　yet　negatively　correlated　in　the　eastern　parts　of　the　Qinghai-　Tibet　Plateau　and　Sichuan　Basin.　Results　can　provide　useful　information　for　improving　parameters　for　calibration　of　the　terrestrial　ecosystem　process　model.