The spatial and temporal variability of primary productivity in the China seas from 2003 to 2005 was estimated using a size-fractionated primary productivity model. Primary productivity estimated from satellite-derived data showed spatial and temporal variability. Annual averaged primary productivity levels were 564.39, 363.08, 536.47, 413.88, 195.77, and 100.09 gCm-2a-1 in the Bohai Sea, northern Yellow Sea (YS), southern YS, northern East China Sea (ECS), southern ECS, and South China Sea (SCS), respectively. Peaks of primary productivity appeared in spring (April–June) and fall (October and November) in the northern YS, southern YS, and southern ECS, while a single peak (June) appeared in the Bohai Sea and northern ECS. The SCS had two peaks in primary productivity, but these peaks occurred in winter (January) and summer (August), with the winter peak far higher than the summer peak. Monthly averaged primary productivity values from 2003 to 2005 in the Bohai Sea and southern YS were higher than those in the other four seas during most months, while those in the southern ECS and SCS were the lowest. Primary productivity in spring (March–June in the southern ECS and April–July in the other five areas) contributed approximately 41% on average to the annual primary productivity in all the study seas except the SCS. The largest interannual variability also occurred in spring (average standard deviation = 6.68), according to the satellite-derived estimates. The contribution during fall (October–January in the southern ECS and August–November in the other five areas) was approximately 33% on average; the primary productivity during this period also showed interannual variability. However, in the SCS, the winter (December–March) contribution was the highest (about 42%), while the spring (April–July) contribution was the lowest (28%). The SCS did share a feature with the other five areas: the larger the contribution, the larger the interannual variability. Spatial and temporal variability of satellite-derived ocean primary productivity may be influenced by physicochemical environmental conditions, such as the chlorophyll-a concentration, sea surface temperature, photosynthetically available radiation, the seasonally reversed monsoon, river discharge, upwelling, and the Kuroshio and coastal currents. The spatial and temporal variability of primary productivity in the China seas from 2003 to 2005 was estimated using a size-fractionated primary productivity model. Primary productivity estimated from satellite-derived data showed spatial and temporal variability. Annual average primary productivity levels were 564.39, 363.08 , 536.47, 413.88, 195.77, and 100.09 gCm-2a-1 in the Bohai Sea, northern Yellow Sea (YS), southern YS, northern East China Sea (ECS), southern ECS, and South China Sea (SCS) Peaks of primary force appeared in spring (April-June) and fall (October and November) in the northern YS, southern YS, and southern ECS, while a single peak (June) appeared in the Bohai Sea and northern ECS. The SCS had two peaks in primary productivity, but these peaks occurred in winter (January) and summer (August), with the winter peak far higher than the summer peak. Monthly average primary productivity values ​​from 2003 to 2005 in the Bohai Sea and southern YS we re higher than those in the other four seas during most months, while those in the southern ECS and SCS were the lowest. Primary productivity in spring (March-June in the southern ECS and April-July in the other five areas) only approximately 41 The largest interannual variability also occurred in spring (average standard deviation = 6.68), according to the satellite-derived estimates. The contribution during fall (October-January in the southern ECS and August-November in the other five areas) was approximately 33% on average; the primary productivity during this period also showed interannual variability. However, in the SCS, the winter (December-March) contribution was the highest 42%), while the spring (April-July) contribution was the lowest (28%). The SCS did share a feature with the other five areas: the larger the contribution, the larger the interannual variability. S patial and temporal variability of satellite-derived ocean primary productivity may be influenced by physicochemical environmental conditions, such as the chlorophyll-a concentration, sea surface temperature, photosynthetically available radiation, the seasonallyllyl, monsoon, river discharge, upwelling, and the Kuroshio and coastal currents.