Remote Sensing for Ocean Primary Productivity and Its Spatio-temporal Variability in the China Seas
中国近海初级生产力的遥感研究及其时空演化

The spatial and temporal variability of ocean primary productivity in the China seas from 2003 to 2005 was estimated by size-fractionated primary productivity model. Satellite primary productivity 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 at the Bohai Sea, the northern Yellow Sea (YS), the southern YS, the northern East China Sea (ECS), the southern ECS, and the South China Sea (SCS), respectively. Peaks of primary productivity appeared twice, in spring (April to 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. Two peaks of primary productivity also appeared in the SCS, one was in winter (January) and the other in summer (August), and the peak in winter was far higher than that in summer. The monthly averaged primary productivity from 2003 to 2005 in the Bohai Sea and southern YS was higher than that in the other four areas during most months, while that in the southern ECS and SCS was lower than that in the other four areas the whole year. The primary productivity during spring period (March to June in the southern ECS and April to July in the other five sea areas) contributed about 41% on average to the annual primary productivity in the above five areas except SCS. Furthermore, satellite primary productivity during that period showed an interannual variability that was also the largest, and the averaged standard deviation was 6.68. Meanwhile, the contribution during fall period (October to January in the southern ECS and August to November in other sea areas) was about 33% on average; and the primary productivity during this period also showed an interannual variability. However, in SCS, the contribution during winter period (December to March) was the highest (about 42%), while that during spring period (April to July) was the lowest (28%). But SCS and the other five areas have one thing in common: the larger the contribution, the larger the interannual variability.