No abstract

Chlorophyll a (Chl) concentrations derived from satellite measurements have been used in oceanographic research, for example to interpret eco-responses to environmental changes on global and regional scales. However, it is unclear how existing Chl products compare with each other in terms of accuracy and consistency in revealing temporal and spatial patterns, especially in the optically complex marginal seas. In this study, we examined three MODIS Chl data products that have been made available to the community by the US NASA using community-accepted algorithms and default parameterization. These included the products derived from the OC3M, GSM and GIOP algorithms. We compared their temporal variations and spatial distributions in the South China Sea. We found that the three products appeared to capture general features such as unique winter peak at the Southeast Asian Time-series Study station (SEATS, 18° N, 116° E), strong upwelling induced bloom off the Vietnam and the Pearl River plume associated bloom in summer, their absolute magnitude, however, may be questionable. Further error statistics using field measured Chl as the truth demonstrated that the three MODIS Chl products may contain high degree of uncertainties in the study region. Root mean square error (RMSE) of the products from OC3M and GSM (on a log scale) was about 0.4 and average percentage error (ε) was ~150% (Chl between 0.03–7.67 mg m^–3, n = 63). In contrast, the GIOP with default parameterization led to higher errors (ϵ = 349%). This study thus advocates more careful interpretation of Chl spatio-temporal variations when using standard Chl products, and also points to the need of local tuning of algorithm parameterization for the study region