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This study used MODIS observed phytoplankton absorption coefficient at 443 nm (Aph) as a preferable index to characterize phytoplankton variability in optically complex waters. Aph derived from remote sensing reflectance (Rrs, both in situ and MODIS measured) with the Quasi-Analytical Algorithm (QAA) were evaluated by comparing them with match-up in situ measurements, collected in both oceanic and nearshore waters in the Taiwan Strait (TWS). For the data with matching spatial and temporal window, it was found that the average percentage error (E) between MODIS derived Aph and field measured Aph was 33.8% (N = 30, Aph ranges from 0.012 to 0.537m-1), with a root mean square error in log space (RMSE_log) of 0.226. By comparison, E was 28.0% (N = 88, RMSE_log = 0.150) between Aph derived from ship-borne Rrs and Aph measured from water samples. However, values of e as large as 135.6% (N = 30, RMSE_log=0.383) were found between MODIS derived chlorophyll-a (Chl, OC3M algorithm) and field measured Chl. Based on these evaluation results, we applied QAA to MODIS Rrs data in the period of 2003-2009 to derive climatological monthly mean Aph for the TWS. Three distinct features of phytoplankton dynamics were identified. First, Aph is low and the least variable in the Penghu Channel, where the South China Sea water enters the TWS. This region maintains slightly higher values in winter (~ 17% higher than that in the other seasons) due to surface nutrient entrainment under winter wind-driven vertical mixing. Second, Aph is high and varies the most in the mainland nearshore water, with values peaking in summer (June-August) when fiver plumes and coastal upwelling enhance surface nutrient loads. Interannual variation of bloom intensity in Hanjiang River estuary in June is highly correlated with alongshore wind stress anomalies, as observed by QuikSCAT. The year of minimum and maximum bloom intensity is in the midst of an El Niño and a La Niña event, respectively. Third, a high Aph patch appears between April and September in the middle of the southern TWS, corresponding to high thermal frontal probabilities, as observed by MODIS. Our results support the use of satellite derived Aph for time series analyses of phytoplankton dynamics in coastal ocean regions, whereas satellite Chl products derived empirically using spectral ratio of Rrs suffer from artifacts associated with non-biotic optically active materials. [ABSTRACT FROM AUTHOR]

This study uses MODIS observed phytoplankton absorption coefficient (aph) as a preferable index of pigmentation to characterize phytoplankton variability in optically complex waters. We chose a quasi-analytical bio-optical inversion algorithm (QAA) to derive aph from remote sensing reflectance (Rrs, both in situ and MODIS measured) and then evaluated the Rrs derived aph by comparing them with match-up in situ measured aph collected in both oceanic and very nearshore waters in the Taiwan Strait (TWS). For the data with matching spatial and temporal window, it is found that the average percentage error (ϵ) between MODIS Rrs derived aph at 443nm (aph(443), ab10 breviated as Aph) and field measured Aph is 33.8% (N=30, Aph ranges from 0.012- 0.537m-1), with a root mean square error in log scale (RMSE) of 0.226. By comparison, ϵis 28.0% (N=88, RMSE=0.150) between ship-borne Rrs derived Aph and field measured Aph. Values of ϵ as large as 135.6% (N=30, RMSE=0.383) are found between MODIS Rrs derived chlorophyll-a (chl-a, OC3M algorithm) and field measured chl-a. Based on these evaluation results, we applied QAA to MODIS Rrs data between 2003-2009 to derive climatological monthly mean Aph for the TWS. Three distinct features of phytoplankton dynamics are identified. First, Aph is low and the least variable in the Penghu Channel, where the South China Sea water enters the TWS. This region maintains slightly higher values in winter (∼17% higher than that in the other seasons)due to surface nutrient entrainment under winter wind-driven vertical mixing. Second, Aph is high and the most variable in the mainland nearshore water, with values peaking in summer (June-August) when river plumes and coastal upwelling enhance surface nutrient loads. Interannual variation of bloom intensity in Hanjiang River estuary in June is highly correlated with alongshore wind stress anomalies, as observed by QuikSCAT. The year of minimum and maximum bloom intensity is in the midst of an El Nino and a La Nina event, respectively. Third, a high Aph patch appears between April and September in the middle of the Southern TWS, corresponding to high thermal frontal probabilities, as observed by MODIS. Our results support the use of satellite observed Aph for time series analyses of phytoplankton dynamics in coastal ocean regions, where satellite chl-a retrievals can suffer from artifacts associated with non-biotic optically active materials. [ABSTRACT FROM AUTHOR]