Revisiting the Intraseasonal Variability of Chlorophyll-a in the Adjacent Luzon Strait With a New Gap-Filled Remote Sensing Data Set

In the northern South China Sea of western Pacific Ocean during winter, clouds, sun glint, and other factors block optic sensors, leading to a high missing rate and hence a major concern in ocean color products such as the chlorophyll-a (CHL) data. These constraints inhibit the understanding of CHL variabilities at short (seasonal) scales. Here, we introduce a new gap-filling method to reconstruct data gaps in a daily CHL remote sensing product. We applied discrete cosine transform with penalized least square (DCT-PLS) approach in the adjacent Luzon Strait, yielding a 15-year full-coverage daily 4-km CHL product. Against the cross-validation set and an independent observational data set collected from 34 cruises, evaluations suggest that DCT-PLS has outperformed the widely applied classical data-interpolating empirical orthogonal function (DINEOF) method. Besides, the DCT-PLS method is characterized by more efficient computation. The complete CHL product was analyzed with a particular focus on the intraseasonal (30x2013;60 days) control on the winter bloom by the Madden-Julian Oscillation (MJO). The MJOx2019;s local signature on the CHL presents asymmetry. The CHL peaks at the late phases of MJO events, which could be explained by the relaxation after the MJO-induced wind strengthening. This gap-filling approach can be promisingly applied in other remote sensing gap-filling problems, which could shed light on the short-term variability of biological and physical dynamics in the ocean.

Automated summary

In the northern South China Sea during winter, missing data in ocean color products, such as chlorophyll-a (CHL) data, is a major concern due to factors like clouds and sun glint. In this study, a new method called DCT-PLS is introduced to reconstruct data gaps in a daily CHL remote sensing product, resulting in a 15-year full-coverage CHL product. Evaluations show that DCT-PLS outperforms the widely used DINEOF method and has more efficient computation. The complete CHL product reveals the influence of the Madden-Julian Oscillation (MJO) on the CHL intraseasonal control during the winter bloom.