Inversion Of Ocean Transparency And Its Merging From Multiple Missions

The ocean transparency can directly reflect the turbidity of water, and the level ofabsorption and scattering of seawater for light, so it’s an important physical quantityfor describing the optical properties of seawater. Study of the temporal and spatialdistribution of ocean transparency has great significance on monitoring of ocean waterquality and underwater military activities. Remote-sensing data from satellites haswide spatial coverage compared to the traditional measurement method, and the oceantransparency with high temporal and spatial resolution can be easily retrieved from it.Due to the influence of cloud and limitation of the scanning field of view by singlesatellite sensor, in order to improve the spatial coverage and reliability of the retrievedquantity, it’s necessary to merge ocean color data from multiple sensors. Meanwhile,the long temporal continuous observation about ocean transparency can beimplemented by merging from multiple missions.The empirical inversion algorithm of ocean transparency about northwest Pacificocean is developed in this paper, which is based on in-situ measured Secchi depth andremote-sensing reflectance. This empirical algorithm is compared withsemi-analytical algorithm, and then, the applicability of the different inversionalgorithm is also discussed. The results show the empirical inversion algorithm has ahigh correlation with the in-situ measured Secchi depth, so the empirical algorithmwas applied in this paper to retrieve ocean transparency in the northwest Pacificocean.For data merging, the Level2data from four satellite sensors were used in thispaper, SeaWiFS, MODIS-Terra, MODIS-Aqua, and MERIS. In order to keepconsistent among these sensors, the relevant cross-calibration and resampling wasapplied.The two data merging method were used in this paper, Averaging(AV) Algorithmand Optimal Interpolation(OI) Algorithm. Then the monthly merged data weregenerated and validated. The validation results showed the merged products have alarge coverage and high reliability, the temporal and spatial distribution characteristicof ocean transparency in the northwest Pacific ocean can be well revealed from theocean transparency merged data.