Long-term continuous monitoring of the diffuse attenuation coefficient at 490 nm from global oceans using combined SeaWiFS and MODISA data

Abstract

ABSTRACT To enhance the long-term monitoring ability of multi-sourced remote sensing data, we needed to minimize the inter-mission biases between the data retrieved from different satellites. We evaluated three existing diffuse attenuation coefficients at 490 nm (K d(490)) using nine independent datasets collected from the global oceans. The results indicate that the updated neural network-based four-band K d(490) retrieval model (updated-NFKM) decreased the uncertainty by > 4% from the NASA official K d(490) retrieval model (NOKM) and the inherent optical properties-based K d(490) retrieval model (IOPK). Specifically, matchup analysis showed that the updated-NFKM model produced < 40% uncertainty in deriving K d(490) from MODISA and SeaWiFS data, and the uncertainty of SeaWiFS-predicted K d(490) was ~ 5% lower than the MODISA-predicted K d(490). Using the updated-NFKM model, >80% of the global ocean had an uncertainty for K d(490) estimates that were lower than 30%, while the model performed much better for the Western Pacific, Arctic Ocean, and Northern Atlantic compared to the Eastern Pacific, South Ocean, and Southern Atlantic. To enable a naturally smooth transition from SeaWiFS to MODISA-observed K d(490) products, it was critical to cross-calibrate the inter-mission difference. The results show that using the cross-calibration models proposed in this study, the MODISA-predicted K d(490) accounted for > 86% of the variations of SeaWiFS-predicted K d(490), even though the empirical coefficients of the cross-calibration model had to be adjusted according to the time scales of the composite remote sensing data. Finally, we used the cross-calibration model to minimize the time series of SeaWiFS and MODISA-predicted K d(490) data. Our results indicate that the K d(490) values gradually increased in the low-latitude regions during past two decades.