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The spatial and temporal resolutions of contemporary microwave-based sea surface salinity (SSS) measurements are insufficient. Thus, we developed a gap-free gridded daily SSS product with higher spatial and temporal resolutions, which can provide information on short-term variability in the East China Sea (ECS), such as the front changes by Changjiang diluted water (CDW). Specifically, we conducted gap-filling for daily SSS products based on the Geostationary Ocean Color Imager (GOCI) with a spatial resolution of 1 km (0.01°), using a machine learning approach during the summer seasons from 2015 to 2019. The comparison of the Soil Moisture Active Passive (SMAP), Copernicus Marine Environment Monitoring Service (CMEMS), and Hybrid Coordinate Ocean Model (HYCOM) SSS products with the GOCI-derived SSS over the entire SSS range showed that the SMAP SSS was highly consistent, whereas the HYCOM SSS was the least consistent. In the < 31 psu range, the SMAP SSS was still the most consistent with the GOCI-derived SSS (R2=0.46; root mean squared error: RMSE = 2.41 psu); in the > 31 psu range, the CMEMS and HYCOM SSS products showed similar levels of agreement with that of the SMAP SSS. We trained and tested three machine learning models – the fine trees, boosted trees, and bagged trees models – using the daily GOCI-derived SSS as output, including the three SSS products, environmental variables, and geographical data. We combined the three SSS products to construct input datasets for machine learning. Using the test dataset, the bagged trees model showed the best results (mean R2=0.98 and RMSE = 1.31 psu), and the models that used the SMAP SSS as input had the highest level. For the dataset in the > 31 psu range, all the models exhibited similarly reasonable performances (RMSE = 1.25–1.35 psu). The comparison with in situ SSS data, time series analysis, and the spatial SSS distribution derived from models showed that all the models had proper CDW distributions with reasonable RMSE levels (0.91–1.56 psu). In addition, the CDW front derived from the model gap-free daily SSS product clearly demonstrated the daily oceanic mechanism during the summer season in the ECS at a detailed spatial scale. Notably, the CDW front in the zonal direction, as captured by the Ieodo Ocean Research Station (I-ORS), moved approximately 3.04 km d−1 in 2016, which is very fast compared with the cases in other years. Our model yielded a gap-free gridded daily SSS product with reasonable accuracy and enabled the successful recognition of daily SSS fronts at the 1 km level, which was previously not possible with ocean color data. Such successful application of machine learning models can further provide useful information on the long-term variation of daily SSS in the ECS. The gridded gap-free SSS dataset at 0.01°×0.01° spatial resolution is freely available at https://doi.org/10.22808/DATA-2023-2 (Shin et al., 2023).

During the Late Pleistocene–Holocene, the Ross Sea Ice Shelf exhibited strong spatial variability in relation to the atmospheric and oceanographic climatic variations. Despite being thoroughly investigated, the timing of the ice sheet retreat from the outer continental shelf since the Last Glacial Maximum (LGM) still remains controversial, mainly due to a lack of sediment cores with a robust chronostratigraphy. For this reason, the recent recovery of sediments containing a continuous occurrence of calcareous foraminifera provides the important opportunity to create a reliable age model and document the early deglacial phase in particular. Here we present a multiproxy study from a sediment core collected at the Hallett Ridge (1800 m of depth), where significant occurrences of calcareous planktonic and benthic foraminifera allow us to document the first evidence of the deglaciation after the LGM at about 20.2 ka. Our results suggest that the co-occurrence of large Neogloboquadrina pachyderma tests and abundant juvenile forms reflects the beginning of open-water conditions and coverage of seasonal sea ice. Our multiproxy approach based on diatoms, silicoflagellates, carbon and oxygen stable isotopes on N. pachyderma, sediment texture, and geochemistry indicates that abrupt warming occurred at approximately 17.8 ka, followed by a period of increasing biological productivity. During the Holocene, the exclusive dominance of agglutinated benthic foraminifera suggests that dissolution was the main controlling factor on calcareous test accumulation and preservation. Diatoms and silicoflagellates show that ocean conditions were variable during the middle Holocene and the beginning of the Neoglacial period at around 4 ka. In the Neoglacial, an increase in sand content testifies to a strengthening of bottom-water currents, supported by an increase in the abundance of the tycopelagic fossil diatom Paralia sulcata transported from the coastal regions, while an increase in ice-rafted debris suggests more glacial transport by icebergs.