Influence of atmospheric dust deposition on sinking particle flux in the northwest Pacific

We examined the flux and composition of sinking particles collected at a water depth of 800 m in the northwest Pacific from November 2017 to August 2018 to assess the impact of dust deposition on organic carbon export. The fluxes of total particulate matter and particulate organic carbon averaged over the study period were 88 ± 63 mg m-2 d-1 and 9.0 ± 5.8 mg m−2 d−1, respectively. Biogenic particles accounted for 82% of the sinking particles, on average. There were two notable pulses in the particle fluxes of both biogenic and lithogenic material in February and May 2018. These flux peaks were decoupled from net primary production in the surface waters but coincided with intervals of high rates of atmospheric dust deposition. The biogenic component of the two peaks was dominated by two different phytoplankton communities, which may have influenced carbon export efficiency. Correlations between the sinking particle flux and the lithogenic flux are found at several locations in the northwest Pacific, implying that East Asian dust deposition has a prevalent influence on the biological pump. Attention should be paid to the effects of changes in the continental dust supply to the oceans on oceanic carbon export

Assessment and Improvement of Global Gridded Sea Surface Temperature Datasets in the Yellow Sea Using In Situ Ocean Buoy and Research Vessel Observations

The sea surface temperature (SST) is essential data for the ocean and atmospheric prediction systems and climate change studies. Five global gridded sea surface temperature products were evaluated with independent in situ SST data of the Yellow Sea (YS) from 2010 to 2013 and the sources of SST error were identified. On average, SST from the gridded optimally interpolated level 4 (L4) datasets had a root mean square difference (RMSD) of less than 1 °C compared to the in situ observation data of the YS. However, the RMSD was relatively high (2.3 °C) in the shallow coastal region in June and July and this RMSD was mostly attributed to the large warm bias (>2 °C). The level 3 (L3) SST data were frequently missing in early summer because of frequent sea fog formation and a strong (>1.2 °C/12 km) spatial temperature gradient across the tidal mixing front in the eastern YS. The missing data were optimally interpolated from the SST observation in offshore warm water and warm biased SST climatology in the region. To fundamentally improve the accuracy of the L4 gridded SST data, it is necessary to increase the number of SST observation data in the tidally well mixed region. As an interim solution to the warm bias in the gridded SST datasets in the eastern YS, the SST climatology for the optimal interpolation can be improved based on long-term in situ observation data. To reduce the warm bias in the gridded SST products, two bias correction methods were suggested and compared. Bias correction methods using a simple analytical function and using climatological observation data reduced the RMSD by 19–29% and 37–49%, respectively, in June