The typhoon Wind-Pump induced upwelling and cold eddy often promote the significant growth of phytoplankton after the typhoon. However, the importance of eddy-pumping and wind-driven upwelling on the sea surface chlorophyll a concentration (Chl-a) during the typhoon are still not clearly distinguished. In addition, the air–sea heat flux exchange is closely related to the upper ocean processes, but few studies have discussed its role in the sea surface Chl-a variations under typhoon conditions. Based on the cruise data, remote sensing data, and model data, this paper analyzes the contribution of the vertical motion caused by the eddy-pumping upwelling and Ekman pumping upwelling on the surface Chl-a, and quantitatively analyzes the influence of air–sea heat exchange on the surface Chl-a after the typhoon Linfa over the northeastern South China Sea (NSCS) in 2009. The results reveal the Wind Pump impacts on upper ocean processes: (1) The euphotic layer-integrated Chl-a increased after the typhoon, and the increasing of the surface Chl-a was not only the uplift of the deeper waters with high Chl-a but also the growth of the phytoplankton; (2) The Net Heat Flux (air–sea heat exchange) played a major role in controlling the upper ocean physical processes through cooling the SST and indirectly increased the surface Chl-a until two weeks after the typhoon; (3) the typhoon-induced cyclonic eddy was the most important physical process in increasing the surface Chl-a rather than the Ekman pumping and wind-stirring mixing after typhoon; (4) the spatial shift between the surface Chl-a blooms and the typhoon-induced cyclonic eddy could be due to the Ekman transport; (5) nutrients uplifting and adequate light were two major biochemical elements supplying for the growth of surface phytoplankton.

New evidences provided that the tropical cyclone (TC) Linfa in 2015 induced looping path of Kuroshio invasion into the northeastern South China Sea (NESCS) through the northwestern Luzon Strait (LS), based on the in-situ measurements, satellite data and model output data. This TC-enhanced Kuroshio invasion with low nutrients and denser waters suppressed the TC "Wind Pump" induced upwelling and nutrients uptake, and therefore inhibited the Chlorophyll a concentration (Chl-a) increase from surface to ~50 m in the open ocean of the NESCS. The TC-induced Kuroshio invasion promoted the generation of the strong cyclonic eddy to its left side where weak Ekman Pumping Velocity was observed. This enhancing cyclonic eddy then dominated the nutrients uplift and increased the surface and subsurface (0-50 m) Chl-a through eddy pumping rather than Ekman Pumping. The TC-declined anti-cyclonic eddy, which shoaled the Mixed Layer Depth (MLD), benefited to the nutrient uptake through TC-induced upwelling and thereby increased the surface Chl-a and raised the Chl-a Maximum Layer (CML) to ~20 m over the southwestern LS. The temporal Chl-a variations were also influenced by TC intensities and biochemical processes. The air-sea heat budget analysis indicated that, the air-sea heat exchange contributed to nearly 80% of the sea surface cooling (SST cooling) over the northwestern LS with Kuroshio invasion, while eddy-induced upwelling dominated the SST cooling over the western LS, and the wind-driven upwelling (and mixing) controlled the SST cooling over the southwestern LS. These different formations of SST cooling then played important role in Chl-a variations. This study is the first case of TC "Wind Pump" induced Chl-a variations considering air-sea heat exchange, Kuroshio invasion and mesoscale eddies over LS, which would help to evaluate the influence of TCs over the other major heat transport arteries of the world ocean: The Gulf Stream area.

In this paper we use data from the Hyperspectral Imager for the Coastal Ocean (HICO, NASA) hyperspectral satellite sensor to identify and qualitatively estimate the content of cyanobacteria (CB) in the coastal waters of the Black and Azov seas. Three data processing algorithms are applied: two use a spectrum shape analysis and one is semianalytical. The first algorithm uses the determination of the minimum of the reflection coefficient spectrum for remote sensing in the spectral region of ~680 nm, the so-called CB presence index. Based on this algorithm, a second was developed to identify the presence of phycocyanin in water, which is a marker pigment for CB. The second algorithm analyzes the minimum of the reflectance spectrum for remote sensing (Rrs) in the region of 620 nm. The third semianalytical algorithm makes it possible to determine the concentration of phycocyanin. The results of automatic identification of the presence of the CB were compared with the visual analysis of the spectra. The results of applying three algorithms to images are compared. It is concluded that phycocyanin is present in the studied water areas and its presence is a consequence of the presence of CB.

Исследование временной изменчивости структуры фитопланктонного сообщества в Южно-Китайском море по спутниковым данным на различных временных масштабах