Guimei Liu

Seasonal variation of eddy kinetic energy in the South China Sea

Mesoscale eddy activity and its modulation mechanism in the South China Sea (SCS) are investigated with newly reprocessed satellite altimetry observations and hydrographic data. The eddy kinetic energy (EKE) level of basin-wide averages show a distinct seasonal cycle with the maximum in August–December and the minimum in February–May. Furthermore, the seasonal pattern of EKE in the basin is dominated by region offshore of central Vietnam (OCV), southwest of Taiwan Island (SWT), and southwest of Luzon (SWL), which are also the breeding grounds of mesoscale eddies in the SCS. Instability theory analysis suggests that the seasonal cycle of EKE is modulated by the baroclinic instability of the mean flow. High eddy growth rate (EGR) is found in the active eddy regions. Vertical velocity shear in the upper 50–500 m is crucial for the growth of baroclinic instability, leading to seasonal EKE evolution in the SCS.

Seasonal variations of phytoplankton phosphorus stress in the Yellow Sea Cold Water Mass

The Yellow Sea is located between the China Mainland and the Korean Peninsula, representing a typical shallow epicontinental sea. The Yellow Sea Cold Water Mass (YSCWM) is one of the most important physical features in the Yellow Sea. The characteristics of vertical profiles and seasonal variations of biogenic elements in the YSCWM may lead the variations of nutrient availability (e.g., phosphorus) and phosphorus stress of phytoplankton. In this study, the authors surveyed the seasonal variations of phytoplankton phosphorus stress with emphasis on the effect of the YSCWM during the four cruises in April and October 2006, March and August 2007. Using both bulk and single-cell alkaline phosphatase activity (APA) assays, this study evaluated phosphorus status of phytoplankton community, succession of phytoplankton community and ecophysiological responses of phytoplankton to phosphorus in the typical region of the YSCWM. With the occurrence of the YSCWM, especially the variations of concentration of dissolved inorganic phosphorus (DIP), the results of bulk APA appeared corresponding seasonal variations. Along Transects A and B, the mean APA in August was the highest, and that in March was the lowest. According to the ELF-labeled assay’s results, seasonal variations of the ELF-labeled percentages within dominant species indicated that diatoms were dominant in March, April and October, while dinoflagellates were dominant in August. During the four cruises, the ELF-labeled percentages of diatoms except Paralia sulcata showed that diatoms were not phosphorus deficient in April 2006 at all, but suffered from severe phosphorus stress in August 2007. In comparison, the ELF-labeled percentages of dinoflagellates were all above 50% during the four time series, which meant dinoflagellates such as Alexandrium and Scrippsiella, sustained perennial phosphorus stress.

Role of Ekman transport versus Ekman pumping in driving summer upwelling in the South China Sea

Relative roles of Ekman transport and Ekman pumping in driving summer upwelling in the South China Sea (SCS) are examined using QuikSCAT scatterometer wind data. The major upwelling regions in the SCS are the coastal regions east and southeast of Vietnam (UESEV), east and southeast of Hainan Island (UESEH), and southeast of Guangdong province (USEG). It is shown that the Ekman transport due to alongshore winds and Ekman pumping due to offshore wind stress curl play different roles in the three upwelling systems. In UESEV, Ekman pumping and Ekman transport are equally important in generating upwelling. The Ekman transport increases linearly from 0.49 Sv in May to 1.23 Sv in August, while the Ekman pumping increases from 0.36 to 1.22 Sv during the same period. In UESEH, the mean estimates of Ekman transport and Ekman pumping are 0.14 and 0.07 Sv, respectively, indicating that 33% of the total wind-driven upwelling is due to Ekman pumping. In USEG, the mean Ekman transport is 0.041 Sv with the peak occurring in July, while Ekman pumping is much smaller (0.003 on average), indicating that the upwelling in this area is primarily driven by Ekman transport. In the summers of 2003 and 2007 following El Niño-Southern Oscillation (ENSO) events, both Ekman transport and Ekman pumping decrease in UESEV due to the abnormally weak southwest monsoon. During the same events, however, Ekman transport is slightly enhanced and Ekman pumping is weakened in UESEH and USEG.

Spatio-temporal variability of chlorophyll a and its responses to sea surface temperature, winds and height anomaly in the western South China Sea

To understand the response of marine ecosystem to environmental factors, the oceanographic (physical and biochemical) data are analyzed to examine the spatio-temporal distributions of chlorophyll a (Chl a) associatedwith surface temperature, winds and height anomaly for long periods (1997–2008) in the western South China Sea (SCS). The results indicate that seasonal and spatial distributions of Chl a are primarily influenced bymonsoon winds and hydrography. A preliminary Empirical Orthogonal Function (EOF) analysis of remotely sensed data is used to assess basic characteristics of the response process of Chl a to physical changes, which reveals interannual variability of anomalous low Chl a values corresponding to strong El Niño (1997–1998), high values corresponding to strong La Niña (1999–2000), low Chl a corresponding to moderate El Niño (2001–2003), upward Chl a after warm event in 2005 off the east coast of Vietnam. The variability of Chl a in nearshore and the Mekong River Estuary (MER) waters also suggests its response to these warm or cold processes. Considering the evidence for covariabilities between Chl a and sea surface temperature, winds, height anomaly (upwelling or downwelling), cold waters input and strong winds mixing may play important roles in the spatial and temporal variability of high Chl a. Such research activities could be very important to gain amechanistic understanding of ecosystemresponses to the climate change in the SCS.

Assimilating the along-track sea level anomaly into the regional ocean modeling system using the ensemble optimal interpolation

The ensemble optimal interpolation (EnOI) is applied to the regional ocean modeling system (ROMS) with the ability to assimilate the along-track sea level anomaly (TSLA). This system is tested with an eddy-resolving system of the South China Sea (SCS). Background errors are derived from a running seasonal ensemble to account for the seasonal variability within the SCS. A fifth-order localization function with a 250 km localization radius is chosen to reduce the negative effects of sampling errors. The data assimilation system is tested from January 2004 to December 2006. The results show that the root mean square deviation (RMSD) of the sea level anomaly decreased from 10.57 to 6.70 cm, which represents a 36.6% reduction of error. The data assimilation reduces error for temperature within the upper 800 m and for salinity within the upper 200 m, although error degrades slightly at deeper depths. Surface currents are in better agreement with trajectories of surface drifters after data assimilation. The variance of sea level improves significantly in terms of both the amplitude and position of the strong and weak variance regions after assimilating TSLA. Results with AGE error (AGE) perform better than no AGE error (NoAGE) when considering the improvements of the temperature and the salinity. Furthermore, reasons for the extremely strong variability in the northern SCS in high resolution models are investigated. The results demonstrate that the strong variability of sea level in the high resolution model is caused by an extremely strong Kuroshio intrusion. Therefore, it is demonstrated that it is necessary to assimilate the TSLA in order to better simulate the SCS with high resolution models.

Assimilating operational SST and sea ice analysis data into an operational circulation model for the coastal seas of China

The prediction of sea surface temperature (SST) is an essential task for an operational ocean circulation model. A sea surface heat flux, an initial temperature field, and boundary conditions directly affect the accuracy of a SST simulation. Here two quick and convenient data assimilation methods are employed to improve the SST simulation in the domain of the Bohai Sea, the Yellow Sea and the East China Sea (BYECS). One is based on a surface net heat flux correction, named as Qcorrection (QC), which nudges the flux correction to the model equation; the other is ensemble optimal interpolation (EnOI), which optimizes the model initial field. Based on such two methods, the SST data obtained from the operational SST and sea ice analysis (OSTIA) system are assimilated into an operational circulation model for the coastal seas of China. The results of the simulated SST based on four experiments, in 2011, have been analyzed. By comparing with the OSTIA SST, the domain averaged root mean square error (RMSE) of the four experiments is 1.74, 1.16, 1.30 and 0.91°C, respectively; the improvements of assimilation experiments Exps 2, 3 and 4 are about 33.3%, 25.3%, and 47.7%, respectively. Although both two methods are effective in assimilating the SST, the EnOI shows more advantages than the QC, and the best result is achieved when the two methods are combined. Comparing with the observational data from coastal buoy stations, show that assimilating the high-resolution satellite SST products can effectively improve the SST prediction skill in coastal regions.

Chlorophyll a increase induced by surface winds in the northern South China Sea

The response of chlorophyll a (Chl a) concentration to wind stress is analyzed in the South China Sea (SCS), using in-situ data of Chl a and remote sensing data (QuikScat-sea surface wind (SSW), AVHRR-sea surface temperature (SST), AVISO merged-sea level anomalies (SLA), SeaWiFS-derived Chl a and MODIS Terra-derived Chl a) in August/September/October 2004, 2006 and 2009. The variability of SSW, SST and SLA 7 d before in-situ Chl a sampling (including the work day of in-situ Chl a sampling) with the same latitude and longitude of the study area are investigated, and the correlation coefficients are calculated between these hydrographic factors and in-situ Chl a concentration. The results show that the Chl a-SSW correlation coefficients at upper layers (such as 0 m and 25 m) are more significant than those at deeper layers (such as 50, 75 and 100 m) 1–3 d before, which indicates that there is a time lag of strong surface winds stimulating phytoplankton bloom. By analyzing the relationship among the daily remote sensing derived (RSderived) SSW, SST, SLA and 3 d averaged SeaWiFS/MODIS-derived Chl a concentration in the northern SCS in September 2004 and 2009 respectively, it shows that the intensity and speed of surface winds could have great influence on extend of Chl a increase. If surface winds reach 4–5 m/s over, Chl a concentration would increase 1–3 d after the process of strong surface winds in open sea area of the northern SCS mainly during September.

Temporal and spatial variability of the carbon cycle in the east of China’s seas: a three-dimensional physical-biogeochemical modeling study

AbstractIn the east of China’s seas, there is a wide range of the continental shelf. The nutrient cycle and the carbon cycle in the east of China’s seas exhibit a strong variability on seasonal to decadal time scales. On the basis of a regional ocean modeling system (ROMS), a three dimensional physical-biogeochemical model including the carbon cycle with the resolution (1/12)°×(1/12)° is established to investigate the physical variations, ecosystem responses and carbon cycle consequences in the east of China’s seas. The ROMS-Nutrient Phytoplankton Zooplankton Detritus (NPZD) model is driven by daily air-sea fluxes (wind stress, long wave radiation, short wave radiation, sensible heat and latent heat, freshwater fluxes) that derived from the National Centers for Environmental Prediction (NCEP) reanalysis2 from 1982 to 2005. The coupled model is capable of reproducing the observed seasonal variation characteristics over the same period in the East China Sea. The integrated air-sea CO2 flux over the entire east of China’s seas reveals a strong seasonal cycle, functioning as a source of CO2 to the atmosphere from June to October, while serving as a sink of CO2 to the atmosphere in the other months. The 24 a mean value of airsea CO2 flux over the entire east of China’s seas is about 1.06 mol/(m2·a), which is equivalent to a regional total of 3.22 Mt/a, indicating that in the east of China’s seas there is a sink of CO2 to the atmosphere. The partial pressure of carbon dioxide in sea water in the east of China’s seas has an increasing rate of 1.15 μatm/a (1μtm/a=0.101 325 Pa), but pH in sea water has an opposite tendency, which decreases with a rate of 0.001 3 a–1 from 1982 to 2005. Biological activity is a dominant factor that controls the

Comparison of air-sea CO2 flux and biological productivity in the South China Sea, East China Sea, and Yellow Sea: a three-dimensional physical-biogeochemical modeling study

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