Dynamics of intraseasonal sea level and thermocline variability in the equatorial Atlantic during 2002-03

Satellite and in situ observations in the equatorial Atlantic Ocean during 2002-03 show dominant spectral peaks at 40-60 days and secondary peaks at 10-40 days in sea level and thermocline within the intraseasonal period band (10-80 days). A detailed investigation of the dynamics of the intraseasonal variations is carried out using an ocean general circulation model, namely, the Hybrid Coordinate Ocean Model (HYCOM). Two parallel experiments are performed in the tropical Atlantic Ocean basin for the period 2000-03: one is forced by daily scatterometer winds from the Quick Scatterometer (QuikSCAT) satellite together with other forcing fields, and the other is forced by the low-passed 80-day version of the above fields. To help in understanding the role played by the wind-driven equatorial waves, a linear continuously stratified ocean model is also used. Within 3 degrees S-3 degrees N of the equatorial region, the strong 40-60-day sea surface height anomaly (SSHA) and thermocline variability result mainly from the first and second baroclinic modes equatorial Kelvin waves that are forced by intraseasonal zonal winds, with the second baroclinic mode playing a more important role. Sharp 40-50-day peaks of zonal and meridional winds appear in both the QuikSCAT and Pilot Research Moored Array in the Tropical Atlantic (PIRATA) data for the period 2002-03, and they are especially strong in 2002. Zonal wind anomaly in the central-western equatorial basin for the period 2000-06 is significantly correlated with SSHA across the equatorial basin, with simultaneous/ lag correlation ranging from-0.62 to 0.74 above 95% significance. Away from the equator (3 degrees-5 degrees N), however, sea level and thermocline variations in the 40-60-day band are caused largely by tropical instability waves (TIWs). On 10-40-day time scales and west of 10 degrees W, the spectral power of sea level and thermocline appears to be dominated by TIWs within 5 degrees S-5 degrees N of the equatorial region. The wind-driven circulation, however, also provides a significant contribution. Interestingly, east of 10 W, SSHA and thermocline variations at 10 40- day periods result almost entirely from wind-driven equatorial waves. During the boreal spring of 2002 when TIWs are weak, Kelvin waves dominate the SSHA across the equatorial basin (2 degrees S-2 degrees N). The observed quasi-biweekly Yanai waves are excited mainly by the quasi-biweekly meridional winds, and they contribute significantly to the SSHA and thermocline variations in 1 degrees-5 degrees N and 1 degrees-5 degrees S regions.

The variability of eddy kinetic energy in the South China Sea deduced from satellite altimeter data

We used fifteen years (1993-2007) of altimetric data, combined from different missions (ERS-1/2, TOPEX/Poseidon, Jason-1, and Envisat), to analyze the variability of the eddy kinetic energy (EKE) in the South China Sea (SCS). We found that the EKE ranged from 64 cm(2)/s(2) to 1 390 cm(2)/s(2) with a mean value of 314 cm(2)/s(2). The highest EKE center was observed to the east of Vietnam (with a mean value of 509 cm(2)/s(2)) and the second highest EKE region was located to the southwest of Taiwan Island (with a mean value of 319 cm(2)/s(2)). We also found that the EKE structure is the consequence of the superposition of different variability components. First, interannual variability is important in the SCS. Spectral analysis of the EKE interannual signal (IA-EKE) shows that the main periodicities of the IA-EKE to the east of Vietnam, to the southwest of Taiwan Island, and in the SCS are 3.75, 1.87, and 3.75 years, respectively. It is to the south of Taiwan Island that the IA-EKE signal has the most obvious impact on EKE variability. In addition, the IA-EKE exhibit different trends in different regions. An obvious positive trend is observed along the east coast of Vietnam, while a negative trend is found to the southwest of Taiwan Island and in the east basin of Vietnam. Correlation analysis shows that the IA-EKE has an obvious negative correlation with the SSTA in Nio3 (5A degrees S-5A degrees N, 90A degrees W-150A degrees W). El Nio-Southern Oscillation (ENSO) affects the IA-EKE variability in the SCS through an atmospheric bridge-wind stress curl over the SCS. Second, the seasonal cycle is the most obvious timescale affecting EKE variability. The locations of the most remarkable EKE seasonal variabilities in the SCS are to the east of Vietnam, to the southwest of Taiwan, and to the west of Philippines. To the east of Vietnam, the seasonal cycle is the dominant mechanism controlling EKE variability, which is attributed primarily to the annual cycle there of wind stress curl. In this area, the maximum EKE is observed in autumn. To the southwest of Taiwan Island, the EKE is enlarged by the stronger SCS circulation, which is caused by the intrusion branch from the Kuroshio in winter. Finally, intra-annual and mesoscale variability, although less important than the former, cannot be neglected. The most obvious intra-annual and mesoscale variability, which may be the result of baroclinic instability of the background flow, are observed to the southwest of Taiwan Island. Sporadic events can have an important effect on EKE variability.

Dynamics of the buoyant plume off the Pearl River Estuary in summer

Field measurements of salinity, wind and river discharge and numerical simulations of hydrodynamics from 1978 to 1984 are used to investigate the dynamics of the buoyant plume off the Pearl River Estuary (PRE), China during summer. The studies have shown that there are four major horizontal buoyant plume types in summer: Offshore Bulge Spreading (Type I), West Alongshore Spreading (Type II), East Offshore Spreading (Type III), and Symmetrical Alongshore Spreading (Type IV). River mouth conditions, winds and ambient coastal currents have inter-influences to the transport processes of the buoyant plume. It is found that all of the four types are surface-advected plumes by analysing the vertical characteristic of the plumes, and the monthly variations of the river discharge affect the plume size dominantly. The correlation coefficient between the PRE plume size and the river discharge reaches 0.85 during the high river discharge season. A wind strength index has been introduced to examine the wind effect. It is confirmed that winds play a significant role in forming the plume morphology. The alongshore wind stress and the coastal currents determine the alongshore plume spreading. The impact of the ambient currents such as Dongsha Current and South China Sea (SCS) Warm Current on the plume off the shelf has also assessed. The present study has demonstrated that both the river discharge and wind conditions affect the plume evolution.

A quasi-synoptic interpretation of water mass distribution and circulation in the western North Pacific II: Circulation

Using the data of conductivity-temperature-depth (CTD) intensive observations conducted during Oct.-Nov. 2005, this study provides the first three-dimension quasi-synoptic description of the circulation in the western North Pacific. Several novel phenomena are revealed, especially in the deep ocean where earlier observations were very sparse. During the observations, the North Equatorial Current (NEC) splits at about 12A degrees N near the sea surface. This bifurcation shifts northward with depth, reaching about 20A degrees N at 1 000 m, and then remains nearly unchanged to as deep as 2 000 m. The Luzon Undercurrent (LUC), emerging below the Kuroshio from about 21A degrees N, intensifies southward, with its upper boundary surfacing around 12A degrees N. From there, part of the LUC separates from the coast, while the rest continues southward to join the Mindanao Current (MC). The MC extends to 2 000 m near the coast, and appears to be closely related to the subsurface cyclonic eddies which overlap low-salinity water from the North Pacific. The Mindanao Undercurrent (MUC), carrying waters from the South Pacific, shifts eastward upon approaching the Mindanao coast and eventually becomes part of the eastward undercurrent between 10A degrees N and 12A degrees N at 130A degrees E. In the upper 2 000 dbar, the total westward transport across 130A degrees E between 7.5A degrees N and 18A degrees N reaches 65.4 Sv (1 Sv = 10(-6) m(3)s(-1)), the northward transport across 18A degrees N from Luzon coast to 130A degrees E is up to 35.0 Sv, and the southward transport across 7.5A degrees N from Mindanao coast to 130A degrees E is 27.9 Sv.

Physical mechanism and numerical simulations of surface layer temperature inversion in tropical ocean

The one-dimensional Kraus-Turner mixed layer model improved by Liu is developed to consider the effect of salinity and the equations of temperature and salinity under the mixed layer. On this basis, the processes of growth and death of surface layer temperature inversion is numerically simulated under different environmental parameters. At the same time, the physical mechanism is preliminarily discussed combining the observations at the station of TOGA-COARE 0 degrees N, 156 degrees E. The results indicate that temperature inversion sensitively depends on the mixed layer depth, sea surface wind speed and solar shortwave radiation, etc., and appropriately meteorological and hydrological conditions often lead to the similarly periodical occurrence of this inversion phenomenon.

Analysis of the sea-level variability along the Chinese coast and estimation of the impact of a CO2-perturbed atmospheric circulation

The relationship between monthly sea-level data measured at stations located along the Chinese coast and concurrent large-scale atmospheric forcing in the period 1960-1990 is examined. It is found that sea-level varies quite coherently along the whole coast, despite the geographical extension of the station set. A canonical correlation analysis between sea-level and sea-level pressure (SLP) indicates that a great part of the sea-level variability can be explained by the action of the wind stress on the ocean surface. The relationship between sea-level and sea-level pressure is analyzed separately for the summer and winter half-years. In winter, one factor affecting sea-level variability at all stations is the SLP contrast between the continent and the Pacific Ocean, hence the intensity of the winter Monsoon circulation. Another factor that affects coherently all stations is the intensity of the zonal circulation at mid-latitudes. In the summer half year, on the other hand, the influence of SLP on sea-level is spatially less coherent: the stations in the Yellow Sea are affected by a more localized circulation anomaly pattern, whereas the rest of the stations is more directly connected to the intensity of the zonal circulation. Based on this analysis, statistical models (different for summer and winter) to hindcast coastal sealevel anomalies from the large-scale SLP field are formulated. These models have been tested by fitting their internal parameters in a test period and reproducing reasonably the sea-level evolution in an independent period. These statistical models are also used to estimate the contribution of the changes of the atmospheric circulation on sea-level along the Chinese coast in an altered climate. For this purpose the ouput of 150 year-long experiment with the coupled ocean-atmosphere model ECHAM1-LSG has been analyzed, in which the atmospheric concentration of greenhouse gases was continuously increased from 1940 until 2090, according to the Scenario A projection of the Intergovermental Panel on Climate Change. In this experiment the meridional (zonal) circulation relevant for sea-level tends to become weaker (stronger) in the winter half year and stronger (weaker) in summer. The estimated contribution of this atmospheric circulation changes to coastal sea-level is of the order of a few centimeters at the end of the integration, being in winter negative in the Yellow Sea and positive in the China Sea with opposite signs in the summer half-year.

Intraseasonal variability of Indian Ocean sea surface temperature during boreal winter: Madden-Julian Oscillation versus submonthly forcing and processes

[ 1] Intraseasonal variability of Indian Ocean sea surface temperature (SST) during boreal winter is investigated by analyzing available data and a suite of solutions to an ocean general circulation model for 1998 - 2004. This period covers the QuikSCAT and Tropical Rainfall Measuring Mission (TRMM) observations. Impacts of the 30 - 90 day and 10 - 30 day atmospheric intraseasonal oscillations (ISOs) are examined separately, with the former dominated by the Madden-Julian Oscillation (MJO) and the latter dominated by convectively coupled Rossby and Kelvin waves. The maximum variation of intraseasonal SST occurs at 10 degrees S - 2 degrees S in the wintertime Intertropical Convergence Zone (ITCZ), where the mixed layer is thin and intraseasonal wind speed reaches its maximum. The observed maximum warming ( cooling) averaged over ( 60 degrees E - 85 degrees E, 10 degrees S - 3 degrees S) is 1.13 degrees C ( - 0.97 degrees C) for the period of interest, with a standard deviation of 0.39 degrees C in winter. This SST change is forced predominantly by the MJO. While the MJO causes a basin-wide cooling ( warming) in the ITCZ region, submonthly ISOs cause a more complex SST structure that propagates southwestward in the western-central basin and southeastward in the eastern ocean. On both the MJO and submonthly timescales, winds are the deterministic factor for the SST variability. Short-wave radiation generally plays a secondary role, and effects of precipitation are negligible. The dominant role of winds results roughly equally from wind speed and stress forcing. Wind speed affects SST by altering turbulent heat fluxes and entrainment cooling. Wind stress affects SST via several local and remote oceanic processes.

IMPACTS OF THE TROPICAL PACIFIC COUPLED PROCESS ON THE INTERANNUAL VARIABILITY IN THE INDIAN OCEAN

The basic features of climatology and interannual variations of tropical Pacific and Indian Oceans were analyzed using a coupled general circulation model (CGCM), which was constituted with an intermediate 2.5-layer ocean model and atmosphere model ECHAM4. The CGCM well captures the spatial and temporal structure of the Pacific El Nino-Southern Oscillation (ENSO) and the variability features in the tropical Indian Ocean. The influence of Pacific air-sea coupled process on the Indian Ocean variability was investigated carefully by conducting numerical experiments. Results show that the occurrence frequency of positive/negative Indian Ocean Dipole (IOD) event will decrease/increase with the presence/absence of the coupled process in the Pacific Ocean. Further analysis demonstrated that the air-sea coupled process in the Pacific Ocean affects the IOD variability mainly by influencing the zonal gradient of thermocline via modulating the background sea surface wind.

Variability of surface circulation in the South China Sea from satellite altimeter data

11-year satellite altimeter sea surface height (SSH) anomaly data from January 1993 to December 2003 are used to present the dominant spatial patterns and temporal variations of the South China Sea (SCS) surface circulation through Empirical Orthogonal Function (EOF) analysis. The first three EOF modes show the obvious seasonal variations of SSH in the SCS. EOF mode one is generally characterized by a basin-wide circulation. Mode two describes the double-cell basin scale circulation structure. The two cells were located off west of the Luzon Island and southeast of Vietnam, respectively. EOF mode three presents the mesoscale eddy structure in the western SCS, which develops into a strong cyclonic eddy rapidly from July to September. EOF mode one and mode three are also embedded with interannual signals, indicating that the SCS surface circulation variation is influenced by El Nino events prominently. The strong El Nino of 1997/98 obviously changed the SCS circulation structure. This study also shows that there existed a series of mesoscale eddies in the western SCS, and their temporal variation indicates intra-seasonal and interannual signals.

A new empirical model for retrieving sea surface salinity in L band

Sea surface salinity is a key physical parameter in ocean science. It is important in the ocean remote sensing to retrieve sea surface salinity by the microwave probe technology. Based on the in situ measurement data and remote sensing data of the Yellow Sea, we have built a new empirical model in this paper, which can be used to retrieve sea surface salinity of the Yellow Sea by means of the brightness temperature of the sea water at L-band. In this model, the influence of the roughness of the sea surface is considered, and the retrieved result is in good agreement with the in situ measurement data, where the mean absolute error of the retrieved sea surface salinity is about 0.288 psu. This result shows that our model has greater retrieval precision compared with similar models.

Seasonal and interannual variability of primary and export production in the South China Sea: a three-dimensional physical-biogeochemical model study

To investigate the seasonal and interannual variations in biological productivity in the South China Sea (SCS), a Pacific basin-wide physical - biogeochemical model has been developed and used to estimate the biological productivity and export flux in the SCS. The Pacific circulation model, based on the Regional Ocean Model Systems (ROMS), is forced with daily air-sea fluxes derived from the NCEP (National Centers for Environmental Prediction) reanalysis between 1990 and 2004. The biogeochemical processes are simulated with a carbon, Si(OH)(4), and nitrogen ecosystem (CoSiNE) model consisting of silicate, nitrate, ammonium, two phytoplankton groups (small phytoplankton and large phytoplankton), two zooplankton grazers (small micrograzers and large mesozooplankton), and two detritus pools. The ROMS-CoSiNE model favourably reproduces many of the observed features, such as ChI a, nutrients, and primary production (PP) in the SCS. The modelled depth-integrated PP over the euphotic zone (0-125 m) varies seasonally, with the highest value of 386 mg C m (-2) d (-1) during winter and the lowest value of 156 mg C m (-2) d (-1) during early summer. The annual mean value is 196 mg C m (-2) d (-1). The model-integrated annual mean new production (uptake of nitrate), in carbon units, is 64.4 mg C m (-2) d (-1) which yields an f-ratio of 0.33 for the entire SCS. The modelled export ratio (e-ratio: the ratio of export to PP) is 0.24 for the basin-wide SCS. The year-to-year variation of biological productivity in the SCS is weaker than the seasonal variation. The large phytoplankton group tends to dominate over the smaller phytoplankton group, and likely plays an important role in determining the interannual variability of primary and new production.

Phytoplankton biomass size structure and its regulation in the Southern Yellow Sea (China): Seasonal variability

Phytoplankton size structure plays a significant role in controlling the carbon flux of marine pelagic ecosystems. The mesoscale distribution and seasonal variation of total and size-fractionated phytoplankton biomass in surface waters. as measured by chlorophyll a (Chl a), was studied in the Southern Yellow Sea using data from four cruises during 2006-2007. The distribution of Chl a showed a high degree of spatial and temporal variation in the study area. Chl a concentrations were relatively high in the summer and autumn, with a mean of 142 and 1.27 mg m(-3), respectively. Conversely, in the winter and spring. the average Chl a levels were only 098 and 0.99 mg m(-3) Total Chl a showed a clear decreasing gradient from coastal areas to the open sea in the summer, autumn and winter cruises. Patches of high Chl a were observed in the central part of the Southern Yellow Sea in the spring due to the onset of the phytoplankton bloom. The eutrophic coastal waters contributed at least 68% of the total phytoplankton biomass in the surface layer. Picophytoplankton showed a consistent and absolute dominance in the central region of the Southern Yellow Sea (>40%) in all of the cruises, while the proportion of microphytoplankton was the highest in coastal waters The relative proportions of pico- and nanophytoplankton decreased with total biomass, whereas the proportion of the micro-fraction increased with total biomass. Relationships between phytoplankton biomass and environmental factors were also analysed. The results showed that the onset of the spring bloom was highly dependent on water column stability. Phytoplankton growth was limited by nutrient availability in the summer due to the strong thermocline. The combined effects of P-limitation and vertical mixing in the autumn restrained the further increase of phytoplankton biomass in the Surface layer. The low phytoplankton biomass in winter was caused by vertical dispersion due to intense mixing. Compared with the availability of nutrients. temperature did not seem to cause direct effects on phytoplankton biomass and its size structure. Although interactions of many different environmental factors affected phytoplankton distributions. hydrodynamic conditions seemed to be the dominant factor. Phytoplankton size structure was determined mainly by the size-differential capacity in acquiring resource. Short time scale events, such as the spring bloom and the extension of Yangtze River plume, can have substantial influences, both on the total Chl a concentration and on the size structure of the phytoplankton. (C) 2009 Elsevier Ltd. All rights reserved.

Metabolism of polychaete Neanthes japonica Izuka: relations to temperature, salinity and body weight

Polychaete Neanthes japonica is a species geographically specific in China and Japan with important scientific implication and commercial value. In this study, the relations of body weight, salinity and temperature to oxygen consumption and ammonia excretion of N. japonica were determined. Three different groups in body weight (large: 2.34 +/- 0.36 g, middle: 1.50 +/- 0.21 g and small: 0.62 +/- 0.12 g) were set for all experiments. Results show that the body weight is negatively related to the rates of oxygen consumption and ammonia excretion; and the relationship is significant. The oxygen consumption and ammonia excretion at 24A degrees C decreased at salinity from 5 to 30 and increased above 30, indicating that both lower and higher salinity are adverse and certain degree of salinity stress is necessary for enhancing the energy demand. At salinity 30, rising temperature from 18A degrees C to 30A degrees C, the oxygen consumption increased before 27A degrees C and then decreased. However, the relation of ammonia excretion and temperature seems more complex. Two-way ANOVA shows that salinity, temperature and body weight all have a significant effect on the oxygen consumption and ammonia excretion of the worm. Moreover, interaction between salinity/temperature and body weight is also significant. O:N (oxygen/nitrogen) ratio varies greatly in this case from 5.97 to 463.22, indicating that N. japonica can regulate the type of metabolic substrate against environment changes.

Phytoplankton distributions and their relationship with the environment in the Changjiang Estuary, China

This study was carried out in the Changjiang Estuary from 19 to 26 May 2003. Based on the data collected from 29 stations, including two anchor stations, phytoplankton taxonomic composition, abundance, diurnal variability and spatial distribution were examined. Eighty-seven species, including 54 species of diatoms and 16 red tide causative species, were identified. Average diversity index (H') and evenness (J) values were 1.04 and 0.40, respectively. A bloom in abundance of certain phytoplankton species, especially Prorocentrum dentatum and Skeletoneina costatum, was thought to be the cause of the low diversity index and evenness values. Total phytoplankton abundance averaged 6.75 x 10(5) cells 1(-1), and was much higher than previous investigation carried out in the same month in 1986. Abundance increased seaward showing a distinct spatial difference, and the dominant species varied with salinity. Correlation between phosphorus and abundance further supported the former conclusion that phosphorus is the controlling factor in phytoplankton growth in the Changjiang Estuary where light is not limiting. Based on the relationship between DO, pH and abundance, it is likely that the bloom was caused by rapid in situ growth of phytoplankton with high nutrients and sufficient light. The data also indicated that the duration of the bloom was not long and

Spatial and temporal variations in pH and total alkalinity at the beginning of the rainy season in the Changjiang Estuary, China

The results of field observation carried out in May 2003 were used to examine pH and total alkalinity behaviors in the Changjiang Estuary. It was showed that PH and total alkalinity took on clear spatial variations in values with the minima in the low salinity region. Like salinity, transect distributions of PH and total alkalinity (TA) in a downriver direction had a sharp gradient each. These gradients appeared in such a sequence that the TA gradient was earlier than salinity and PH gradients, and the salinity gradient was earlier than the PH gradient. These distribution characteristics seemed to be strongly influenced by the mixing process of freshwater and seawater, for both PH and total alkalinity had significant linear relationships with salinity and temperature. For PH, phytoplankton activities also had a significant impact upon its spatial distribution. During a period of 48 h, PH and total alkalinity changed within wide ranges for every layer of the two anchor stations, namely, Stas 13 and 20, which were located at the mixed water mass and seawater mass, respectively. For both Stas 13 and 20, PH and TA fluctuation of every layer could be very wide during a 4 h period. As a whole, the data of the two anchor stations showed that neither variations in salinity and temperature nor phytoplankton activities were the main factors strongly influencing the total alkalinity temporal variability on a small time scale. The data of Sta. 20 implied that both salinity variation and phytoplankton activities had a significant influence on PH temporal variability, but the same conclusion could not be drawn from the data of Sta. 13.