Statistical analyses of sea state conditions in South China Sea

The statistical characterization of sea conditions in the South China Sea(SCS) was investigated by analyzing a 30-year(1976–2005) numerically simulated daily wave height and wind speed data. The monthly variation of these parameters shows that wave height and wind speed have minimum values of 0.54 m and 4.15 ms~(-1), respectively in May and peak values of 2.04 m and 8.12 ms~(-1), respectively in December. Statistical analysis of the daily wave height and wind speed and the subsequent characterization of the annual, seasonal and monthly mean sea state based on these parameters were also done. Results showed that, in general, the slight sea state prevails in the SCS and has nearly the highest occurrence in all seasons and months. The moderate sea condition prevails in the winter months of December and January while the smooth(wavelets) sea state prevails in May. Furthermore, spatial variation of sea states showed that calm and smooth sea conditions have high occurrences(25%–80%) in the southern SCS. The slight sea condition shows the largest occurrence(25%–55%) over most parts of the SCS. High occurrences(8%–17%) of the rough and very rough seas distribute over some regions in the central SCS. Sea states from high to phenomenal conditions show rare occurrence(12%) in the northern SCS. The calm(glassy) sea condition shows no occurrence in the SCS.     

Observation and numerical experiments for drag coefficient under typhoon wind forcing

This paper presents a study on drag coefficients under typhoon wind forcing based on observations and numerical experiments. The friction velocity and wind speed are measured at a marine observation platform in the South China Sea. Three typhoons: SOULIK(2013), TRAMI(2013) and FITOW(2013) are observed at a buoy station in the northeast sea area of Pingtan Island. A new parameterization is formulated for the wind drag coefficient as a function of wind speed. It is found that the drag coefficient(Cd) increases linearly with the slope of 0.083′10~(-3) for wind speed less than 24 m s~(-1). To investigate the drag coefficient under higher wind conditions, three numerical experiments are implemented for these three typhoons using SWAN wave model. The wind input data are objective reanalysis datasets, which are assimilated with many sources and provided every six hours with the resolution of 0.125?×0.125?. The numerical simulation results show a good agreement with wave observation data under typhoon wind forcing. The results indicate that the drag coefficient levels off with the linear slope of 0.012′10~(-3) for higher wind speeds(less than 34 m s~(-1)) and the new parameterization improvese the simulation accuracy compared with the Wu(1982) default used in SWAN.     

Numerical simulation of wave field in the South China Sea using WAVEWATCH III

Wave fi elds of the South China Sea(SCS) from 1976 to 2005 were simulated using WAVEWATCH III by inputting high-resolution reanalysis wind fi eld datasets assimilated from several meteorological data sources. Comparisons of wave heights between WAVEWATCH III and TOPEX/Poseidon altimeter and buoy data show a good agreement. Our results show seasonal variation of wave direction as follows: 1. During the summer monsoon(April–September), waves from south occur from April through September in the southern SCS region, which prevail taking about 40% of the time; 2. During the winter monsoon(December–March), waves from northeast prevail throughout the SCS for 56% of the period; 3. The dominant wave direction in SCS is NE. The seasonal variation of wave height H s in SCS shows that in spring, H s ≥1 m in the central SCS region and is less than 1 m in other areas. In summer, H s is higher than in spring. During September–November, infl uenced by tropical cyclones, H s is mostly higher than 1 m. East of Hainan Island, H s 2 m. In winter, H s reaches its maximum value infl uenced by the north-east monsoon, and heights over 2 m are found over a large part of SCS. Finally, we calculated the extreme wave parameters in SCS and found that the extreme wind speed and wave height for the 100-year return period for SCS peaked at 45 m/s and 19 m, respectively, SE of Hainan Island and decreased from north to south.     

两种海浪模式对一次台风浪过程的模拟分析

以CCMP（Cross—Calibrated,Multi—Platfoml）风场为驱动场,分别驱动目前国际先进的第3代海浪模式ww3（WAVEWATCH—III）、SWAN（Simulating WAves Nearshore）,对2010年9月发生在东中国海的台风“圆规”所致的台风浪进行数值模拟,就台风浪的特征进行分析,并对比分析两个海浪模式的模拟效果。结果表明：1）以CCMP风场分别驱动WW3、SWAN海浪模式,可以较好地模拟发生在东中国海的台风浪,风向与波向保持了大体一致,波高与风速的分布特征保持了很好的一致性;2）综合相关系数、偏差、均方根误差、平均绝对误差来看,两个模式模拟的有效波高（SWH—Significant Wdve Height）都具有较高精度,SWAN模拟的SWH略低于观测值,WW3模拟的SWH与观测值更为接近;3）台风浪可给琉球群岛海域带来5m左右的大浪,台风浪进入东海后,波高、风速都有一定程度的增加,当台风沿西北路径穿越朝鲜半岛时,受到半岛地形的巨大影响,风速和波高都明显降低。     

Trends in significant wave height and surface wind speed in the China Seas between 1988 and 2011

Wind and waves are key components of the climate system as they drive air-sea interactions and influence weather systems and atmospheric circulation. In marine environments, understanding surface wind and wave fields and their evolution over time is important for conducting safe and efficient human activities, such as navigation and engineering. This study considers long-term trends in the sea surface wind speed(WS) and significant wave height(SWH) in the China Seas over the period 1988–2011 using the Cross-Calibrated Multi-Platform(CCMP) ocean surface wind product and a 24-year hindcast wave dataset obtained from the WAVEWATCH-III(WW3) wave model forced with CCMP winds. The long-term trends in WS and SWH in the China Seas are analyzed over the past 24 years to provide a reference point from which to assess future climate change and offshore wind and wave energy resource development in the region. Results demonstrate that over the period 1988–2011 in the China Seas: 1) WS and SWH showed a significant increasing trend of 3.38 cm s~(-1)yr~(-1) and 1.52 cm yr~(-1), respectively; 2) there were notable regional differences in the long-term trends of WS and SWH; 3) areas with strong increasing trends were located mainly in the middle of the Tsushima Strait, the northern and southern areas of the Taiwan Strait, and in nearshore regions of the northern South China Sea; and 4) the long-term trend in WS was closely associated with El Ni?o and a significant increase in the occurrence of gale force winds in the region.     

Numerical simulation and preliminary analysis of typhoon waves during three typhoons in the Yellow Sea and East China Sea

In this study, typhoon waves generated during three typhoons(Damrey(1210), Fung-wong(1416), and Chan-hom(1509)) in the Yellow Sea and East China Sea were simulated in a simulating waves nearshore(SWAN) model, and the wind forcing was constructed by combining reanalyzed wind data with a Holland typhoon wind model. Various parameters, such as the Holland fitting parameter(B) and the maximum wind radius(R), were investigated in sensitivity experiments in the Holland model that affect the wind field construction. Six different formulations were considered and the parameters determined by comparing the simulated wind results with in-situ wind measurements. The key factors affecting wave growth and dissipation processes from deep to shallow waters were studied, including wind input, whitecapping, and bottom friction. Comparison with in-situ wave measurements suggested that the KOMEN scheme(wind input exponential growth and whitecapping energy dissipation) and the JONSWAP scheme(dissipation of bottom friction) resulted in good reproduction of the significant wave height of typhoon waves. A preliminary analysis of the wave characteristics in terms of wind-sea and swell wave revealed that swell waves dominated with the distance of R to the eye of the typhoon, while wind-sea prevailed in the outer region up to six to eight times the R values despite a clear misalignment between wind and waves. The results support the hypothesis that nonlinear wave-wave interactions may play a key role in the formation of wave characteristics.     

Analysis of Wave Distributions Using the WAVEWATCH-Ⅲ Model in the Arctic Ocean

In this work, we examined long-term wave distributions using a third-generation numerical wave model called WAVE- WATCH-Ⅲ(WW3) (version 6.07). We also evaluated the influence of sea ice on wave simulation by using eight parametric switches. To select a suitable ice-wave parameterization, we validated the simulations from the WW3 model in March, May, September, and December 2017 against the measurements from the Jason-2 altimeter at latitudes of up to 60?N. Generally, all parameterizations ex-hibited slight differences, i.e., about 0.6 m root mean square error (RMSE) of significant wave height (SWH) in May and September and about 0.9 m RMSE for the freezing months of March and December. The comparison of the results with the SWH from the European Centre for Medium-Range Weather Forecasts for December 2017 indicated that switch IC4_M1 performed most effec-tively (0.68 m RMSE) at high latitudes (60?– 80?N). Given this finding, we analyzed the long-term wave distributions in 1999 – 2018 on the basis of switch IC4_M1. Although the seasonal variability of the simulated SWH was of two types, i.e., 'U' and 'sin' modes, our results proved that fetch expansion prompted the wave growth. Moreover, the interannual variability of the specific regions in the 'U' mode was found to be correlated with the decade variability of wind in the Arctic Ocean.     

STUDY OF WATER—TRANSPORT THROUGH SOME MAIN STRAITS IN THE EAST CHINA SEA AND SOUTH CHINA SEA

OCCAM global ocean model results were applied to calculate the monthly water transport through 7 straits around the East China Sea(ECS)and the South china Sea(SCS).Analysis of the features of velocity profiles and their variations in the Togara Strait,Luzon Strait and Eastern Taiwan Strait showed that;1)the velocity profiles had striped pattern in the Eastern Taiwan Strait,where monthly flux varied from 22.4 to 28.1 Sv and annual mean was about 25.8 Sv;2)the profiles of velocity in the Togara Strait were characterized by core structure,and monthly flux varied from 23.3 to 31.4 Sv,with annual mean of about 27.9 Sv;3)water flowed from the SCS to the ECS in the Taiwan Strait,with maximum flux of 3.1 Sv in July and minimum of 0.9 Sv in November;4)the flux in the Tsushima Strait varied by only about 0.4 Sv by season and its annual mean was about 2.3 Sv;5)Kuroshio water flowed into the SCS in the Luzon Strait throughout the year and the velocity profiles were characterized by multi-core structure.The flux in the Luzon Strait was minimun in June(about 2.4 Sv)and maximum in February(about 9.0 Sv),and its annual mean was 4.8 Sv;6)the monthly flux in the Mindoro Strait was maximum in December(3.0 Sv)and minimum in June(Only 0.1 Sv),and its annual mean was 1.3 Sv;7)Karimata Strait water flowed into the SCS from May to August,with maximum in-flow flux of about 0.75 Sv in June and flowed out from September to April at maximum outflow flux of 3.9 Sv in January.The annual mean flux was about 1.35 Sv.     

Analysis of seasonal variation of water masses in East China Sea

Seasonal variations of water masses in the East China Sea （ECS） and adjacent areas are investigated, based on historical data of temperature and salinity （T-S）. Dynamic and thermodynamic mechanisms that affect seasonal variations of some dominant water masses are discussed, with reference to meteorological data. In the ECS above depth 600 m, there are eight water masses in summer but only five in winter. Among these, Kuroshio Surface Water （KSW）, Kuroshio Intermediate Water （KIW）, ECS Surface Water （ECSSW）, Continental Coastal Water （CCW）, and Yellow Sea Surface Water （YSSW） exist throughout the year. Kuroshio Subsurface Water （KSSW）, ECS Deep Water （ECSDW）, and Yellow Sea Bottom Water （YSBW） are all seasonal water masses, occurring from May through October. The CCW, ECSSW and KSW all have significant seasonal variations, both in their horizontal and vertical extents and their T-S properties. Wind stress, the Kuroshio and its branch currents, and coastal currents are dynamic factors for seasonal variation in spatial extent of the CCW, KSW, and ECSSW, whereas sea surface heat and freshwater fluxes are thermodynamic factors for seasonal variations of T-S properties and thickness of these water masses. In addition, the CCW is affected by river runoff and ECSSW by the CCW and KSW.     

A modelling study of inter-annual variation of Kuroshio intrusion on the shelf of East China Sea

Inter-annual variability of the Kuroshio water intrusion on the shelf of East China Sea (ECS) was simulated with a nested global and Northwest Pacific ocean circulation model. The model analysis reveals the influence of the variability of Kuroshio transport east of Taiwan on the intrusion to the northeast of Taiwan: high correlation (r = 0.92) with the on-shore volume flux in the lower layer (50–200 m); low correlation (r = 0.50) with the on-shore flux in the upper layer (0–50 m). Spatial distribution of correlations between volume fluxes and sea surface height suggests that inter-annual variability of the Kuroshio flux east of Taiwan and its subsurface water intruding to the shelf lag behind the sea surface height anomalies in the central Pacific at 162°E by about 14 months, and could be related to wind-forced variation in the interior North Pacific that propagates westward as Rossby waves. The intrusion of Kuroshio surface water is also influenced by local winds. The intruding Kuroshio subsurface water causes variations of temperature and salinity of bottom waters on the southern ECS shelf. The influence of the intruding Kuroshio subsurface water extends widely from the shelf slope northeast of Taiwan northward to the central ECS near the 60 m isobath, and northeastward to the region near the 90 m isobath.     

Numerical simulation and preliminary analysis on ocean waves during Typhoon Nesat in South China Sea and adjacent areas

Using the wave model WAVEWATCH III(WW3), we simulated the generation and propagation of typhoon waves in the South China Sea and adjacent areas during the passage of typhoon Nesat(2011). In the domain 100°–145°E and 0°–35°N, the model was forced by the cross-calibrated multi-platform(CCMP) wind fi elds of September 15 to October 5, 2011. We then validated the simulation results against wave radar data observed from an oil platform and altimeter data from the Jason-2 satellite. The simulated waves were characterized by fi ve points along track using the Spectrum Integration Method(SIM) and the Spectrum Partitioning Method(SPM), by which wind sea and swell components of the 1D and 2D wave spectra are separated. There was reasonable agreement between the model results and observations, although the WW3 wave model may underestimate swell wave height. Signifi cant wave heights are large along the typhoon track and are noticeably greater on the right of the track than on the left. Swells from the east are largely unable to enter the South China Sea because of the obstruction due to the Philippine Islands. During the initial stage and later period of the typhoon, swells at the fi ve points were generated by the propagation of waves that were created by typhoons Haitang and Nalgae. Of the two methods, the 2D SPM method is more accurate than the 1D SIM which overestimates the separation frequency under low winds, but the SIM method is more convenient because it does not require wind speed and wave direction. When the typhoon left the area, the wind sea fractions decreased rapidly. Under similar wind conditions, the points located in the South China Sea are affected less than those points situated in the open sea because of the infl uence of the complex internal topography of the South China Sea. The results reveal the characteristic wind sea and swell features of the South China Sea and adjacent areas in response to typhoon Nesat, and provide a reference for swell forecasting and offshore structural designs.     

On spatiotemporal characteristics of sea fog occurrence over the Northern Atlantic from 1909 to 2008

In this paper, the International Comprehensive Ocean and Atmosphere Data Set(ICOADS) is utilized to investigate the horizontal distribution of sea fog occurrence frequency over the Northern Atlantic as well as the meteorological and oceanic conditions for sea fog formation. Sea fog over the Northern Atlantic mainly occurs over middle and high latitudes. Sea fog occurrence frequency over the western region of the Northern Atlantic is higher than that over the eastern region. The season for sea fog occurrence over the Northern Atlantic is generally from April to August. When sea fogs occur, the prevailing wind direction in the study area is from southerly to southwesterly and the favorable wind speed is around 8 m s-1. It is most favorable for the formation of sea fogs when sea surface temperature(SST) is 5℃ to 15℃. When SST is higher than 25℃, it is difficult for the air to get saturated, and there is almost no report of sea fog. When sea fogs form, the difference between sea surface temperature and air temperature is mainly-1 to 3℃, and the difference of 0℃ to 2℃ is the most favorable conditions for fog formation. There are two types of sea fogs prevailing in this region: advection cooling fog and advection evaporating fog.     

Current and Thermohaline Characteristics of the Arabian Sea During January 1998

Based on a ship survey during January 1998, the characteristics of the flow, the thermohaline properties and the volume transport of the Arabian Sea are discussed. A strong westward flow exists between 10.5?N and 11?N, part of which turns to the south as the Somali current near the coast at about 10?N and the rest turns north. At the passage between the African continent and the So- cotra Island, the northern branch separates into two flows: the left one enters the passage and the right one flows eastward along the southern slope of the island. Off the island the flow separates once more, most of it meandering northeast and a small fraction flow- ing southeast. Volume transport calculation suggests that the tidal transport is one or two orders of magnitude smaller than the total transport in this region and it becomes more important near the coast. The average velocity of the flow in the upper layer (0-150 m) is about 20 cm s-1, with a maximum of 53 cm s-1 appearing east of the Socotra Island, and the subsurface layer (200-800 m) has an aver- age velocity of 8.6 cm s-1; the velocity becomes smaller at greater depths. The depth of the seasonal thermocline is about 100 m, above which there is a layer with well mixed temperature and dissolved oxygen. High-salinity and oxygen-rich water appears near the surface of the northern Arabian Sea; a salinity maximum and oxygen minimum at 100 m depth along 8?N testifies the subduction of surface water from the northern Arabian Sea. Waters from the Red Sea and the Persian Gulf also influence the salinity of the area.     

TEMPORAL VARIATIONS OF HYDROLOGY AND LIGHT TRANSMISSION AT TWO FIXED OBSERVATION STATIONS IN THE EAST CHINA SEA

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The research on typhoon wave spectrum in northwestern South China Sea

Based upon the one-year wind wave measurement data, collected from the South China Sea (SCS) at coordinates 20° 36.298′N, 110°45.433′E. by Acoustic Wave And Current (AWAC), we analyzed the wave characteristics and concluded that the most common wave direction was E and the second most common direction was ENE, the mean and the maximum values of significant height was 1.2 m and 4.36 m, respectively. The mean period was 4.0 s. We also evaluated the wave spectrums under conditions existing in three typhoons: Rumbi, Jeti and Utor. We found that unimodal spectrums occurred more often than others, and the maximum spectrum peak was 30.7911 m² s. The minimum peak frequency was 0.0625 Hz, and the mean peak frequency was 0.126 Hz. The wave period is important for the design of marine structures, especially the position of peak frequency had a great influence on the stress calculation. Spectral analysis showed that the values of peak frequency distributed between 0.063 Hz and 0.217 Hz, with the mean value 0.114 Hz. We fit the normalized spectrum with 6 theoretical spectral models, out of which, the Wen spectrum, JONSWAP spectrum and Wallops spectrum were proved to give the best fit. What distinguished the Wen Spectrum from the rest was that it does not rely on the measured spectrum for parameter estimation. Hence, we recommend that the Wen spectrum should be widely used in marine construction.     

Study on the growth of wind wave frequency spectra generated by cold waves in the northern East China Sea

The growth of frequency spectra and spectral parameters of wind waves generated by cold waves, a kind of severe weather system, in the northern East China Sea is studied in this paper. Based on a third-generation wave action model(the Simulating WAves Nearshore model), simulations were developed to analyze the spatiotemporal characteristics of wind waves and to output spectral data. It is shown that the cold wave-induced spectra can be well described by the modified Joint North Sea Wave Project spectral form. The growth of wave spectra is comprehensively reflected by the evolution of the three characteristic parameters: peak frequency, spectral peak and wave energy. Besides, the approximations of dependences between spectral parameters and the three types of universal induced factors are obtained with the least squares method and compared systematically. Fetch and peak frequency turn out to be suitable parameters to describe the spectral parameters, while the dependences on the inverse wave age vary in different sea areas. In general, the derived relationships improve on results from previous studies for better practical application of the wind wave frequency spectrum in the northern East China Sea.     

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????T/P(TOPEX/POSEIDON)????????????????????????????????????T/P?????????????????????????????????????????????????????????У??????С????????????????????????????????????????????????????Ч??????T/P?????Ч???????0.3m??????T/P????????Jason??1?????????????????????????????????????????????????????????????????????????????????????????????????????á?T/P??Jason??1????????????????Ч?????????????????????????0.21 m??0.05 m??     

Interannual to decadal variation of spring sea level anomaly in the western South China Sea

Satellite observations of sea level anomalies(SLA) from January 1993 to December 2012 are used to investigate the interannual to decadal changes of the boreal spring high SLA in the western South China Sea(SCS) using the Empirical Orthogonal Function(EOF) method. We find that the SLA variability has two dominant modes. The Sea Level Changing Mode(SLCM) occurs mainly during La Ni?a years, with high SLA extension from west of Luzon to the eastern coast of Vietnam along the central basin of the SCS, and is likely induced by the increment of the ocean heat content. The Anticyclonic Eddy Mode(AEM) occurs mainly during El Ni?o years and appears to be triggered by the negative wind curl anomalies within the central SCS. In addition, the spring high SLA in the western SCS experienced a quasi-decadal change during 1993–2012; in other words, the AEM predominated during 1993–1998 and 2002–2005, while the La Ni?a-related SLCM prevailed during 1999–2001 and 2006–2012. Moreover, we suggest that the accelerated sea level rise in the SCS during 2005–2012 makes the SLCM the leading mode over the past two decades.     

Chaos particle swarm optimization combined with circular median filtering for geophysical parameters retrieval from Windsat

This paper established a geophysical retrieval algorithm for sea surface wind vector, sea surface temperature, columnar atmospheric water vapor, and columnar cloud liquid water from WindSat, using the measured brightness temperatures and a matchup database. To retrieve the wind vector, a chaotic particle swarm approach was used to determine a set of possible wind vector solutions which minimize the difference between the forward model and the WindSat observations. An adjusted circular median filtering function was adopted to remove wind direction ambiguity. The validation of the wind speed, wind direction, sea surface temperature, columnar atmospheric water vapor, and columnar liquid cloud water indicates that this algorithm is feasible and reasonable and can be used to retrieve these atmospheric and oceanic parameters. Compared with moored buoy data, the RMS errors for wind speed and sea surface temperature were 0.92 m s~(-1) and 0.88℃, respectively. The RMS errors for columnar atmospheric water vapor and columnar liquid cloud water were 0.62 mm and 0.01 mm, respectively, compared with F17 SSMIS results. In addition, monthly average results indicated that these parameters are in good agreement with AMSR-E results. Wind direction retrieval was studied under various wind speed conditions and validated by comparing to the Quik SCAT measurements, and the RMS error was 13.3?. This paper offers a new approach to the study of ocean wind vector retrieval using a polarimetric microwave radiometer.     

Current status of small yellow croaker resources in the southern Yellow Sea and the East China Sea

We used data from bottom trawl surveys to study the factors influencing the abundance of small yellow croaker, Larimichthys polyactis, in the southern Yellow Sea (SYS) and the East China Sea (ECS). The resource density index (RDI) was generally higher in summer and autumn than in spring and winter. RDIs were also significantly greater in the SYS than in the ECS in summer and autumn. The bottom water salinity and depth of spatial distribution of small yellow croaker was similar between the two areas in summer, but different in other seasons. Regression analysis suggested that environmental factors such as bottom water temperature, salinity, and depth influenced the RDIs in summer in these areas. Growth condition factor (GCF) in the two areas varied monthly and the croaker in the SYS grew more slowly than those in the ECS. This was likely due to the low bottom temperature of the Yellow Sea Cold Water Mass in summer and autumn or to higher human fishing pressure in the ECS. To ensure sustainable utilization of the croaker stocks in these regions, we recommend reducing the fishing intensity, increasing the cod-end mesh size, and improving the protection of juveniles.