The long-term trend of the sea surface wind speed and the wave height (wind wave, swell, mixed wave)in global ocean during the last 44 a

Utilizing the 45 a European Centre for Medium-Range Weather Forecasts(ECMWF)reanalysis wave data(ERA-40),the long-term trend of the sea surface wind speed and(wind wave,swell,mixed wave)wave height in the global ocean at grid point 1.5×1.5 during the last 44 a is analyzed.It is discovered that a majority of global ocean swell wave height exhibits a significant linear increasing trend(2–8 cm/decade),the distribution of annual linear trend of the significant wave height(SWH)has good consistency with that of the swell wave height.The sea surface wind speed shows an annually linear increasing trend mainly concentrated in the most waters of Southern Hemisphere westerlies,high latitude of the North Pacific,Indian Ocean north of 30 S,the waters near the western equatorial Pacific and low latitudes of the Atlantic waters,and the annually linear decreasing mainly in central and eastern equator of the Pacific,Juan.Fernandez Archipelago,the waters near South Georgia Island in the Atlantic waters.The linear variational distribution characteristic of the wind wave height is similar to that of the sea surface wind speed.Another find is that the swell is dominant in the mixed wave,the swell index in the central ocean is generally greater than that in the offshore,and the swell index in the eastern ocean coast is greater than that in the western ocean inshore,and in year-round hemisphere westerlies the swell index is relatively low.     

中国海域有效波高、海表风速长期变化趋势的季节特征

Long-term variations in a sea surface wind speed(WS) and a significant wave height(SWH) are associated with the global climate change, the prevention and mitigation of natural disasters, and an ocean resource exploitation,and other activities. The seasonal characteristics of the long-term trends in China's seas WS and SWH are determined based on 24 a(1988–2011) cross-calibrated, multi-platform(CCMP) wind data and 24 a hindcast wave data obtained with the WAVEWATCH-III(WW3) wave model forced by CCMP wind data. The results show the following.(1) For the past 24 a, the China's WS and SWH exhibit a significant increasing trend as a whole, of3.38 cm/(s·a) in the WS, 1.3 cm/a in the SWH.(2) As a whole, the increasing trend of the China's seas WS and SWH is strongest in March-April-May(MAM) and December-January-February(DJF), followed by June-July-August(JJA), and smallest in September-October-November(SON).(3) The areal extent of significant increases in the WS was largest in MAM, while the area decreased in JJA and DJF; the smallest area was apparent in SON. In contrast to the WS, almost all of China's seas exhibited a significant increase in SWH in MAM and DJF; the range was slightly smaller in JJA and SON. The WS and SWH in the Bohai Sea, the Yellow Sea, East China Sea, the Tsushima Strait, the Taiwan Strait, the northern South China Sea, the Beibu Gulf, and the Gulf of Thailand exhibited a significant increase in all seasons.(4) The variations in China's seas SWH and WS depended on the season. The areas with a strong increase usually appeared in DJF.     

全球有效波高和风速的时空变化及相关关系研究

The climatology of significant wave height（SWH） and sea surface wind speed are matters of concern in the fields of both meteorology and oceanography because they are very important parameters for planning offshore structures and ship routings. The TOPEX/Poseidon altimeter, which collected data for about 13 years from September 1992 to October 2005, has measured SWHs and surface wind speeds over most of the world＇s oceans. In this paper, a study of the global spatiotemporal distributions and variations of SWH and sea surface wind speed was conducted using the TOPEX/Poseidon altimeter data set. The range and characteristics of the variations were analyzed quantitatively for the Pacific, Atlantic, and Indian oceans. Areas of rough waves and strong sea surface winds were localized precisely, and the correlation between SWH and sea surface wind speed analyzed.     

Seasonal and spatial distributions of phytoplankton biomass associated with monsoon and oceanic environments in the South China Sea

Seasonal variations of phytoplankton/chlorophyll-a （Chl-a） distribution, sea surface wind, sea height anomaly, sea surface temperature and other oceanic environments for long periods are analyzed in the South China Sea （SCS）, especially in the two typical regions off the east coast of Vietnam and off the northwest coast of Luzon, using remote sensing data and other oceanographic data. The results show that seasonal and spatial distributions of phytoplankton biomass in the SCS are primarily influenced by the monsoon winds and oceanic environments. Off the east coast of Vietnam, Chl-a concentration is a peak in August, a jet shape extending into the interior SCS, which is associated with strong southwesterly monsoon winds, the coastal upwetling induced by offshore Ekman transport and the strong offshore current in the western SCS. In December, high Chl-a concentration appears in the upwelling region off the northwest coast of Luzon and spreads southwestward. Strong mixing by the strong northeasterly monsoon winds, the cyclonic circulation, southwestward coastal currents and river discharge have impacts on distribution of phytoplankton, so that the high phytoplankton biomass extends from the coastal areas over the northern SCS to the entire SCS in winter. These research activities could be important for revealing spatial and temporal patterns of phytoplankton and their interactions with physical environments in the SCS.     

南海沿海季节性海平面异常变化特征及成因分析

Based on sea level, air temperature, sea surface temperature(SST), air pressure and wind data during 1980–2014,this paper uses Morlet wavelet transform, Estuarine Coastal Ocean Model(ECOM) and so on to investigate the characteristics and possible causes of seasonal sea level anomalies along the South China Sea(SCS) coast. The research results show that:(1) Seasonal sea level anomalies often occur from January to February and from June to October. The frequency of sea level anomalies is the most in August, showing a growing trend in recent years. In addition, the occurring frequency of negative sea level anomaly accounts for 50% of the total abnormal number.(2) The seasonal sea level anomalies are closely related to ENSO events. The negative anomalies always occurred during the El Ni?o events, while the positive anomalies occurred during the La Ni?a(late El Ni?o) events. In addition, the seasonal sea level oscillation periods of 4–7 a associated with ENSO are the strongest in winter, with the amplitude over 2 cm.(3) Abnormal wind is an important factor to affect the seasonal sea level anomalies in the coastal region of the SCS. Wind-driven sea level height(SSH) is basically consistent with the seasonal sea level anomalies. Moreover, the influence of the tropical cyclone in the coastal region of the SCS is concentrated in summer and autumn, contributing to the seasonal sea level anomalies.(4) Seasonal variations of sea level, SST and air temperature are basically consistent along the coast of the SCS, but the seasonal sea level anomalies have no much correlation with the SST and air temperature.     

东海沿海季节性海平面异常成因

Based on the analysis of sea level, air temperature, sea surface temperature(SST), air pressure and wind data during 1980–2013, the causes of seasonal sea level anomalies in the coastal region of the East China Sea(ECS) are investigated. The research results show:(1) sea level along the coastal region of the ECS takes on strong seasonal variation. The annual range is 30–45 cm, larger in the north than in the south. From north to south, the phase of sea level changes from 140° to 231°, with a difference of nearly 3 months.(2) Monthly mean sea level(MSL)anomalies often occur from August to next February along the coast region of the ECS. The number of sea level anomalies is at most from January to February and from August to October, showing a growing trend in recent years.(3) Anomalous wind field is an important factor to affect the sea level variation in the coastal region of the ECS. Monthly MSL anomaly is closely related to wind field anomaly and air pressure field anomaly. Wind-driven current is essentially consistent with sea surface height. In August 2012, the sea surface heights at the coastal stations driven by wind field have contributed 50%–80% of MSL anomalies.(4) The annual variations for sea level,SST and air temperature along the coastal region of the ECS are mainly caused by solar radiation with a period of12 months. But the correlation coefficients of sea level anomalies with SST anomalies and air temperature anomalies are all less than 0.1.(5) Seasonal sea level variations contain the long-term trends and all kinds of periodic changes. Sea level oscillations vary in different seasons in the coastal region of the ECS. In winter and spring, the oscillation of 4–7 a related to El Ni?o is stronger and its amplitude exceeds 2 cm. In summer and autumn, the oscillations of 2–3 a and quasi 9 a are most significant, and their amplitudes also exceed 2 cm. The height of sea level is lifted up when the different oscillations superposed. On the other hand, the height of sea level is fallen down.     

A preliminary study on the response of marine primary production to monsoon variations in the South China Sea Basic characteristics

Seasonal, interannual and interdecadal variations of monsoon over the South China Sea （SCS） directly influence the ocean circulation and the mass transport process, etc. , especially the changes of horizontal circulation pattern and upwelling area. These changes directly influence the nutrient transport and the photosynthesis of phytoplankton, which induce the change of the marine ecosystem in the SCS, including the change of marine primary production in this sea area. On the basis of climatic data for long-time series and primary production estimated by remote sensing, the multi-time scale variations of monsoon, seasonal and interannual variations of primary production, and the response of primary production to monsoon variations were analyzed. Furthermore, the spatio-temporal variations of primary production in different sea areas of the SCS and their relations to the monsoon variations were given. The results showed that the strong southwesterly prevailed over the SCS in summer whereas the vigorous northeasterly in winter. The seasonal primary production in the entire sea area of the SCS also produced a strong peak in winter and a suhpeak in summer. And the seasonal primary production distributions displayed different characteristics in every typical sea area. The variations of the annual and summer averaged primary production in the entire sea area of the SCS showed almost the same rising trend as the intensity of the summer monsoon. Especially for 1998, the summer monsoon reached almost the minimum in the past 54 a when the primary production was also found much lower than any other year （ 1999--2005 ）. The responses of annual primary production to monsoon variation were displayed to different extent in different sea areas of the SCS ; especially it was better in the deep sea basin. Such research activities could be very important for revealing the response of marine ecosystem to the monsoon variations in the SCS.     

Global air-sea surface carbon-dioxide transfer velocity and flux estimated using ERS-2 data and a new parametric formula

Using data from the European remote sensing scatterometer（ERS-2） from July 1997 to August 1998,global distributions of the air-sea CO₂ transfer velocity and flux are retrieved.A new model of the air-sea CO₂ transfer velocity with surface wind speed and wave steepness is proposed.The wave steepness（5） is retrieved using a neural network（NN） model from ERS-2 scatterometer data,while the wind speed is directly derived by the ERS-2 scatterometer.The new model agrees well with the formulations based on the wind speed and the variation in the wind speed dependent relationships presented in many previous studies can be explained by this proposed relation with variation in wave steepness effect.Seasonally global maps of gas transfer velocity and llux are shown on the basis of the new model and the seasonal variations of the transfer velocity and llux during the 1 a period.The global mean gas transfer velocity is 30 cm/h after area-weighting and Schmidt number correction and its accuracy remains calculation with in situ data.The highest transfer velocity occurs around 60°N and 60°S,while the lowest on the equator.The total air to sea CO₂ llux（calculated by carbon） in that year is 1.77 Pg.The strongest source of CO₂ is in the equatorial east Pacific Ocean, while the strongest sink is in the 68°N.Full exploration of the uncertainty of this estimate awaits further data.An effectual method is provided to calculate the effect of waves on the determination of air-sea CO₂ transfer velocity and fluxes with ERS-2 scatterometer data.     

使用参数化初猜测谱算法提取VV极化Sentinel-1 SAR图像的海浪要素并与ECMWF再分析数据以及浮标数据进行验证对比

The purpose is to study the accuracy of ocean wave parameters retrieved from C-band VV-polarization Sentinel-1Synthetic Aperture Radar(SAR) images, including both significant wave height(SWH) and mean wave period(MWP), which are both calculated from a SAR-derived wave spectrum. The wind direction from in situ buoys is used and then the wind speed is retrieved by using a new C-band geophysical model function(GMF) model,denoted as C-SARMOD. Continuously, an algorithm parameterized first-guess spectra method(PFSM) is employed to retrieve the SWH and the MWP by using the SAR-derived wind speed. Forty–five VV-polarization Sentinel-1 SAR images are collected, which cover the in situ buoys around US coastal waters. A total of 52 subscenes are selected from those images. The retrieval results are compared with the measurements from in situ buoys. The comparison performs good for a wind retrieval, showing a 1.6 m/s standard deviation(STD) of the wind speed, while a 0.54 m STD of the SWH and a 2.14 s STD of the MWP are exhibited with an acceptable error.Additional 50 images taken in China's seas were also implemented by using the algorithm PFSM, showing a 0.67 m STD of the SWH and a 2.21 s STD of the MWP compared with European Centre for Medium-range Weather Forecasts(ECMWF) reanalysis grids wave data. The results indicate that the algorithm PFSM works for the wave retrieval from VV-polarization Sentinel-1 SAR image through SAR-derived wind speed by using the new GMF C-SARMOD.     

多源卫星高度计海浪资料在中国近海的验证及应用

Studies of offshore wave climate based on satellite altimeter significant wave height(SWH) have widespread application value. This study used a calibrated multi-altimeter SWH dataset to investigate the wave climate characteristics in the offshore areas of China. First, the SWH measurements from 28 buoys located in China's coastal seas were compared with an Ifremer calibrated altimeter SWH dataset. Although the altimeter dataset tended to slightly overestimate SWH, it was in good agreement with the in situ data in general. The correlation coefficient was 0.97 and the root-mean-square(RMS) of differences was 0.30 m. The validation results showed a slight difference in different areas. The correlation coefficient was the maximum(0.97) and the RMS difference was the minimum(0.28 m) in the area from the East China Sea to the north of the South China Sea.The correlation coefficient of approximately 0.95 was relatively low in the seas off the Changjiang(Yangtze River) Estuary. The RMS difference was the maximum(0.32 m) in the seas off the Changjiang Estuary and was0.30 m in the Bohai Sea and the Yellow Sea. Based on the above evidence, it is confirmed that the multialtimeter wave data are reliable in China's offshore areas. Then, the characteristics of the wave field, including the frequency of huge waves and the multi-year return SWH in China's offshore seas were analyzed using the23-year altimeter wave dataset. The 23-year mean SWH generally ranged from 0.6–2.2 m. The greatest SWH appeared in the southeast of the China East Sea, the Taiwan Strait and the northeast of the South China Sea.Obvious seasonal variation of SWH was found in most areas; SWH was greater in winter and autumn than in summer and spring. Extreme waves greater than 4 m in height mainly occurred in the following areas: the southeast of the East China Sea, the south of the Ryukyu Islands, the east of Taiwan-Luzon Island, and the Dongsha Islands extending to the Zhongsha Islands, and the frequency of extreme waves was 3%–6%. Extreme waves occurred most frequently in autumn and rarely in spring. The 100-year return wave height was greatest from the northwest Pacific seas extending to southeast of the Ryukyu Islands(9–12 m), and the northeast of the South China Sea and the East China Sea had the second largest wave heights(7–11 m). For inshore areas, the100-year return wave height was the greatest in the waters off the east coast of Guangdong Province and the south coast of Zhejiang Province(7–8 m), whereas it was at a minimum in the area from the Changjiang Estuary to the Bohai Sea(4–6 m). An investigation of sampling effects indicates that when using the 1°×1°grid dataset, although the combination of nine altimeters obviously enhanced the time and space coverage of sampling, the accuracy of statistical results, particularly extreme values obtained from the dataset, still suffered from undersampling problems because the time sampling percent in each 1°×1°grid cell was always less than33%.     

石岛海域海浪数值模拟及特征分析

本文基于SWAN(Simulating Waves Nearshore)模式研究了2001～2016年石岛海浪有效波高的季节和年际变化特征,评估了不同区域风场对其贡献,并探讨了其与ENSO的关系。结果表明,石岛有效波高受黄海季风系统的影响呈现显著的季节变化:12月份最大, 6月份最小, 1%大波有效波高季节变化不显著。石岛有效波高年际变化信号显著,其与风速年际变化之间的关系存在季节性差异:石岛有效波高和石岛、黄海区域平均风速不同月份的年际异常分别在7、10月份相关性较高,而石岛1%大波有效波高和石岛、黄海区域平均1%大风风速不同月份的年际异常则在8月份左右相关性最高。不同区域风场对石岛有效波高场的影响也呈现了季节性差异:夏季,黄海南部区域风场对石岛海浪的贡献较大,而石岛风场的贡献较小;冬季,石岛风场的贡献较大。ENSO(El Ni?o-Southern Oscillation)事件会对石岛有效波高的年际变化产生一定的影响,但影响比较小。本研究旨在对石岛海浪在季节和年际尺度上的变化特征以及风场等影响因素进行研究,对该海域海浪场进行了详细的认识,对了解该海域海浪有重要意义。     

Wind-Wave Characteristics and Climate Variability in the Indian Ocean Region Using Altimeter Data

The significant wave height and wind speed derived for the period 1993–2010 from altimeter data sets over the Arabian Sea, Bay of Bengal, and the Indian Ocean categorized as six zones has been analyzed. The average variation of both significant wave height and wind speed is found to be almost stable for the period of study. The study reveals that the average wind speed increases by about 6cm/sec/year during monsoon and post monsoon in the southern Indian Ocean. The distribution of wind and waves was studied in the context of seasonal variations. In addition, the average inter-annual and intra-annual variations along with the statistical parameters such as standard deviation, and root mean square wave height for the six zones are also reported in this paper.     

1988—2009年中国海波候、风候统计分析

利用高精度、高时空分辨率、长时间序列的CCMP(Cross-Calibrated,Multi-Platform)风场,驱动国际先进的第三代海浪模式WAVEWATCH-Ⅲ(WW3),得到中国海1988年1月～2009年12月的海浪场。对中国海的波候(风候)进行精细化的统计分析,分析了海表风场和浪场的季节特征、极值风速与极值波高、风力等级频率和浪级频率、海表风速和波高的逐年变化趋势,结果显示:(1)中国海的海浪场与海表风场具有较好的一致性,尤其是在DJF(December,January,February)期间;海表风速和波高在MAM(March,April,May)期间为全年最低,在DJF期间达到全年最大;MAM和JJA(June,July,August)期间,中国海大部分海域的波周期在3～5.5s,SON(September,October,November)和DJF期间为4.5～6.5s。(2)中国海极值风速、极值波高的大值区分布于渤海中部海域、琉球群岛附近海域和台湾以东广阔洋面、台湾海峡、东沙群岛附近海域、北部湾海域、中沙群岛南部海域。(3)吕宋海峡在MAM、SON、DJF期间均为6级以上大风和4m以上大浪的相对高频海域,JJA期间,6级以上大风的高频海域位于中国南半岛东南部海域,4m以上大浪主要出现在10°N以北。(4)在近22a期间,中国海大部分海域的海表风速、有效波高呈显著性逐年线性递增趋势,风速递增趋势约0.06～0.15m.s-1.a-1,波高递增趋势约0.005～0.03m.a-1。     

WWATCH模式模拟南海海浪场的结果分析

利用美国NOAA/NCEP环境模拟中心海洋模拟小组近年新开发的一个准业务化的海浪数值模式WAVEWATCH Ⅲ(以下简称WWATCH),以每天4次的NOAA/NCEP再分析风场资料为输入,模拟了1996年的南海海域的海面风浪场,通过分析TOPEX/Poseidon(以下简称T/P)高度计的上升和下降轨道在南海海域的交叉点位置处的风、浪观测资料与NCEP风场和WWATCH模式模拟的有效波高大小,可以看出,NCEP风场基本与T/P高度计的风速观测结果一致,相应的模式模拟的有效波高也基本与卫星高度计的有效波高观测结果相一致,但从空间上看,在计算区域中心附近海域的结果一致性较好,靠近计算边界附近海域的结果相对较差,但这种因边界而影响模拟结果的范围很有限;从时间上看,冬季风期间的结果一致性较好,而夏季风期间的结果偏小的趋势明显,并且这种偏小主要出现在夏季风期间的极小风速值附近。     

黄海海浪季节变化的数值模拟研究

利用第三代海浪数值模式SWAN,研究了黄海海浪有效波高的季节变化特征及相关的物理过程。结果表明,在黄海的大部分区域,混合浪有效波高的最大值出现在冬季,而最小值则基本出现在夏季。北黄海北部和山东半岛南岸的近海海域呈现稍微不同的季节变化,有效波高的最大值出现在春季。全年4个季节中混合浪有效波高的空间分布基本一致:均在济州岛西南最大,沿黄海中部区域向北和由中部区域向近岸区域逐渐减小。黄海海浪为风浪占主,涌浪有效波高远小于风浪有效波高。在黄海的大部分区域,白冠耗散和四波非线性相互作用对黄海海浪的季节变化均至关重要;对于外海区域,四波非线性相互作用更为重要,而对于近海区域,白冠耗散则影响更大。本研究旨在研究黄海海浪的季节变化特征及其物理过程,为进一步探讨该海域海浪在其他时间尺度上的变异特征和动力学过程提供研究基础。     

南海海面风、浪场时空变化特征及其关系分析

利用长时间序列的卫星观测数据,对南海海域的风、浪场时空分布及其相互关系进行了分析。结果显示,海面风距平场VEOF分解后得到的第一模态具有明显的季节变化,即季风特征,说明季风是影响整个南海风速的主要因素;第二模态具有较强的区域变化特征,是季风转换时期的距平场特征;第三模态反映的是海面风距平场受陆地地形影响所表现的分布特征。有效波高距平场EOF分解后得到的第一模态、第二模态与风距平场的前2个模态的空间分布较为相似,并且,风、浪距平场第一模态间的相关系数达0.76,均说明南海作为边缘海其波浪场与风场变化有很好的相关性。有效波高第三模态的分布与风场的第三模态相关性较弱,反映的是受海底地形影响所表现的分布特征。     

Seismic ambient noise around the South China Sea: seasonal and spatial variations, and implications for its climate and surface circulation

With its strong seasonal variation in wave climate and various bathymetric features due to the complex tectonics, the South China Sea (SCS) provides a natural laboratory to study the microseism. We collected data from seismic stations around the SCS and calculated their noise spectra, through which seasonal and spatial variations of microseism, as well as the general feature of seismic ambient noise in this marginal sea were revealed. Microseism seasonal variations in general reflect influences of the East Asian monsoon in winter and the Indian monsoon in summer, respectively. The two microseism components, the single frequency microseism (SFM) and the double frequency microseism (DFM), show striking alternating variation patterns both seasonally and spatially. These variation patterns, along with the bathymetric feature near the stations, indicate SFM and DFM are generated through different physical mechanisms. More interestingly, seasonal and spatial variations of DFM appear to be consistent with the basin-scale surface circulation model of the SCS, in which the upper SCS experiences cyclonic in winter and anti-cyclonic in summer. These consistencies provide observational evidence for the hypothesis that the cyclonic depression is a favorable condition to generate DFM.     

太平洋波高分布及变化规律研究

使用 Topex/ Poseidon卫星高度计 1 992年 1 0月～ 1 998年 1 2月连续 75个月 ,2 30个重复周期的有效波高资料对南北太平洋的有效波高进行了统计 ,分析了太平洋有效波高的多年平均、多年各月平均和多年各季平均的空间分布特征和时间变化规律。结果表明 ,太平洋波高分布具有明显季节变化的规律 ,与太平洋的风速分布特征具有良好的对应关系     

南海海域浮游植物叶绿素与海表温度季节变化特征分析

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