舟山摘箬山岛风能资源评价

文章利用摘箬山岛风电场70 m高测风塔2011年1月—2014年1月的观测资料,对平均风速、风速频率、风向频率、风能频率、有效风力时数及风功率密度等风能参数进行计算分析,并依据国标《风电场风能资源评估方法》(GB/T18710-2002)中风功率密度等级划分标准对风电场的风能资源进行评估。结果表明:风电场各高度年平均风速在3.28~6.56 m/s,风速频率主要集中区间为1~8 m/s,有效风力时数为54.5%~86.9%,年平均风功率密度为54.8~283.2 W/m2。风电场10 m和70 m处主导风向分别为N风和S风,频率分别为13.0%和13.4%,主导风能分别为N风和NNW风,频率分别为14.7%和14.8%。该风电场风功率密度接近3级,具有一定开发利用价值。     

基于CCMP卫星资料的中国海域风能资源分析

基于1988—2011年CCMP卫星资料对中国海域的风能资源进行分析评估,研究中国海域风能资源的空间格局及气候变化特征,并进行风能资源区划。研究结果表明:(1)中国海域年风功率密度各海域分布在79.2(琼州海峡)~465.8(巴士海峡)W/m~2,其中东海南部、南海东北部和巴士海峡的年平均风功率密度大于400 W/m~2,其次为南海中东部、东海北部、台湾海峡、台湾以东洋面(300~400 W/m~2),渤海海峡、黄海北部、北部湾、渤海和琼州海峡的风功率密度在200 W/m~2以下;(2)DJF期间,中国海区风功率密度平均值最大(412.5 W/m2),大值区的风功率密度达800~1000W/m~2;JJA期间,中国海域风功率密度平均值最小(159.4 W/m~2);(3)1988—2011年中国各海区风功能密度上升趋势为20.8(琼州海峡)~124.7(台湾海峡)W/(m~2?10 a),除南海西南部和南海东南部海区外,其他海区的变化趋势均通过了0.05的显著性检验;(4)中国海域风能资源分区结果表明,中国海区超过80%的海区适合并网风力发电,其中非常适合的海域占海区面积的62.3%。在风电开发技术可控范围内(水深5~50 m),台湾海峡、南海东北近海海区(水深0~50 m)风能资源最丰富,最高处达490 W/m~2,其次是东海北部近海海区(水深20~50 m),风功率密度达300~350 W/m~2。     

龙口海洋站风能资源分析与评价

根据中国《风电场风能资源评估方法》和相关技术规定,对龙口海洋站的风能资源进行了分析与评价.结果表明,1995 -2008年龙口海洋站10m处的平均风速为6.8 m/s,年平均风功率密度为377 W/m2,年平均有效小时数为7589 h,主风向较为显著,风能分布集中,湍流强度处于中等水平.龙口海洋站附近区域风能资源丰富,...     

上海海域站位观测风能资源分析

为探究上海海域风能资源的情况,按照《风电场风能资源评估方法》和《全国风能资源评价技术规定》中的相关方法,对东海浮标（深远海）和南槽灯船（近海）处2013—2018年实测的气象资料进行了分析比较。结果表明,东海浮标处累年平均风速为6.30 m/s,南槽灯船处累年平均风速为5.80 m/s,东海浮标处累年平均风速比南槽灯船处高8.6%;东海浮标处累年平均风功率密度为345.1 W/m²,南槽灯船处累年平均风功率密度为239.5 W/m²,东海浮标处累年平均风功率密度比南槽灯船处高44.1%;东海浮标处湍流强度的累年平均值为0.114,比南槽灯船处（0.125）低8.8%,对发电机组运行的影响低于南槽灯船处。本研究结果表明,东海浮标处的风能资源比南槽灯船处丰富,东海深远海的风能资源比近海丰富。     

我国近海风能资源分布特征分析

基于美国NCEP(National Centers for Environmental Prediction)的CFSR(Climate Forecast System Reanalysis)近20a(1991-2010)10m风场再分析数据(0.3°×0.3°,1h/次,简称CFSR风场),对我国近海风能资源分布特征进行了统计分析与评估。利用天津渤海A平台观测站(118°25′E,38°27′N)逐时观测风速数据对CFSR风速数据进行了检验,发现均方根误差和平均偏差仅为均较小(分别为2.28m/s与0.16m/s)。基于此CFSR风场,本文章进一步统计并给出了我国陆地年平均风功率密度分布,结果与第三次风能普查(1971-2000年)及相关文献结果 (1991-2010年)相当一致。依据国家风电场风能资源评估方法,由CFSR风场推算了我国近海20a平均的70m高度风能资源分布。结果显示,年平均风功率密度均达到了200 W/m2以上,大于6m/s的风速累积小时数为4 000h以上;其中台湾海峡和东海南部海区风能最为丰富,黄海中部、渤海中部和辽东湾海区风能次之。参照海上风场选址要求,28°N以北的近岸海域由于水深较浅,30m/s以上风速发生频次极低,比较适合建立海上风电场。     

基于ERA-interim资料中国近海风能资源时空分布

未来风能开发的重心将逐渐转移到风能更为丰富的近海区域,通过1979—2014年的ERA-interim再分析资料,对不同高度和水深条件下的中国近海风能资源的时空分布特征进行了分析研究。结果显示我国近海风能资源整体呈南高北低分布,大值区位于台湾海峡、巴士海峡及南海东南部,过去36 a我国近海风能资源没有显著变化趋势。风能资源所研究区域的水深越深、风机高度越高,风电的可开发潜力就越大,100 m高度条件及50 m水深条件下我国近海年平均风功率密度约为160 W/m2。此外我国近海风能资源存在明显的季节差异,冬季开发条件最好,夏季最差,且与ENSO存在显著的遥相关关系。     

琼州海峡潮流能资源的数值模拟评估

近年来,我国能源消耗量不断的增长使我们更加重视可再生能源的开发利用,而我国近海拥有复杂的海岸线和广阔的大陆架,其中许多海域蕴藏着丰富的潮流能资源。潮流能资源评估则是其电站站址选择、发电量预测等工程设计的首要工作。结合两个站位的潮流实测数据,本文利用FVCOM海洋环流数值模式较好的模拟了琼州海峡潮波传播状况,分析了该海域潮流能资源水平分布规律和时间变化特征,初步估算了该水道的潮流能的理论蕴藏量,并采用FLUX方法对该水道的技术可开发量进行了评估。结果表明,琼州海峡中心海域功率密度高,两岸资源低;可能最大流速、大潮年平均最大功率密度、小潮年平均功率密度和年平均功率密度等特征值分布基本相似;其丰富区域出现在海峡东口南部海域以及海峡中部海域,其中东口南部海域可能最大流速可达4.6 m/s,表层流大潮年平均最大功率密度为5996 W/m²,小潮平均最大功率密度仅为467 W/m²,年平均功率密度为819 W/m²,代表点超过0.7 m/s的潮流流速年统计时间约为4717 h;海峡潮流能资源理论蕴藏量为189.55MW,利用FLUX、FARM、GC方法得到该水道的潮流能可开发量分别为249GW/yr、20.2GW/yr和263GW/yr。     

山东半岛沿海风能资源评估与分布研究

全球性的能源危机和气候变化,推动了风力发电在世界范围的迅速发展,调查风能资源分布是大规模发展风电的关键步骤.利用1990-2007年山东半岛10个风观测站的气象观测资料,对山东半岛沿海风能资源进行了评估.结果表明,风能资源在山东半岛沿海和海岛丰富,可以成为未来风能开发的重点区域.     

宁德沿海风能和波浪能资源评估

收集了宁德沿海2011年9月-2012年8月1周年的风和波浪连续观测资料,并对该海域的风和波浪特征进行了统计分析。该海域观测期间内全年平均风速年均为7.2m/s,平均有效波高为1.04m。常风向为NNE向,强风向为NE向。常浪向为E向,强浪向为E向。根据风和波浪场数据对宁德沿海的风能和波浪能进行评估,评估结果发现宁德沿海的风能和波浪能蕴藏量较丰富,年平均风能密度能达到411W/m~2,平均波浪能密度能达到2.6kW/m。对研究海域重现期波浪极值进行了推算,受东侧四礵列岛阻挡,宁德沿海南部海域主要受SE向波浪影响,北部海域主要受E向波浪影响。若对宁德沿海进行新能源开发,可以进行风能和波浪能的联合开发利用。     

俄罗斯北部海域风能资源的时空特征分析

利用欧洲中期天气预报中心(ECMWF)风场资料,对1997—2016年俄罗斯北部海域风能资源展开评估,并建立选址指标体系,识别潜在海上风电场建址区域。结果表明:俄罗斯北部海域的风功率密度大小和风功率密度等级分布均为"西高东低"型,即巴伦支海风能资源最丰富且风功率密度等级最高,东西伯利亚海风能资源较少且风功率密度等级最低;有效风速出现频率为单谷型,夏季出现谷值,春季、秋季和冬季出现峰值;风功率密度变异系数有明显季节变化,冬季变异系数较高,夏季变异系数达到最低值;喀拉海适宜开发近海风能资源,巴伦支海适宜开发深海风能资源;风向频率最高的风向是NE,其次是NNE与ENE向。研究结果可为未来国内相关单位参与北极风能资源开发提供依据和参考。     

Comparative Analysis of Satellite Databases of Incoming Short-Wavelength Fluxes to the World Ocean Surface

This work involves satellite data provided by EUMETSAT’s Satellite Application Facility on Climate Monitoring (CM SAF). The data cover the period from 1982 to 2015 depending on the type of satellite and coverage region. It has been found that monthly and daily average values for regional databases in the area of their overlap are overestimated for the western part and underestimated in the eastern part by approximately 25 W/m². The largest values for the mismatch of fluxes are observed at points close to the centers of database areas where the root-mean-square deviation reaches approximately 25 W/m². Comparative analysis of global and regional data reveals an area corresponding to the center of visibility for geostationary satellites. In this area, data from the satellites are comparable with global data; the difference between fluxes is less than 10 W/m². At the periphery of the satellite visibility area, the situation is the reverse: the global coverage data are more overstated than the regional data of geostationary satellites by more than 10 W/m²; the root-meansquare deviation is about 30 W/m² for daily average values and about 45 W/m² for hourly average values.     

Satellite-derived measurements of spatial and temporal chlorophyll-a variability in Funka Bay, southwestern Hokkaido, Japan

Chlorophyll-a (chl-a) concentration has an important economic effect in coastal and marine environments on fisheries resources and marine aquaculture development. Monthly climatologies the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) derived chl-a from February 1998 to August 2004 around Funka Bay were used to investigate the spatial and temporal variability of chl-a concentrations. SeaWiFS-derived suspended sediment, MODIS derived sea surface temperature (SST), solar radiation and wind data were also analyzed. Results showed two distinct chlorophyll blooms in spring and autumn. Chl-a concentrations were relatively low (<0.3 mg m⁻³) in the bay during summer, with high concentrations occurring along the coast, particularly near Yakumo and Shiraoi. In spring, chl-a concentrations increased, and a large (>2 mg m⁻³) phytoplankton bloom occurred. The spatial and temporal patterns were further confirmed by empirical orthogonal function (EOF) analysis. About 83.94% of the variability could be explained by the first three modes. The first chl-a mode (77.93% of the total variance) explained the general seasonal cycle and quantified interannual variability in the bay. The spring condition was explained by the second mode (3.89% of the total variance), while the third mode (2.12% of the total variance) was associated with autumn condition. Local forcing such as the timing of intrusion of Oyashio water, wind condition and surface heating are the mechanisms that controlled the spatial and temporal variations of chlorophyll concentrations. Moreover, the variation of chlorophyll concentration along the coast seemed to be influenced by suspended sediment caused by resuspension or river discharge.     

基于长时间序列ERA-Interim再分析资料的广东沿海波浪能资源分布特征分析

波浪能的开发利用作为海洋可再生能源发展的重要组成部分,持续受到社会和学界的广泛关注。广东省波浪能资源的开发利用具有得天独厚的优势,但其发展水平还处于探索阶段,亟须进一步加强。本文利用长达40年(1979—2018年)的ERA-Interim再分析波浪资料,从总体分布特征上分析了广东沿海波浪能资源及其长期变化趋势。粤东-珠江口-粤西沿岸一线,波浪能资源呈现"低-高-低-高-低"的分布特征,具有显著的季节变化特征;长期变化趋势上呈现显著的逐年线性递增特征,递增速率为0.054 3 kW/(m·a),其中1979—1994年变化较为快速,2001—2018年变化较为平缓。     

Annual and Seasonal Variations of the Sea Surface Heat Fluxes in the East Asian Marginal Seas

Based on the twice-daily marine atmospheric variables which were derived mostly from the weather maps for 18 years period from 1978 to 1995, the surface heat flux over the East Asian marginal seas was calculated at 0.5°×0.5° grid points twice a day. The annual mean distribution of the net heat flux shows that the maximum heat loss occurs in the central part of the Yellow Sea, along the Kuroshio axis and along the west coast of the northern Japanese islands. The area off Vladivostok turned out to be a heat-losing region, however, on the average, the amount of heat loss is minimum over the study area and the estuary of the Yangtze River also appears as a region of the minimum heat loss. The seasonal variations of heat flux show that the period of heat gain is longest in the Yellow Sea, and the maximum heat gain occurs in June. The maximum heat loss occurs in January over the study area, except the Yellow Sea where the heat loss is maximum in December. The annual mean value of the net heat flux in the East/Japan Sea is −108 W/m² which is about twice the value of Hirose et al. (1996) or about 30% higher than Kato and Asai (1983). For the Yellow Sea, it is about −89 W/m² and it becomes −75 W/m² in the East China Sea. This increase in values of the net heat flux comes mostly from the turbulent fluxes which are strongly dependent on the wind speed, which fluctuates largely during the winter season. This revised version was published online in August 2006 with corrections to the Cover Date.     

基于ERA5再分析资料的中国近海浅水区域风能潜力评估

风能潜力评估是风电场选址工作的基础工作。本文基于欧洲中期天气预报中心的ERA5再分析数据,采用风功率密度（Wind Power Density,WPD）中值、容量系数（Capacity Factor,CF）以及鲁棒性变异系数（Robust Coefficient of Variation, RCoV）三种指标,对中国近海浅水区域的风能潜力进行评估,研究结果表明:（1）台湾海峡和东海南部风能资源最为丰富并且风能利用率最高,风功率密度中值和容量系数分别为400~900 和0.45~0.7。总体来看,风功率密度中值从渤海到台湾海峡,呈逐渐增加的趋势,从台湾海峡到琼州湾,呈逐渐减小的趋势,容量系数大小分布情况相似。（2）鲁棒性变异系数大小无明显分布规律,广东湛江近岸海域鲁棒性变异系数在0.70~0.75之间,风能发电量最为稳定,但该地区的风能资源丰富程度较低。（3）福州近岸海域不仅有丰富的风能资源和风能利用率,且发电量较为稳定。在不考虑其它因素的影响下,是中国近海浅水区域建设海上风电场的最佳地点。     

2014年大西洋水在楚科奇边陲区域的上边界混合

This study presents an analysis of the CTD data and the turbulent microstructure data collected in 2014, the turbulent mixing environment above the Atlantic Water(AW) around the Chukchi Borderland region is studied.Surface wind becomes more efficient in driving the upper ocean movement along with the rapid decline of sea ice,thus results in a more restless interior of the Arctic Ocean. The turbulent dissipation rate is in the range of4.60×10~(–10)~(–3.31×10~(–9) W/kg with a mean value of 1.33×10~(–9) W/kg, while the diapycnal diffusivity is in the range of1.45×10~(–6)–1.46×10~(–5)m~2/s with a mean value of 4.84×10~(–6) m~2/s in 200–300 m(above the AW). After investigating on the traditional factors(i.e., wind, topography and tides) that may contribute to the turbulent dissipation rate, the results show that the tidal kinetic energy plays a dominating role in the vertical mixing above the AW. Besides, the swing of the Beaufort Gyre(BG) has an impact on the vertical shear of the geostrophic current and may contribute to the regional difference of turbulent mixing. The parameterized method for the double-diffusive convection flux above the AW is validated by the direct turbulent microstructure results.     

Coastal Upwelling Activity on the Pacific Shelf of the Baja California Peninsula

High primary productivity on the Pacific coast of the Baja California Peninsula is usually related to coastal upwelling activity that injects nutrients into the euphotic zone in response to prevailing longshore winds (from the northwest to north). The upwelling process has maximum intensity from April to June, with the coastal upwelling index varying from 50 to 300 m³/s per 100 m of coastline. Along the entire coast of the peninsula, the upwelling intensity changes in accordance with local wind conditions and bottom topography. Spatial variability can also be modulated by the influence of mesoscale meanders of the California Current. We have identified the seasonal and synoptic variability of upwelling signatures on the Baja California shelf, using averaged monthly and weekly sea surface temperature (SST) distributions obtained from remote sensing imagery from the Advanced Very High Resolution Radiometer in the period from 1996 to 2001. Analysis of SST distribution and direct experimental data on temperature and nutrient concentration shows that the areas with the coldest SST anomalies were closely related to the bottom slope, shelf width, and coastline orientation relating to wind direction. We also assume that the nutrient transport into the coastal lagoons may be forced by the coupling of coastal upwelling and tidal pumping of surface waters into the lagoon system. This revised version was published online in August 2006 with corrections to the Cover Date.     

2006年冬季北黄海网采浮游植物群落结构

根据2006年12月30日—至2007年1月17日北黄海的调查资料,对该海域浮游植物的种类组成、优势种、丰度及其分布和多样性等基本状况进行了分析。本次调查共鉴定浮游植物4门68属131种,主要以温带近岸和广布性种为主,其中硅藻有53属113种,占总种数的86.3%,甲藻有11属16种,占总种数的12.2%。浮游植物丰度平均值为88.89×104个/m3,硅藻丰度平均值为86.58×104个/m3,甲藻丰度平均值为2.28×104个/m3,硅藻丰度分布趋势决定了浮游植物丰度的分布趋势。辽宁南岸是浮游植物密集区,山东半岛北岸其次,而北黄海中部是浮游植物的稀疏区。优势种为:短角弯角藻(Eucampia zodiacus)、具槽帕拉藻(Paralia sulcata)、尖刺拟菱形藻(Pseu-do-nitzschia pungens)、密连角毛藻(Chaetoceros densus)、柔弱角毛藻(Chaetoceros debilis)、刚毛根管藻(Rhizosolenia setigera)。浮游植物群落Shannon-Weiner物种多样性指数平均值为1.80,Peilou均匀度指数平均值为0.42。与1959年1月相比,2007年1月北黄海浮游植物丰度由150.00×104个/m3降为88.89×104个/m3,下降了近41%,硅藻丰度由148.00×104个/m3降为86.58×104个/m3,而甲藻丰度由1.25×104个/m3上升为2.28×104个/m3,占浮游植物丰度的比例由0.8%上升为2.5%。主要优势种及优势属也发生了一定程度的变化,但浮游植物群落结构仍以硅藻为主、甲藻其次,浮游植物丰度总的分布格局变化不明显。     

Delta lobe degradation and hurricane impacts governing large-scale coastal behavior,South-central Louisiana,USA

A large deficit in the coastal sediment budget, high rates of relative sea-level rise (~0.9 cm/year), and storm-induced current and wave erosion are forcing barrier shoreface retreat along the periphery of the Mississippi River delta plain. Additionally, conversion of interior wetlands to open water has increased the bay tidal prism, resulting in degradation of barrier islands due to inlet widening, formation of new inlets, and sediment sequestration at ebb-tidal deltas. Single-beam bathymetric surveys along a 165-km stretch of south-central Louisiana barrier coast, from Raccoon Point in Terrebonne Parish to Sandy Point in Plaquemines Parish, were conducted in 2006. These data, combined with historical bathymetry from three time periods (dating to the 1880s), provide a series of digital elevation models that were used to calculate sediment volumetric changes and determine long-term erosional-depositional trends. Dominant patterns during the 125-year period include (1) erosion of ~1.6 × 10⁹ m³ from the shoreface, forcing up to 3 km of shoreface retreat, (2) sediment deposition in coastal bights and at ebb-tidal deltas, and (3) a combined increase in tidal inlet cross-sectional area from ~41,400 m² to ~139,500 m². Bathymetric and shoreline change datasets separated by shorter time periods (sub-annual) demonstrate that these long-term trends are driven by processes associated with major hurricane impacts, and that rates of shoreface erosion are an order of magnitude greater during active hurricane seasons compared to long-term trends.