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1.
3种海面风场资料在台湾海峡的比较和评估   总被引:7,自引:3,他引:4  
本文对3种海面风场资料(CCMP、NCEP、ERA)在台湾海峡风场的平面分布和时间变化特征进行了相互比较,并应用2011年浮标观测的风速和风向资料分别对3种风场的误差进行了分析及评估。主要结论如下:(1)3种资料风场的平面分布、季节变化和年际变化特征基本一致,差异主要表现在冬季NCEP资料在海峡中部和南部的风速相对CCMP和ERA资料较大;(2)CCMP资料的风速偏差、风速均方根误差和风向均方根误差分别为-0.62m/s、1.67m/s和31°,NCEP分别为0.15m/s、1.64m/s和31°,ERA分别为-1.36m/s、2.4m/s和33°;NCEP资料的风速整体略偏大、CCMP略偏小、ERA偏小明显,CCMP和NCEP资料比ERA资料更接近观测;(3)在西南季风影响期以及风速较小时(风速不大于10m/s)CCMP资料的风速可信度较高、NCEP资料的风速偏大;在东北季风影响期以及风速较大时(大于10m/s)NCEP资料的风速可信度较高、CCMP资料的风速偏小;(4)3种资料的风向误差接近,均在低风速时(风速小于5m/s)误差较大。本文的结论可以为台湾海峡的海洋和大气科学研究选择合适的海面风场资料提供借鉴和参考。  相似文献   

2.
利用中国近海23个浮标对2015年一整年的ASCAT轨道风场和ERA-Interim再分析风场进行质量评估,并对比了ERA-Interim和CFSV2两种再分析风场资料在中国近海的适用性。结果表明:ASCAT在中国近海与浮标风速的一致性优于ERA-Interim,而二者与浮标风向的一致性则相差不大。同时,对比CFSV2与ERA-Interim的误差统计结果发现,CFSV2的风速误差较ERAInterim略小,风向误差相差不大。  相似文献   

3.
利用1990—2014年的ICOADS观测资料,从空间分布、季节变化和不同风速风向特征等角度,对3种海面风场资料(ERA-I、CCMP、CFSR)在吕宋海峡处的风速和风向质量进行了较为全面详细的对比和评估。主要结论如下:(1)3种风场资料在吕宋海峡处风速整体偏小,海峡中部误差较小,南北两端误差较大;均方根误差季节变化显著,6月最小,12月最大;(2)风速误差随不同风速、不同风向而不同,整体呈现高风速时风速较观测偏大,低风速时风速偏小的特点,且低风速段误差较小,高风速段误差随风速增大而增大;(3)3种风场资料在吕宋海峡处风向整体偏右,海峡中部误差较小,南北两端误差较大;季节变化显著,12月最小,5月最大;(4)风向误差随不同风速、不同风向而不同,偏北方向,风向偏右;偏东方向,低风速段风向偏右,高风速段风向偏左;偏南方向,低风速段风向偏左,高风速段风向偏右;偏西方向,风向呈偏左状态。风向误差整体随风速的增大而减小;(5)综合比较,CCMP的风速、风向资料质量均好于其他两种资料。  相似文献   

4.
利用我国东南近海5个浮标站观测资料,对2012—2016年ERA-Interim和NCEP/NCAR再分析资料10 m风、2 m气温、海平面气压的适用性进行了评估。结果表明:NCEP/NCAR的再分析10 m风适用性更好,ERA-Interim的2 m气温适用性更好,海平面气压两者差异不大。风速再分析值与观测值具有较好的一致性,相关系数达0.8~0.9,但再分析风速总体上有偏小的趋势,平均偏差在-1.3~0 m/s之间,均方根误差在1.5~3 m/s。再分析资料的平均风向有顺时针偏差的趋势,温州浮标偏右达14°以上,均方根误差大多在40°~50°。不管风速还是风向,5个浮标站中均以舟山浮标的再分析值与观测值最为接近;分析还表明,再分析资料的冬季风代表性相对较差,这是造成风速和风向系统性偏差的主要原因。再分析资料与观测2 m气温相关系数均在0.95以上,且有偏高的趋势,NCEP偏高更为明显,有4个浮标站平均偏差达1~2℃,而ERA-I仅1个浮标站偏差1~2℃,4个在1℃以内。春季和冬季气温偏高最为明显,春季升温过程存在异常偏高的可能,秋季气温与观测值最为接近。海平面气压适用性较好,总体优于10 m风和2 m气温,且季节间差异也不大。  相似文献   

5.
再分析风场资料在海洋气象的研究中得到广泛应用。本文基于黄河口区域孤东59井验潮站和桩西106验潮站现场观测资料,对CCMP(cross-calibrated multi-platform)、CFSR(climate forecast system reanalysis)、ERA-interim、JRA-55 4种再分析资料的近地面10 m高度风场在黄河口区域的适用性进行对比分析。结果表明CCMP风场数据的平均相对误差和均方根误差最小,与实测数据的相关系数最大,能够较好反映黄河三角洲海域海上风场特征。同时, CCMP风场也能较好反映该海域的强风过程,其中冬季拟合程度比夏季好。基于CCMP风场资料, 1988—2018年黄河三角洲海上风场多年平均风速为5.33 m/s,其中1988—2009年,冬、夏季及全年风速均呈上升趋势;而自2010年后,夏季风速上升速度加快,冬季由于8 m/s以下风速减弱的影响而呈逐年减小趋势,年平均风速也在冬季风控制下呈现降低趋势。  相似文献   

6.
再分析风场资料已广泛应用于我国舟山群岛海域可再生能源评估、海洋灾害预防决策以及港口运维和船舶运输等涉海发展领域,然而不同业务机构所提供的再分析数据在舟山近海的性能表现不一,严重阻碍了此类数据的有效应用。基于2018年全年单点浮标观测资料,综合评价了舟山群岛近海面(10 m)风场的长期变化趋势,并利用误差分析和风玫瑰图等统计工具对6种主流海表风场再分析资料,包括:ECMWF第五代全球大气再分析数据(the 5th generation ECMWF atmospheric reanalysis,ERA5)、NECP第二版全球高分辨率再分析数据(climate forecast system version 2,CFSv2)、美国宇航局物理海洋学分布存档中心的多卫星融合资料(cross-calibrated multi-platform,CCMP)、日本55年再分析数据(Japanese 55-year reanalysis,JRA-55)、第二版现代研究与应用回顾性分析数据(modern-era retrospective analysis for research and applications version 2,MERRA-2)和ECMWF哥白尼大气监测服务再分析数据(the Copernicus Atmosphere Monitoring Service,CAMS)在时间变化特征上进行了对比与评估。研究表明:在综合性能方面,ERA5对风场的再现能力最优,其次为JRA-55;在要素可信度方面,ERA5对风速的再现情况相对较优,而CFSv2的风向再现情况较好;风场产品在不同季节的模拟能力有所差异;不同风场产品在不同风速区间的重构能力也有所不同;在全年风向分布方面,各再分析资料都存在显著的东向偏差。研究结果为不同应用场景下风场资料的选取提供评估依据,并为进一步开发适用于舟山群岛近海的高精度长周期风场数据产品奠定基础。  相似文献   

7.
星载微波散射计是获取全球海面风场信息的主要手段, HY-2B卫星散射计的成功发射为全球海面风场数据获取的持续性提供了重要保障。本文利用欧洲中期天气预报中心(European Center for Medium-Range Weather Forecasts, ECMWF)再分析风场数据、热带大气海洋观测计划(Tropical Atmosphere Ocean Array, TAO)和美国国家数据浮标中心(National Data Buoy Center, NDBC)浮标获取的海面风矢量实测数据, 对HY-2B散射计海面风场数据产品的质量进行统计分析。分析表明, HY-2B风场与ECMWF再分析风场对比, 在4~24m·s-1风速区间内, 风速和风向均方根误差(root mean square error, RMSE)分别为1.58m·s-1和15.34°; 与位于开阔海域的TAO浮标数据对比, 风速、风向RMSE分别为1.03m·s-1和14.98°, 可见HY-2B风场能较好地满足业务化应用的精度要求(风速优于2m·s-1, 风向优于20°)。与主要位于近海海域的NDBC浮标对比, HY-2B风场的风速、风向RMSE分别为1.60m·s-1和19.14°, 说明HY-2B散射计同时具备了对近海海域风场的良好观测能力。本文还发现HY-2B风场质量会随风速、地面交轨位置等变化, 为用户更好地使用HY-2B风场产品提供参考。  相似文献   

8.
海面风场在海浪模拟和预报中起着重要作用。文中分别利用CCMP风场和Q/N混合风场驱动WAVEWATCHⅢ海浪模式对北太平洋海域的海浪过程进行了模拟。利用NDBC(美国国家浮标资料中心)提供的浮标资料和Jason-1卫星高度计资料对模拟结果进行了检验分析。分析表明:在北太平洋海域,CCMP风场较Q/N混合风场与浮标风速资料有更好的一致性,更能代表该海域的海面风场状况;CCMP风场驱动下的海浪模拟结果总体上优于Q/N混合风场的结果。  相似文献   

9.
利用南海浮标及海洋观测站的实测资料作为真实值对HY-2A散射计反演的风矢量作多角度对比分析,结果表明:HY-2A散射计风速与浮标(海洋站)实测风速数据具有良好的相关性,散射计观测风速普遍大于浮标(海洋站)实测风速;风速误差符合正态分布,风力≤3级时,风向的平均绝对误差最大;4~5级时风速平均偏差和平均绝对偏差均最小。逐月统计发现:1—3月的风速平均偏差最小,两者基本吻合。7—9月的风速平均偏差最大,12月的风向平均偏差最小。另外,东北向的风速平均偏差最小,西北向风速平均偏差最大;远海站点的风速和风向检验误差均小于近海站点。以上结论表明HY-2A散射计风场资料在南海海域具有可信性,为HY-2A散射计风场在南海的应用和研究提供依据。  相似文献   

10.
为实现合成孔径雷达数据与数值预报模式资料融合,提高海面风场精度和业务化运用水平,提出了一种基于星载SAR数据与模式资料的变分融合方法。其研究思路是采用二维连续小波变换提取SAR图像中高精度风条纹风向,结合地球物理模型函数求解海面风场的经向分量和纬向分量,然后采用Kriging插值方法将数值预报模式风速插值到SAR海面风场覆盖区域,得到SAR风速观测算子,由此构建SAR风场与模式风场融合的代价函数,并采用变分方法求解分析风场,最终得到融合后的海面风场结果。仿真分析结果表明,变分融合后的海面风速和风向结果更接近于理想值,尤其在SAR海面风场覆盖区域更为明显。选取ENVISAT/ASAR资料和与其时空匹配的欧洲中期天气预报中心模式风场资料开展实例验证,结果表明融合后的海面风场结果比模式风场更加接近于浮标观测结果。  相似文献   

11.
The influences of the three types of reanalysis wind fields on the simulation of three typhoon waves occurred in 2015 in offshore China were numerically investigated. The typhoon wave model was based on the simulating waves nearshore model (SWAN), in which the wind fields for driving waves were derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Interim (ERA-interim), the National Centers for Environmental Prediction climate forecast system version 2 (CFSv2) and cross-calibrated multi-platform (CCMP) datasets. Firstly, the typhoon waves generated during the occurrence of typhoons Chan-hom (1509), Linfa (1510) and Nangka (1511) in 2015 were simulated by using the wave model driven by ERA-interim, CFSv2 and CCMP datasets. The numerical results were validated using buoy data and satellite observation data, and the simulation results under the three types of wind fields were in good agreement with the observed data. The numerical results showed that the CCMP wind data was the best in simulating waves overall, and the wind speeds pertaining to ERA-Interim and CCMP were notably smaller than those observed near the typhoon centre. To correct the accuracy of the wind fields, the Holland theoretical wind model was used to revise and optimize the wind speed pertaining to the CCMP near the typhoon centre. The results indicated that the CCMP wind-driven SWAN model could appropriately simulate the typhoon waves generated by three typhoons in offshore China, and the use of the CCMP/Holland blended wind field could effectively improve the accuracy of typhoon wave simulations.  相似文献   

12.
Three archived reanalysis wind vectors at 10 m height in the wind speed range of 2–15 m/s, namely, the second version of the National Centres for Environmental Prediction(NCEP) Climate Forecast System Reanalysis(CFSv2), European Centre for Medium-Range Weather Forecasting Interim Reanalysis(ERA-I) and NCEPDepartment of Energy(DOE) Reanalysis 2(NCEP-2) products, are evaluated by a comparison with the winds measured by moored buoys in coastal regions of the South China Sea(SCS). The buoy data are first quality controlled by extensive techniques that help eliminate degraded measurements. The evaluation results reveal that the CFSv2 wind vectors are most consistent with the buoy winds(with average biases of 0.01 m/s and 1.76°). The ERA-I winds significantly underestimate the buoy wind speed(with an average bias of –1.57 m/s), while the statistical errors in the NCEP-2 wind direction have the largest magnitude. The diagnosis of the reanalysis wind errors shows the residuals of all three reanalysis wind speeds(reanalysis-buoy) decrease with increasing buoy wind speed, suggesting a narrower wind speed range than that of the observations. Moreover, wind direction errors are examined to depend on the magnitude of the wind speed and the wind speed biases. In general, the evaluation of three reanalysis wind products demonstrates that CFSv2 wind vectors are the closest to the winds along the north coast of the SCS and are sufficiently accurate to be used in numerical models.  相似文献   

13.
This study investigates the long-term changes of monthly sea surface wind speeds over the China seas from 1988 to 2015. The 10-meter wind speeds products from four major global reanalysis datasets with high resolution are used: Cross-Calibrated Multi-Platform data set(CCMP), NCEP climate forecast system reanalysis data set(CFSR),ERA-interim reanalysis data set(ERA-int) and Japanese 55-year reanalysis data set(JRA55). The monthly sea surface wind speeds of four major reanalysis data sets have been investigated through comparisons with the longterm and homogeneous observation wind speeds data recorded at ten stations. The results reveal that(1) the wind speeds bias of CCMP, CFSR, ERA-int and JRA55 are 0.91 m/s, 1.22 m/s, 0.62 m/s and 0.22 m/s, respectively.The wind speeds RMSE of CCMP, CFSR, ERA-int and JRA55 are 1.38 m/s, 1.59 m/s, 1.01 m/s and 0.96 m/s,respectively;(2) JRA55 and ERA-int provides a realistic representation of monthly wind speeds, while CCMP and CFSR tend to overestimate observed wind speeds. And all the four data sets tend to underestimate observed wind speeds in Bohai Sea and Yellow Sea;(3) Comparing the annual wind speeds trends between observation and the four data sets at ten stations for 1988-1997, 1988–2007 and 1988–2015, the result show that ERA-int is superior to represent homogeneity monthly wind speeds over the China seaes.  相似文献   

14.
有效波高是描述海浪的关键参数。欧洲中期天气预报中心(ECMWF)提供的ERA-Interim再分析数据提供了全球海浪的有效波高,本文选取该数据在台湾海峡2013年3月份的有效波高结果,分别与浮标观测数据以及海浪数值模式SWAN (Simulating Waves Nearshore)的数值模拟结果相对比,来分析其预报效果。结果显示:在浮标点,ERA-Interim数据和SWAN模拟浪高数据与浮标浪高数据的时间相关系数分别为0.94和0.98,ERA-Interim数据的浪高均值约为浮标的51%,为SWAN模拟数据的70%。在台湾海峡区域,ERA-Interim数据与SWAN模拟浪高之间的空间异常相关系数(ACC)月均值为0.51,时序ACC曲线显示,一般在海峡东北口风初起时刻ACC值最小,在风吹遍海峡并增长的过程中,ACC迅速增加,在风速达到最大值之后,ACC开始下降,但ERA-Interim数据与SWAN数值模拟结果在整个海峡区域的浪高最大值与最小值分布位置基本一致。综合分析,ERA-Interim数据能够反映台湾海峡区域此时间段的有效波高的时空变化趋势,在数值上有明显低估。  相似文献   

15.
杨兵  侯一筠 《海洋与湖沼》2020,51(5):978-990
基于高分辨率CFSR(climate forecast system reanalysis)风场资料、气候态海洋混合层厚度资料和卫星高度计海面高度异常资料,本文估计了大气风场向全球海洋混合层的近惯性能通量和近惯性能量输入功率,并探究了混合层厚度、风场时间分辨率、经验衰减系数和中尺度涡旋涡度对近惯性能通量和能量输入功率的影响。浮标实测风场和流速表明,本文所用的风场和阻尼平板模型可用于估计风场向全球海洋的近惯性能通量。本文计算得到的大气向全球海洋输入近惯性能量的功率为0.56TW(1TW=10~(12)W),其中北半球贡献0.22TW,南半球贡献0.34TW。在时间上,风场的近惯性能通量呈现各个半球冬季最强、夏季最弱的特征,这和西风带风场的季节变化有关。在空间上,近惯性能通量的高值海域为南、北半球西风带海洋,尤其是南大洋。混合层厚度和风场空间不均匀性使得西风带近惯性能通量呈现纬向变化,即海盆西部强于海盆东部。风场时间分辨率对近惯性能通量的估计至关重要,低时间分辨率风场对近惯性能通量的低估达到13%—30%。阻尼平板模型中的经验衰减系数对近惯性能通量估计的影响不超过5%。中尺度涡旋涡度仅改变近惯性能通量的空间分布,而对全球近惯性能量输入功率的影响可以忽略。  相似文献   

16.
基于浮标实测数据的WindSat海洋反演产品精度分析   总被引:1,自引:1,他引:0  
To evaluate the ocean surface wind vector and the sea surface temperature obtained from Wind Sat, we compare these quantities over the time period from January 2004 to December 2013 with moored buoy measurements. The mean bias between the Wind Sat wind speed and the buoy wind speed is low for the low frequency wind speed product(WSPD_LF), ranging from –0.07 to 0.08 m/s in different selected areas. The overall RMS error is 0.98 m/s for WSPD_LF, ranging from 0.82 to 1.16 m/s in different selected regions. The wind speed retrieval result in the tropical Ocean is better than that of the coastal and offshore waters of the United States. In addition, the wind speed retrieval accuracy of WSPD_LF is better than that of the medium frequency wind speed product. The crosstalk analysis indicates that the Wind Sat wind speed retrieval contains some cross influences from the other geophysical parameters, such as sea surface temperature, water vapor and cloud liquid water. The mean bias between the Wind Sat wind direction and the buoy wind direction ranges from –0.46° to 1.19° in different selected regions. The overall RMS error is 19.59° when the wind speed is greater than 6 m/s. Measurements of the tropical ocean region have a better accuracy than those of the US west and east coasts. Very good agreement is obtained between sea surface temperatures of Wind Sat and buoy measurements in the tropical Pacific Ocean; the overall RMS error is only 0.36°C, and the retrieval accuracy of the low latitudes is better than that of the middle and high latitudes.  相似文献   

17.
风场对SWAN模式在台湾海峡后报结果的影响   总被引:2,自引:2,他引:0  
本文利用SWAN模式模拟分析了CCMP和DASCAT两种常用风场数据在台湾海峡海面的浪场结果。东北季风期3个月的浪场模拟结果与浮标实测波高时序数据相比,偏差均值不大于0.33 m,偏差均方根不大于0.59 m。一般在浮标波高大于3.5 m和小于1.0 m时,偏差偏大。6 h分辨率的风场数据相较于24 h分辨率风场数据对应的模拟结果更接近于浮标实测结果。在6 h和24 h分辨率的CCMP风场数据和24 h分辨率的DASCAT风场数据的模拟结果中,两两结果间的空间相关系数均不低于0.90,偏差均值不大于0.32 m,偏差均方根不大于0.4 m。  相似文献   

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