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1.
选用了布设在渤海海域的浮标、平台、海岛共计18个站点,利用COARE算法进行站点风速的高度修正,对ASCAT卫星反演风与三类站点风进行对比分析。统计检验结果表明,卫星风与站点风相比,整体上卫星风速比站点风速大。浮标与卫星的风速差最小,而平台和海岛与卫星的风速差较大。风向对比结果显示,卫星风与站点风的风向平均偏差都很小,但均方根偏差却比较大。随着风速的增加,三类站点的风速平均偏差都是由大到小变化,由正值变化为负值,弱风速的时候卫星风速大于站点风速,高风速的时候卫星风速小于站点风速;风速的均方根偏差则相对稳定。卫星风与站点风的风向均方根偏差随着风速的增加而减小,在不同的方向上,风速偏差和风向偏差等统计量的区别较小。随季节的变化中,平台和海岛站的风速与卫星风速的平均偏差秋冬季大而春夏季小。  相似文献   

2.
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   

3.
利用2000—2009年美国国家航空航天局(NASA)在中国近海海域(0°~45°N,105°~135°E)的QuikSCAT卫星遥感风场资料与近海测风塔(位于上海近海)、海上石油平台(位于东海和渤海)、岛屿站(南海珊瑚岛和西沙海边观测塔)的实测风场资料进行对比分析,检验了QuikSCAT卫星遥感风场资料在中国近海海域的可靠性。研究结果如下:各站点实测风速与站点位置以及站点附近的QuikSCAT卫星遥感风场资料相关系数均在0.7以上;QuikSCAT卫星遥感风场资料与海上石油平台的风速均方根误差较小(约1.5 m/s);其年均值均大于实测值,差值范围是0.1~1.3 m/s;其Weibull形状参数K与海上石油平台以及近海测风塔的K值较为接近,表明QuikSCAT卫星遥感风场资料各风速段的频次分布形态与观测站的实测值基本吻合,QuikSCAT卫星遥感风场资料能基本合理地反映出中国近海风速的分布状况。利用QuikSCAT卫星遥感风场资料分析了中国近海及其邻近水域风速的空间分布特征:(1)台湾海峡是中国近海风速最大的区域,从台湾海峡向东北至日本海,往西南至南海北部115°E附近和巴林塘海峡为风速的次大值区;(2)28°N到长江入海口的东海海域年均风速为7.0~7.5 m/s,在黄海和渤海为5.5~7.0 m/s,在南海北部自东向西由8.5 m/s递减为6.0 m/s,北部湾最大风速区位于东方附近海域。  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.
陈剑桥 《台湾海峡》2011,30(2):158-164
采用布放在台湾海峡及其邻近海域的2个浮标对2008年冬季(2008年12月至2009年2月)QuikSCAT卫星遥感观测的风场资料进行了检验.结果表明,这两者风速的相关系数为0.93,平均偏差为-0.03 m/s,均方根误差为1.10 m/s,平均绝对误差为1.54 m/s;风向平均偏差为-9.53°,均方根误差为22.83°,平均绝对误差为33.84.°这表明QuikSCAT卫星遥感风场资料在台湾海峡及其邻近海域冬季风观测中具有很高的适用性.本文利用2008年冬季QuikSCAT卫星遥感的平均风速场,分析了在"狭管效应"影响下台湾海峡及其邻近海域的风速特征.结果显示其平均风速具有3个基本特征:(1)台湾海峡中部存在着明显高于附近其他海域的高风速区,平均风速高出1~4m/s,风速高值区更贴近海峡东岸.(2)台湾海峡南部平均风速大于北部.(3)台湾岛东北角和西南角各有一个风速低值区.结合对2009年2月15~18日一次冷空气大风过程的分析发现,风速越大台湾海峡"狭管效应"越明显.  相似文献   

6.
利用2013年1月—2014年12月山东近海的8个浮标站、海岛站和自动站资料与ASCAT近岸风速和风向进行对比,以分析ASCAT反演风场在山东沿海的适用性。研究发现:总体上看,ASCAT近岸风速与代表站实况风速正相关,ASCAT近岸风速在山东沿海误差较小,风向有明显的偏离。ASCAT近岸风在渤海、渤海海峡和黄海北部的适用性优于黄海中部。风力不同时,ASCAT近岸风速与实况偏差有明显差别,表现为当实况出现6级及以上的大风,ASCAT近岸风速小于实况;当实况出现6级以下的风,ASCAT近岸风速大于实况。就ASCAT风速偏差而言,6级以下的风速偏差小于6级及以上风。ASCAT近岸风向与实况偏差也有明显差别,当实况出现6级及以上的大风,ASCAT近岸风向与实况的偏离变小;当实况出现6级以下的风,ASCAT近岸风向与实况的偏离变大。因此,ASCAT近岸风速在山东沿海有较好的适用性,6级以下风更优;ASCAT近岸风向也有一定的适用性,6级及以上风向可用性比6级以下强。  相似文献   

7.
针对 CYGNSS卫星风速产品的适用性问题,以美国国家数据浮标中心(NDBC)的实测风速与美国国家飓风中心(NHC)的最佳路径风速为参照,选取美国西南部海域为研究区,通过数据匹配和对比分析,评估了CYGNSS不同模型估算风速产品的精度。结果表明,CYGNSS FDS模型估算的中、低风速产品与NDBC浮标实测风速具有较好的一致性,CYGNSS风速与浮标风速的差异在春夏季稍高、秋冬季略低;CYGNSS YSLF模型估算的高风速产品与NHC最大风速存在较大差异,CYGNSS风速低于NHC最大风速;对于CYGNSS两种模型估算的风速产品,利用遥感观测量NBRCS反演出的风速都比LES反演出的风速具有更好的精度。总体而言,本研究验证了CYGNSS风速产品的真实有效性,对提高海洋数值预报能力具有一定的意义。  相似文献   

8.
ASCAT洋面风资料在中国北方海域的真实性检验   总被引:2,自引:0,他引:2  
采用北方海域6个海洋观测站风资料对2009年3月—2013年6月ASCAT卫星反演洋面风(10 m)资料进行了检验。ASCAT反演洋面风与测站风向、风速偏差均较小,二者风速平均偏差为0.99 m/s,ASCAT风速略高于测站风速,二者风向平均偏差为-12.97°,表明ASCAT洋面风资料在北方海域具有可信性;分风级统计表明,在北方海域,风力为0—7级(0—17.1 m/s)时,利用ASCAT风速代表洋面风速是可行的(其中风力为4—5级时,ASCAT与测站风速误差最小,为0.10 m/s),当风力达到8级以上时ASCAT的可信度较低。  相似文献   

9.
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   

10.
为进行海洋表层风场的物理结构重建与基础理论溯源,需选用可靠准确且通过检验的高时空分辨率风场资料。本文利用NDBC、TAO和嵊泗站现场观测资料,在全面比较分析的基础上,对其中应用较广泛的CFSR/CFSv2、ERA-Interim、FNL和CCMP四种风场产品在北半球海域(北太平洋、北大西洋)进行了检验评估,得出结论:1)4种资料的风速都不同程度地低估了实际观测风速;在低风速区的风向偏差较大,风速越低,偏差越多;产品资料在远岸地区比近岸地区更接近实测资料,在高纬地区的效果优于低纬地区。2)通过比较4种产品资料与浮标实测资料的风向和风速的偏差、均方根误差、误差标准差和相关系数,发现CCMP资料是4种资料中整体效果最好的一种,而CFSR/CFSv2资料是较差的一种。3)嵊泗站观测平台资料与浮标观测资料验证的结论略有差异,结果显示:FNL资料是4种资料产品中效果最好的产品,ERA-Interim资料的效果仅次于FNL,而用浮标验证效果较好的CCMP资料在嵊泗站点效果却较差,CFSR/CFSv2资料是4种资料中效果最差的。4)通过分析4种风场资料的偏差分布发现,CCMP与ERA-Interim风场资料的偏差较小,而CFSR/CFSv2与FNL风场资料的偏差较小。CCMP资料与其他3种资料的纬向风偏差在海洋上以负偏差为主,陆地以及沿岸地区的偏差较大,且分布不均匀;经向风偏差分布中,南半球的正偏差区较为明显,而北半球的负偏差区则较为明显,但偏差程度要小于纬向风偏差。  相似文献   

11.
A comparison of monthly wind stress derived from winds of NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis and UWM/COADS (The University of Wisconsin-Milwaukee/Comprehensive Ocean-Atmosphere Data Set) dataset (1950–1993), and of NCEP/NCAR reanalysis and satellite-based QuikSCAT dataset (2000–2006), is made over the South Atlantic (10°N–40°S). On a mean seasonal scale, the comparison shows that these three wind stress datasets have qualitatively similar patterns. Quantitatively, in general, from about the equator to 20°S in the mid-Atlantic the wind stress values are stronger in NCEP/NCAR data than those in UWM/COADS data. On the other hand, in the Intertropical Convergence Zone (ITCZ) area the wind stress values in NCEP/NCAR data are slightly weaker than those in UWM/COADS data. In the South Atlantic, between 20° S–40°S, the QuikSCAT dataset presents complex circulation structures which are not present in NCEP/NCAR and UWM/COADS data. The wind stress is used in a numerical ocean model to simulate ocean currents, which are compared to a drifting-buoy observed climatology. The modeled South Equatorial Current agrees better with observations between March–May and June–August. Between December–February, the South Equatorial Current from UWM/COADS and QuikSCAT experiments is stronger and more developed than that from NCEP/NCAR experiment. The Brazil Current, in turn, is better represented in the QuikSCAT experiment. Comparison of the annual migration of ITCZ at 20° and 30°W in UWM/COADS and NCEP/NCAR data sources show that the southernmost position of ITCZ at 30°W in February, March and April coincides with the rainy season in NE Brazil, while the northernmost position of ITCZ at 20°W in August coincides with the maximum rainfall of Northwest Africa.  相似文献   

12.
The geophysical model function (GMF) describes the relationship between a backscattering and a sea surface wind, and enables a wind vector retrieval from backscattering measurements. It is clear that t...  相似文献   

13.
为提高降雨条件下星载全极化微波辐射计海面风场精度,通过匹配WindSat海面风场和降雨率数据以及美国国家浮标中心浮标观测数据,得到18 996组匹配样本,深入分析了降雨对海面风场反演精度的严重影响,构建了风场校正模型。试验结果表明,降雨导致海面风速被严重高估,风向误差随着降雨率的增大而增大。校正后的风速精度在低风速段提升明显。无论降雨率多大,校正后风速精度均比校正前高。风速均方根误差由原来的2.9 m/s降低到了2.1 m/s,风向均方根误差由原来的26.9°降低到了26.3°。  相似文献   

14.
The accurate surface wind in the equatorial Indian Ocean is crucial for modeling ocean circulation over this region. In this study, the surface wind analysis generated at the European Center for Medium Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) are compared with NASA QuikSCAT satellite derived Level2B (swath level) and Level3 (gridded) surface winds for the year 2005. It is observed that the ECMWF winds exhibit speed bias of 1.5 m/s with respect to QuikSCAT Level3 in the southern equatorial Indian Ocean. The NCEP winds are found to exhibit speed bias (1.0–1.5 m/s) in the southern equatorial Indian Ocean specifically during January–February 2005. The biases are also observed in the analysis when compared with Level2B product as well; however, it is less in comparison to Level3 products. The amplitude of daily variations of both ECMWF and NCEP wind speed in Bay of Bengal and parts of the Arabian Sea is about 80% of that in QuikSCAT, while in the equatorial Indian Ocean it is about 60% of that of QuikSCAT.  相似文献   

15.
Wind-velocity data obtained from in situ measurements at the Golitsyno-4 marine stationary platform have been compared with QuikSCAT scatterometer data; NCEP, MERRA, and ERA-Interim global reanalyses and MM5 regional atmospheric reanalysis. In order to adjust wind velocity measured at a height of 37 m above the sea surface to a standard height of 10 m with stratification taken into account, the Monin–Obukhov theory and regional atmospheric reanalysis data are used. Data obtained with the QuikSCAT scatterometer most adequately describe the real variability of wind over the Black Sea. Errors in reanalysis data are not high either: the regression coefficient varies from 0.98 to 1.06, the rms deviation of the velocity amplitude varies from 1.90 to 2.24 m/s, and the rms deviation of the direction angle varies from 26° to 36°. Errors in determining the velocity and direction of wind depend on its amplitude: under weak winds (<3 m/s), the velocity of wind is overestimated and errors significantly increase in determining its direction; under strong winds (>12 m/s), its velocity is underestimated. The influence of these errors on both spatial and temporal estimates of the characteristics of wind over the Black Sea is briefly considered.  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.
利用1999年8月-2009年7月具有高精度的QuikSCAT/NCEP混合风场,对中国海海表风场的风速风向、极值风速、大风频率等特征进行分析,研究发现:MAM和SON的风速大值中心位于台湾海峡,JJA位于南海西南部海域,DJF大值区主要位于琉球群岛-台湾海峡-东沙群岛-平顺海岛一带,风向也具有明显的季节特征;极值风速...  相似文献   

18.
An ocean model was used to examine whether the scatterometer winds can improve the model performance both dynamically and thermodynamically. Comparisons were done using QuikSCAT and NCEP2 winds for both the mean and variability from 2000 to 2004. The comparisons showed that the model forced by QuikSCAT winds gives more realistic mean SST, 20 °C isotherm depth (Z20), and latent heat flux than NCEP2 winds do. Sensitivity experiments indicated that QuikSCAT mean wind stress is important for the improved mean SST, Z20, and latent heat release to the atmosphere in the eastern Pacific. QuikSCAT wind speed, through its effect on the turbulent heat fluxes, is most important for the mean SST in the western Pacific. Finally, there were comparable correlations with observations of both SST and Z20 on the intra-seasonal time scale between the model forced with QuikSCAT winds and the model forced with NCEP2 winds.  相似文献   

19.
This paper proposes a rain considered geophysical model function (GMF), to be noted as GMF plus Rain. GMF plus Rain is based on the basic raidative transfer model with attenuation and scattering effects of rain on radar signal considered. Combined with the NSCAT2 GMF and the rain correction model, the GMF plus Rain model is used to retrieve the ocean wind vectors from the collocated QuikSCAT and SSM/I rain rate data for typhoon Melor. The resulting wind speed estimates of typhoon Melor show improved agreement with the wind fields derived from the best track analysis of Japan Meteorological Agency (JMA). The results imply that compared with the GMF model, the GMF plus Rain model can improve the precision of wind retrieval under the rain condition. Then, a new general algorithm of locating the eye of typhoon through the normalized radar cross section (NRCS) is proposed. The implementation of this algorithm in the ten QuikSCAT observations of typhoon Melor suggests that this algorithm is effective.  相似文献   

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