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1.
With the launch of SARAL/AltiKa altimeter, efforts have been made to develop wind speed retrieval algorithms. Here we present two algorithms for estimating and validating wind speed from AltiKa. The first method is based on a theoretical Geophysical Model Function (GMF) using forward model simulations for Ka band specifications. The second is the model function developed using the matched database of input and output vectors of Normalized Radar Cross Section (NRCS) from AltiKa and wind speed measurements from concurrent Jason-2 altimeters. Since the NRCS depends on both the surface roughness due to surface wind speed and on mean square slope of the surfaces, the significant wave height is used along with wind speed for model development as an proxy variable. Both the theoretical and empirical GMFs are evaluated for retrieval of wind speed from AltiKa and validated with NDBC buoys data. The empirical model provide wind speed retrieval accuracy of 1.4 m/s. The accuracy of wind retrievals from theoretical model is also in the similar range (1.6 m/s), indicating the sound physical basis applicable for the future altimeters with various incidence angles. The retrieved wind speed is applied for various case studies, bringing out all the regional and global features quite well.  相似文献   

2.
卫星高度计海面风速的校准与验证   总被引:2,自引:1,他引:1  
徐圆  杨劲松  郑罡  徐广珺 《海洋学报》2014,36(7):125-132
为了改善不同卫星高度计海面风速数据之间的一致性,以浮标数据为基准,对国内的HY-2A和国外的T/P、GFO、Jason-1、Envisat、Jason-2、CryoSat-2共7颗卫星高度计的海面风速数据进行了分析,给出了各个卫星高度计的海面风速校准公式,并对其校准效果进行了验证。验证结果表明:各个卫星高度计的海面风速在经过校准后,与浮标海面风速差异的均值和均方根都有所降低,其中HY-2A最为显著。经过校准后所有卫星高度计的海面风速与浮标海面风速差异的均值都在±0.2m/s以内。除了HY-2A、GFO和Jason-1,其余4颗卫星高度计校准后的海面风速与浮标海面风速差异的均方根都在1.6m/s以下。由此可以得出结论,利用本文的校准公式对各个卫星高度计(特别是HY-2A卫星高度计)的海面风速进行校准,可以有效减少其与浮标海面风速之间的差异。  相似文献   

3.
本文利用角动量模式计算获得高风速资料,并通过气象观测站实测资料验证了风速资料的准确性,并将所得风速应用于Jason-1高度计风速反演模式函数研究,得到了一个新的风速反演模式函数。研究结果表明,本文提出的模式函数能更好地反映台风经过时海表面风速情况,实现了高度计对高风速(10~40 m/s)的反演,可作为Jason-1高度计风速反演业务化算法在高风速情况下的补充,以提高高度计风速反演精度。  相似文献   

4.
基于雷达高度计增益自动控制数据的风速反演算法研究   总被引:1,自引:1,他引:0  
基于Jason-1卫星雷达高度计与NDBC(National Data Buoy Center)浮标的时空匹配数据集,利用BP(Back Propagation)神经网络方法建立了基于后向散射系数σ0与有效波高(Significant Wave Height,SWH,)的双参数(σ0-Hsw)风速反演模型,并探讨利用AGC(Automatic Gain Control)来代替σ0对风速反演的可行性进行研究。结果表明,所建立的σ0-SWH风速反演均方根优于0.3 m/s(风速范围为0.5~20 m/s); AGC-SWH模型反演精度偏低(1.3 m/s),但在星星交叉定标的基础上,模型精度提高了0.9 m/s。这个研究工作尤其是交叉定标基础上的AGC-SWH模型反演流程对"HY-2"海面风速反演有一定的借鉴意义。  相似文献   

5.
针对现行业务运行的宙达高度计风速反演算法从考虑0~20 m/s的缺陷,提出了vc算法(Vandemark-Chapron Algorithm)与Young算法联合反演高度计海曲风速的方法,通过对Jason-1资料的统计试验,确定了后向散射截面临界点,当高度计后向散射截面大于等于该临界点时采用VC算法反演风速,反之采用Y...  相似文献   

6.
国内外对海上阵风的研究并不多,且大多集中在阵风预报和应用研究方面,对于海洋阵风数据的获取技术未见文献系统论述。本文利用HY-2B卫星雷达高度计观测的后向散射系数,结合校正微波辐射计观测的亮度温度信息,提出联合反演阵风风速的方法。两个遥感载荷联合反演得到的阵风风速与2019–2021年美国国家浮标数据中心(NDBC)浮标数据进行真实性检验,结果显示:阵风风速均方根误差(RMSE)为0.98 m/s,相关系数为0.82;基于本方法利用国外同类卫星Jason-3得到的阵风风速与2016–2018年NDBC浮标数据的RMSE为0.96 m/s,相关系数为0.88。本文在HY-2B卫星雷达高度计海面风速观测的基础上,纳入同一卫星平台校正微波辐射计的同步观测信息联合实现了海面阵风的观测,数据的比对结果证明文中方法具有较高的观测精度。同时,该方法对于具有相同观测体制的国内外卫星也适用。  相似文献   

7.
This study represents an attempt to quantitatively assess the capability of a spaceborne radar altimeter to infer ocean surface wind speeds from a measurement of the backscattered power at vertical incidence. The study uses data acquired during 184 near overflights of NOAA data buoys with the GEOS-3 satellite radar altimeter and encompasses a wind-speed range from less than 1 to 18 m/s. An algorithm is derived from the data comparison for converting measurements of the normalized scattering cross section of the ocean surface at 13.9 GHz into estimates of the surface wind speed at the standard anemometer height of 10 m. The algorithm is straightforward and potentially useful for on-board processing of raw altimeter data for the purpose of providing real-time estimates of surface wind speed. For winds in the range of 1 to 18 m/s, the mean difference between the altimeter-inferred winds and the buoy measurements is negligible while the standard deviation of the difference is 1.74 m/s.  相似文献   

8.
基于浮标数据的卫星雷达高度计海浪波高数据评价与校正   总被引:1,自引:1,他引:0  
卫星雷达高度计是海浪有效波高(significant wave height,SWH)观测的重要手段之一,本文利用时空匹配方法对T/P、Jason-1、Envisat、Jason-2、Cryosat-2和HY-2A共6颗卫星雷达高度计SWH数据与NDBC(National Data Buoy Center,NDBC)浮标SWH数据进行对比验证,并对雷达高度计SWH数据进行校正。全部卫星雷达高度计SWH数据时间跨度为1992年9月25日到2015年9月1日,对比验证NDBC浮标共53个,包括7个大洋浮标。精度评价发现除T/P外,各卫星雷达高度计SWH的RMSE都在0.4~0.5 m之间,经过校正后,RMSE都有显著下降,下降程度最大为13.82%;对于大洋浮标,评价结果RMSE在0.20~0.28 m之间,结果明显优于全部NDBC浮标的精度评价结果;HY-2A卫星雷达高度计SWH在经过校正后数据质量与国外其他5颗卫星雷达高度计SWH数据质量差异较小。  相似文献   

9.
Sea-surface acoustic backscattering measurements at moderate to high frequencies were performed in the shallow water of the south Yellow Sea, using omnidirectional spherical sources and omnidirectional hydrophones. Sea-surface backscattering data for frequencies in the 6–25 k Hz range and wind speeds of(3.0±0.5)and(4.5±1.0) m/s were obtained from two adjacent experimental sites, respectively. Computation of sea-surface backscattering strength using bistatic transducer is described. Finally, we calculated sea-surface backscattering strengths at grazing angles in the range of 16°–85°. We find that the measured backscattering strengths agree reasonably well with those predicted by using second order small-roughness perturbation approximation method with "PM" roughness spectrum for all frequencies at grazing angles ranged from 40° to 80°. The backscattering strengths varied slightly at grazing angles of 16°–40°, and were much stronger than roughness scattering. It is speculated that scattering from bubbles dominates the backscattering strengths at high wind speeds and small grazing angles. At the same frequencies and moderate to high grazing angles, the results show that the backscattering strengths at a wind speed of(4.5±1.0) m/s were approximately 5 d B higher than those at a wind speed of(3.0±0.5) m/s. However, the discrepancies of backscattering strength at low grazing angles were more than 10 d B. Furthermore the backscattering strengths exhibited no significant frequency dependence at 3 m/s wind speed. At a wind speed of 4.5 m/s, the scattering strengths increased at low grazing angles but decreased at high grazing angles with increasing grazing angle.  相似文献   

10.
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   

11.
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   

12.
本文选取142幅RADARSAT-2全极化合成孔径雷达(SAR)影像,在没有入射角输入的情况下,首先利用C-2PO模型进行海面风速反演。随后,将同一时空下的ASCAT散射计风向作为初始风向,提取相应雷达入射角,利用地球物理模式函数(GMF) CMOD5.N对142幅SAR影像进行风速计算。反演结果与美国国家资料浮标中心海洋浮标风速数据对比,结果显示:CMOD5.N GMF和C-2PO模型均可反演出较高精确度的海面风速,其均方根误差分别为1.68 m/s和1.74 m/s。此外,研究发现,在低风速段,CMOD5.N GMF的风速反演精度要明显优于C-2PO模型。针对这一现象,本文以SAR系统成像机理为基础,以低风速SAR图像为具体案例,给出了3种造成这一现象的原因。  相似文献   

13.
南极中山站夏季下降风数值模拟个例研究   总被引:3,自引:2,他引:1  
南极内陆地面辐射冷却产生的近表层冷空气,沿高原斜坡向下流动而形成下降风,其分布形态决定了南极大陆近表层风场的主要特征。我国南极中山站全年均受下降风的强烈影响。夏季晴天时,中山站的下降风一般在傍晚开始出现,风速在午夜达到极值,在次日中午之前逐渐减弱,风速有显著的日循环特征。本文选取南极中山站2010年1月的夏季下降风个例,使用常规地面气象观测资料和Polar WRF极地大气数值模式进行了分析研究。结果表明:中山站夏季夜间晴天出现偏东向的下降风时,近地面风速变化趋势与地面气温呈负相关,相关系数为-0.91。数值模拟发现,中山站下降风在距地面高度约100~150 m之间时风速最大,约为15~21 m/s。在下降风发生时,近地层大气存在逆温现象。下降风较强时,近地层逆温也较强,逆温层厚度约为200~300 m,逆温强度约为4~6℃。在地面摩擦的作用下,中山站近地面下降风风向为东南,随着高度的增加,风向逆时针偏转,最终趋于与地形等高线平行。没有太阳直接辐射时,南极大陆地区存在持续的逆温层,逆温层的出现加强了下降风气流,随着逆温的增强,大风区逐渐西移,且面积不断增加。在夏季太阳辐射造成的逆温消失的短暂时间内,逆温时产生的下降风尚不能完全消失,由此形成了较稳定的风向空间分布特征。  相似文献   

14.
As well as range, the AltiKa altimeter provides estimates of wave height, Hs and normalized backscatter, σ0, that need to be assessed prior to statistics based on them being included in climate databases. An analysis of crossovers with the Jason-2 altimeter shows AltiKa Hs values to be biased high by only ?0.05m, with a standard deviation (s.d.) of ?0.1m for seven-point averages. AltiKa's σ0 values are 2.5–3 dB less than those from Jason-2, with a s.d. of ?0.3 dB, with these relatively large mismatches to be expected as AltiKa measures a different part of the spectrum of sea surface roughness. A new wind speed algorithm is developed through matching a histogram of σ0 values to that for Jason-2 wind speeds. The algorithm is robust to the use of short durations of data, with a consistency at roughly the 0.1 m/s level. Incorporation of Hs as a secondary input reduces the assessed error at crossovers from 0.82 m/s to 0.71 m/s. A comparison across all altimeter frequencies used to date demonstrates that the lowest wind speeds preferentially develop the shortest scales of roughness.  相似文献   

15.
The focus of this study is the validation of significant wave height (SWH) and sea surface height anomaly (SSHA) obtained from the first Ka-band altimeter AltiKa onboard SARAL (Satellite for ARGOS and Altimeters). It is a collaborative mission of the Indian Space Research Organization and Centre National d'Etudes Spatiales (CNES). This is done using in-situ observations from buoy and Jason-2 measurements. Validation using buoy observations are at particular locations while that using Jason-2 altimeter is an attempt towards global validation of Altika products. The results clearly indicate that the SARAL/AltiKa provide high-quality data and the errors are within a predefined range of accuracy. A parallel validation of SWH from other altimeters, which monitored ocean since last decade, like EnviSAT and Jason-2 was also performed with buoy observations. The results clearly show that the accuracy of AltiKa SWH is much better than EnviSAT and comparable to reference mission Jason-2. The accuracy is quite good for the calm sea while in the rough seas the accuracy degrades some. The inter-comparison of SARAL/AltiKa SSHA with Jason-2 indicates a fair match between them. These validation exercises demonstrate the high quality of AltiKa products, usable for practical applications.  相似文献   

16.
以欧洲中期天气预报中心ECMWF(European Centre for Medium Range Weather Forecasts)的ERA5风场数据为真实风速参考值,利用HY-2B卫星散射计L2A数据,使用反向传播神经网络方法对风速进行了反演,分别建立了中高风速、中低风速和全风速反演模型.与基于NSCAT-4地球...  相似文献   

17.
海洋声速剖面严重影响着水下声传播特性,近实时地获取声速剖面对水下声通信、水下定位、鱼群探测等都有重要意义。单经验正交函数回归(single Empirical Orthogonal Function regression,sEOF-r)方法通过建立声速剖面的经验正交系数与海面遥感数据之间的线性回归关系来反演声速剖面。但是,海洋是一个复杂的动力系统,声速与海面遥感数据并不是简单的线性关系,因此,本文基于Argo历史网格数据,通过自组织映射(Self-Organizing Map,SOM)生成海平面高度异常(Sea Level Anomaly,SLA)、海表面温度(Sea Surface Temperature,SST)等海表遥感数据以及表层声速仪测量的表层声速与声速剖面异常之间的非线性映射;然后利用近实时的海表遥感数据和表层声速反演三维海洋声速场。声速剖面反演的结果表明,在多源信息融合的优势下,本文方法的反演性能最稳定且精度最高,声速剖面的平均反演精度比经典sEOF-r方法提高约2 m/s,比未考虑表层声速的经典SOM方法提高约1 m/s。  相似文献   

18.
Wind speed and wave height measured by satellite altimeters represent a good data source to the study of global and regional wind and wave conditions. In this paper, the TOPEX altimeter wind and wave measurements in the Yellow and East China Seas are analyzed. The results provide a glimpse on the statistical properties and the spatial distributions of the regional wind and wave conditions. These data are excellent for use in the validation and verification of numerical simulations on global and regional scales. The altimeter measurements are compared with model output of temporal statistics and spatial distributions. The results show that the model simulations are in good agreement with TOPEX measurements in terms of the local mean and standard deviation of the variables (wave height and wind speed). For the comparison of spatial distributions, the quality of agreement between numerical simulations and altimeter measurements varies significantly from cycle to cycle of altimeter passes. In many cases, trends in the spatial distributions of wave heights and wind speeds between simulations and measurements are opposite. The statistics of biases, rms differences, linear regression coefficients and correlation coefficients are presented. A rather large percentage (∼50%) of cases show poor agreement based on a combination of low correlation, large rms difference or bias, and poor regression coefficient. There are indications that wave age is a factor affecting the performance of wave modeling skills. Generally speaking, the error statistics in the wave field is correlated to the corresponding error statistics in the wind field under the condition of active wind-wave generation. The error statistics between the wave field and the wind field become less correlated for large wave ages. This revised version was published online in August 2006 with corrections to the Cover Date.  相似文献   

19.
地球物理模型函数是一种常被用于同极化合成孔径雷达(synthetic aperture radar,SAR)的风场反演方法。在使用该方法提取SAR数据的风速时,需要将风向作为输入信息,这导致反演风速的精度受风向精度的影响,且使SAR风场反演无法独立完成。为了解决这些问题,通过数值模拟获取仿真的组网SAR卫星数据,3颗SAR同时以不同的入射角观测同一海面。针对仿真的组网SAR卫星数据,发展了一种风场优化反演方法,可以在不输入风向的前提下反演风速,提供参考风向还可以进一步提高风场反演的精度。  相似文献   

20.
全球有效波高和风速的时空变化及相关关系研究   总被引:2,自引:1,他引:1  
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.  相似文献   

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