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1.
通过地球物理模型建立后向散射系数与海面风矢量的关系,可将散射计从不同方位角测得的风矢量单元后向散射系数反演得到风矢量,因此地球物理模型在风速反演中起着至关重要的作用。使用神经网络方法,利用C波段经验模型CMOD4和Ku波段经验模型QSCAT—1仿真数据建立了形式统一的C波段和Ku波段地球物理模型。新模型将电磁波频率作为模型的参数之一,使新模型不再局限于特定的传感器,并使C波段与Ku波段具有统一的形式。分析表明,由新模型建立的后向散射系数与海面风矢量的关系同经验模型具有很好的可比性。利用新模型反演的风速与CMOD4和QSCAT—1模型反演的风速具有很好的一致性,说明新模型在具有统一简洁形式的同时也兼有与经验统计模型相同的有效性。 相似文献
2.
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
3.
海洋微波散射模型相比于以经验统计建立的地球物理模式函数具有不受特定微波频率限制的优势。组合布拉格散射模型和几何光学模型形成了复合雷达后向散射模型。利用南海北部气象浮标2014年海面风速风向实测值作为散射模型输入，分别比较了复合雷达后向散射模型与RADARSAT-2卫星C波段SAR、HY-2A卫星Ku波段微波散射计的海面后向散射系数，偏差分别为(?0.22±1.88) dB (SAR)、(0.33±2.71) dB (散射计VV极化）和(?1.35±2.88) dB (散射计HH极化)；以美国浮标数据中心(NDBC)浮标2011年10月1日至2014年9月30日共3年的海面风速、风向实测值作为散射模型输入，分别比较了复合雷达后向散射模型与Jason-2、HY-2A卫星Ku波段高度计海面后向散射系数，偏差分别为(1.01±1.15) dB和(1.12±1.29) dB。中等入射角和垂直入射下的卫星传感器后向散射系数观测值与复合雷达后向散射模型模拟值比较，具有不同的偏差，但具有相同的海面风速检验精度，均方根误差小于1.71 m/s。结果表明，复合雷达后向散射模型可模拟计算星载SAR、散射计和高度计观测条件下的海面雷达后向散射系数，且与CMOD5、NSCAT-2、高度计业务化海面风速反演的地球物理模式函数的计算结果具有一致性；复合雷达后向散射模型可用于微波遥感器的定标与检验、海面雷达后向散射的模拟。 相似文献
4.
基于SAR图像雨团足印的海面风向提取方法 总被引：1，自引：1，他引：0
利用地球物理模式函数进行SAR海面风速反演时，需以风向作为地球物理模式函数的输入。本文应用了一种利用SAR图像上雨团足印顺风一侧比逆风一侧明亮的图像特征的海面风向提取方法，以进行海面风速反演。4景RADARSAT-2卫星SAR示例数据风向提取结果相对于ASCAT散射计的风向均方根误差满足不大于16°。分别以本文方法提取的风向和ASCAT散射计风向作为输入，利用地球物理模式函数CMOD5进行海面风速的SAR反演，两者的风速反演结果基本一致，其均方根误差差值不超过0.3 m/s。本文利用SAR图像雨团足印信息的风向提取方法准确可靠，可应用于SAR海面风速反演。 相似文献
5.
The principal purpose of this paper is to extract entire sea surface wind＇s information from spaceborne lidar, and particularly to utilize a appropriate algorithm for removing the interference information due to white caps and subsurface water. Wind speeds are obtained through empirical relationship with sea surface mean square slopes. Wind directions are derived from relationship between wind speeds and wind directions im plied in CMOD5n geophysical models function （GMF）. Whitecaps backscattering signals were distinguished with the help of lidar depolarization ratio measurements and rectified by whitecaps coverage equation. Subsurface water backscattering signals were corrected by means of inverse distance weighted （IDW） from neighborhood non-singular data with optimal subsurface water backscattering calibration parameters. To verify the algorithm reliably, it selected NDBC＇s TAO buoy-laying area as survey region in camparison with buoys＇ wind field data and METOP satellite ASCAT of 25 km single orbit wind field data after temporal-spa tial matching. Validation results showed that the retrieval algorithm works well in terms of root mean square error （RMSE） less than 2m/s and wind direction＇s RMSE less than 21 degree. 相似文献
6.
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
7.
Evaluation of ENVISAT ASAR data for sea surface wind retrieval in Hong Kong coastal waters of China 总被引：2，自引：1，他引：1
The C-band wind speed retrieval models, CMOD4, CMOD - IFR2, and CMOD5 were applied to retrieval of sea surface wind speeds from ENVISAT （European environmental satellite） ASAR （advanced synthetic aperture radar） data in the coastal waters near Hong Kong during a period from October 2005 to July 2007. The retrieved wind speeds are evaluated by comparing with buoy measurements and the QuikSCAT （quick scatterometer） wind products. The results show that the CMOD4 model gives the best performance at wind speeds lower than 15 m/s. The correlation coefficients with buoy and QuikSCAT winds are 0.781 and 0.896, respectively. The root mean square errors are the same 1.74 m/s. Namely, the CMOD4 model is the best one for sea surface wind speed retrieval from ASAR data in the coastal waters near Hong Kong. 相似文献
8.
利用散射计测量海面后向散射系数, 并通过地球物理模型函数(geophysical model function, GMF)反演得到海面风场。目前散射计风场反演所采用的GMF一般只考虑雷达极化方式、雷达入射角、风速和相对风向对海面后向散射系数的影响, 而相关研究表明海表温度(sea surface temperature, SST)对Ku波段散射计风场反演具有不可忽略的影响。文章利用海洋二号A卫星散射计(Haiyang-2A Scatterometer, HY2A-SCAT)后向散射系数观测值、欧洲中期天气预报中心(European Center for Medium-Range Weather Forecasts, ECMWF )再分析风矢量和SST数据, 采用人工神经网络方法, 建立起一种SST相关的GMF (TNGMF)。对TNGMF进行分析后发现, 海面后向散射系数随着SST的增加而增加, 并且其增加幅度与雷达极化方式、风速有关。为了对比, 文章使用相同数据集和相同方法建立了不包含SST的GMF (NGMF), 将美国国家航天航空局散射计-2 (National Aeronautics and Space Administration Scatterometer-2, NSCAT2) GMF、TNGMF和NGMF分别用于HY2A-SCAT风场反演实验。试验结果表明, 采用NSCAT2 GMF、NGMF反演得到的风速在低温时系统性偏小, 在高温时系统性偏大; 而TNGMF可较好地纠正SST对风速偏差均值的影响, 从而提高反演风场质量。 相似文献
9.
Conventional retrieval and neural network methods are used simultaneously to retrieve sea surface wind speed(SSWS) from HH-polarized Sentinel-1(S1) SAR images. The Polarization Ratio(PR) models combined with the CMOD5.N Geophysical Model Function(GMF) is used for SSWS retrieval from the HH-polarized SAR data. We compared different PR models developed based on previous C-band SAR data in HH-polarization for their applications to the S1 SAR data. The recently proposed CMODH, i.e., retrieving SSWS directly from the HHpolarized S1 data is also validated. The results indicate that the CMODH model performs better than results achieved using the PR models. We proposed a neural network method based on the backward propagation(BP)neural network to retrieve SSWS from the S1 HH-polarized data. The SSWS retrieved using the BP neural network model agrees better with the buoy measurements and ASCAT dataset than the results achieved using the conventional methods. Compared to the buoy measurements, the bias, root mean square error(RMSE) and scatter index(SI) of wind speed retrieved by the BP neural network model are 0.10 m/s, 1.38 m/s and 19.85%,respectively, while compared to the ASCAT dataset the three parameters of training set are –0.01 m/s, 1.33 m/s and 15.10%, respectively. It is suggested that the BP neural network model has a potential application in retrieving SSWS from Sentinel-1 images acquired at HH-polarization. 相似文献
10.
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 总被引：2，自引：1，他引：1
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. 相似文献
11.
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
12.
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
13.
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
14.
The main objective of this paper is to propose a newly developed ocean Significant Wave Height(SWH) retrieval method from Envisat Advanced Synthetic Aperture Radar(ASAR) imagery. A series of wave mode imagery from January, April and May of 2011 are collocated with ERA-Interim reanalysis SWH data. Based on the matched datasets, a simplified empirical relationship between 22 types of SAR imagery parameters and SWH products is developed with the Genetic Algorithms Partial Least-Squares(GA-PLS) model. Two major features of the backscattering coefficient σ_0 and the frequency parameter S_(10) are chosen as the optimal training feature subset of SWH retrieval by using cross validation. In addition, we also present a comparison of the retrieval results of the simplified empirical relationship with the collocated ERA-Interim data. The results show that the assessment index of the correlation coefficient, the bias, the root-mean-square error of cross validation(RMSECV) and the scattering index(SI) are 0.78, 0.07 m, 0.76 m and 0.5, respectively. In addition, the comparison of the retrieved SWH data between our simplifying model and the Jason-2 radar altimeter data is proposed in our study.Moreover, we also make a comparison of the retrieval of SWH data between our developed model and the wellknown CWAVE_ENV model. The results show that satisfying retrieval results are acquired in the low-moderate sea state, but major bias appears in the high sea state, especially for SWH5 m. 相似文献
15.
合成孔径雷达反演黄海海面风场 总被引：1，自引：0，他引：1
基于后向散射系数反演高空间分辨率海面风场,采用谱方法确定风向,并利用CMOD4模式函数反演风速。以ERS-2 SAR黄海区域图像为例,反演海面风场,并将反演结果同QuikSCAT散射计对比,比较吻合,证明该方法在黄海区域的可行性。 相似文献
16.
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
17.
A buoy for measuring wind speed and the ambient noise sound pressure level from 10 to 1500 Hz with 1-Hz resolution is described. The measurement buoy was deployed in a remote fjord in southeastern Alaska from October to December, 1989. The results from the data collected show that, for a wind speed of 5 kn, the measured ambient noise level at 900 Hz lies well below the Knudsen curve for open-ocean, wind-generated noise. As the wind speed increases from 5 to 10 kn, the measured ambient noise level approaches the Knudsen curve, increasing at 4 dB/kn compared to 1 dB/kn for the Knudsen curve. Above 10 kn, the measured ambient noise level matches the Knudsen curve 相似文献
18.
Michael Reynolds 《Ocean Engineering》1983,10(1):65-76
A small, inexpensive, and easily deployable meteorological buoy is described. Buoy motion is greatly reduced by appropriate ballast techniques; vector averaging further removes buoy motion effects from wind data. Data is transmitted to the GOES satellite and is retrieved by telephone. Measurements are vector-averaged wind components, wind speed, wind direction, water temperature, air temperature, and compass direction. Data from two field trials are discussed. Speed comparisons averaged 0.2 m sec−1 with a standard deviation of 0.6 m sec−1. Direction comparisons were different due to local topography, but they indicate a probable accuracy of ±5°. 相似文献
19.
《Oceanic Engineering, IEEE Journal of》2005,30(3):508-515
A methodology for retrieving high-resolution ocean surface wind fields from satellite-borne synthetic aperture radar (SAR) data is introduced and validated. The algorithms developed are suited for ocean SAR data, which were acquired at the C band of either vertical (VV) or horizontal (HH) polarization in transmission and reception. Wind directions are extracted from wind-induced streaks that are visible in SAR images of the ocean at horizontal scales greater than 200 m. These wind streaks are very well aligned with the mean surface wind direction. To extract the orientation of these streaks, two algorithms are introduced, which are applied either in the spatial or spectral domain. Ocean surface wind speeds are derived from the normalized radar cross section (NRCS) and image geometry of the calibrated SAR images, together with the local SAR-retrieved wind direction. Therefore, several C-band models (CMOD IFR2, CMOD4, and CMODS) are available, which were developed for VV polarization, and have to be extended for HH polarization. To compare the different algorithms and C-band models as well as demonstrate their applicability, SAR-retrieved wind fields are compared to numerical-model results considering advanced SAR (ASAR) data from Environmental Satellite (ENVISAT), a European satellite. 相似文献
20.
QIN Bangyong ZHOU Xuan ZHANG Honglei YANG Xiaofeng LU Rong YU Yang SHI Lijian 《海洋学报(英文版)》2014,33(7):83-88
Rain effect and lack of in situ validation data are two main causes of tropical cyclone wind retrieval errors. The National Oceanic and Atmospheric Administration＇s Climate Prediction Center Morphing technique （CMORPH） rain rate is introduced to a match-up dataset and then put into a rain correction model to remove rain effects on ＂Jason-1＂ normalized radar cross section （NRCS）; Hurricane Research Division （HRD） wind sPeed, which integrates all available surface weather observations, is used to substitute in situ data for establishing this relationship with ＂Jason-l＂ NRCS. Then, an improved ＂Jason-l＂ wind retrieval algorithm under tropical cyclone conditions is proposed. Seven tropical cyclones from 2003 to 2010 are studied to validate the new algorithm. The experimental results indicate that the standard deviation of this algorithm at C-band and Ku-band is 1.99 and 2.75 m/s respectively, which is better than the existing algorithms. In addition, the C-band algorithm is more suitable for sea surface wind retrieval than Ku-band under tropical cyclone conditions. 相似文献