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星载SAR对雨团催生海面风场的观测研究 总被引：2，自引：1，他引：1
雨团或对流雨是热带与亚热带地区的主要降雨形式,较易被高分辨率星载合成孔径雷达（SAR）探测到。SAR图像上的雨团足印是由大气中雨滴的散射与吸收、下沉气流等共同导致形成的。本文以RADARSAT-2卫星100 m分辨率的SAR图像上雨团引起的海面风场及其结构反演与解译作为实例进行分析。使用CMOD4地球物理模式函数,分别以NCEP再分析数据、欧洲MetOp-A卫星先进散射计（ASCAT）和中国HY-2卫星微波散射计的风向为外部风向,进行了SAR图像的海面风场反演。反演的海面风速相对于NCEP、ASCAT和HY-2的均方根误差（RMSE）分别为1.48 m/s,1.64 m/s和2.14 m/s。SAR图像上一侧明亮另一侧昏暗的圆形信号图斑被解译为雨团携带的下沉气流对海面风场（海面粗糙度）的改变所致。平行于海面背景风场其通过雨团圆形足印中心的剖面上的风速变化可拟合为正弦或余弦曲线,其拟合线性相关系数均不低于0.80。背景风场的风速大小、雨团引起的风速大小以及雨团足印的直径可利用拟合曲线获得,雨团足印的直径大小一般为数千米或数十千米,本文的8例个例解译与分析均验证了该结论。 相似文献
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利用一种改进的算法对中国高分三号同极化SAR图像反演的有效波高的验证 总被引：1，自引：1，他引：0
Chinese Gaofen-3(GF-3) is the first civilian satellite to carry C-band(5.3 GHz) synthetic aperture radar(SAR).During the period of August 2016 to December 2017, 1 523 GF-3 SAR images acquired in quad-polarization(vertical-vertical(VV), horizontal-horizontal(HH), vertical-horizontal(VH), and horizontal-vertical(HV)) mode were recorded, mostly around China's seas. In our previous study, the root mean square error(RMSE) of significant wave height(SWH) was found to be around 0.58 m when compared with retrieval results from a few GF-3 SAR images in co-polarization(VV and HH) with moored measurements by using an empirical algorithm CSAR_WAVE. We collected a number of sub-scenes from these 1 523 images in the co-polarization channel,which were collocated with wind and SWH data from the European Centre for Medium-Range Weather Forecasts(ECMWF) reanalysis field at a 0.125° grid. Through the collected dataset, an improved empirical wave retrieval algorithm for GF-3 SAR in co-polarization was tuned, herein denoted as CSAR_WAVE2. An additional 92 GF-3 SAR images were implemented in order to validate CSAR_WAVE2 against SWH from altimeter Jason-2, showing an about 0.52 m RMSE of SWH for co-polarization GF-3 SAR. Therefore, we conclude that the proposed empirical algorithm has a good performance for wave retrieval from GF-3 SAR images in co-polarization. 相似文献
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利用中国GF-3卫星SAR和HY-2A卫星微波散射计的首次台风联合定量观测 总被引：4，自引：0，他引：4
<正>The typhoon,as a mature tropical cyclone that develops in the western part of the North Pacific Ocean with high wind speed and heavy rainfall,is one of the most lethal and costly of natural disasters for the densely populated countries of East Asia.It can be easily detected by space-borne sensors operated at microwave,visible or infrared bands(Liu et al.,2014).Synthetic Aperture Radar(SAR)is 相似文献
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Gaofen-3(GF-3), a Chinese civil synthetic aperture radar(SAR) at C-band, has operated since August 2016.Remarkably, several typhoons have been captured by GF-3 around the China Seas over its last two-year mission.In this study, six images acquired in Global Observation(GLO) and Wide ScanSAR(WSC) modes at verticalvertical(VV) polarization channel are discussed. This work focuses on investigating the observation of rainfall using GF-3 SAR. These images were collocated with winds from the European Centre for Medium-Range Weather Forecasts(ECMWF), significant wave height simulated from the WAVEWATCH-III(WW3) model, sea surface currents from climate forecast system version 2(CFSv2) of the National Centers for Environmental Prediction(NCEP) and rain rate data from the Tropical Rainfall Measuring Mission(TRMM) satellite. Sea surface roughness,was compared with the normalized radar cross section(NRCS) from SAR observations, and indicated a 0.8 correlation(COR). We analyzed the dependences of the difference between model-simulated NRCS and SARmeasured NRCS on the TRMM rain rate and WW3-simulated significant wave height. It was found that the effects of rain on SAR damps the radar signal at incidence angles ranging from 15° to 30°, while it enhances the radar signal at incidence angles ranging from 30° to 45° and incidence angles smaller than 10°. This behavior is consistent with previous studies and an algorithm for rain rate retrieval is anticipated for GF-3 SAR. 相似文献
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基于理论的气旋条件下双极化C波段合成孔径雷达波参数检测 总被引：2，自引：1，他引：1
Theoretical-based ocean wave retrieval algorithms are applied by inverting a synthetic aperture radar(SAR)intensity spectrum into a wave spectrum, that has been developed based on a SAR wave mapping mechanism. In our previous studies, it was shown that the wave retrieval algorithm, named the parameterized first-guess spectrum method(PFSM), works for C-band and X-band SAR at low to moderate sea states. In this work, we investigate the performance of the PFSM algorithm when it is applied for dual-polarization c-band sentinel-1(S-1) SAR acquired in extra wide-swath(EW) and interferometric wide-swath(IW) mode under cyclonic conditions.Strong winds are retrieved from six vertical-horizontal(VH) polarization S-1 SAR images using the c-band crosspolarization coupled-parameters ocean(C-3 PO) model and then wave parameters are obtained from the image at the vertical-vertical(VV) polarization channel. significant wave height(SWH) and mean wave period(MWP) are compared with simulations from the WAVEWATCH-III(WW3) model. The validation shows a 0.69 m root mean square error(RMSE) of SWH with a –0.01 m bias and a 0.62 s RMSE of MWP with a –0.17 s bias. Although the PFSM algorithm relies on a good quality SAR spectrum, this study confirms the applicability for wave retrieval from an S-1 SAR image. Moreover, it is found that the retrieved results have less accuracy on the right sector of cyclone eyes where swell directly affects strong wind-sea, while the PFSM algorithm works well on the left and rear sectors of cyclone eyes where the interaction of wind-sea and swell is relatively poor. 相似文献
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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
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舟山海域夏季常年存在上升流，且强度、范围等具有年际变化。本文利用2002—2011年7—8月份的海表温度和叶绿素a浓度数据，研究了舟山夏季上升流区域的物理特征、年际变化；此外，利用上升流区域与外海的海表温度差值以及对应的叶绿素a浓度分布范围，定义了上升流的边界。研究结果显示，舟山海域夏季海表温度明显低于外围海域，范围在29°～31°N,122°～123°E,中心平均温差在1.5℃。7月份的叶绿素a浓度均值达到6.6 mg/m3,且上升流区域和非上升流区域叶绿素a浓度差异大，表明上升流处于强势期。8月份的叶绿素a浓度均值达到6.4 mg/m3,但各年份间的差异较大，具有明显的年际变化特征。结合叶绿素a浓度分布特征和海表温度差值数据，可定义7月份的舟山上升流边界温度阈值为0.75℃,8月份阈值为0.5℃。 相似文献
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