Please wait a minute...
img

官方微信

遥感技术与应用  2007, Vol. 22 Issue (2): 238-241    DOI: 10.11873/j.issn.1004-0323.2007.2.238
研究与应用     
星载SAR在海气边界层气象学中的应用研究
陈艳玲1,2,3,丁晓利1,黄 王成2,李志伟1
(1.香港理工大学土地测量与地理资讯学系,香港; 2.中国科学院上海天文台,上海 200030;3.中国科学院研究生院,北京 100039)
The Preliminary Study on Marine Atmospheric Boundary Layer Using Synthetic Aperture Radar
CHEN Yan-ling1,2,3, DING Xiao-li1, HUANG Cheng2, LI Zhi-wei1
(1.Department of Land Surveying and Geo-Informatics,The Hong Kong Polytechnic University,Hong Kong; 2.Shanghai Astronomical Observatory,Chinese Academy of Sciences,Shanghai200030,China; 3.Graduate School of Chinese Academy of Sciences,Beijing100039,China)
 全文: PDF 
摘要:

SAR(Synthetic Aperture Radar,合成孔径雷达)作为一种现代高空间分辨率成像侧视雷达,对地球表面海洋所成的图像中蕴含了极为丰富的中尺度及亚中尺度海洋大气边界层的信息,因此对边界层气象学研究有着非常重要的意义。但是,使用SAR研究海气边界层这一涵盖微波遥感、气象学及海洋学等学科的科学前沿课题在国内却少有文献报道。在此背景下,首先介绍了SAR反演海洋大气边界层的研究概况,回顾了SAR反演海气边界层参数的原理和方法。然后以2002年5月7日当地时间10时53分ERS-2卫星获取的香港地区(22.097°N,E 114.300°E)SAR海洋图像为例,进行了反演风向风速的初步试验,最终获得了较高精度的风矢量。具体过程如下:先对SAR图像进行预处理,包括ADC(Analog Digital Converter,模数转换器)补偿、精确校准及斑点滤波等过程;然后利用经典的谱分析方法求得具有180°模糊度的风向,再用香港天文台气象浮标实测资料消除这一不确定性得到了真实的相对风向;紧接着利用CMOD4地球物理模式函数计算得到了海面上10 m高的风速。与气象浮标站所记录的平均风速和风向比较,两个20 km×20 km大小的试验区域求得的风向误差分别为23.71°和7.00°,平均风速误差分别为0.18 m/s和-0.12 m/s。结果表明,如果对SAR预先进行严格的预处理,结合经典的谱分析方法和CMOD4模型,即可获取高精度的风矢量。这一结果为今后海洋大气边界层的研究奠定了良好的基础。

关键词: SAR海气边界层风矢量相似理论    
Abstract:

Synthetic Aperture Radar(SAR) is a high resolution, modern side-look imaging radar. SAR images of ocean surface contain a wealth of information of mesoscale and sub-mesoscale marine atmospheric boundary layer (MABL) phenomenon. Thus it is a very important data source for MABL meteorology study. However this hot topic, which covers microwave remote sensing, meteorology and oceanology, etc. have got reported by few Chinese open literature. Based on such situation, firstly we summarize the recent MABL studies, and introduce the principle and methods of studying MABL with SAR images. As an example,ERS-2 SAR image covering Hong Kong region acquired on May 7, 2002 is used for the preliminary test of wind vector retrieval. The processing include:①pre-processing the SAR images, including Analog Digital Converter (ADC) compensation, accurate calibration and speckle removal; and②wind direction and wind speed retrieval with the classic SAR Wind Direction Algorithm spectral method. The wind direction thus estimated is however with 180°ambiguity. Buoy data collected by the Hong Kong Observatory are then used to resolve the uncertainty. Finally, the GMF(Geophysical Model Function)-CMOD4 is adopted to estimate the wind speed at the height of 10m above sea level.
Compared with the wind direction and wind speed data recorded by Hong Kong Observatory, the error of the retrieved wind directions of two selected regions, (20 km×20 km each) are 23.71°and 7.00°,respectively, while that of the retrieved mean wind speed are 0.18 m/s and -0.12 m/s, respectively. The results show that high quality wind vector can be acquired if strict pre-processing, classical spectral analysis algorithm and CMOD4 model are adopted. The results are very encouraging for the future MABL research.

Key words: Synthetic aperture radar    Marine atmospheric boundary layer    Wind vector    Similarity theory
收稿日期: 2007-12-15 出版日期: 2011-11-25
:  TP 751   
基金资助:

香港RGC(polyu 5157/05E)和国家自然科学基金(40404001)资助。

作者简介: 陈艳玲(1980-),女,博士研究生,研究方向为微波遥感的应用。
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  

引用本文:

陈艳玲,丁晓利,黄 王成,李志伟. 星载SAR在海气边界层气象学中的应用研究[J]. 遥感技术与应用, 2007, 22(2): 238-241.

CHEN Yan-ling, DING Xiao-li, HUANG Cheng, LI Zhi-wei. The Preliminary Study on Marine Atmospheric Boundary Layer Using Synthetic Aperture Radar. Remote Sensing Technology and Application, 2007, 22(2): 238-241.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2007.2.238        http://www.rsta.ac.cn/CN/Y2007/V22/I2/238

[1] Gerling T W. Structure of the Surface Wind Field from SeaSat SAR[J]. Journal of Geophysical Research, 1987,91:2308-2320.
[2] Alpers W, Brummer B. Atmospheric Boundary Layer Rolls Observed by the SAR Aboard the ERS-1 Aatellite[J].Journal of Geophysical Research, 1994, 99: 12613-12621.
[3] Sikora T D. An Investigation of Convective Marine Atmospheric Boundary Layer Using Real and Synthetic Aperture Radar[D]. The Pennsylvania State University, 1996.
[4] Winstead N S. Using Synthetic Aperture Radar to Remotely Sense Mesoscale and Submesoscale Processes in the Marine Atmospheric Boundary Layer [D]. The Pennsylvania state University, 1999.
[5] Young G S, Sikora T D, Winstead S. Inferring Marine Atmospheric Boundary Layer Properties from Spectral Characteristics of Satellite-borne SAR Imagery [J]. Monthly Weather Review, 2000,128 :1506-1520.
[6] 王超,潘广东.航天飞机成像雷达海面风矢量观测研究[J].遥感学报,2000,4(1):51-54.
[7] 万凯.卫星SAR图像的海洋大气边界层特征参数反演[J].海洋科学进展,2005,23(3):320-327.
[8] Stoffelen A, Ander son D. Scatterometer Data Interpretation: Estimation and Validation of the Transfer Function CMOD4[J]. Journal of Geophysical Research, 1997, 102:5767-5780.
[9] Fetterer F, Gineris D, Wackerman C. Validating A Scatterometer Wind Algorithm for ERS-1 SAR[J]. IEEE Trans on Geosciences and Remote Sensing, 1998, 36(2): 479-492.

[1] 李姣姣,刘玉,陈锟山. 基于香农熵的极化SAR相干矩阵信息量评价#br#[J]. 遥感技术与应用, 2018, 33(5): 842-849.
[2] 王常颖,田德政,韩园峰,隋毅,初佳兰. 基于属性差决策树的全极化SAR影像海冰分类[J]. 遥感技术与应用, 2018, 33(5): 975-982.
[3] 郭欣,赵银娣. 基于Sentinel-1A SAR的湖南省宁乡市洪水监测[J]. 遥感技术与应用, 2018, 33(4): 646-656.
[4] 张程,张红,王超. 基于PCDM香农熵的全极化SAR图像船舶目标检测方法[J]. 遥感技术与应用, 2018, 33(3): 499-507.
[5] 张宜振,韩震,朱情逸,王艺晴,胡旭冉. 不同季节海面风矢量对海表面亮温增益的影响研究[J]. 遥感技术与应用, 2018, 33(2): 331-336.
[6] 刘建歌,慕德俊. 基于SAR影像海冰动态特征的提取方法[J]. 遥感技术与应用, 2018, 33(1): 55-60.
[7] 张王菲,陈尔学,李增元,赵磊,姬永杰. 干涉、极化干涉SAR技术森林高度估测算法研究进展[J]. 遥感技术与应用, 2017, 32(6): 983-997.
[8] 周晓宇,陈富龙. 四川大熊猫栖息地PALSAR时序数据森林覆盖动态监测研究[J]. 遥感技术与应用, 2017, 32(6): 1100-1106.
[9] 扎西央宗,李林,卓玛,冯岩,李学东,白玛央宗. 西藏年楚河流域冰川变化监测方法研究[J]. 遥感技术与应用, 2017, 32(6): 1126-1131.
[10] 姜爱辉,刘国林,陈富龙. 基于PALSAR-1影像的汉函谷关遗迹变化检测研究[J]. 遥感技术与应用, 2017, 32(5): 787-793.
[11] 尤江彬,陈富龙. 西域都护府/且末古城数字地望考与长波段雷达次地表考古初探[J]. 遥感技术与应用, 2017, 32(5): 794-800.
[12] 张宝华,周文涛,吕晓琪. 基于稀疏分解和改进MRF模型的SAR海冰图像分割方法[J]. 遥感技术与应用, 2017, 32(4): 709-713.
[13] 王苏芸,孙中昶,郭华东,申维. 基于面向对象的东营市城乡建设用地信息提取[J]. 遥感技术与应用, 2017, 32(4): 780-786.
[14] 孙亚勇,黄诗峰,李纪人,李小涛,马建威,曲伟. Sentinel-1A SAR数据在缅甸伊洛瓦底江下游区洪水监测中的应用[J]. 遥感技术与应用, 2017, 32(2): 282-288.
[15] 王娜,李强子,赵龙才,王红岩,李德江,黄慧萍. 基于变异系数法的SAR船舶检测优化研究[J]. 遥感技术与应用, 2017, 32(2): 305-314.