利用卫星资料反演表面海流的研究
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摘要
海流对海洋中多种物理过程、化学过程、生物过程和地质过程,以及海洋上空的气候和天气的形成及变化,都有影响和制约的作用；对于海军作战,海流是考虑作战的重要因素之一,恰当地利用海流,对作战会起到降低战争消耗,增加胜利因素的一个筹码。然而,目前利用的常规手段对大面积海域的表面海流实施高频率实时观测几乎是不可能的。卫星资料具有覆盖范围广,时间分辨率和空间分辨率高的特点,因此,研究如何利用卫星资料开展表面海流遥感反演,具有非常重要的理论和实践意义。
基于优化通道组合和减少阈值设置的思想,利用MODIS资料的多光谱特性,提出了一种多种算法结合优化的云检测方法,为海流的监测反演计算提供了较高的晴空像元可信度。分析最大相关系数方法(MCC)海表流反演原理以及其误差来源,基于连续时刻水体红外、光学特征,利用MCC方法反演得到表面海流场。采用DINEOF方法,对卫星反演的海表流场结果中,由于云覆盖和反演方法本身缺陷所导致的数据空白区插值补缺；并提出了一种基于变分同化方法并结合正则化思想的表面海流场全局优化方法,对插值后数据进行优化调整。通过对Jason-1资料统计试验,确定后向散射截面临界点,使其可作为采用VC算法和Young算法的依据,实现0-20m/s与20-40m/s高度计风速反演算法的结合；利用海面高度数据,计算地转流分量,并分析了其与MCC流和地波雷达实测流的差异。所得结论如下：
(1)提出的云检测算法,实现了海上薄云和透明云以及耀斑区的云检测,提高了海面低云、碎云以及部分被云覆盖像元的识别准确率；
(2)MCC方法反演的表面海流,与实测数据相比在流速流向上基本一致,并且不同示踪物反演结果,互为补充,大大提高了反演的覆盖度；
(3)利用变分同化方法并结合正则化思想,提出的一种表面海流场优化调整方法,使得流场达到全局最优,反演精度明显提高；
(4)提出的海面风速校准方法,避免了单一方法在风速反演上产生的误差；在近岸区域,高度计获得的流与实测流场存在较大差异,MCC方法更适用于近岸。
The ocean currents has an impact and constraints on ocean physical processes, chemical processes, biological processes and geological processes, as well as over the ocean climate and weather formation and change, so to understand and master the law of currents, has great significance for fisheries, shippinggreat, sewage etc. Ocean currents is an important factor in considering the operations for the Naval Operations. However,the high-frequency real-time observation of a large area sea surface currents is almost impossible, to conventional means. Therefore, Remote sensing inversion of surface currents has a very important theoretical and practical significance.
Based on the thinking of optimized combination of channels and reduce the threshold set, used of multi-spectral characteristics of the MODIS data,an of the cloud detection optimization method has been proposed. A high clear sky pixel credibility has been provided to calculation of the currents monitoring. Ocean currents have been retrievaled by using sea surface temperature data and550nm reflectance data and MCC method.And, using DINEOF interpolation method, fill the data of lack ocean currents generated by the cloud and the MCC method itself For the filled data, using the variational assimilation method combined with the idea of the regularization,a ocean surface currents to optimize and adjustment method has been proposed. The joint sea surface wind speed calibration method of Vandemark-Chapron algorithm and Young algorithm has been launched. Sea surface height data has been used to calculate the geostrophic flow component, and the causes of the differences geostrophic currents component,the MCC currents and measured currents. The conclusions are:
(1) Sea thin cloud and transparent cloud have been detected nicely. The identification accuracy of low clouds, broken cloud, and part of the cloud,has been improved on the sea.
(2) The surface currents of MCC method is the same with the measured data.And, different tracer inversion results, complements each other, greatly improves the coverage of the inversion.
(3) Using the variational assimilation method combined with the idea of the regularization,a sea surface currents to optimize and adjustment method has been proposed. Retrieval accuracy is significantly improved.
(4) Sea surface wind speed calibration method has been proposed to avoid a single method in the0-20m/s and20-40m/s wind speed retrieval error. In the near-shore region,geostrophic currents component have a big difference with the measured data,MCC method currents are more practical.
基于优化通道组合和减少阈值设置的思想,利用MODIS资料的多光谱特性,提出了一种多种算法结合优化的云检测方法,为海流的监测反演计算提供了较高的晴空像元可信度。分析最大相关系数方法(MCC)海表流反演原理以及其误差来源,基于连续时刻水体红外、光学特征,利用MCC方法反演得到表面海流场。采用DINEOF方法,对卫星反演的海表流场结果中,由于云覆盖和反演方法本身缺陷所导致的数据空白区插值补缺；并提出了一种基于变分同化方法并结合正则化思想的表面海流场全局优化方法,对插值后数据进行优化调整。通过对Jason-1资料统计试验,确定后向散射截面临界点,使其可作为采用VC算法和Young算法的依据,实现0-20m/s与20-40m/s高度计风速反演算法的结合；利用海面高度数据,计算地转流分量,并分析了其与MCC流和地波雷达实测流的差异。所得结论如下：
(1)提出的云检测算法,实现了海上薄云和透明云以及耀斑区的云检测,提高了海面低云、碎云以及部分被云覆盖像元的识别准确率；
(2)MCC方法反演的表面海流,与实测数据相比在流速流向上基本一致,并且不同示踪物反演结果,互为补充,大大提高了反演的覆盖度；
(3)利用变分同化方法并结合正则化思想,提出的一种表面海流场优化调整方法,使得流场达到全局最优,反演精度明显提高；
(4)提出的海面风速校准方法,避免了单一方法在风速反演上产生的误差；在近岸区域,高度计获得的流与实测流场存在较大差异,MCC方法更适用于近岸。
The ocean currents has an impact and constraints on ocean physical processes, chemical processes, biological processes and geological processes, as well as over the ocean climate and weather formation and change, so to understand and master the law of currents, has great significance for fisheries, shippinggreat, sewage etc. Ocean currents is an important factor in considering the operations for the Naval Operations. However,the high-frequency real-time observation of a large area sea surface currents is almost impossible, to conventional means. Therefore, Remote sensing inversion of surface currents has a very important theoretical and practical significance.
Based on the thinking of optimized combination of channels and reduce the threshold set, used of multi-spectral characteristics of the MODIS data,an of the cloud detection optimization method has been proposed. A high clear sky pixel credibility has been provided to calculation of the currents monitoring. Ocean currents have been retrievaled by using sea surface temperature data and550nm reflectance data and MCC method.And, using DINEOF interpolation method, fill the data of lack ocean currents generated by the cloud and the MCC method itself For the filled data, using the variational assimilation method combined with the idea of the regularization,a ocean surface currents to optimize and adjustment method has been proposed. The joint sea surface wind speed calibration method of Vandemark-Chapron algorithm and Young algorithm has been launched. Sea surface height data has been used to calculate the geostrophic flow component, and the causes of the differences geostrophic currents component,the MCC currents and measured currents. The conclusions are:
(1) Sea thin cloud and transparent cloud have been detected nicely. The identification accuracy of low clouds, broken cloud, and part of the cloud,has been improved on the sea.
(2) The surface currents of MCC method is the same with the measured data.And, different tracer inversion results, complements each other, greatly improves the coverage of the inversion.
(3) Using the variational assimilation method combined with the idea of the regularization,a sea surface currents to optimize and adjustment method has been proposed. Retrieval accuracy is significantly improved.
(4) Sea surface wind speed calibration method has been proposed to avoid a single method in the0-20m/s and20-40m/s wind speed retrieval error. In the near-shore region,geostrophic currents component have a big difference with the measured data,MCC method currents are more practical.
引文
[1]奥特加,多元方程组解法迭代解法(朱季纳译),科学出版社,1983.
[2]白洁,王洪庆,陶祖钰.GMS卫星红外云图云迹风的反演.北京大学学报(自然科学版),1997,1：85-92.
[3]鲍登K F.沿岸水域物理海洋学.北京：海洋出版社,1992.
[4]边肇祺,张学工等.模式识别(第二版).北京：清华大学出版社,2000.
[5]陈渭民.卫星气象学.北京：气象出版社,2003.
[6]陈华,许健民等.用高度调整法进行云迹风高度的质量控制.气象科学,1999,19(1)：20-25.
[7]陈刚毅,丁旭羲,赵丽妍.用模糊神经网络自动识别云的技术研究.大气科学,2005,5：169-176.
[8]陈戈,方朝阳,徐萍.利用双波段补偿法提高卫星高度计海面风速反演精度.中国图形图像学报,1999,4(A11)：970-975.
[9]程云鹏.矩阵论.西北工业大学出版社,2000.
[10]程亮,郭洪涛.我国东南沿海区域海表面流场卫星遥感监测.海洋预报,2007,24(3)：65-75.
[11]程亮.基Kriging插值方法的MODIS资料的几何纠正方法[J].海洋技术,2007.26(2)：51-53.
[12]程亮,李培军,张水平.基于分形插值技术的MODIS资料的几何纠正方法[J].热带海洋学报,2005.24(6)：80-83.
[13]丑纪范,数值天气预报中的若干新技术,气象出版社,1995,262-294.
[14]董超华.气象卫星业务产品释用手册.北京：气象出版社,1999.
[15]丁守国,赵春生,石广玉,等.近20年全球总云量变化趋势分析.应用气象学报,2005,16(5)：670-677.
[16]方翔,许健民,张其松.高密度云导风资料所揭示的发展和不发展热带气旋的对流层上部环流特征.热带气象学报,2000,217-224.
[17]费文龙.变分方法在GMS-5气象卫星云图处理中的应用研究.南京理工大学硕士论文,2004.
[18]冯士筰,李凤岐,李少菁.海洋科学导论.北京：高等教育出版社,1999.
[19]郭洪涛,王毅,刘向培等.卫星云图云检测的一种综合优化算法,解放军理工大学学报(自然科学版),2010,11(2)：221-227.
[20]郭洪涛,谢欢欢,马英等.基于支持向量机的云相态分析.解放军理工大学学报(自然科学版),录用待刊.
[21]郭广猛.非星历法去除MODIS图像边缘重叠影响研究[J].遥感技术与应用,2003.Vol 18,NO 3.
[22]何全军等.基于多光谱综合的MODIS数据云检测研究[J].国土资源遥感,2006,69(3)：19-22.
[23]洪梅,张韧,孙照渤.多光谱卫星云图的高维特征聚类与降水天气判别.遥感学报,2006,2：42-48.
[24]洪梅,张韧,万齐林,等.模糊聚类与遗传算法相结合的卫星云图云分类.地球物理学进展,2005,4：1-1.
[25]韩雷,王洪庆,林隐静.光流法在强对流天气临近预报中的应用.北京大学学报(自然科学版),2008,44(5)：752-755.
[26]黄思训,伍荣生,大气科学中的数学物理问题,气象出版社,2001.
[27]姜祝辉,黄思训,刘刚.星载雷达高度计资料反演海而风速进展研究.海洋通报,2011,5：588-594.
[28]姜祝辉,黄思训,郭洪涛等.Vandem ark-Chapron算法与Young算法联合反演雷达高度计海面风速方法研究.海洋通报,2011,6：679-682.
[29]姜祝辉,黄思训,杜华栋等.利用变分结合正则化方法对高度计风速资料调整海面风场的研究.物理学报,2010,59(12)：8968-8977.
[30]姜祝辉,黄思训,何然等.合成孔径雷达资料反演海面风场的正则化方法研究.物理学报,2011,60(6)：068401.
[31]蒋耿明MODIS数据基础处理方法研究和软件实现.中国科学院研究生院硕士学位论文,2003.6.
[32]李艳兵,李元祥,翟景秋.卫星云图形态特征提取和表示的一种方法.南京气象学院学报,2006,NO.5.
[33]李昀英,宇如聪,徐幼平,等.中国南方地区层状云的形成和日变化特征分析.气象学报,2003,61(6)：733-743.
[34]李微,方圣辉,佃袁勇等.基于光谱分析的MODIS云检测算法研究[J].武汉大学学报(信息科学版),2005.30(5)：435-443.
[35]李柳霞.MODIS影像数据预处理技术研究,中国农业大学硕士学位论文,2004.6.
[36]李培军,郭洪涛.极轨气象卫星图像的两种投影算法.气象科学,2008,28(1)：90-94.
[37]刘向陪.台湾地区云检测方法研究.解放军理工大学硕士学位论文,2009.6.
[38]刘良明,刘廷,刘建强等.卫星海洋遥感导论.武汉：武汉大学出版社,2005.
[39]刘艳,翁笃呜.中国地区云对地2气系统辐射强迫温度效应的气候研究..气象学报,2002,60(6)：766-773.
[40]刘健,许健民,方宗义.利用NOAA卫星AVHRR资料分析云的性质[J].应用气象学报,1998.Vol.9,NO.4
[41]刘志刚,李元祥,黄峰.基于动态聚类的MODIS云检测算法[J].遥感应用,2007.33-36.
[42]刘湘航,曹晓光,郁文霞.基于分形维数的云检测算法.第五届全国“信号与信息处理”联合学术会议暨陕西省生物医学工程学会二○○六年学术年会。134-137.
[43]刘博.卫星雷达高度计近海反演算法研究.南京：解放军理工大学气象学院硕士学位论文,2011.
[44]吕咸青、刘文剑,数据同化中伴随方法及其有关问题的研究,海洋科学,2001,第25卷,第3期.
[45]马芳,张强,郭铌等.多通道卫星云图云检测方法的研究.大气科学,2007,31(1)：119-128.
[46]毛志华,潘德炉等.常规信息对遥感海表流场的修正方法.海洋学报,1997,3：142-149.
[47]毛志华,潘德炉等.利用卫星遥感SST估算海表流场.海洋通报,1996,1：84-90.
[48]师春香,瞿建华.用神经网络方法对NOAA-AVHRR资料进行云客观分类.气象学报,2002,2：123-128.
[49]师春香,吴蓉璋,项续康.多阈值和神经网络卫星云图云系自动分割试验.应用气象学报,2001,1：72-81.
[50]石汉青,何明元,刘寒.对气象卫星亮温的一种云、地分离方法[J].气象科学,2003.Vol.23,NO.1.
[51]侍茂崇.物理海洋学.山东：山东教育出版社,2004.12.
[52]孙从容,张正,张为良,曾韬.利用卫星遥感进行海上透明云薄云的检测[J].海洋预报,2005,22(5)：88-93.
[53]宋小英,赵英时.MODIS图像的云检测及分析[J].中国图像图形学报,2003,8(9)：1079-1083.
[54]盛峥,石汉青,丁又专.利用DINEOF方法重构缺测的卫星遥感海温数据,海洋科学进展.2009,Vol.27(2)：243-249.
[55]吴咏明,张韧,蒋国荣,等.多光谱卫星图像的一种模糊聚类方法.热带气象学报,2004,6：74-81.
[56]瓦普尼克.统计学习理论的本质.北京：清华大学出版社,2000.
[57]王振会,许建明,Kelly G.基于傅立叶相位分析的卫星导风技术.气象科学,2004,3：9-15.
[58]王振会,曾维麟.卫星云迹风微机客观导出系统.南京气象学院学报,1996,19(1)：69-75.
[59]王振会,陈金娥等.卫星云迹风导出系统的结果分析.南京气象学院学报,1997,20(3)：382-386.
[60]王毅.国际新一代对地观测系统的发展及其主要应用.北京：气象出版社,2006.
[61]王峰,许健民.云迹风资料所揭示的对流层上部环流形势与1998年夏季我国南方雨带的关系,1998年长江嫩江流域特大暴雨的成因及预报应用研究.北京：气象出版社,2001,142-147.
[62]王惠文.偏最小二乘回归方法及其应用.北京：国防工业出版社,1999.
[63]王永亮.MODIS图像的薄云透明云检测[J].气象科学,2007,27(1)：76-81.
[64]王广运,王海瑛,许国昌.卫星测高原理.北京：科学出版社,1995.
[65]工艳娇.基于悬浮泥沙影响的水深遥感方法研究.南京师范大学博士论文,2006.
[66]伍荣生,动力气象学,上海科技出版社,1983.
[67]许健民,静止气象卫星导风产品,气象卫星业务产品释用手册.北京：气象出版社,1999.
[68]许健民,张其松,方翔.用红外和水汽两个通道的卫星测值指定云迹风的高度.气象学报,1997.
[69]许健民,张其松,王大昌,等.云迹风计算中的两个几何问题.应用气象学报,1997.
[70]薛俊韬,刘正光,刘还珠.小波变换在云图边缘处理中的应用.天津大学学报,2002,35(6)：736-739.
[71]杨枝灵.数字图像获取、处理及实现应用.北京：人民邮电出版社,2004.
[72]杨文凯.静止气象卫星导风技术的研究.解放军理工大学气象学院硕士论文,2004.
[73]杨澄,袁招洪,顾松山.用多谱闽值法进行GMS-5卫星云图云型分类的研究.南京气象学院学报,2002,25(6)：747-754.
[74]英国Dundee卫星接收站MODIS常见问题列表. http://www.sat.dundee.ac.uk/modis-faq.html#geo.
[75]郑君杰,黄峰,张韧,等.基于纹理与分形理论的气象卫星云图目标物识别.气象科学,2005,3：1-1.
[76]张守峰,王诗文.应用卫星云导风进行台风路径预报试验试验.热带气象学报,1999,15(4)：347-355.
[77]张鹰,张东,张芸.南黄海辐射沙脊群海域的水深遥感.海洋学报,2009,3：142-149.
[78]Ackerman, S A, Strabala K I, Menzel W P, et al. Gumley. Discriminating clear sky clouds with MODIS. J Geophys Res,1998,103,32:141-32.
[79]Alexander A K, Vladimir V R, Marco V, et al. Semi-Analytical CloUd Retrieval Algorithm for SCIAM ACHY/ENVISAT, April 1st,2006.
[80]Baker W E. Utilisation of Satellite Winds for Climate and Global Change Studies, Proc. NOAA Conference on Operational Satellites:Sentinels for the Monitoring of Climate and Global Change. Global Planetary Change, 1991,4:157-163.
[81]Barrick D E. Remote sensing of the sea stateby radar. IEEE Oceans,1972,4:186-192.
[82]Batteen, M.L.,1997:Wind-forced modeling studies of currents, meanders and eddies in the California Current System. J.Geophys. Res.,102,985-1,010.
[83]Beckers J, Rixen M. EOF calculations and data filling from incomplete oceanographic data sets. Journal of Atmospheric and Oceanic Technology,2003,20(12):1839-1856.
[84]Bowen M, Emery W, Wilkin J, et al. Extracting multiyear surface currents from sequential thermal imagery using the Maximum Cross-correlation Technique, J Atmos Oceanic Technol,2002.131:1665-1676.
[85]Brown G S. The average impulse response of a rough surface and its applications. IEEE Transactions on antennas and propagation,1977, AP-25(1):67-74.
[86]Brown G S, Stanley H R, Roy N A. The wind-speed measurement capability of spaceborne radar altimeters. IEEE Journal of Oceanic Engineering,1981, OE-6(2):59-63.
[87]Brown R A. Longitudinal instabilities and secondary flows in the planetary boundary layer:A review. Rev Geophys,1980,18:683-697.
[88]Buhler Y, Holmlund K. The CMW Extraction Algorithm for MTP/MPEF, Proceedings of the 2nd International Winds Workshop.EUMETSAT, EUM P Tokyo,1993,14:205-217.
[89]Carrere L, Mertz F, Dorandeu J, et al. Observing and studying extreme low pressure events with altimetry. Sensors,2009,9:1306-1329, doi:10.3390/s90301306.
[90]Campbell G G, Holmlund K. Geometric Cloud Heights from Meteosat and AVHRR, Proceedings Fifth International Wind Workshop. Lorne Australia, March 2000,28:109-115.
[91]Cushman-Roisin, B.,1994:Introduction to Geophysical Fluid Dynamics, Prentice Hall, New Jersey.
[92]Chapron B, Collard F, Ardhuin F. Direct measurement of ocean surface velocity from space:Interpretation and validation, J Geophys Res.2005,110, C0022, doi:10.1029/2004JC0022.
[93]Chelton D B, Mccabe P J. A review of satellite altimeter measurement of sea surface wind speed:with a proposed new algorithm. JGeophysRes,1985,90 (C3):4707-4720.
[94]Choi H, Bindschadler R. Cloud detection in Landsat imagery of ice sheets using shadow matching technique and automatic normalized difference snow index threshold value decision. Remote Sensing of Environment,2004, 91(2):237-242.
[95]Cote S, Tatnall A. The Hopfield neural network as a tool for feature trackingand recognition from satellite sensor images. Inte J Rem Sens,18:871-885.
[96]Crocker R., Emery,W, Matthews D, et al. Computing Ocean Surface Currents from Infrared and Ocean Color Imagery. IEEE Trans. Geosci. Rem. Sens,2007,45:435-447.
[97]Dobson E F, Monaldo F, Goldhirsh J. Validation of Geosat altimeter-derived wind speeds and significant wave heights using buoy data. J Geophys Res,1987,92:10719-10731.
[98]Dumont J P, Thibaut P, Zanife O Z. ALT_CAL_GEN_01-To generate waveforms. Algorithm definition, accuracy and sp ecification volume 2:CM A altimeter level lb processing(SMM-ST-M 2-EA-11010-CN).2001,64-69.
[99]Emery W J, Thomas A C, Collins M J, et al. An Objective Method for Computing Advective Surface Velocities From Sequential Infrared Satellite Images. J Geophys Res,1991 (C11):12,865-12.
[100]Emery, W.J., A.C. Thomas, M.J. Collins, W.R. Crawford & D.L. Mackas,1986:An objective procedure to computeadvection from sequential infrared satellite images. J.Geophys. Res.,91 (color issue),12,865-12,879.
[101]Emery W J, Fowler C, Clayson A. Satellite image-derived Gulf Stream currents compared with numerical model results. J Atmospheric Oceanic Technology,1992,9:286-304.
[102]Emery W J, Fellow, IEEE, D. Baldwin, and D. Matthews.Maximum Cross Correlation Automatic Satellite Image Navigation and Attitude Corrections for Open-Ocean Image Navigation. IEEE TRANSACTIONS ON GEOSCIENCE AND REM OTE SENSING,VOL.41, NO.1, JANUARY 2003. p33-42.
[103]Garcia C A, Robinson I S. Sea surface velocities in shallow seas extracted from sequential Coastal ZoneColor Scanner Satellite data. J Geophys. Res,1989,94(C12):12681-12691.
[104]Gao Bocai.Goetz F H.Cirrus Cloud Detection from Airborne Imaging Spectrometer Data Using the 1.38 Water Vapor Band[J]. Journal of Geophysical Research Letter,1993,20(4):301-304.
[105]Gao Bocai. Selection of 1.375 MODIS Channel for Remote Sensing of Cirrus Clouds and Stratospheric Aerosols from Space[J].American Meteorological Society,1995:4231-4237
[106]Gesell,G.:An algorithm for snow and ice detection using AVHRR data:An extension to the APOLLO software package. Int. J. Remote Sensing,1989,10(2):897-905.
[107]Goodman A H, Henderson S A. Cloud detection and analysis:A review of recent progress. Atmospheric Research, 1988,21:203-228.
[108]Gourrion J, Vandemark D, Bailey S, et al. Satellite altimeter models for surface wind speed developed using ocean satellite crossovers.2000, Technical report, Report No:IFREM ER-DROOS-2000-02.
[109]Guo Hongtao, Chang Zhiguo, He Shanwei. Geostationary Meteorological Satellite Data Processing System, advanced Materials Research journals,2011,181-182.
[110]Guo Hongtao, Xie Huanhuan. Application of MODIS data to monitor sea ice in Bohai sea.2010 Second IITA International Conference on Geoscience and Remote Sensing,2010,36-38.
[111]Guo Hongtao, Zhang Ying. Application of optical flow method in inversion of ocean surface flow field.2010 Second IITA International Conference on Geoscience and Remote Sensing,2010,31-36.
[112]Hayne G S. Radar altimeter mean return waveform from near nominal-incidence ocean surface scattering IEEE Trans Antennas Propag,1980, AP-28:687-692.
[113]Holyer R J, Peckinpaugh S H. Edge detection applied to satellite imagery of the oceans. IEEE Trans Geosci Rem Sens,1989,27:46-56.
[114]Horn B K P, Schunck B G. Determining optical flow.Artlficial Intelligence,1981,17:185-204.
[115]Huang N E, Long S R. A study of the surface elevation probability distribution function and statistics of wind generated waves. J Fluid Mechanics,1980,101:179-200.
[116]Huang P A, Sletten M A. Energy dissipation of wind-generated waves and whitecap coverage. J Geophys Res, 2008a,113, C02012, doi:10.1029/2007JC004277.
[117]Huang P A, Sletten M A.Toporkov J V Analysis of radar sea return for breaking wave investigation. J Geophys Res,2008b,118, C02003, doi:10.1029/2007JC004319.
[118]http://modis.gsfc.nasa.gov:MODIShomepage
[119]Isern-Fontanet J, Chapron B, Lapeyre G, et al. Potential use of microwave sea surface temperatures for the estimation of ocean currents. Geophys. Res. Lett.,2006,22, L24608,doi:10.1029/2006GL027801.
[120]Isern-Fontanet J, Turiel A., Garcia-Ladona E, et al. Microcanonical Multifractal For malism:application to the estimation of ocean surface velocities. J Geophys Res,2007,112.C05024, doi:10.1029/2006JC003878.
[121]Jedlovec, G J, Laws K. GOES Cloud detection at the Global Hydrology and Climate Center. Preprints,12th Conf. on Satellite Meteorology and Oceanography, Long Beach, CA, Amer. Meteor. Soc., CD-ROM,P1.21,2003.
[122]Johannessen J, Kudryavtsev V, Akimov D, et al.On Radar Imaging of Current Features; Part 2:Mesoscale Eddy and Current Front detection. J Geophys Res.2005,110, C07017, doi:10.1029/2004JC002802.
[123]Kamachi M. Advective surface velocities derived from sequential images for rotational flow field:Limitations and applications of maximum cross-correlation method with rotational registration. J Geophys Res,1989, 94(C12):18227-18233.
[124]Kelly K A.An inverse model for near-surface velocity from infrared images. J Phys Oceanogr,1989,19:1845-1864.
[125]Kelly K A, Strub PT. Comparison of velocity estimates from Advanced Very High Resolution Radiometer in the coastal transition zone. J Geophys Res.1992,97 (C6):9653-9668.
[126]Krasnopolski, V.M., and L.C. Breaker,1994. The problem of AVHRR image navigation revisited, International Journal of Remote Sensing,15(2):979-1008.
[127]Kriebel, K.T., R.W. Saunders, and G.Gesell:Optical properties of clouds derived from fully cloudy pixels. Contr. Phys.Atmos.,62,165-171,1989.
[128]Larouche P, Thomassin E, Boucher, J M, et al. Sea surface velocity estimations using SST images In Proceedings of the 4th Int. Conf. on Remote Sens. for Marand Coastal Environments, Orlando, FL,1997,431-438.
[129]Le Dimet, F, and O. Talagrand, Variational algorithms for analysis and assimilation of meteorological observations:Theoretical aspects. Tellus,1986,38A,97-110.
[130]Leese J A, Novak C S. An Automated Technique for Obtaining Cloud Motion from Geosynchronous Satellite DataUsingCross Correlation. J ApplMeteor,1971,10:118-132.
[131]Liu A K, Martin S, Kwok R. Tracking of Ice Edges and Ice Floes by Wavelet Analysis of SAR Images. Journal of Atmospheric and Oceanic Technology,1997,14:1187-1198.
[132]M cClain E P,Pichel W G and Walton C C.Comp arative p erformance of AVHRR-based multichannel sea surface temperatures.J Geophys Res.1985,90:11587-11601.
[133]Menzel W P, Smith W L, Stewart T R.Improved Cloud Motion Wind Vector and Altitude Assignment Using VAS. J Cli AppliMeteor.1983,22:377-384.
[134]MenzelWP. Application with Meteorological Satellites.WMOTechnical Document,2001,1078, SAT-28.
[135]Meteorological Satellite Center.1989. TheGMSUser Guide. Meteorological Satellite Center JMA,190P
[136]Monaldo F, Dobson E. On using significant wave height and radar cross section to improve radar altimeter measurements of wind speed. J Geophys Res,1989,94:12699-12701.
[137]Moore R K, Williams C S. Radar terrain return at near vertical incidence. Proc. IRE,1957,2(45):228-238.
[138]Nakamura Y, Ozawa E, Onogi K, et al. Impact Experiments on NWP with Rapid Scan AM Vs, Proceedings of the 6th International Winds Workshop. USA Madison, EUMETSAT Publication,2002, EUM P35:171-178.
[139]Nieman S J, Menzel W P, Hayden C M, et al. Fully Automatic Cloud-Drift Winds in NESDIS Operations. Bulletin of the American Meteorological Society,1997,78(6):1121-1133.
[140]Nieman S J, Schmetz J, Menzel W P. A Comparison of Several Techniques to Assign Heights to Cloud Tracers. Journal of Applied Meteorology,1993,32:1559-1568.
[141]Pailleux J.The Impact of Satellite Data on Global Numerical Weather Prediction. Remote Sensing Applications in Meteorology and Climatology, Vaughan R A Ed,1987,173-187.
[142]Parol F, Buriez J C, Brogniez G, Fouquart Y Information Content of AVHRR Channels 4 and 5 with Respect to the Effective Radius of Cirrus Cloud Particles. Journal of Applied Meteorology,1991,30:873-984.
[143]Pascual A, Faugere Y Larnicol G, et al. Improved description of the ocean mesoscale variability by combining four satellite altimeters. Geophys Res Lett,2006,33,611,doi:10.1029/2005GL024633.
[144]Peak J E, Tag P M. Toward automated interpretation of satellite imagery for navy shipboard applications. Bulletin of the American Meteorological Society,1992,73(7):995-1008.
[145]Peak J E, Tag P M. Segmentation of satellite imagery using hierarchical thresholding and neural networks. Journal of Applied Meteorology,1994,33:605-616.
[146]Quilfen Y, Tournadre J, Chapron B. Altimeter dual-frequency observations of surface winds, waves, and rain rate in tropical cyclone Isabel. J Geophys Res,2006,111:C01004.
[147]Rao P K, Holmes S J,Anderson R K等编,许建民等译,气象卫星—系统资料及其在环境中的应用.北京：气象出版社,1994.
[148]Remy F, Parouty S. Antarctic ice sheet and radar altimetry:A review. Remote Sensing,2009,1:1212-1239, doi:10.3390/rs1041212.
[149]Rolnald M.Errico, What is a adjoint model?, Bulletin of the American Meteorological Society,1997,Vol.78, No. 11.
[150]Rosmorduc V, Benveniste J, Lauret O, et al. Radar altimetry tutorial. J. Benveniste and N. Picot Ed., http://www.altimetry.info,2009.
[151]Sadler J C. A role of the tropical upper tropospheric trough in early season typhoon development. M W R,1976, 104:1266-1278.
[152]Santek D, Key J, Velden C, et al. Deriving Winds from Polar Orbiting Satellite Data. Proceedings of the 6th International Winds Workshop, USA Madison,2002, EUM ETSAT Publication, EUM P35:251-261.
[153]Saunders. R. W, Kriebel. K.T. An improved method for detecting clear sky and cloudy radiances from AVHRR data. Int. J. Remote Sens.,9,NO.1,123-150,1988
[154]Schmetz J, Holmlund K, Hoffman J, et al.Operational Cloud Motion Winds from Meteosat Infrared Images. Journal of Applied Meteorology.1993,32(7):1206-1225.
[155]Schmetz J, Hinsman D, Menzel W P.Summary of the Fourth International Wind Workshop. Bulletin of the American Meteorological Society,1999,80(5):893-899.
[156]Simpsona J J, Gobata J I. Improved cloud detection in GOES scenes over the oceans. Remote Sensing of Environment,1995,52(2):79-94.
[157]Smith W, Harrison W, Hinton D, et al. GIFTS-A System for Wind Profiling from Geostationary Satellites, Proceedings Fifth International Wind Workshop, Lome Australia,M arch 2000, EUM P 28:253-258.
[158]Stanley Q K,Kankiewicz J A. Meteosat Second Generation Cloud Algorithms for Use at AFWA. BACIMO Monterey,2005, CA:12-14.
[159]Steve Ackerman, Kathleen Strabala, Paul Menzel.etc.(MODIS Cloud Mask Team) Discriminating clear-sky from cloud with M ODIS.2006,10.
[160]Stowe, L. L., E.P. McClain, R. Carey, P. Pellegrino, G. Gutman, P. Davis, C. Long, and S.Hart,1991:Global distribution of cloud cover derived from NOAA/AVHRR operational satellite data. Adv. Space Res.,11,51-54.
[161]Szejwach G. Determination of Semitransparent Cirrus Cloud Temperature from Infrared Radiances:Application to Meteosat. Journal of Ap plied Meteorology,1982,21(3):384-393.
[162]Talagrand, O.,Assimilation of observations, an introduction. J.Meteor.Soc. Japan.,1997,75,191-209.
[163]Talagrand, O., and P. Curtier, Variational assimilation of meteorological observations with the adjoint vorticity equation. Part Ⅰ:Theory. Quart. J.Roy. Meteor. Soc.,1987,113,1311-1328.
[164]Tokmakian R T, Strub P T, McClean-Padman J. Evaluation of the maximum cross-correlation method of estimating sea surface velocities from sequential satellite images. J Atmos Ocean Tech,1990,7:852-865.
[165]Tran N, Vandemark D, Chapron B, et al. New models for satellite altimeter sea state bias correction developed using global wave model data. J GeophysRes,2006,111(C9):1-48.
[166]Tran N, Vandemark D, Lbroue S, et al. Sea state bias in altimeter sea level estimates determined by combining wave model and satellite data. J Geophy s Res,2010,115, C03020, doi:2009JC005534.
[167]Tran N, Vandemark D, Chapron B, et al. New models for satellite altimeter sea state bias correction developed using global wave model data. J Geophys Res,2006,111(C9):1-48.
[168]Tran N, Vandemark D, Lbroue S, et al. Sea state bias in altimeter sea level estimates determined by combining wave model and satellite data. J Geophys Res,2010,115, C03020, doi:2009JC005534.
[169]Traon P L, Dibarboure G. An illustration of the unique contribution of the TOPEX/Poseidon-Jason-1 tandem mission to mesoscale variability studies. Marine Geodesy,2004,27:3-13.
[170]Traon P L, Nadal F, Ducet N. An improved mapping method of multisatellite altimeter data. J Atmos Oceanic Technol.1998,15:522-534.
[171]Traon P L, Faugere Y, Hernandez F, et al. Can we merge GEOSAT Follow-On with TOPEX/POSEIDON and ERS-2 for an improved description of theocean circulation? J Atmos Oceanic Technol.2003,20:889-895.
[172]Turiel A, Parga NThe multi-fractal structure of contrast changes in natural images:from sharp edges to textures.Neural Computation,2000,12:763-793.
[173]Turiel A, Grazzini J, Yahia H. Multiscale techniques for the detection of precipitation using thermal IR satellite images. IEEE Geosci Remote Sens Lett,2005,2,447-450.
[174]Turiel A, Isern-Fontanet J, Garcia-Ladona E, et al.Multifractal method for the instant taneous evaluation of the stream function in geophysical flows. Phys. Rev. Lett.2005,95,104502,doi:10.1103/PhysRevLett.95.104502.
[175]Turiel A, Perez-Vicente C, Grazzini J. Numerical methods for the estimation of multifractal singularity spectra on sampled data:a comparative study. J Computat Phys.2006,216:362-390.
[176]Turiel A, Sole J, Nieves V, et al. Tracking oceanic currents by singularity analysis of Micro-Wave Sea Surface Temperatureimages. Rem Sens Environ,2008,112:2246-2260.
[177]Turiel A, Yahia H, P'erez-Vicente C. Microcanonical Multifractal Formalism:a geometrical approach to multifractal systems. Part Ⅰ:Singularity analysis. J Phys A,2008,41,015 501, doi:10.1088/1751-8113/41/1/015501.
[178]Turiel A V, Nieves E, Garcia-Ladona, et al. The multifractal structure of satellite sea surface temperature maps can be used to obtain global maps of streamlines. Ocean Sci Discuss.2009,6,129-151.
[179]User Manual for the PGE01-02-03 of the SAFNWC/M SG:Scientific part, Issue 1, Rev.2,3,2005.
[180]Vigan X, Provost C, Bleck R, et al. Sea surface velocities from sea surface temperature image sequences.1, Method and validation using primitive equation model output. J Geophys Res.2000,105:19499-19514.
[181]William B R, Leonid C G. Cloud detection using Satellite Measurements of Infrared and Visible Radiances for ISCCP.1993,6:2341-2369.
[182]Witter D L, Chelton D B. A Geosat altimeter wind speed algorithm and a method for altimeter wind speed algorithm development. J Geophys Res,1991,96:8853-8860.
[183]Wolf D E, Hall D J, Endlich R M. Experiments in Automatic Clound Tracking Using SMS-GOES Data. J Appl Meteor,1977,16:1219-1230.
[184]Wunsch C, Stammer D. Satellite altimetry, the marine geoid, and the oceanic general circulation. Ann Rev Earth Planet Sci,1998,26:219-353.
[185]Wylie, D. P., and W. P. Menzel,1994:Four years of global cirrus cloud statistics using HIRS. J. Climate,7, 1972-1986.
[186]Yang Le, Zou Ju-hong Lin Ming-sen, et al. Method to correct both foam and rain effects on dual frequency altimeter Jasonl wind measurements in typhoon Shanshan. In proceedings of SPIE, Remote sensing of the ocean, sea ice, and large water regions,2008a,7105,71050L, doi:10.1117/12.799623.
[187]Yang L, Lin M, Zou J, et al. Improving the wind and wave estimation of dual-frequency altimeter Jason-1 in Typhoon Shanshan and considering the rain effects. Acta Oceanologica Sinica,2008b,27(5):49-62.
[188]Young I R. An estimate of the Geosat altimeter wind speed algorithm at high wind speeds. J Geophys Res,1993, 98(C11):20275-20285.
[189]Zhao D L, Toba Y A spectral approach for determining altimeter wind speed model functions. Journal of Oceanography,2003,59:235-244.
[190]Zhao D L, Toba Y Effect of wave states on altimeter wind speed algorithm at high wind speeds.22nd Asian Conference on Remote Sensing, Singapore,5-9 November 2001.
[191]Zieger S, Vinoth J, Young I R. Joint calibration of multi-platform altimeter measurements of wind speed and wave height over thepast 20 years. J Atmos Oceanic Tech,2009,26, Doi 10.1175/2009JTCHA1303.1.
[2]白洁,王洪庆,陶祖钰.GMS卫星红外云图云迹风的反演.北京大学学报(自然科学版),1997,1：85-92.
[3]鲍登K F.沿岸水域物理海洋学.北京：海洋出版社,1992.
[4]边肇祺,张学工等.模式识别(第二版).北京：清华大学出版社,2000.
[5]陈渭民.卫星气象学.北京：气象出版社,2003.
[6]陈华,许健民等.用高度调整法进行云迹风高度的质量控制.气象科学,1999,19(1)：20-25.
[7]陈刚毅,丁旭羲,赵丽妍.用模糊神经网络自动识别云的技术研究.大气科学,2005,5：169-176.
[8]陈戈,方朝阳,徐萍.利用双波段补偿法提高卫星高度计海面风速反演精度.中国图形图像学报,1999,4(A11)：970-975.
[9]程云鹏.矩阵论.西北工业大学出版社,2000.
[10]程亮,郭洪涛.我国东南沿海区域海表面流场卫星遥感监测.海洋预报,2007,24(3)：65-75.
[11]程亮.基Kriging插值方法的MODIS资料的几何纠正方法[J].海洋技术,2007.26(2)：51-53.
[12]程亮,李培军,张水平.基于分形插值技术的MODIS资料的几何纠正方法[J].热带海洋学报,2005.24(6)：80-83.
[13]丑纪范,数值天气预报中的若干新技术,气象出版社,1995,262-294.
[14]董超华.气象卫星业务产品释用手册.北京：气象出版社,1999.
[15]丁守国,赵春生,石广玉,等.近20年全球总云量变化趋势分析.应用气象学报,2005,16(5)：670-677.
[16]方翔,许健民,张其松.高密度云导风资料所揭示的发展和不发展热带气旋的对流层上部环流特征.热带气象学报,2000,217-224.
[17]费文龙.变分方法在GMS-5气象卫星云图处理中的应用研究.南京理工大学硕士论文,2004.
[18]冯士筰,李凤岐,李少菁.海洋科学导论.北京：高等教育出版社,1999.
[19]郭洪涛,王毅,刘向培等.卫星云图云检测的一种综合优化算法,解放军理工大学学报(自然科学版),2010,11(2)：221-227.
[20]郭洪涛,谢欢欢,马英等.基于支持向量机的云相态分析.解放军理工大学学报(自然科学版),录用待刊.
[21]郭广猛.非星历法去除MODIS图像边缘重叠影响研究[J].遥感技术与应用,2003.Vol 18,NO 3.
[22]何全军等.基于多光谱综合的MODIS数据云检测研究[J].国土资源遥感,2006,69(3)：19-22.
[23]洪梅,张韧,孙照渤.多光谱卫星云图的高维特征聚类与降水天气判别.遥感学报,2006,2：42-48.
[24]洪梅,张韧,万齐林,等.模糊聚类与遗传算法相结合的卫星云图云分类.地球物理学进展,2005,4：1-1.
[25]韩雷,王洪庆,林隐静.光流法在强对流天气临近预报中的应用.北京大学学报(自然科学版),2008,44(5)：752-755.
[26]黄思训,伍荣生,大气科学中的数学物理问题,气象出版社,2001.
[27]姜祝辉,黄思训,刘刚.星载雷达高度计资料反演海而风速进展研究.海洋通报,2011,5：588-594.
[28]姜祝辉,黄思训,郭洪涛等.Vandem ark-Chapron算法与Young算法联合反演雷达高度计海面风速方法研究.海洋通报,2011,6：679-682.
[29]姜祝辉,黄思训,杜华栋等.利用变分结合正则化方法对高度计风速资料调整海面风场的研究.物理学报,2010,59(12)：8968-8977.
[30]姜祝辉,黄思训,何然等.合成孔径雷达资料反演海面风场的正则化方法研究.物理学报,2011,60(6)：068401.
[31]蒋耿明MODIS数据基础处理方法研究和软件实现.中国科学院研究生院硕士学位论文,2003.6.
[32]李艳兵,李元祥,翟景秋.卫星云图形态特征提取和表示的一种方法.南京气象学院学报,2006,NO.5.
[33]李昀英,宇如聪,徐幼平,等.中国南方地区层状云的形成和日变化特征分析.气象学报,2003,61(6)：733-743.
[34]李微,方圣辉,佃袁勇等.基于光谱分析的MODIS云检测算法研究[J].武汉大学学报(信息科学版),2005.30(5)：435-443.
[35]李柳霞.MODIS影像数据预处理技术研究,中国农业大学硕士学位论文,2004.6.
[36]李培军,郭洪涛.极轨气象卫星图像的两种投影算法.气象科学,2008,28(1)：90-94.
[37]刘向陪.台湾地区云检测方法研究.解放军理工大学硕士学位论文,2009.6.
[38]刘良明,刘廷,刘建强等.卫星海洋遥感导论.武汉：武汉大学出版社,2005.
[39]刘艳,翁笃呜.中国地区云对地2气系统辐射强迫温度效应的气候研究..气象学报,2002,60(6)：766-773.
[40]刘健,许健民,方宗义.利用NOAA卫星AVHRR资料分析云的性质[J].应用气象学报,1998.Vol.9,NO.4
[41]刘志刚,李元祥,黄峰.基于动态聚类的MODIS云检测算法[J].遥感应用,2007.33-36.
[42]刘湘航,曹晓光,郁文霞.基于分形维数的云检测算法.第五届全国“信号与信息处理”联合学术会议暨陕西省生物医学工程学会二○○六年学术年会。134-137.
[43]刘博.卫星雷达高度计近海反演算法研究.南京：解放军理工大学气象学院硕士学位论文,2011.
[44]吕咸青、刘文剑,数据同化中伴随方法及其有关问题的研究,海洋科学,2001,第25卷,第3期.
[45]马芳,张强,郭铌等.多通道卫星云图云检测方法的研究.大气科学,2007,31(1)：119-128.
[46]毛志华,潘德炉等.常规信息对遥感海表流场的修正方法.海洋学报,1997,3：142-149.
[47]毛志华,潘德炉等.利用卫星遥感SST估算海表流场.海洋通报,1996,1：84-90.
[48]师春香,瞿建华.用神经网络方法对NOAA-AVHRR资料进行云客观分类.气象学报,2002,2：123-128.
[49]师春香,吴蓉璋,项续康.多阈值和神经网络卫星云图云系自动分割试验.应用气象学报,2001,1：72-81.
[50]石汉青,何明元,刘寒.对气象卫星亮温的一种云、地分离方法[J].气象科学,2003.Vol.23,NO.1.
[51]侍茂崇.物理海洋学.山东：山东教育出版社,2004.12.
[52]孙从容,张正,张为良,曾韬.利用卫星遥感进行海上透明云薄云的检测[J].海洋预报,2005,22(5)：88-93.
[53]宋小英,赵英时.MODIS图像的云检测及分析[J].中国图像图形学报,2003,8(9)：1079-1083.
[54]盛峥,石汉青,丁又专.利用DINEOF方法重构缺测的卫星遥感海温数据,海洋科学进展.2009,Vol.27(2)：243-249.
[55]吴咏明,张韧,蒋国荣,等.多光谱卫星图像的一种模糊聚类方法.热带气象学报,2004,6：74-81.
[56]瓦普尼克.统计学习理论的本质.北京：清华大学出版社,2000.
[57]王振会,许建明,Kelly G.基于傅立叶相位分析的卫星导风技术.气象科学,2004,3：9-15.
[58]王振会,曾维麟.卫星云迹风微机客观导出系统.南京气象学院学报,1996,19(1)：69-75.
[59]王振会,陈金娥等.卫星云迹风导出系统的结果分析.南京气象学院学报,1997,20(3)：382-386.
[60]王毅.国际新一代对地观测系统的发展及其主要应用.北京：气象出版社,2006.
[61]王峰,许健民.云迹风资料所揭示的对流层上部环流形势与1998年夏季我国南方雨带的关系,1998年长江嫩江流域特大暴雨的成因及预报应用研究.北京：气象出版社,2001,142-147.
[62]王惠文.偏最小二乘回归方法及其应用.北京：国防工业出版社,1999.
[63]王永亮.MODIS图像的薄云透明云检测[J].气象科学,2007,27(1)：76-81.
[64]王广运,王海瑛,许国昌.卫星测高原理.北京：科学出版社,1995.
[65]工艳娇.基于悬浮泥沙影响的水深遥感方法研究.南京师范大学博士论文,2006.
[66]伍荣生,动力气象学,上海科技出版社,1983.
[67]许健民,静止气象卫星导风产品,气象卫星业务产品释用手册.北京：气象出版社,1999.
[68]许健民,张其松,方翔.用红外和水汽两个通道的卫星测值指定云迹风的高度.气象学报,1997.
[69]许健民,张其松,王大昌,等.云迹风计算中的两个几何问题.应用气象学报,1997.
[70]薛俊韬,刘正光,刘还珠.小波变换在云图边缘处理中的应用.天津大学学报,2002,35(6)：736-739.
[71]杨枝灵.数字图像获取、处理及实现应用.北京：人民邮电出版社,2004.
[72]杨文凯.静止气象卫星导风技术的研究.解放军理工大学气象学院硕士论文,2004.
[73]杨澄,袁招洪,顾松山.用多谱闽值法进行GMS-5卫星云图云型分类的研究.南京气象学院学报,2002,25(6)：747-754.
[74]英国Dundee卫星接收站MODIS常见问题列表. http://www.sat.dundee.ac.uk/modis-faq.html#geo.
[75]郑君杰,黄峰,张韧,等.基于纹理与分形理论的气象卫星云图目标物识别.气象科学,2005,3：1-1.
[76]张守峰,王诗文.应用卫星云导风进行台风路径预报试验试验.热带气象学报,1999,15(4)：347-355.
[77]张鹰,张东,张芸.南黄海辐射沙脊群海域的水深遥感.海洋学报,2009,3：142-149.
[78]Ackerman, S A, Strabala K I, Menzel W P, et al. Gumley. Discriminating clear sky clouds with MODIS. J Geophys Res,1998,103,32:141-32.
[79]Alexander A K, Vladimir V R, Marco V, et al. Semi-Analytical CloUd Retrieval Algorithm for SCIAM ACHY/ENVISAT, April 1st,2006.
[80]Baker W E. Utilisation of Satellite Winds for Climate and Global Change Studies, Proc. NOAA Conference on Operational Satellites:Sentinels for the Monitoring of Climate and Global Change. Global Planetary Change, 1991,4:157-163.
[81]Barrick D E. Remote sensing of the sea stateby radar. IEEE Oceans,1972,4:186-192.
[82]Batteen, M.L.,1997:Wind-forced modeling studies of currents, meanders and eddies in the California Current System. J.Geophys. Res.,102,985-1,010.
[83]Beckers J, Rixen M. EOF calculations and data filling from incomplete oceanographic data sets. Journal of Atmospheric and Oceanic Technology,2003,20(12):1839-1856.
[84]Bowen M, Emery W, Wilkin J, et al. Extracting multiyear surface currents from sequential thermal imagery using the Maximum Cross-correlation Technique, J Atmos Oceanic Technol,2002.131:1665-1676.
[85]Brown G S. The average impulse response of a rough surface and its applications. IEEE Transactions on antennas and propagation,1977, AP-25(1):67-74.
[86]Brown G S, Stanley H R, Roy N A. The wind-speed measurement capability of spaceborne radar altimeters. IEEE Journal of Oceanic Engineering,1981, OE-6(2):59-63.
[87]Brown R A. Longitudinal instabilities and secondary flows in the planetary boundary layer:A review. Rev Geophys,1980,18:683-697.
[88]Buhler Y, Holmlund K. The CMW Extraction Algorithm for MTP/MPEF, Proceedings of the 2nd International Winds Workshop.EUMETSAT, EUM P Tokyo,1993,14:205-217.
[89]Carrere L, Mertz F, Dorandeu J, et al. Observing and studying extreme low pressure events with altimetry. Sensors,2009,9:1306-1329, doi:10.3390/s90301306.
[90]Campbell G G, Holmlund K. Geometric Cloud Heights from Meteosat and AVHRR, Proceedings Fifth International Wind Workshop. Lorne Australia, March 2000,28:109-115.
[91]Cushman-Roisin, B.,1994:Introduction to Geophysical Fluid Dynamics, Prentice Hall, New Jersey.
[92]Chapron B, Collard F, Ardhuin F. Direct measurement of ocean surface velocity from space:Interpretation and validation, J Geophys Res.2005,110, C0022, doi:10.1029/2004JC0022.
[93]Chelton D B, Mccabe P J. A review of satellite altimeter measurement of sea surface wind speed:with a proposed new algorithm. JGeophysRes,1985,90 (C3):4707-4720.
[94]Choi H, Bindschadler R. Cloud detection in Landsat imagery of ice sheets using shadow matching technique and automatic normalized difference snow index threshold value decision. Remote Sensing of Environment,2004, 91(2):237-242.
[95]Cote S, Tatnall A. The Hopfield neural network as a tool for feature trackingand recognition from satellite sensor images. Inte J Rem Sens,18:871-885.
[96]Crocker R., Emery,W, Matthews D, et al. Computing Ocean Surface Currents from Infrared and Ocean Color Imagery. IEEE Trans. Geosci. Rem. Sens,2007,45:435-447.
[97]Dobson E F, Monaldo F, Goldhirsh J. Validation of Geosat altimeter-derived wind speeds and significant wave heights using buoy data. J Geophys Res,1987,92:10719-10731.
[98]Dumont J P, Thibaut P, Zanife O Z. ALT_CAL_GEN_01-To generate waveforms. Algorithm definition, accuracy and sp ecification volume 2:CM A altimeter level lb processing(SMM-ST-M 2-EA-11010-CN).2001,64-69.
[99]Emery W J, Thomas A C, Collins M J, et al. An Objective Method for Computing Advective Surface Velocities From Sequential Infrared Satellite Images. J Geophys Res,1991 (C11):12,865-12.
[100]Emery, W.J., A.C. Thomas, M.J. Collins, W.R. Crawford & D.L. Mackas,1986:An objective procedure to computeadvection from sequential infrared satellite images. J.Geophys. Res.,91 (color issue),12,865-12,879.
[101]Emery W J, Fowler C, Clayson A. Satellite image-derived Gulf Stream currents compared with numerical model results. J Atmospheric Oceanic Technology,1992,9:286-304.
[102]Emery W J, Fellow, IEEE, D. Baldwin, and D. Matthews.Maximum Cross Correlation Automatic Satellite Image Navigation and Attitude Corrections for Open-Ocean Image Navigation. IEEE TRANSACTIONS ON GEOSCIENCE AND REM OTE SENSING,VOL.41, NO.1, JANUARY 2003. p33-42.
[103]Garcia C A, Robinson I S. Sea surface velocities in shallow seas extracted from sequential Coastal ZoneColor Scanner Satellite data. J Geophys. Res,1989,94(C12):12681-12691.
[104]Gao Bocai.Goetz F H.Cirrus Cloud Detection from Airborne Imaging Spectrometer Data Using the 1.38 Water Vapor Band[J]. Journal of Geophysical Research Letter,1993,20(4):301-304.
[105]Gao Bocai. Selection of 1.375 MODIS Channel for Remote Sensing of Cirrus Clouds and Stratospheric Aerosols from Space[J].American Meteorological Society,1995:4231-4237
[106]Gesell,G.:An algorithm for snow and ice detection using AVHRR data:An extension to the APOLLO software package. Int. J. Remote Sensing,1989,10(2):897-905.
[107]Goodman A H, Henderson S A. Cloud detection and analysis:A review of recent progress. Atmospheric Research, 1988,21:203-228.
[108]Gourrion J, Vandemark D, Bailey S, et al. Satellite altimeter models for surface wind speed developed using ocean satellite crossovers.2000, Technical report, Report No:IFREM ER-DROOS-2000-02.
[109]Guo Hongtao, Chang Zhiguo, He Shanwei. Geostationary Meteorological Satellite Data Processing System, advanced Materials Research journals,2011,181-182.
[110]Guo Hongtao, Xie Huanhuan. Application of MODIS data to monitor sea ice in Bohai sea.2010 Second IITA International Conference on Geoscience and Remote Sensing,2010,36-38.
[111]Guo Hongtao, Zhang Ying. Application of optical flow method in inversion of ocean surface flow field.2010 Second IITA International Conference on Geoscience and Remote Sensing,2010,31-36.
[112]Hayne G S. Radar altimeter mean return waveform from near nominal-incidence ocean surface scattering IEEE Trans Antennas Propag,1980, AP-28:687-692.
[113]Holyer R J, Peckinpaugh S H. Edge detection applied to satellite imagery of the oceans. IEEE Trans Geosci Rem Sens,1989,27:46-56.
[114]Horn B K P, Schunck B G. Determining optical flow.Artlficial Intelligence,1981,17:185-204.
[115]Huang N E, Long S R. A study of the surface elevation probability distribution function and statistics of wind generated waves. J Fluid Mechanics,1980,101:179-200.
[116]Huang P A, Sletten M A. Energy dissipation of wind-generated waves and whitecap coverage. J Geophys Res, 2008a,113, C02012, doi:10.1029/2007JC004277.
[117]Huang P A, Sletten M A.Toporkov J V Analysis of radar sea return for breaking wave investigation. J Geophys Res,2008b,118, C02003, doi:10.1029/2007JC004319.
[118]http://modis.gsfc.nasa.gov:MODIShomepage
[119]Isern-Fontanet J, Chapron B, Lapeyre G, et al. Potential use of microwave sea surface temperatures for the estimation of ocean currents. Geophys. Res. Lett.,2006,22, L24608,doi:10.1029/2006GL027801.
[120]Isern-Fontanet J, Turiel A., Garcia-Ladona E, et al. Microcanonical Multifractal For malism:application to the estimation of ocean surface velocities. J Geophys Res,2007,112.C05024, doi:10.1029/2006JC003878.
[121]Jedlovec, G J, Laws K. GOES Cloud detection at the Global Hydrology and Climate Center. Preprints,12th Conf. on Satellite Meteorology and Oceanography, Long Beach, CA, Amer. Meteor. Soc., CD-ROM,P1.21,2003.
[122]Johannessen J, Kudryavtsev V, Akimov D, et al.On Radar Imaging of Current Features; Part 2:Mesoscale Eddy and Current Front detection. J Geophys Res.2005,110, C07017, doi:10.1029/2004JC002802.
[123]Kamachi M. Advective surface velocities derived from sequential images for rotational flow field:Limitations and applications of maximum cross-correlation method with rotational registration. J Geophys Res,1989, 94(C12):18227-18233.
[124]Kelly K A.An inverse model for near-surface velocity from infrared images. J Phys Oceanogr,1989,19:1845-1864.
[125]Kelly K A, Strub PT. Comparison of velocity estimates from Advanced Very High Resolution Radiometer in the coastal transition zone. J Geophys Res.1992,97 (C6):9653-9668.
[126]Krasnopolski, V.M., and L.C. Breaker,1994. The problem of AVHRR image navigation revisited, International Journal of Remote Sensing,15(2):979-1008.
[127]Kriebel, K.T., R.W. Saunders, and G.Gesell:Optical properties of clouds derived from fully cloudy pixels. Contr. Phys.Atmos.,62,165-171,1989.
[128]Larouche P, Thomassin E, Boucher, J M, et al. Sea surface velocity estimations using SST images In Proceedings of the 4th Int. Conf. on Remote Sens. for Marand Coastal Environments, Orlando, FL,1997,431-438.
[129]Le Dimet, F, and O. Talagrand, Variational algorithms for analysis and assimilation of meteorological observations:Theoretical aspects. Tellus,1986,38A,97-110.
[130]Leese J A, Novak C S. An Automated Technique for Obtaining Cloud Motion from Geosynchronous Satellite DataUsingCross Correlation. J ApplMeteor,1971,10:118-132.
[131]Liu A K, Martin S, Kwok R. Tracking of Ice Edges and Ice Floes by Wavelet Analysis of SAR Images. Journal of Atmospheric and Oceanic Technology,1997,14:1187-1198.
[132]M cClain E P,Pichel W G and Walton C C.Comp arative p erformance of AVHRR-based multichannel sea surface temperatures.J Geophys Res.1985,90:11587-11601.
[133]Menzel W P, Smith W L, Stewart T R.Improved Cloud Motion Wind Vector and Altitude Assignment Using VAS. J Cli AppliMeteor.1983,22:377-384.
[134]MenzelWP. Application with Meteorological Satellites.WMOTechnical Document,2001,1078, SAT-28.
[135]Meteorological Satellite Center.1989. TheGMSUser Guide. Meteorological Satellite Center JMA,190P
[136]Monaldo F, Dobson E. On using significant wave height and radar cross section to improve radar altimeter measurements of wind speed. J Geophys Res,1989,94:12699-12701.
[137]Moore R K, Williams C S. Radar terrain return at near vertical incidence. Proc. IRE,1957,2(45):228-238.
[138]Nakamura Y, Ozawa E, Onogi K, et al. Impact Experiments on NWP with Rapid Scan AM Vs, Proceedings of the 6th International Winds Workshop. USA Madison, EUMETSAT Publication,2002, EUM P35:171-178.
[139]Nieman S J, Menzel W P, Hayden C M, et al. Fully Automatic Cloud-Drift Winds in NESDIS Operations. Bulletin of the American Meteorological Society,1997,78(6):1121-1133.
[140]Nieman S J, Schmetz J, Menzel W P. A Comparison of Several Techniques to Assign Heights to Cloud Tracers. Journal of Applied Meteorology,1993,32:1559-1568.
[141]Pailleux J.The Impact of Satellite Data on Global Numerical Weather Prediction. Remote Sensing Applications in Meteorology and Climatology, Vaughan R A Ed,1987,173-187.
[142]Parol F, Buriez J C, Brogniez G, Fouquart Y Information Content of AVHRR Channels 4 and 5 with Respect to the Effective Radius of Cirrus Cloud Particles. Journal of Applied Meteorology,1991,30:873-984.
[143]Pascual A, Faugere Y Larnicol G, et al. Improved description of the ocean mesoscale variability by combining four satellite altimeters. Geophys Res Lett,2006,33,611,doi:10.1029/2005GL024633.
[144]Peak J E, Tag P M. Toward automated interpretation of satellite imagery for navy shipboard applications. Bulletin of the American Meteorological Society,1992,73(7):995-1008.
[145]Peak J E, Tag P M. Segmentation of satellite imagery using hierarchical thresholding and neural networks. Journal of Applied Meteorology,1994,33:605-616.
[146]Quilfen Y, Tournadre J, Chapron B. Altimeter dual-frequency observations of surface winds, waves, and rain rate in tropical cyclone Isabel. J Geophys Res,2006,111:C01004.
[147]Rao P K, Holmes S J,Anderson R K等编,许建民等译,气象卫星—系统资料及其在环境中的应用.北京：气象出版社,1994.
[148]Remy F, Parouty S. Antarctic ice sheet and radar altimetry:A review. Remote Sensing,2009,1:1212-1239, doi:10.3390/rs1041212.
[149]Rolnald M.Errico, What is a adjoint model?, Bulletin of the American Meteorological Society,1997,Vol.78, No. 11.
[150]Rosmorduc V, Benveniste J, Lauret O, et al. Radar altimetry tutorial. J. Benveniste and N. Picot Ed., http://www.altimetry.info,2009.
[151]Sadler J C. A role of the tropical upper tropospheric trough in early season typhoon development. M W R,1976, 104:1266-1278.
[152]Santek D, Key J, Velden C, et al. Deriving Winds from Polar Orbiting Satellite Data. Proceedings of the 6th International Winds Workshop, USA Madison,2002, EUM ETSAT Publication, EUM P35:251-261.
[153]Saunders. R. W, Kriebel. K.T. An improved method for detecting clear sky and cloudy radiances from AVHRR data. Int. J. Remote Sens.,9,NO.1,123-150,1988
[154]Schmetz J, Holmlund K, Hoffman J, et al.Operational Cloud Motion Winds from Meteosat Infrared Images. Journal of Applied Meteorology.1993,32(7):1206-1225.
[155]Schmetz J, Hinsman D, Menzel W P.Summary of the Fourth International Wind Workshop. Bulletin of the American Meteorological Society,1999,80(5):893-899.
[156]Simpsona J J, Gobata J I. Improved cloud detection in GOES scenes over the oceans. Remote Sensing of Environment,1995,52(2):79-94.
[157]Smith W, Harrison W, Hinton D, et al. GIFTS-A System for Wind Profiling from Geostationary Satellites, Proceedings Fifth International Wind Workshop, Lome Australia,M arch 2000, EUM P 28:253-258.
[158]Stanley Q K,Kankiewicz J A. Meteosat Second Generation Cloud Algorithms for Use at AFWA. BACIMO Monterey,2005, CA:12-14.
[159]Steve Ackerman, Kathleen Strabala, Paul Menzel.etc.(MODIS Cloud Mask Team) Discriminating clear-sky from cloud with M ODIS.2006,10.
[160]Stowe, L. L., E.P. McClain, R. Carey, P. Pellegrino, G. Gutman, P. Davis, C. Long, and S.Hart,1991:Global distribution of cloud cover derived from NOAA/AVHRR operational satellite data. Adv. Space Res.,11,51-54.
[161]Szejwach G. Determination of Semitransparent Cirrus Cloud Temperature from Infrared Radiances:Application to Meteosat. Journal of Ap plied Meteorology,1982,21(3):384-393.
[162]Talagrand, O.,Assimilation of observations, an introduction. J.Meteor.Soc. Japan.,1997,75,191-209.
[163]Talagrand, O., and P. Curtier, Variational assimilation of meteorological observations with the adjoint vorticity equation. Part Ⅰ:Theory. Quart. J.Roy. Meteor. Soc.,1987,113,1311-1328.
[164]Tokmakian R T, Strub P T, McClean-Padman J. Evaluation of the maximum cross-correlation method of estimating sea surface velocities from sequential satellite images. J Atmos Ocean Tech,1990,7:852-865.
[165]Tran N, Vandemark D, Chapron B, et al. New models for satellite altimeter sea state bias correction developed using global wave model data. J GeophysRes,2006,111(C9):1-48.
[166]Tran N, Vandemark D, Lbroue S, et al. Sea state bias in altimeter sea level estimates determined by combining wave model and satellite data. J Geophy s Res,2010,115, C03020, doi:2009JC005534.
[167]Tran N, Vandemark D, Chapron B, et al. New models for satellite altimeter sea state bias correction developed using global wave model data. J Geophys Res,2006,111(C9):1-48.
[168]Tran N, Vandemark D, Lbroue S, et al. Sea state bias in altimeter sea level estimates determined by combining wave model and satellite data. J Geophys Res,2010,115, C03020, doi:2009JC005534.
[169]Traon P L, Dibarboure G. An illustration of the unique contribution of the TOPEX/Poseidon-Jason-1 tandem mission to mesoscale variability studies. Marine Geodesy,2004,27:3-13.
[170]Traon P L, Nadal F, Ducet N. An improved mapping method of multisatellite altimeter data. J Atmos Oceanic Technol.1998,15:522-534.
[171]Traon P L, Faugere Y, Hernandez F, et al. Can we merge GEOSAT Follow-On with TOPEX/POSEIDON and ERS-2 for an improved description of theocean circulation? J Atmos Oceanic Technol.2003,20:889-895.
[172]Turiel A, Parga NThe multi-fractal structure of contrast changes in natural images:from sharp edges to textures.Neural Computation,2000,12:763-793.
[173]Turiel A, Grazzini J, Yahia H. Multiscale techniques for the detection of precipitation using thermal IR satellite images. IEEE Geosci Remote Sens Lett,2005,2,447-450.
[174]Turiel A, Isern-Fontanet J, Garcia-Ladona E, et al.Multifractal method for the instant taneous evaluation of the stream function in geophysical flows. Phys. Rev. Lett.2005,95,104502,doi:10.1103/PhysRevLett.95.104502.
[175]Turiel A, Perez-Vicente C, Grazzini J. Numerical methods for the estimation of multifractal singularity spectra on sampled data:a comparative study. J Computat Phys.2006,216:362-390.
[176]Turiel A, Sole J, Nieves V, et al. Tracking oceanic currents by singularity analysis of Micro-Wave Sea Surface Temperatureimages. Rem Sens Environ,2008,112:2246-2260.
[177]Turiel A, Yahia H, P'erez-Vicente C. Microcanonical Multifractal Formalism:a geometrical approach to multifractal systems. Part Ⅰ:Singularity analysis. J Phys A,2008,41,015 501, doi:10.1088/1751-8113/41/1/015501.
[178]Turiel A V, Nieves E, Garcia-Ladona, et al. The multifractal structure of satellite sea surface temperature maps can be used to obtain global maps of streamlines. Ocean Sci Discuss.2009,6,129-151.
[179]User Manual for the PGE01-02-03 of the SAFNWC/M SG:Scientific part, Issue 1, Rev.2,3,2005.
[180]Vigan X, Provost C, Bleck R, et al. Sea surface velocities from sea surface temperature image sequences.1, Method and validation using primitive equation model output. J Geophys Res.2000,105:19499-19514.
[181]William B R, Leonid C G. Cloud detection using Satellite Measurements of Infrared and Visible Radiances for ISCCP.1993,6:2341-2369.
[182]Witter D L, Chelton D B. A Geosat altimeter wind speed algorithm and a method for altimeter wind speed algorithm development. J Geophys Res,1991,96:8853-8860.
[183]Wolf D E, Hall D J, Endlich R M. Experiments in Automatic Clound Tracking Using SMS-GOES Data. J Appl Meteor,1977,16:1219-1230.
[184]Wunsch C, Stammer D. Satellite altimetry, the marine geoid, and the oceanic general circulation. Ann Rev Earth Planet Sci,1998,26:219-353.
[185]Wylie, D. P., and W. P. Menzel,1994:Four years of global cirrus cloud statistics using HIRS. J. Climate,7, 1972-1986.
[186]Yang Le, Zou Ju-hong Lin Ming-sen, et al. Method to correct both foam and rain effects on dual frequency altimeter Jasonl wind measurements in typhoon Shanshan. In proceedings of SPIE, Remote sensing of the ocean, sea ice, and large water regions,2008a,7105,71050L, doi:10.1117/12.799623.
[187]Yang L, Lin M, Zou J, et al. Improving the wind and wave estimation of dual-frequency altimeter Jason-1 in Typhoon Shanshan and considering the rain effects. Acta Oceanologica Sinica,2008b,27(5):49-62.
[188]Young I R. An estimate of the Geosat altimeter wind speed algorithm at high wind speeds. J Geophys Res,1993, 98(C11):20275-20285.
[189]Zhao D L, Toba Y A spectral approach for determining altimeter wind speed model functions. Journal of Oceanography,2003,59:235-244.
[190]Zhao D L, Toba Y Effect of wave states on altimeter wind speed algorithm at high wind speeds.22nd Asian Conference on Remote Sensing, Singapore,5-9 November 2001.
[191]Zieger S, Vinoth J, Young I R. Joint calibration of multi-platform altimeter measurements of wind speed and wave height over thepast 20 years. J Atmos Oceanic Tech,2009,26, Doi 10.1175/2009JTCHA1303.1.