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1.
Reconstruction of incomplete oceanographic data sets using empirical orthogonal functions: application to the Adriatic Sea surface temperature 总被引：8，自引：1，他引：8
A method for the reconstruction of missing data based on an EOF decomposition has been applied to a large data set, a test case of Sea Surface Temperature satellite images of the Adriatic Sea. The EOF decomposition is realised with a Lanczos method, which allows optimising computational time for large matrices. The results show that the reconstruction method leads to accurate reconstructions as well as a low cpu time when dealing with realistic cases. The method has been tested with different amounts of missing data, artificially adding clouds ranging from 40% to 80% of data loss, and then compared to the same data set with no missing data. A comparison with in situ data has also been made. These validation studies show that results are robust, even when the amount of missing data is very high. The reconstruction of the data from the Adriatic Sea shows realistic features and a reliable temperature distribution. In addition, the method is compared to an Optimal Interpolation reconstruction. The results obtained with both methods are very similar. The main difference is the computational time, which is reduced nearly 30 times with the method presented here. Once the reconstruction has been performed, the EOF decomposition is analysed to show the method’s reliability, and a cold event on the Albanian coast is studied. The reconstructed data reflect the effect of wind on the Albanian coast, that led to a cold-water episode in this zone for a 6-day period. 相似文献
2.
针对海表温度数据集的数据缺失,提出了一种基于自组织映射算法(SOM)和经验正交函数算法(EOF)有机结合的重构缺失值的新方法。该方法应用了SOM的非线性估计,能够很好的反映数据集的非线性结构,并把SOM估计的结果用于EOF算法的初始化,克服了EOF对数据集初始化敏感的问题。在处理过程中,对奇异值分解使用了lanczos算子分解矩阵,提高了程序运行效率。此外,该方法还引入蒙特卡罗交叉校正集,确定最佳重构的EOF模态数,最终高精度计算出重构误差。使用AQUA遥感卫星海表温度数据进行实验,结果表明该方法能够很好地重构出缺失率高达83.23%的数据集,且重构精度高。 相似文献
3.
4.
静止轨道海洋水色成像仪(Geostationary Ocean Color Imager, GOCI)提供了时间分辨率达小时级的海洋水色数据,使得对海洋环境的逐时变化监测成为可能。然而受到海洋上空云、雾和霾的影响,数据出现连续高缺失率甚至完全缺失的情况,使得数据使用价值大大降低。在经验正交函数重构法(Data INterpolating Empirical Orthogonal Functions, DINEOF)的基础上,突出时间要素在重构中的地位,运用异常像元检测、拉普拉斯平滑滤波和时间模态2次分解插值,提出了适用于静止海洋水色卫星数据的重构方法——DINEOF-G。利用此方法对杭州湾2017年的GOCI总悬浮物质量浓度数据进行重构,结果表明该方法相比经典方法在重构精度上提高了8%,数据重构率提高了36%,且重构结果较好地反映了杭州湾总悬浮物质量浓度的季节变化规律和空间分布特征。 相似文献
5.
卫星遥感业务系统海表温度误差控制方法 总被引：11，自引：1，他引：11
提高卫星遥感海表温度的反演精度是各种反演模型追求的目标,也是遥感系统业务化应用的关键.据相关文献报道,在晴空无云的条件下遥感海表温度的精度达到了0.5℃,但考虑到影响海表温度反演精度的多种因素,在遥感业务系统真正实现SST精度在1℃以内是非常困难的.在北太平洋渔场速报制作系统中,对遥感海表温度与船测温度误差统计显示均方根误差达到5.71℃,匹配点误差分布显示存在大量较大的负误差值,最大的为-17.2℃,遥感温度图也反映出存在片状温度低值区,这些区域很可能被错误地当作冷涡或冷锋区,严重干扰渔情分析,这些异常的温度误差很难通过海表温度反演模式和云检测技术来消除.采用一种标准海表温度参考图用于温度误差控制技术,可有效地检测温度反演异常值,将均方根值从5.71℃降低到1.75℃,如果采用2℃阈值控制计算均方根值,则海表温度精度达到0.785℃.该方法基本消除了遥感海表温度的低值现象,明显提高了遥感海表温度的精度,并已成功地应用于北太平洋渔区的海况速报产品制作中. 相似文献
6.
在内波条件下,水声信道稳定性变差,声速剖面的重构具有一定难度。与其他方法相比,经验正交分解法优点在于能用少量参数进行重构,而不需要引入大量的参数。利用南海北部陆坡测量的温度链数据,采用经验正交分解法对声速剖面进行重构。结果表明:在内波剧烈的南海北部海域,通过经验正交分解法重构声速剖面具有可行性,其前3个模态累计贡献率达到96.7%。分析样本的周期覆盖率对重构结果的影响后发现,当样本覆盖完整的海洋潮汐活动周期时,基于EOF分析对本组声速剖面的重构均方根误差小于1.1 m/s,重构声速剖面结果理想;而当采集的样本不能覆盖完整周期时,误差较大。 相似文献
7.
Damien Sirjacobs Aida Alvera-Azcárate Alexander Barth Geneviève Lacroix YoungJe Park Bouchra Nechad Kevin Ruddick Jean-Marie Beckers 《Journal of Sea Research》2011,65(1):114-130
Optical remote sensing data is now being used systematically for marine ecosystem applications, such as the forcing of biological models and the operational detection of harmful algae blooms. However, applications are hampered by the incompleteness of imagery and by some quality problems. The Data Interpolating Empirical Orthogonal Functions methodology (DINEOF) allows calculation of missing data in geophysical datasets without requiring a priori knowledge about statistics of the full dataset and has previously been applied to SST reconstructions. This study demonstrates the reconstruction of complete space–time information for 4 years of surface chlorophyll a (CHL), total suspended matter (TSM) and sea surface temperature (SST) over the Southern North Sea (SNS) and English Channel (EC). Optimal reconstructions were obtained when synthesising the original signal into 8 modes for MERIS CHL and into 18 modes for MERIS TSM. Despite the very high proportion of missing data (70%), the variability of original signals explained by the EOF synthesis reached 93.5% for CHL and 97.2% for TSM. For the MODIS TSM dataset, 97.5% of the original variability of the signal was synthesised into 14 modes. The MODIS SST dataset could be synthesised into 13 modes explaining 98% of the input signal variability. Validation of the method is achieved for 3 dates below 2 artificial clouds, by comparing reconstructed data with excluded input information. Complete weekly and monthly averaged climatologies, suitable for use with ecosystem models, were derived from regular daily reconstructions. Error maps associated with every reconstruction were produced according to Beckers et al. (2006). Embedded in this error calculation scheme, a methodology was implemented to produce maps of outliers, allowing identification of unusual or suspicious data points compared to the global dynamics of the dataset. Various algorithm artefacts were associated with high values in the outlier maps (undetected cloud edges, haze areas, contrails, and cloud shadows). With the production of outlier maps, the data reconstruction technique becomes also a very efficient tool for quality control of optical remote sensing data and for change detection within large databases. 相似文献
8.
The variability in global oceanic evaporation data sets was examined for the period 1988-2000. These data sets are satellite estimates based on bulk aerodynamic formulations and include the NASA/Goddard Space Flight Center Satellite-based Surface Turbulent Flux version 2 （ GSSTF2）, the Japanese-ocean flux using remote sensing observations （J-OFURO）, and the Hamburg Ocean-Atmosphere Parameters and Fluxes from Satellite version 2 （HOAPS2）. The National Center for Environmental Prediction （NCEP） reanalysis is also included for comparison. An increase in global average surface latent heat flux （SLHF） can be observed in all the data sets. Empirical mode decomposition （EMD） shows long-term increases that started around 1990 for all remote sensing data sets. The effect of Mt. Pinatubo eruption in 1991 is clearly evident in HOAPS2 but is independent of the longterm increase. Linear regression analyses show increases of 9.4%, 13.0%, 7. 3%, and 3.9% for GSSTF2, J-OFURO, HOAPS2 and NCEP, for the periods of the data sets. Empirical orthogonal function （EOF） analyses show that the pattern of the first EOF of all data sets is consistent with a decadal variation associated with the enhancement of the tropical Hadley circulation, which is supported by other satellite observations. The second EOF of all four data sets is an ENSO mode, and the correlations between their time series and an SO1 are 0.74, 0.71,0.59, and 0.61 for GSSTF2, J-OFURO, HOAPS2, and NCEP in that order. When the Hadley modes are removed from the remote sensing data, the residue global increases are reduced to 2.2% , 7. 3%, and 〈 1% for GSSTF2, J-OFURO and HOAPS, respectively. If the ENSO mode is used as a calibration standard for the data sets, the Hadley mode is at least comparable to, if not larger than, the ENSO mode during our study period. 相似文献
9.
The paper suggests a method for reconstructing the spatial structure of hydrological elements, using incomplete information,
with the noise component being concurrently filtered. This problem is of vital relevance in the context of conducting satellite
observations when the observed area is covered by clouds. To solve the problem, the fields are decomposed by the system of
empirical orthogonal functions.
The reconstructed fields acquired by the different techniques using model andin situ data are then compared. As an example, the paper examines the reconstruction of the oxygen field, using the survey data compiled
during the summer of 1986. The computations allow a deduction that the method at issue may be efficiently employed to handle
the problems of field reconstruction, using scarce data, with the purpose of generating a data base on spatio-temporal variability
of diverse environment components.
Translated by Vladimir A. Puchkin. 相似文献
10.
Reconstruction of the surface temperature fields according to the fragmentary data of remote sensing
E. F. Vasechkina 《Physical Oceanography》2011,21(3):195-210
We propose a gap-filling method for the data of remote sensing of the hydrophysical and biological characteristics of the
water surface. The proposed method of reconstruction is based on the representation of the fields of surface characteristics
as the sums of certain numbers of empirical orthogonal functions (EOF) making the largest contributions to the total variance
of the field. According to the fragmentary data obtained as a result of processing of the satellite images for the summer
season, we construct estimates of the mean field and of the four-dimensional space covariance function of the surface temperature
of the Black Sea. The coefficients of expansion are computed by the method of least squares or determined with the help of
a genetic searching algorithm. The results of numerical experiments show that the proposed method is quite promising for applications
in the problems of gap filling in the available satellite data. 相似文献
11.
基于第三版本HOAPs (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data)海表面温度、潜热通量、感热通量、海表面空气比湿以及海表面风场5个参量的18 a(1988～2005年)逐月平均资料,利用经验正交函数和奇异值分解方法分析了异常潜热和感热通量场在西北太平洋的时空分布特征及造成这种分布的主要影响因素.EOF的分析结果表明,异常潜热通量场主要体现为第一第二两个模态的变化,第一模态显示整个海域呈同相变化且在时间上呈准年周期变化,第二模态则描述了分别位于10°N,25°N和40°N的3个极值中心并伴随多年振荡,由因子载荷分布可知热带太平洋是第二模态的行为中心,因此该模态可能与ENSO事件相关.异常感热通量场则主要表现为第一模态的变化,在时间上呈准年周期变化并伴随有多年时间尺度的振荡.奇异值分解方法的分析结果表明异常海表面风场是异常潜热和感热通量场时空变化的重要影响因素. 相似文献
12.
东、黄海SST与850hPa气温季节变化关系的SVD分析 总被引：2，自引：0，他引：2
利用1998~2004年的热带降雨测量卫星的卫星遥感海表面温度(SST)数据以及美国NO-AA/NCEP再分析产品的850 hPa气温数据,采用EOF分析方法,分析了850 hPa气温的季节内变化特征,运用奇异值分解(SVD)分析方法对东、黄海SST与850 hPa气温季节内变化的相关关系进行了分析。对850 hPa气温季节内变化的EOF分析结果表明,EOF分析获得的前4个模态的累积方差贡献率为86.51%,其中EOF的第一模态的方差贡献率占44.49%,其空间模态呈现出明显的东南海域为正值、西北海域为负值的反相分布特征,这一模态的显著变化周期为6.6周(约46 d)和2.8周(约19 d)。SVD分析结果表明,第一对模态的协方差解释率为83.6%,基本上能体现出SST温度场与850 hPa气温场季节变化的特征,其空间分布型表明,东海北部以及黄海近岸等海区SST季节变化与30°N以南的东海海区850 hPa气温的季节振荡存在显著的正相关关系,SVD第一对模态空间分布型时间系数之间的相关系数达到0.29。 相似文献
13.
采用TOPEX/POSEIDON(T/P)卫星高度计 1 993年 1月— 2 0 0 0年 1 2月海面高度数据 ,研究包含了整个南极绕极流流系 (40°— 6 0°S)的海面高度低频变化。首先采用EOF分解方法获取南大洋时空分布的主要模态 ,前 3个EOF模态分别占总方差的 2 4 .8%、1 3 .8%和 1 0 .7%。然后采用EMD方法分别分析了各个EOF模态的时间系数曲线的组成成分 ,对南极绕极流海域的各种时间尺度变化给出了清晰的描述 ,对于不同尺度变化所占的比例得到了定量的结果。研究结果表明 ,EOF的各个模态不仅在形态上存在差异 ,而且具有相互独立的物理背景。EOF的第一模态主要体现了以太阳辐射冬夏差异形成的年周期变化 ,另一个显著的特征就是南极绕极流从 1 993— 2 0 0 0年海面的整体上升趋势。EOF的第二模态体现了陆地地形对南极绕极流的约束作用 ,同时也显示了ENSO过程对南极绕极流 ,特别是对南太平洋的海面高度变化的影响。EOF的第三模态则体现了南极绕极流对南大洋表面风场东西方向不均匀变化的响应。同时 ,本文的研究也证明了EOF与EMD方法联合使用对揭示大范围时空变化有重要的实际意义 相似文献
14.
Empirical orthogonal functions (EOFs) or principal components were used to extract the significant modes of shoreline variability from several data sets collected at three very different locations. Although EOFs have proven to be a valuable tool in the analysis of nearshore data, most applications have focused on the ability of the technique to describe cross-shore or profile variability. Here however, EOFs were used to help identify the dominant modes of longshore shoreline variability at Duck, North Carolina, the Gold Coast, Australia, and at several locations within the Columbia River Littoral Cell in the U.S. Pacific Northwest. In part one of this analysis, characteristic patterns of shoreline variability identified by the EOF analysis are described in detail. At each site, the dominant modes consisting of the first four eigenfunctions were found to describe nearly 95% of the total shoreline variability. At both Duck and the Gold Coast, several interesting longshore periodic features suggestive of sand waves were identified, while boundary effects related to natural headlands and navigational structures/entrances dominated the Pacific Northwest data sets. 相似文献
15.
Using simulation results from three different regional ocean models (HOPS, ROMS and FVCOM) we show that only a few spatio-temporal POD (proper orthogonal decomposition) modes are sufficient to describe the most energetic ocean dynamics. In particular, we demonstrate that the simulated ocean dynamics in New Jersey coast, Massachusetts Bay and Gulf of Maine is energetically equivalent to the wake dynamics behind a cylinder at low Reynolds number. Moreover, the extrema of the POD spatial modes are very good locations for sensor placement and accurate field reconstruction. We employ a modified POD theory to incorporate a limited number of measurements in reconstructing the velocity and temperature fields, and we study systematically the corresponding reconstruction errors as a function of the sensor location, number of sensors, and number of POD modes. This new approach is quite accurate in short-term simulation, and hence it has the potential of accelerating the use of real-time adaptive sampling in data assimilation for ocean forecasting. 相似文献
16.
针对海表高度计资料的同化,考查了背景误差协方差矩阵的不同求逆方案对同化效果的影响。所使用的求逆方案包括避免求逆的经验正交函数方案(EOF/EOF_var)、递归滤波方案(RF/RF_var)以及采用初等变换法直接求逆的方案(Inv)。基于上述方案开展了热带太平洋地区2002年1-7月的TOPEX/Poseidon高度计资料同化试验,并利用SODA再分析资料和TAO观测资料评估了各方案对温度场的同化效果,主要得到如下结果:与SODA相比较,Inv方案对模式温度场改进甚微,其余四种方案在100~300 m深度之间对温度场改进较多,在其它深度范围内则改进较少;与TAO观测相比较,EOF_var、RF_var方案对模式温度场改进最多,EOF和RF方案次之,Inv方案则对温度场改进甚少。 相似文献
17.
A. P. Tolstosheev 《Physical Oceanography》2009,19(6):358-365
A method for the estimation of the results of reconstruction of the trajectories of drifting buoys is proposed. It is based
on the comparison of the estimates of power spectral densities for the components of current velocity computed according to
three data sets: the data set of the coordinates of a drifting buoy with a built-in GPS receiver, the data set of coordinates formed on the basis of the first set but with data missing and observational errors
corresponding to the actual trajectory measurements by the Argos satellite location and data collection system by the Doppler method, and the data set of coordinates obtained as a result
of interpolation of the second set. As an example, we consider the procedure of realization of the proposed method and demonstrate
the efficiency of its application for the improvement of the reliability of reconstruction of the trajectories of drifting
buoys. 相似文献
18.
MODIS影像是浒苔业务化卫星遥感监测的重要数据源,但其空间分辨率(250m)较低,混合像元效应导致传统的NDVI(Normalized Difference Vegetation Index)阈值法浒苔提取误差较大。为解决此问题,本文以准同步的较高分辨率的HJ-1CCD影像浒苔提取结果为基准,建立基于MODIS NDVI与浒苔像元丰度(浒苔覆盖面积占像元面积百分比)关系的浒苔信息提取模型,利用该模型可提取每个像元的丰度(即浒苔覆盖率),从而提高整景影像浒苔覆盖面积提取精度。该模型可为浒苔灾害等级的确定以及防灾减灾应急决策提供支持。 相似文献
19.
基于数据挖掘的GF-1 遥感影像绿潮自适应阈值分区智能检测方法研究 总被引：1，自引：0，他引：1
由于受到云雾的影响，可见光影像能够高效用于绿潮检测的数据源较为有限，特别是云覆盖较为严重的可见光影像，基本无法用于检测绿潮。即使影像数据是在薄云、薄雾、无云覆盖的情况下获取的，由于其光谱反射值存在较大差异，依然很难采用同一阈值进行绿潮检测。基于此，为了提高可见光影像的利用率，实现不同云覆盖情况下，绿潮的高精度自适应阈值的自动检测，本文以GF-1影像为数据源，首先采用K-means聚类和C4.5决策树方法实现影像云覆盖情况的自动识别；其次，选取大量不同云覆盖情况下子图像样本（每个子图像样本中均包含绿潮和海水两类），分析得出不同云覆盖情况下绿潮和海水的区分阈值y与影像光谱差x=bandnir-bandred之间所具有的线性关系；然后，利用分析得出的线性关系提出一种适用于GF-1影像的绿潮分区自适应阈值自动检测方法。最后，为验证提出方法的有效性，分别采用NDVI方法、EVI方法和本文提出的自适应阈值自动检测方法进行绿潮提取实验。实验结果表明，对于GF-1卫星遥感数据，本文提出的绿潮自适应阈值分区自动检测方法明显优于传统的NDVI和EVI检测方法，不仅提高了绿潮的监测精度，而且实现了绿潮提取的全自动化。 相似文献