二维线性与非线性海面电磁散射特性比对研究

二维线性和非线性海面模型与低阶小斜率近似(small slope approximation,SSA)法相结合,对比研究了不同海面的统计特征及其电磁散射特性。研究表明:非线性海浪比相应的线性海浪具有更尖锐的波峰和更为平坦的波谷,虽然其高度均方根保持不变,但斜率变大,且偏离高斯分布;相应地,非线性海面归一化雷达散射截面(normalized radar cross section,NRCS)在远离镜面反射方向上略高于线性海面的NRCS,其后向散射系数也有所提高,并且该差异在小擦地角下更为显著。

一维线性海面弱流场对雷达后向散射系数的影响

基于谱扰动理论,分析了一维线性海面弱流场与微尺度表面波之间的相互作用及由此产生的海浪谱扰动。根据布拉格散射模型讨论了谱扰动对雷达后向散射系数的影响,并进行了数值模拟。针对辐聚、辐散流分别给出了不同流速梯度和不同雷达波长情况下雷达散射系数的影响。从而定量地描述了海面弱流场对雷达后向散射系数的影响。

油膜覆盖的非线性海面电磁散射多普勒谱特性研究

当海面上方漂浮油膜时,海面的毛细波成分将因油膜的阻尼作用而被破坏.本文采用PM谱,基于Marangoni阻尼效应,建立油膜覆盖的一维Creamer非线性海面模型,并简单分析了油膜的阻尼作用对海面轮廓的影响.在此基础上,利用迭代物理光学方法研究了L波段下该模型的后向散射回波的多普勒谱特性,通过与基于线性模型的海面散射回波多普勒谱对比发现,在大中入射角下,非线性海面散射回波与线性海面多普勒谱的差异不可忽略,说明采用Creamer非线性理论建立海面几何模型的必要性.研究发现,油膜覆盖海面的散射回波的多普勒频移及展宽与干净海面雷达回波的多普勒特性具有明显差异,这表明海面上漂浮的油膜对雷达散射回波的多普勒特性具有显著的影响.数值结果重点分析了入射角、油膜参数以及风速对油膜覆盖海面散射回波多普勒谱展宽和频移的影响规律.

三维动态海面建模与海洋回波模拟

雷达系统的研究和开发一般要经过反复的试验,为解决实地测试浪费大量人力、物力的问题,本文建立了一个以海杂波为主的回波模拟器,用于雷达测试,降低成本。本文先在Elfouhaily谱基础上利用尖浪模型建立非线性动态海面,利用网格映像法将海面划分为不同的分辨单元。首次将网格化的海面与回波的后向散射特性相结合生成模拟回波,并且在模拟过程中提出了一种利用海浪特点对擦地角进行修正的算法。最后将模拟出的回波与实测和理论数据进行分析拟合,证明了模拟回波的有效性。

Improvement of Urban Impervious Surface Estimation in Shanghai Using Landsat7 ETM+ Data

This paper explores the potential to improve the impervious surface estimation accuracy using a multi-stage approach on the basis of vegetation-impervious surface-soil (V-I-S) model. In the first stage of Spectral Mixture Analysis (SMA) process, pixel purity index, a quantitative index for defining endmember quality, and a 3-dimensional endmember selection method were applied to refining endmembers. In the second stage, instead of obtaining impervious surface fraction by adding high and low albedo fractions directly, a linear regression model was built between impervious surface and high/low albedo using a random sampling method. The urban impervious surface distribution in the urban central area of Shanghai was predicted by the linear regression model. Estimation accuracy of spectral mixture analysis and impervious surface fraction were assessed using root mean square (RMS) and color aerial photography respectively. In comparison with three different research methods, this improved estimation method has a higher overall accuracy than traditional Linear Spectral Mixture Analysis (LSMA) method and the normalized SMA model both in root mean square error (RMSE) and standard error (SE). However, the model has a tendency to overestimate the impervious surface distribution.

Comparison of nonlinear and linear PCA on surface wind,surface height,and SST in the South China Sea

We compared nonlinear principal component analysis(NLPCA) with linear principal component analysis(LPCA) with the data of sea surface wind anomalies(SWA),surface height anomalies(SSHA),and sea surface temperature anomalies(SSTA),taken in the South China Sea(SCS) between 1993 and 2003.The SCS monthly data for SWA,SSHA and SSTA(i.e.,the anomalies with climatological seasonal cycle removed) were pre-filtered by LPCA,with only three leading modes retained.The first three modes of SWA,SSHA,and SSTA of LPCA explained 86%,71%,and 94% of the total variance in the original data,respectively.Thus,the three associated time coefficient functions(TCFs) were used as the input data for NLPCA network.The NLPCA was made based on feed-forward neural network models.Compared with classical linear PCA,the first NLPCA mode could explain more variance than linear PCA for the above data.The nonlinearity of SWA and SSHA were stronger in most areas of the SCS.The first mode of the NLPCA on the SWA and SSHA accounted for 67.26% of the variance versus 54.7%,and 60.24% versus 50.43%,respectively for the first LPCA mode.Conversely,the nonlinear SSTA,localized in the northern SCS and southern continental shelf region,resulted in little improvement in the explanation of the variance for the first NLPCA.

Influence of the Pacific Decadal Oscillation on regional sea level rise in the Pacific Ocean from 1993 to 2012

The rate of regional sea level rise （SLR） provides important information about the impact of human activities on climate change. However, accurate estimation of regional SLR can be severely affected by sea surface height （SSH） change caused by the Pacific Decadal Oscillation （PDO-SSH）. Here, the PDO- SSH signal is extracted from satellite altimeter data by multi-variable linear regression, and regional SLR in the altimeter era is calculated, before and after removing that signal. The results show that PDO-SSH trends are rising in the western Pacific and falling in the eastern Pacific, with the strongest signal confined to the tropical and North Pacific. Over the past 20 years, the PDO-SSH accounts for about 30%/-400% of altimeter-observed SLR in the regions 8° 15°N, 130°-160°E and 30°-40°N, 170°-220°E. Along the coast ＆North America, the PDO-SSH signal dramatically offsets the coastal SLR, as the sea level trends change sign from falling to rising.

Quantifying the Mean Sea Level Change at the Gulf of Finland Coast Caused by the Realistic Portion of the Global Warming Forcing

Quantifying the coastal mean sea level change causing by the winter positive phase of the North Atlantic oscillation index NAO＋ at the Gulf of Finland coast is of high priority for detecting and predicting the global warming impact in this region. Both boreal winter months and season of three long-term data station series of the coastal mean sea levels and the NAO indices were linked for two cases, i.e.： different periods and the 1977-1994 period. This study is dedicated to： （1） Detecting the exclusive impacts of the NAO＋; （2） Estimating the significant standard bivariate linear regression models; （3） Calculating the climatic linear trend coefficient by using three methods （OLS, GLS, Theil-Sen）; （4） Correcting the mean sea level series anomalies by using the significant linear regression equations as a function of NAO＋ anomalies, over the period 1977-1994; （5） Calculating the realistic linear trend caused as a function of NAO＋ for period 1977-1994 in the context of the realistic portion of the global warming. The results reveal that, the NAO＋ manifests their impacts on the coastal mean sea levels and its contribution in the configured linear trends. The realistic linear changes have detected and predicted. The Gulf of Finland coast showed the wannest regions in the context of the realistic portion of the global warming during the winters of the period 1977-1994.

Scattering of Oblique Surface Waves by the Edge of Small Deformation on a Porous Ocean Bed

The scattering of oblique incident surface waves by the edge of a small cylindrical deformation on a porous bed in an ocean of finite depth, is investigated here within the framework of linearized water wave theory. Using perturbation analysis, the corresponding problem governed by modified Helmholtz equation is reduced to a boundary value problem for the first-order correction of the potential function. The first-order potential and, hence, the reflection and transmission coefficients are obtained by a method based on Green＇s integral theorem with the introduction of appropriate Green＇s function. Consideration of a patch of sinusoidal ripples shows that when the quotient of twice the component of the incident field wave number along x-direction and the ripple wave number approaches one, the theory predicts a resonant interaction between the bed and the free-surface, and the reflection coefficient becomes a multiple of the number of ripples. Again, for small angles of incidence, the reflected energy is more as compared to the other angles of incidence. It is also observed that the reflected energy is somewhat sensitive to the changes in the porosity of the ocean bed. From the derived results, the solutions for problems with impermeable ocean bed can be obtained as particular cases.

DIAGNOSTIC PREDICTIONS OF SST IN THE EQUATORIAL EASTERN PACIFIC OCEAN BASED ON FUZZY INFERRING AND WAVELET DECOMPOSITION

Methods and approaches are discussed that identify and filter off affecting factors (noise) above primary signals,based on the Adaptive-Nework-Based Fuzzy Inference System. Influences of the zonal winds in equatorial eastern and middle/western Pacific on the SSTA in the equatorial region and their contribution to the latter are diagnosed and verified with observations of a number of significant El Nio and La Nia episodes. New viewpoints are propsed. The methods of wavelet decomposition and reconstruction are used to build a predictive model based on independent domains of frequency,which shows some advantages in composite prediction and prediction validity.The methods presented above are of non-linearity, error-allowing and auto-adaptive/learning, in addition to rapid and easy access,illustrative and quantitative presentation,and analyzed results that agree generally with facts. They are useful in diagnosing and predicting the El Nio and La Nia problems that are just roughly described in dynamics.