Variation characteristics of evaporation in the Gulang River Basin during 1959-2013

Based on monthly evaporation of two meteorological stations in the Gulang River Basin of China, the inter-annual variation of evaporation during 1959-2013 were analyzed using Mann-Kendall and wavelet analysis. The results demonstrated that the annual evaporation show a fluctuating increase over the past 50 years approximately, with an average increase rate of 4.26 mm per decade. The overall trend was decrease-increase-decrease. According to the cumulative anomaly curve,the turning point of the annual evaporation occurred in 1979, in which the evaporation increased in the early stage and decreased in the later stage. Meanwhile, the seasonal variation of the evaporation shows that it decreased in Spring and Autumn, and increased in Summer and Winter, especially obvious for the later. The evaporation abruptly changed in Spring and Summer in 2008 and in Winter in 1994. In addition, all evaporation increased after the changes. However,the evaporation in Autumn abruptly changed in 1986 and 1999, which show a trend of increase-decrease-increase.Wavelet analysis shows that evaporation in Summer and wet season would decrease in the next few years, and in the other seasons would increase. Based on the aforementioned analysis, it can be concluded that increased evaporation is mainly induced by increase of evaporation in dry season, especially in Winter, and this trend to be continued in the future for the Gulang River Basin.     

Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data

Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, we obtained fourteen hyperspectral images from the Gaofen-5 (GF-5) satellite and decomposed and reconstructed the original reflectance (OR) and the first derivative reflectance (FDR) using discrete wavelet transform (DWT) at different scales. At these different scales, as inputs, we selected the 3 optimal bands with the highest weight coefficient using principal component analysis and chose the normalized difference index (NDI), ratio index (RI) and difference index (DI) with the strongest correlation with the SOC content using a contour map method. These inputs were then used to build regional-scale SOC prediction models using random forest (RF), support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. The results indicated that: 1) at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined with DWT can improve the SOC prediction accuracy significantly; 2) the method of selecting inputs using principal component analysis and a contour map can eliminate the redundancy of hyperspectral data while retaining the physical meaning of the inputs. For the model with the highest prediction accuracy, the inputs were all derived from the wavelength range of SOC variations; 3) the differences in prediction accuracy among the different prediction models are small; and 4) the SOC prediction accuracy using hyperspectral satellite data is greatly improved compared with that of previous SOC prediction studies using multispectral satellite data. This study provides a highly robust and accurate method for predicting and mapping regional SOC contents.     

球面小波模型在GPS高程拟合中的应用

本文利用某地共99个GPS水准点的大地高和正常高求取高程异常,使用DOG球面小波模型和多面函数,分别对高程异常进行拟合。拟合时剔除模型残差大于2倍中误差的点,并在剔除粗差后重新进行拟合。通过比较外部检核点的已知高程异常值和球面小波模型值、多面函数拟合值之间的均方差评价模型的精度。数据结果表明,以外部检核均方差最小为准则,球面小波模型拟合精度较优,其拟合精度为1.65 cm,多面函数拟合精度为2.35 cm。     

Arctic sea-ice motion and its relation to pressure field

Daily Arctic sea-ice motion maps during the winter seasons (December–March) from December 1988 to March 2003 derived from NSCAT, QuikSCAT, SSM/I, and AMSRE data by a wavelet analysis method have been merged with those derived from buoy data. These merged sea-ice motion data have been used to study the circulation regimes and winter-to-winter variability of Arctic sea-ice motion. The relation between sea-ice motion and the pressure field in the Arctic Ocean was also studied by applying Principal Component Analysis (PCA) to the monthly merged sea-ice motion data and the monthly pressure field data from IABP. The mean Arctic sea-ice motion map of the 15 winter seasons has two distinct features: the Beaufort Gyre and a cyclonic circulation system in the Eurasian Basin, which moves ice from the Laptev Sea to Fram Strait. The strengths and sizes of the two features change from one winter season to another. Seasons with a strong or normal Beaufort Gyre alternate with seasons with a weak or no Beaufort Gyre every one to three seasons. The principal components of the first two modes of PCA of the monthly sea-ice motion are closely correlated with their counterparts of the monthly pressure field in the Arctic Ocean. The mode-one components of these two anomalies alternate between anticyclonic and cyclonic circulation systems. The correlation between Arctic Oscillation indexes and the principal components of the first mode of PCA of the monthly Arctic sea-ice motion is low but statistically significant.     

2008年中国沿岸冬季寒潮激发陆架波的小波分析

This study applies the wavelet analysis to the tidal gauge records, alongshore winds, atmospheric temperature and pressure along the China coast in winter 2008. The analysis results show three events of sea level oscillations(SLOs) on the shelf induced by winter storms. The first event occurred from January 9 to 21. The SLO periods were double-peaked at 1.6–5.3 and 7.0–16.0 d with the power densities of 0.04–0.05 and 0.10–0.15 m2·d, respectively.The second event occurred from February 5 to 18. The SLO period was single-peaked at 2.3–3.5 d with power density of 0.03–0.04 m2·d. The third event occurred from February 20 to March 8. The SLO periods were doublepeaked at 1.5–4.3 and 6.1–8.2 d with the power densities of 0.08–0.11 and 0.02–0.08 m2·d, respectively. The SLOs propagated along the coast from Zhejiang in north to Guangdong in south. The phase speeds ranged about 9–29m/s from Kanmen to Pingtan, 5–11 m/s from Xiamen to Huizhou and 11–22 m/s from Huizhou to Shuidong. The dispersion relation of the SLOs shows their nature of coastal-trapped wave.     

小波变换压制噪声在单道地震资料处理中的应用

海洋区域地质调查中,单道地震勘探以其高分辨率、方便快捷等优点成为揭示浅地层地质构造的重要手段之一.结合前人研究成果并出于保护信号的完整性,对低频部分的噪声采用带通滤波进行滤除,而对高频信号中的随机噪声采用小波阈值去噪方法进行压制处理.在小波阈值去噪过程中,通过比较选用最佳小波基函数sym5对地震剖面进行三层小波分解.结果表明:两种阈值去噪方法在带通滤波的基础上进一步提升了剖面的质量,使得反射层面变得连续可追踪.软阈值去噪滤掉了剖面上的较多信息,去噪效果较为彻底,硬阈值去噪则保留了较多的细节信息.     

基于经验模态分解和小波分解估算海气通量涡相关计算中的截断时间尺度

基于时长38天的海表风场实测数据,应用经验模态分解(EmpiricalModeDecomposition,EMD)和小波分解(Wavelet Decomposition, WD)这两种数据处理方法首先对涡相关法中的截断时间尺度(CutoffTimescale,CTS)进行估算,结果显示:基于EMD与WD方法估算出的CTS一般都在40秒左右(EMD的结果略小),远远小于传统涡相关法中CTS的取值(固定为10分钟),且EMD和WD的使用使得每一段数据都能够根据自身的湍流特点而获得合适的CTS; EMD方法和WD方法有效的去除了计算结果中的非湍部分,且对通量传输方向的刻画也更加合理,极大提高了通量的计算精度,所得通量与传统方法计算的通量偏差平均值高达45%;研究还对EMD和WD的优缺点进行了对比分析,结果表明EMD相比于WD有更高的自主性,而WD对信号的分离程度则更高。     

气压对巴伦台钻孔倾斜的影响特征及机制研究

以巴伦台钻孔倾斜及分量应变辅助观测气压数据为研究对象,运用相关及小波分析研究气压对巴伦台钻孔倾斜的影响特征。结果表明,气压对巴伦台钻孔倾斜影响表现为准线性关系,对NS向的影响大于EW向。气压对NS向影响的显著频段有2 048～8 192、32 768～65 536 min,对EW向影响的显著频段为2 048～8 192 min。探讨了气压对巴伦台钻孔倾斜的影响机制。     

基于小波变换法定义的波群参数

通过小波变换分析的波能过程定义了两个描述波浪群性的参数,由数值模拟波浪和实测波浪资料对其与常用的波群参数进行对比分析,结果表明基于小波波能过程定义的群性参数是有效的,从而展示了小波变换用于在时频域上分析波群的能力。详细探讨了波浪记录长度对群性参数稳定性的影响,分析结果表明,波浪观测长度对于波群参数的影响较大,在考虑波浪群性的波浪模拟及分析时,建议模拟时间长度应在400~500个波以上。     

一种新的基于PCA变换多源遥感影像像素级融合方法

在多源遥感影像融合中,基于传统PCA变换的多源遥感影像融合的光谱分辨率受到较大影响。提出了一种新的基于PCA变换的多源遥感影像像素级融合方法,通过在传统PCA变换融合算法基础上引入小波变换融合,保留了多波段遥感图像光谱特性的有用信息,进一步提高融合后遥感影像的效果。给出实验的融合结果,并与传统PCA变换方法进行对比,证明了该方法的有效性。