The sea dynamics inferred from satellite sequential radiometry images

1.海表温度（SST）数据来自NOAA卫星辐射测量，并从海洋-大气综合数据集压缩海洋报告中推导出来。汇编的数据集涵盖了包括日本海在内的西北太平洋。SST分布是上层海洋湍流和海流的间接结果。利用分形、小波和反演技术，从海表温度（SST）序列场推断海洋动力.首次将分维估计和二维正交小波变换技术应用于星载SST图像。分形和小波分析揭示了日本海表层温度场的非线性和多尺度现象。(1)分形维数的计算表明了上层海洋动力学的混沌行为。(2)小波分析的结果表明，秋Cooli ...更多信息 ng导致三维混合的增强，而春季加热开始时，上层海稳定的层结条件有利于地转涡尺度的扰动.原始的反演方法是从SST等被动示踪物的时变分布反演海面近地表速度和混合系数。(1)第一种方法涉及瞬态流的情况。本文用极大似然估计方法导出了SST守恒方程中未知的水平速度、扩散张量和衰减率。在数值模拟中，它表明，ML估计为我们提供了一致的估计的混合系数的不同分辨率的数据网格。它还可以提供合理的平流速度在一定范围内的海洋条件的普遍利益。(2)第二种方法致力于从长时间序列观测中估计气候平均对流扩散输送。通过对西北太平洋冬季海温距平观测资料的协方差拟合一个随机偏微分温度守恒方程，得到了未知参数。反演应用于1965年至1990年10天平均基础上的平均在1度纬度x 2度经度箱的SST数据。净平流速度的估计值与冬季西北太平洋表层大气环流的大小和方向一致。扩散系数的估计也是可靠的。分析支持Hasselmann的理论，即中纬度SST异常的产生持续的大气过程的主导时间尺度主要归因于短期随机天气强迫。但分析表明，在西边界附近和热带地区，海温异常对前期风的“记忆”惯性作用不可忽视。少

1. The sea surface temperature (SST) data were acquired from the NOAA satellites radiometry surveys and deduced from the Comprehensive Ocean-Atmosphere Data Set Compressed Marine Reports. The Compiled data sets cover the Northwestern Pacific including the Japan Sea. The SST distri-butions represent an indirect result of the turbulence and currents in the upper ocean. The fractal, wavelet and inversion techniques were used to infer the sea dynamics from the sequen-tial fields of the sea surface temperature (SST).2. For the first time the fractal dimension estimation and two-dimensional orthonormal wavelet transform techniques were applied to the satellite born SST images. The fractal and wavelet analyzes demonstrated the intermittence and multiscale phenomena in the the the Japan Sea surface temperature patterns. (1) The fractal dimension calculations indicated the chaotic behaviorof the upper sea dynamics. (2) The results of the wavelet analysis allowed to suggest that the autumn cooli … More ng leads to enhancement of the three dimensional mixing, while at the beginning of thespring heating the stably stratified conditions in the upper sea are favorable for stirring by eddies at scales ofthe geostrophic turbulence.3. The original inversion methods were deeloped to obtain the sea near-surface velocities and mixing coefficients from time dependent distributions of passive tracers such as SST.(1) The first approach concerned the case of the transient flow. The unknown horizontal velocities, diffusion tensor and decaying rate in a conservation equation for SST are derived by means of a maximum likelihood (ML) estimator. In the numerical simulations it is shown that the ML esti-mator provides us with consistent estimates of the mixing coefficients for different resolu-tions of the data grid. Also it can provide reasonable advection velocities in a certain range of oceanic conditions of general interest. (2) The second approach was devoted to estimate of climatically mean advection-diffusion transport from the long time-series of observations. The unknown parameters were found by fitting a stochastic partial differential temperature conser-vation equation to the observed covariances of the winter SST anomalies over the Northwestern Pacific. The inversion was applied to the SST data averaged at 1deg latitude x 2deg longitude boxes on a 10-day mean basis from 1965 to 1990. The estimates of the net advection velocity are consistent in magnitude and direction with the general circulation in the surface layr of the Northwest Pacific in winter. The estimates of the diffusion coefficient were also reliable. The analysis supports Hasselmann's theory in which generation of midlatitude SST anomalies lasting the dominant timescale of atmospheric processes is primarily attributed to the short period stochastic weather forcing. However, the analysis indicates that the inertia of SST anomalies to their "memory" of earlier winds can not be neglected in the vicinity of the western boundary and in the tropics. Less