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算出来。汇编的数据集覆盖了西北太平洋，包括日本海。海温分布是上层海洋湍流和洋流的间接结果。利用分形、小波和反演技术，从海表面温度(SST)序列场中推断了海洋动力学。首次将分维估计和二维正交化小波变换技术应用于星载海温图像。用分形和小波分析揭示了日本海表面温度分布的间歇性和多尺度现象。(1)分维计算揭示了上层海洋动力学的混沌行为。(2)小波分析结果表明，秋季凉爽的…在春季加热初期，上层稳定的层结条件有利于地转湍流尺度上的涡旋搅动，数值越大，三维混合越强。最初的反演方法是从被动示踪剂如SST的随时间变化的分布中获得近海面速度和混合系数。(1)第一种方法涉及瞬变流的情况。利用极大似然(ML)估计，导出了SST守恒方程中的未知水平速度、扩散张量和衰减率。数值模拟表明，对于不同分辨率的数据网格，最大似然估计器提供了一致的混合系数估计。它还可以在人们普遍关心的一定范围的海洋条件下提供合理的平流速度。(2)第二种方法用于从长时间序列观测中估计气候平均平流-扩散输送。通过对西北太平洋冬季海温异常的观测协方差拟合出随机偏差温度守恒方程，得到未知参数。对1965-1990年10天平均的1度×2度经度箱平均的海温资料进行了反演。估计的净平流速度在大小和方向上与冬季西北太平洋近地面环流基本一致。扩散系数的估计也是可靠的。这一分析支持Hasselmann的理论，即持续大气过程的主要时间尺度的中纬度SST异常的产生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”的惯性是不容忽视的。较少

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