A Medium/Long-Range Forecast of Pacific Subtropical High Based on Dynamic Statistic Model Reconstruction

Based on the 500-hPa geopotential height field series of T106 numerical forecast products,by empirical orthogonal function(EOF)time-space separation,and on the hypotheses of EOF space-models being stable, the EOF time coefficient series were taken as dynamical statistic model variables.The dynamic system reconstruction idea and genetic algorithm were introduced to make the dynamical model parameters opti- mized,and a nonlinear dynamic statistic model of EOF separating time coefficient series was established.By the model time integral and EOF time-space reconstruction,a medium/long-range forecast of subtropical high was carried out.The results show that the dynamical model forecast and T106 numerical forecast were approximately similar in the short-range forecast(≤5 days),but in the medium/long-range forecast (≥5 days),the forecast results of dynamical model was superior to that of T106 numerical products.A new method and idea were presented for diagnosing and forecasting complicated weathers such as subtropical high,and showed a better application outlook.     

A CHARACTERISTIC CORRELATION ANALYSIS BETWEEN THE ASIA SUMMER MONSOON MEMBERS AND THE WEST PACIFIC SUBTROPICAL HIGH

In this paper, by using the pentad-mean NCAR/NCEP reanalysis data for the period of 1958-1997, some characteristic indices of describing the activity of Asian summer monsoon system members are defined and calculated. Based on the above works, a time-lag correlation analysis method is introduced for the correlation analysis between the Asian summer monsoon system and the west Pacific subtropical high (WPSH) area index, and some meaningful interaction processes and characteristic phenomena between them are revealed and discussed accordingly. It is shown that there exists some remarkable time-lag correlations in various degree between the Asian summer monsoon system members and the WPSH area index, and they interact and feedback with each other, which consists of the whole Asian summer monsoon system.     

南亚夏季风影响西太平洋副高南北进退活动的小波包能量诊断

基于小波包分解重构方法,利用NCEP/NCAR逐日再分析资料,讨论了南亚夏季风与季内西太平洋副高活动的关系,提出和定义了用以诊断副高活动的夏季风频域能量判据.诊断结果除佐证了副高已有的一些研究结果和变化规律外,还揭示出副高与季风间一些新的关系特征.     

近赤道海温影响西太平洋副高的小波多尺度分析

利用小波分解、相关分析、解释方差及位相对比方法,分析讨论了近赤道海温与西太平洋副高在不同时间尺度上的结构特征与对应关系.分析表明,不同海域海温变化与副高活动的幅值和位相存在明显的多尺度特征和强度差异,不同海域的海温热力作用分别在不同的时间尺度上显著影响和制约西太平洋副高活动.     

南海夏季风爆发前后海-气界面热交换特征

文中利用 2 0 0 0与 2 0 0 2年二次南海海 气通量观测资料和同期西沙站资料 ,研究了南海夏季风爆发前后海洋表面热收支变化特征。研究表明 :南海夏季风爆发前后 ,影响海面热收支变化的主要分量是净短波辐射通量和潜热通量 ,在季风爆发前后不同阶段 ,二个分量的变化有不同表现形式 ,但不论二者如何变化 ,季风爆发与活跃期 ,海面热收入减小或为净支出 ;季风爆发前及中断期间 ,海面热收入逐渐增加 ;由于大的热惯性 ,海温变化落后于海面热收支的变化 ,海温的这种滞后效应通过影响潜热通量调节海面热收支的变化 ,又反过来影响自身的变化 ,形成短期振荡过程 ,这种振荡过程与季风的活跃、中断过程相对应。     

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 Nino and La Nina 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 Nino and La Nina problems that are just roughly described in dynamics.     

西太平洋副热带高压非线性稳定性问题的研究

本文采用了包含热力强迫和涡动耗散的三维非线性动力学模式，从系统稳定性的角度出发，探讨了夏季东亚副热带地区的环流状况，东亚大陆季风雨带和南海季风槽雨带的凝结加热以及扰动流的相互作用等因素对西太平洋副热带高压进退的制约和影响。给出了反映系统稳定性状况的能量判据，并据此进行了动力学分析和模式大气的计算。研究结果为一些天气分析事实提供了动力学解释，得到了一些新的见解，并为判断和预测西太平洋副热带高压在东亚上空的活动提供了参考依据。     

模糊逻辑仿真建模及其在青岛海雾分析中的应用

引入模糊推理仿真建模方法，在传统定性分析的基础上，基于观测事实和预报经验，建立起了青岛海雾定量化的模糊推理映射模型，在此基础上对青岛海雾发生发展的影响因子和变化特征进行了诊断和预报探讨。仿真试验结果表明，模糊推理方法在定量性、客观性和自动化程度方面优于传统的天气分析预报方法，在分析、预报诸如海雾等地域性特征明显的天气中有较好的实用意义和应用前景。     

基于遗传聚类算法的印度洋环境特征区划

利用全球海洋 Agro 观测计划提供的温、盐浮标资料,开展了印度洋海域水下环境特征提取与区划分析.在垂直方向运用Akima 方法对浮标剖面进行插值,提取一组表征跃层、声速场的特征指标,并针对常规模糊 C 均值聚类算法中初始聚类数难以客观选取和聚类结果易陷入局部最优等问题,利用遗传算法的全局搜索能力对聚类算法作了改进.通过在遗传进化过程中引入动态变化的聚类中心解决了聚类数难以客观确定的问题,并在该算法的生存策略中引入 Boltzmann 选择机制,提高算法的收敛速度.在对印度洋海域温、盐跃层、声速分布及层结稳定度分析的基础上,利用改进的遗传聚类方法对印度洋海域水下环境特征进行聚类区划,得到一个基本的特征分类构型,结合各类构型的典型特征,分析了对水下潜器活动、声纳探测和水声通信等的影响.     

基于模糊C均值聚类的云图样本修正与云类自动识别

基于云类样本的红外-可见光二维灰度空间投影,采用模糊聚类方法调整优化云类样本特征区域,消除采样误差。针对常规模糊C均值聚类(FCM)方法在处理上述问题时表现出的局限性,提出用样本特征均值替代FCM中随机初始中心的改进办法,既避免了常规FCM方法对初始中心敏感的缺陷,又可纠正其聚类结果对云类样本特征结构的歪曲。改进后的聚类结果既消除了采样误差,又保持了云类样本的基本特征属性。基于该判据的分类结果,可较为准确地分辨出陆地、水体、低云、中云、卷云、对流云和积雨云,分割判另9结果符合客观实际。