大同—阳高Ms6.1地震前兆综合加权信息熵的变化

利用“地震预报计算机专家系统”的思想对大同 -阳高 Ms6 .1地震前每一前兆异常事件进行综合评估 ,以每一异常的最可能发震时间来计算发震概率 ,利用地震前兆综合加权信息熵研究了系统熵值与地震的关系。对华北地区的地震前兆综合加权信息熵研究表明 ,在大同 -阳高 Ms6 .1地震前 ,信息熵出现了明显的减熵有序变化     

江汉盆地钻孔测井资料确定地应力最大水平主压应力方向

利用钻孔测井资料并运用地层倾角测量信息分析法，给出了江汉盆地地应力最大水平主压应力方向为ＮＥ６０～６５°     

East Asian monsoon variation and climate changes in Jeju Island, Korea, during the latest Pleistocene to early Holocene

A 4.96-m-long sediment core from the Hanon paleo-maar in Jeju Island, Korea was studied to investigate the paleoclimatic change and East Asian monsoon variations during the latest Pleistocene to early Holocene (23,000-9000 cal yr BP). High-resolution TOC content, magnetic susceptibility, and major element composition data indicate that Jeju Island experienced the coldest climate around 18,000 cal yr BP, which corresponds to the last glacial maximum (LGM). Further, these multi-proxy data show an abrupt shift in climatic regime from cold and arid to warm and humid conditions at around 14,000 cal yr BP, which represents the commencement of the last major deglaciation. After the last major deglaciation, the TOC content decreased from 13,300 to 12,000 cal yr BP and from 11,500 to 9800 cal yr BP, thereby reflecting the weakening of the summer monsoon. The LGM in Jeju Island occurred later in comparison with the Chinese Loess Plateau. Such a disparity in climatic change events between central China and Jeju Island appears to be caused by the asynchrony between the coldest temperature event and the minimum precipitation event in central China and by the buffering effect of the Pacific Ocean.     

多传感器观测下带乘性噪声系统的逆向滤波与反褶积融合算法

针对多传感器观测环境下带乘性噪声系统的逆向最优滤波与反褶积融合估计问题 ,本文提出了 1种基于极大似然准则的最优融合算法。该算法中各单传感器间并行计算 ,并且融合中心与单传感器处理中心间无反向通讯 ,因而执行效率较高。仿真表明 ,该融合算法产生的逆向滤波与反褶积比单传感器处理结果有较明显提高     

太湖表面定振波的数值计算和最大熵谱分析

利用水动力学方程对太湖表面的定振波进行计算，算得定振波周期约为４５２ｍｉｎ，另外，利用１９９２年８月２９－３１日在太湖西山观测到的水位资料，采用最大熵谱法，分析太湖表面的定振波，得周期值约为４５０ｍｉｎ。计算和分析的周期值基本吻合，取熵谱分析结果得太湖表面的单节点定振波周期值为４５０ｍｉｎ。     

南海波高熵和风速熵

根据风速的统计分布，给出了有因次风速熵和无因次风速熵的定义及其计算方法，使用ＧＥＯＳＡＴ高度计１９８６年１１月－１９８９年２月的有效波高和风速的资料，计算，分析了南海海域上的波高熵，风速熵，给出它们的时间变化特征和空间变化特征，并对不同随机量的无因次熵，即随机度进行了比较。     

全球海洋与大气界面的熵通量估算

给出并讨论了海洋系统中由于热量交换、物质交换以及外力做功引起的熵通量的表达式;同时,根据新近调整的全球海 气界面的气候平均资料,估计了全球海洋与大气界面气候年平均的熵通量(熵流),这一熵通量主要取决于海 气界面的热量和物质交换的空间不均匀性。计算结果显示,由热量交换分量引起的熵通量对海洋系统的总熵通量起到主要的贡献作用,其值约为-555.6mW·(m2·K)-1;由海表风应力做功引起的熵通量相对较小,约为-0.09mW·(m2·K)-1;由物质交换引起的熵通量最小,仅为-0.02mW·(m2·K)-1。总的来说,海洋系统从外界获得的总熵通量为-555.7mW·(m2·K)-1,这也就意味着在气候平均定态下,海洋系统内部的熵产生在量值上等于系统的熵交换,即为555.7mW·(m2·K)-1。海洋系统的负熵流与其内部的各种不可逆过程引起的熵产生取得平衡,确保了全球海洋系统处于非平衡热力学定态,并维持着海洋系统中各种尺度的时 空有序现象的消长过程。     

Preliminary study on different nutrient pools supplies for the phytoplankton growth in the Jiaozhou Bay in China in the fall of 2004

The source and significance of two nutrients, nitrogen and phosphorous, were investigated by a modified dilution method performed on seawater samples from the Jiaozhou Bay, in autumn 2004. This modified dilution method accounted for the phytoplankton growth rate, microzooplankton grazing mortality rate, the internal and external nutrient pools, as well as nutrient supplied through remineralization by microzooplankton. The results indicated that the phytoplankton net growth rate increased in turn from inside the bay, to outside the bay, to in the Xiaogang Harbor. The phytoplankton maximum growth rates and microzooplankton grazing mortality rates were 1.14 and 0.92 d-1 outside the bay, 0.42 and 0.32 d-1 inside the bay and 0.98 and 0.62 d-1 in the harbor respectively. Outside the bay, the remineralized nitrogen (Kr=24.49) had heavy influence on the growth of the phytoplankton. Inside the bay, the remineralized phosphorus(Kr=3.49) strongly affected the phytoplankton growth. In the harbor, the remineralized phosphorus (Kr=3.73) was in larger demand by phytoplankton growth. The results demonstrated that the different nutrients pools supplied for phytoplankton growth were greatly in accordance with the phytoplankton community structure, microzooplankton grazing mortality rates and environmental conditions. It is revealed that nutrient remineralization is much more important for the phytoplankton growth in the Jiaozhou Bay than previously believed.