Distribution of <Superscript>226</Superscript>Ra in the Arctic Ocean and the Bering Sea and its hydrologic implications

Radium-226 (²²⁶Ra) activities were measured in the surface water samples collected from the Arctic Ocean and the Bering Sea during the First Chinese National Arctic Research Expedition. The results showed that ²²⁶Ra concentrations in the surface water ranged from 0.28 to 1.56 Bq/m³ with an average of 0.76 Bq/m³ in the Arctic Ocean, and from 0.25 to 1.26 Bq/m³ with an average of 0.71 Bq/m³ in the Bering Sea. The values were obviously lower than those from open oceans in middle and low latitudes, indicating that the study area may be partly influenced by sea ice meltwater. In the Bering Sea, ²²⁶Ra in the surface water decreased northward, probably as a result of the exchange between the ²²⁶Ra-deficient sea ice meltwater and the ²²⁶Ra-rich Pacific water. In the Arctic Ocean, ²²⁶Ra in the surface water increased northward and eastward. This spatial distribution of ²²⁶Ra reflected the variation of the ²²⁶Ra-enriched river component in the water mass of the Arctic Ocean. The vertical profiles of ²²⁶Ra in the Canadian Basin showed a concentration maximum at 200 m, which could be attributed to the inputs of the Pacific water or/and the bottom shelf water with high ²²⁶Ra concentration. This conclusion was consistent with the results from ²H, ¹⁸O tracers.     

A Flare-Triggered Heating of a Quiescent Filament

Using data obtained with the 20-cm H full-disk telescope at Big Bear Solar Observatory and Fexii 195 Å EIT on SOHO, we analyze a sudden disappearance event of a quiescent filament in detail. The filament was located along the common boundary of the active regions NOAA 9672 (S19 E13) and NOAA 9673 (N03 E18). The filament disappeared during a time interval between 17:59 UT and 19:47 UT on 22 October 2001 immediately after the onset of a major flare, which occurred in the active region NOAA 9672. At about 23:23 UT of the same day, the filament began to reappear in H and, after about 15 hours, the filament recovered to its steady state with its size being slightly smaller than that before its disappearance. This filament disappearance event belongs to the thermal type of sudden filament disappearances, which is caused by an input of additional heat. The heating mechanism that leads to sudden thermal disappearances of quiescent filaments is still not well understood. This simple event, due to the explicit cause and effect relationship between the flare and the disappearance of the filament, shows us that the flare triggered some kind of heating mechanism which continued several hours. The heat may come from the flare via heat conduction from its ribbon or from the excitation of dissipating Alfvén waves. However, from the data analysis, we conclude that the flare triggered an in-situ heating, which is likely caused by magnetic reconnection.     

黄浦江水质指标与反射光谱特征的关系分析

利用地物光谱测量技术及同步配套的常规水质采样分析实验，对上海市黄浦江全河段水体进行调查研究。共选取31个典型站位进行了光谱测量和同步水质取样，每个测点分析了9个水质指标，包括TP，TN，CODMn，CODCr，NH3-N，BOD5，DO，悬浮物浓度和浊度。各水质参数之间存在较大的相关性，以总氮（TN）和悬浮物浓度两个水质指标为例，分析了这两个水质指标与单波段归一化反射率、反射率的一阶微分、不同波段之间反射率的比值以及反射率取对数等之间的相关关系，给出了以上两个水质指标的单波段归一化反射率、一阶微分反射率识别的特征波段，以及两个波段比值的最佳波段组合。建立了常规水质参数与水体光谱反射率之间的关系模型，为利用遥感技术监测水环境提供了基础。     

一次强对流天气过程的成因分析

利用常规气象资料和多普勒雷达资料，从天气形势、物理量场和雷达回波演变特征分析2005年5月5日福建省强对流天气过程的成因。结果表明：这次强对流天气过程发生在锋前暖区内，高空弱冷空气的侵入对不稳定能量释放起触发作用，高低空急流的相互配置为强对流的发生提供了有利的动力抬升条件，大气的不稳定和良好的水汽输送条件有利于飑线的形成和发展，移入型的回波在福建境内发展加强形成飑线，飑线是此次强对流天气过程的直接影响系统。     

基于GIS的秦岭山地气温空间分布

提出一种以气象站点观测资料为基础,用G IS技术建立山地平均气温分布模型的方法。通过数字高程模型(DEM),获取地形数据,建立山地天文辐射模型。考虑海拔高度、地形等影响气温空间分布因子,建立山地气温分布模型。     

回归分析方法在地震科学应用中的问题与探讨

分析了回归分析方法在地震科学应用中存在的问题,提出了按变量之间的物理关系进行分类回归的新观点。针对实际地震问题给出了具体的分类方案,从理论上论述了不同类型问题采用不同的回归方法的必要性。通过对实际地震问题分析,剖析了现有回归分析方法的优缺点和适用条件。在此基础上,对不同类型统计问题如何选用适当的回归分析方法提出了合理的建议。     

NUMERICAL ANALYSIS OF THE MECHANICS OF SOIL REINFORCEMENT

1 INTRODUCTION China is rich in mountains. The mountainous area occupies 69% of the total land of the country. Thus, landslides frequently occur in the mountain areas of China. Landslides originating in subsurface soils are typical, and constitute approxi…     

Early J2 basalts in SE China: Incipience of large-scale late Mesozoic magmatism

Magmatism in SE China was dormant during 204–180 Ma, but was reactivated in 180–170 Ma (early J₂), and then became more and more intensive towards the end of early Cretaceous. The small-scale early J₂ magmatism is the incipience to long-term and large-scale magmatism in this region. A near east-west (EW) trend volcanic belt was distributed across south Hunan, south Jiangxi and southwest Fujian was formed during early J₂ time. Along this belt from the inland toward the coast, the lithology of basalts changes from alkali into tholeiite, and the amount of erupted volcanic rocks and the proportions of rhyolites coexisting with the basalts increase. On the basis of geochemical characteristics of these basalts, we infer that the melting degree of source rocks and the extent of fractional crystallization and crustal contamination all increased whereas the depth of mantle source decreased from the inland to the coast, which led to the variations of geological characteristics of the volcanic belt. In early J₂, the western spreading Pacific plate began to subduct underneath SE China continental block, reactivating near EW trend deep fault that was originally formed during the Indosinian event. The stress of the western spreading Pacific plate and the extent of asthenosphere upwelling increased from the inland to the coast, which is consistent with the generation and evolution of early J₂ basalts.     

Four-dimensional data assimilation method based on SVD: Theoretical aspect

Summary A new method of four-dimensional data assimilation based on Singular Value Decomposition (SVD) is proposed. In it, a set of atmospheric states is obtained by integrating a numerical weather prediction model and simulated observations are taken and calculated from the model variables. Then the SVD technique is used to create the base vectors from this coupled data set. Finally, the analysis is obtained by projecting actual observation data into a space spanned by the base vectors. Using this approach, the four-dimensional data assimilation becomes a simple linear inverse problem the linearization of the nonlinear forward model is avoided, and the developments of the adjoint and background error covariance matrix are no longer needed. Since the SVD technique is used here, the method is simply called 4DSVD.     

夏热冬暖地区建筑节能设计分析

本文根据夏热冬暖地区的气候特点，针对目前建筑节能设计存在的薄弱环节，分析了建筑围护结构的构造措施及其热工性能，提出在节能设计中应注意的问题。