中国东部地壳与上地幔速度不均匀性和各向异性的初步研究(英文)

本文利用763式地震仪记录的地震瑞利面波资料,用双台法计算出瑞利面波的频散曲线,从而得到相速度.将我国东部地区(99.8°—123.8°E,20°—44°N)分成4°×4°大小的方格,利用代数重建法得出该地区上地幔与地壳的横向不均匀性.对同一地区再进行一次分块,块的大小为8°×8°,考虑到各向异性对面波相速度的影响,利用周期为60 s 的面波相速度资料,反演出我国东部的横向不均匀和各异向性的特征。     

Studies of early comprehensive judgment on seismic tendency after a moderate or strong earthquake

In this paper, the methods of pattern recognition and fuzzy cluster are applied to estimate comprehensive whether there would be an earthquake which magnitude is commensurate with (N=M ₀±0.3) or greatM>M ₀) thanM ₀ within 3 months using sequential data in 3 days immediately after a moderate or strong earthquake (M ₀≥4.7) occurred, The result of retrospective test indicates that the comprehensive judgment effects by using these applied mathematics methods are better than that of using every individual method obviously. TheV mark value of algorithm CORA-3 in pattern recognition is the highest among them. There are 44 known earthquake sequence data (5 type- I and 39 type- II) used to learn and train, the results of internal coincidence test show that all 44 sequence samples could be distinguished correctly. Extrapolation test by using other 4 known earthquake sequences (2 type- I and 2 type- II) shows that all 4 extrapolation samples could be distinguished correctly also. In the process of study, these methods have been applied to judge the post-earthquake tendency of 2 moderate earthquakes occurred recently, one is distinguished correctly and the other wrong. The algorithm Hamming in pattern recognition and fuzzy cluster method have been applied to judge the early post-earthquake tendency after a moderate or strong earthquake, too. TheV mark values of internal coincidence tests could get above 0.8 most cases of extrapolating are correct. The Chinese version of this paper appeared in the Chinese edition ofActa Seismologica Sinica,15, 15–21, 1993.     

夏季东半球热带海温异常对亚洲季风环流和降水影响的数值试验

利用一个全球大气环流谱模式，模拟了７月份大气对东半球热带海洋（阿拉伯海、孟加拉湾、南海、西太平洋）海温异常的响应。试验结果表明，热带海洋的热状况是影响亚洲季风环流和降水的一个重要因素。     

滇东磷矿风化型矿石的判别指标讨论及次生风化富集作用

风化型磷矿石－风化磷块岩是滇东最主要的磷矿石，为判别矿石为原生成风化磷块岩，前人已提出过１０余种作为判别标志的风化指标，但是这些指标的计算仅以矿石的化学组成为依据。笔者研究后指出，应以次生风化作用过程中磷块岩的组成和结构变化为基础，再合理使用上述某些判别指标，才能正确确定风化矿石，决定其利用价值和方法。笔者还指出，在次生风化作用中被溶蚀的不仅是碳酸盐，只要条件适当，石英和粘土矿物也可以溶蚀，使磷矿石品位增高，结构疏松，成为有利于洗选的优质矿石。     

吉林省金城洞绿岩带构造变形序列

金城洞绿岩带自晚太古代以来经历了多期变形：Ｄ＿１变形幕，形成片理、片麻理及无根褶曲，是深部构造层次的产物；Ｄ＿２变形幕，形成轴面片理及一系列轴向ＮＷ或ＮＷＷ向的紧闭同斜或平卧褶皱，并伴有英云闪长岩—奥长花岗岩侵入，是中深部构造层次的产物；Ｄ＿３变形幕，形成大型开阔褶皱，晚期形成韧性剪切带，是中浅部构造层次的产物。这三幕变形奠定了本区的基本构造格架。Ｄ＿４变形幕在中浅构造部位形成ＮＥ向开活褶皱。古生代以来，本区主要发生脆性变形。     

组合拱形喷粉桩在深基坑支护中的应用

从支护方案的选择、支护结构形式、施工工艺及支护效果等方面介绍了一种新颖、经济有效的支护结构─组合拱型喷粉桩在上海合流污水治理工程箱涵基坑施工中的应用。     

西部山区总辐射气候学计算及分布

根据西部山区太阳总辐射的实测资料分析，指出，西部山区总辐射的气候学计算必须考虑日照，水汽分布及海拔高度的影响。为此研制了适宜于西部山区的总辐射气候学计算公式Ｑ＝Ｑ０（ａ＋ｂｓ１＋ｃｓ１＾２），进而讨论了西部山区总辐射的时，空分布。     

“雅安天漏”研究 II. 数值预报试验

本文建立了一个用于研究“雅安天漏”的有限区域数值预报模式，并用该模式对10个“雅安天漏”个例进行了数值预报试验，取得了较满意的结果。该模式动力框架的主要特点是: (1) 模式的基本方程组便于构造出完全能量守恒的差分格式；(2)采用了静力扣除；(3)模式的垂直坐标选用了η坐标；(4)选用E网格作为变量的水平分布形式；(5)位势高度与其他预报量在垂直方向交错分布；(6)对E网格的波解分离问题采取了特殊的处理技巧；(7) 首次采用“半格距”差分解决了矩形E网格及球坐标E网格沿对角线的差分计算；(8)采用显示分解的时间积分方案；(9)尽量保留初始场信息。模式的物理过程主要包括: (1)大尺度凝结降水；(2)对流调整及对流降水；(3)水平扩散和垂直通量输送；(4)地面辐射收支和边界层参数化。试报降水的主要降水中心及降水范围与观测分析比较相似。大于10 mm和２５ mm降水的TS平均评分分别为0.41和0.32。     

模式识别在强余震等早期综合判别中的应用研究

本文利用所收集到的２９个６级以上地震序列，探讨将模式识别ＣＯＲＡ－３算法用于５级以上强余震或震群或再发生更大地震的前震－主震－余震型地震序列早期综合判断的可能性及具体方法。文中参与学习和训练的２５个地震序列中，８个Ｉ类序列全部被正确识别，１７个ＩＩ类序列中有１６个被正确识别，只有１个被误判为Ｉ类，预报评分Ｖ值达０．９２。对于留作外推的４个地震序列中，２个ＩＩ类序列全部被正确识别，２个Ｉ类序列，１个     

Simplified Dynamic Models of Grass Field Ecosystem

Some simplified dynamic models of grass field ecosystem are developed and investigated. The maximum simpli-fied one consists of two variables, living grass biomass and soil wetness. The analyses of such models show that there exists only desert regime without grasses if the precipitation p is less than a critical value pc; the grass biomass continuously depends on p if the interaction between grass biomass and the soil wetness is weak, but the strong interaction results in the bifurcation of grass biomass in the vicinity of pc; the grass biomass is rich as p > pc, but it becomes desertification as p < pc. Periodic solutions also exist in the model, if the seasonal cycle of model’s parameters is introduced. An improved model consists of three variables, i.e. the living grass biomass x, the nonliving grass biomass accumulated on the ground surface y and the soil wetness z. The behaviours of such three variables model are more complicated. The initial values of y and z play a very important role.